How Space Armies will Define the Artificial Intelligence Race with David YakobovitchAvailable for reading on Medium: https://medium.com/@david.yakobovitch/how-space-armies-will-define-the-artificial-intelligence-race-8f288ac23031 .🚀 You could sponsor today's episode. Learn about your ad-choices.💙 Show your support for HumAIn with a monthly membership.📰 Receive subscriber-only content with our newsletter.🧪 Visit us online and learn about our trend reports on technology trends and how to bounce back from COVID-19 unemployment.About HumAIn Podcast:The HumAIn Podcast is a leading artificial intelligence podcast that explores the topics of AI, data science, future of work, and developer education for technologists. Whether you are an Executive, data scientist, software engineer, product manager, or student-in-training, HumAIn connects you with industry thought leaders on the technology trends that are relevant and practical. HumAIn is a leading data science podcast where frequently discussed topics include ai trends, ai for all, computer vision, natural language processing, machine learning, data science, and reskilling and upskilling for developers. Episodes focus on new technology, startups, and Human Centered AI in the Fourth Industrial Revolution. HumAIn is the channel to release new AI products, discuss technology trends, and augment human performance.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

Is AI a Job Killer or a Job Creator with David YakobovitchAvailable for reading on Medium: https://medium.com/datadriveninvestor/is-ai-a-job-killer-or-job-creator-49dc12d8f3b9 .🚀 You could sponsor today's episode. Learn about your ad-choices.💙 Show your support for HumAIn with a monthly membership.📰 Receive subscriber-only content with our newsletter.🧪 Visit us online and learn about our trend reports on technology trends and how to bounce back from COVID-19 unemployment.About HumAIn Podcast:The HumAIn Podcast is a leading artificial intelligence podcast that explores the topics of AI, data science, future of work, and developer education for technologists. Whether you are an Executive, data scientist, software engineer, product manager, or student-in-training, HumAIn connects you with industry thought leaders on the technology trends that are relevant and practical. HumAIn is a leading data science podcast where frequently discussed topics include ai trends, ai for all, computer vision, natural language processing, machine learning, data science, and reskilling and upskilling for developers. Episodes focus on new technology, startups, and Human Centered AI in the Fourth Industrial Revolution. HumAIn is the channel to release new AI products, discuss technology trends, and augment human performance.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

The Paradox of Artificial Intelligence: Accountability, Responsibility and Ethics in Artificial Intelligence.Available for reading on Medium: https://medium.com/datadriveninvestor/the-paradox-of-artificial-intelligence-accountability-responsibility-and-ethics-in-artificial-d9b204e731f .🚀 You could sponsor today's episode. Learn about your ad-choices.💙 Show your support for HumAIn with a monthly membership.📰 Receive subscriber-only content with our newsletter.🧪 Visit us online and learn about our trend reports on technology trends and how to bounce back from COVID-19 unemployment.About HumAIn Podcast:The HumAIn Podcast is a leading artificial intelligence podcast that explores the topics of AI, data science, future of work, and developer education for technologists. Whether you are an Executive, data scientist, software engineer, product manager, or student-in-training, HumAIn connects you with industry thought leaders on the technology trends that are relevant and practical. HumAIn is a leading data science podcast where frequently discussed topics include ai trends, ai for all, computer vision, natural language processing, machine learning, data science, and reskilling and upskilling for developers. Episodes focus on new technology, startups, and Human Centered AI in the Fourth Industrial Revolution. HumAIn is the channel to release new AI products, discuss technology trends, and augment human performance.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

In this Flash Briefing, David Yakobovitch shares his insights Why Amazon's Return to NYC is Good for All New Yorkers.🚀 You could sponsor today's episode. Learn about your ad-choices.💙 Show your support for HumAIn with a monthly membership.📰 Receive subscriber-only content with our newsletter.🧪 Visit us online and learn about our trend reports on technology trends and how to bounce back from COVID-19 unemployment.About HumAIn Podcast:The HumAIn Podcast is a leading artificial intelligence podcast that explores the topics of AI, data science, future of work, and developer education for technologists. Whether you are an Executive, data scientist, software engineer, product manager, or student-in-training, HumAIn connects you with industry thought leaders on the technology trends that are relevant and practical. HumAIn is a leading data science podcast where frequently discussed topics include ai trends, ai for all, computer vision, natural language processing, machine learning, data science, and reskilling and upskilling for developers. Episodes focus on new technology, startups, and Human Centered AI in the Fourth Industrial Revolution. HumAIn is the channel to release new AI products, discuss technology trends, and augment human performance.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSKaren Bhatia is the Senior Vice President at the New York City Economic Development Corporation, leading Creative and Applied Tech strategies and initiatives to promote economic development and entrepreneurship throughout the city. Karen is also an attorney, entrepreneur and startup advisor. She was the principal of her own law firm advising tech startups on corporate issues, financing and overall business strategy. As an entrepreneur, Karen founded ActionCam, an educational platform explaining public policy issues and providing resources for people to take action. Karen also founded and is President of Stanford Startups NY, a business network of over 650 Stanford entrepreneurs and investors in the area. She is also on the Board of Trustees of Mott Hall, a middle school in the Bronx. Karen has a B.A. from Stanford University, a Master's degree in Public Policy from Harvard's Kennedy School of Government and a J.D. from George Washington University Law School.Episode Links:  Karen Bhatia’s LinkedIn: https://www.linkedin.com/in/karenbhatia/ Karen Bhatia’s Twitter:  https://twitter.com/karenbhatia Karen Bhatia’s Website: Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(03:25) –New York City Economic Development Corporation, NYCEDC, is responsible for driving and shaping economic growth throughout the five boroughs as the city's economic engine through real estate used for strategic development, building infrastructure, bringing together public and the private sector academia for all and investments in tech.(05:24) –Some reasons why New York is such an attractive place for technology: NYC access to capital, extremely diverse industries, top-notch educational facilities and organizations, an extremely vibrant startup community and the largest and most diverse workforce in the country.(09:58) – All of the industries now integrate technology and need a workforce that's well-versed in technology too. It's not just technology that's growing in New York, but also the applications that industries are leveraging there.(11:24) – Some of the new centers that have been launched in the last five years: Varick Street Incubator, The Cornell and the Technion relationship, the Data Science Institute in Columbia University, NYU's CUS program, the Urban Tech Hub, the Brooklyn Navy Yard, as well as a program at Grand Central Tech now called The Company, Future Works, The Grid, New York City Blockchain Week in partnership with CoinDesk, New York City Blockchain Resource Center and a Virtual Reality and Augmented Reality lab also located at the Brooklyn Navy Yard.(19:36) – How we ensure that New York stays at the forefront of innovation is the most critical component of all of this. There's a workforce development component of training for VR and AR technologies as well. Our strategy for technology is to think about how we ensure that tech growth in New York is equitable and inclusive. (23:30) – The New York City Center for Responsible AI, an applied research lab focused on real pilots, real applications of AI that are being developed in particular industries or in the public sector.(26:45) – New York City Center for Responsible AI is intended to come away with practical solutions for people as they're developing AI. The second component is to think about access to data. The third part is training.(33:04) – The Fourth Industrial Revolution and what's coming up, it's about how we ensure that everybody has access to opportunities, that everybody is able to maximize and realize their potential as well. The second aspect is the future of work. (39:39) – Ultimately it comes down to people first and ensuring that whatever it is that we're working on has an ethical component and is actually used for purposes that we believe in. To ensure that tech is taken to the next level that it's responsible and that it's inclusive as well.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSChris Van Pelt joined Weights & Biases as Co-Founder in 2017.Chris co-founded CrowdFlower. He was previously a technical product manager at Powerset, Inc., a natural language search technology company later acquired by Microsoft. Chris has worked as a studio artist, computer scientist, and web engineer, and pours his diverse background into his role as Chief Technology Officer. He combines deep design insight coding abilities that enables him to produce anything, sometimes within minutes. Chris studied both art and computer science at Hope College.Episode Links:  Chris Van Pelt’s LinkedIn: https://www.linkedin.com/in/chrisvanpelt/ Chris Van Pelt’s Twitter:  @vanpelt Chris Van Pelt’s Website: https://wandb.ai/site Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:55) –Enabling AI is a paradigm shift in software development. It's going to change the way that software is getting written. (02:32) – Enabling AI by opening up to the community through “benchmarks”, which are  mini Kaggle competitions, oftentimes focused around social good or something to make positive change in the world.(02:54) – Drought Watch exemplifies one of these benchmarks. It's taking satellite imagery of various drought prone regions in the world, as a call to folks in the machine learning community to create an algorithm to predict drought conditions before they happen so that we can take appropriate action and ensure that the impact on humanity is minimal.(05:58) – Developer tools for machine learning show two different approaches in the marketplace: data science as a service from data ingestion and transformation to training of models to actually deploying those models. Weights & Biases tries to create an entire platform as a service focusing on the training and experimentation around creating models. (07:59) – Figure Eight can give companies data in a highly scalable, efficient and accurate manner. Weights & Biases is a tool intended to build a model. But first you'd need to label the data. FigureEight calls it a “Human in the loop” who targets examples that maybe the model didn't do well to go back through a labeling pipeline and get labels on to further improve the model as it is being retrained. (09:56) – Companies like Google have spent tens of millions of dollars, hundreds of years of compute and processing power on working on data sets and labeling data to get it to a good enough steady state that now can outperform a human and still have Humans in the loop. It is a core aspect of any real-world mature machine learning application.(12:38) – The tooling in the space of deep learning was pretty lacking. Weights & Biases was first trying to address this issue of keeping track of what you had done and then hopefully better enabling teams to reproduce any results that had been obtained in the past. (16:13) – We're at least a few years out before we see any meaningful usage of technology, before getting autonomous.(18:42) – Computer vision started the hype around deep learning a few years back. And it's been really exciting to see the advances in natural language processing over the last couple of years. Image captioning merges both worlds.(22:50) – We are going to continue to need humans for cognitively challenging tasks such as authentication, fingerprinting and spoofing. Any time there's some underlying pattern in your data that is not getting after the core of what you're trying to predict, but instead, the systematic of something else in your data collection process, that is bias.(25:00) – Reducing bias by trying to understand data sets. In the initial training data creation and curation process, pull all sorts of statistics over various axes.And once you've created a model, measure how the outputs of that model are performing across an evaluation data center, some set of data. (27:42) – As we create deep learning models with tens of thousands or millions of parameters, it becomes really difficult to explain why any given output was chosen or what their thought process was. (29:15) – Reinforcement learning is definitely more on the frontier of ML. Some companies use Weight and Biases’ RL at least in an experimental context. (31:11) – Research trends include unsupervised machine learning use cases being able to take data that hasn't been labeled by any human and actually surface or unearth patterns simply by looking at all the data.(32:30) – Data sets are going to continue to become larger and computes is going to become less constrained. It's all about the custom hardware. Many startups are trying to make hardware chips that can do all of this matrix math really quickly and highly parallelized. Those are going to be continued innovation, and likely some big step gains as the market matures.(37:46) – Using Weights and Biases tools will help you unearth any underlying bias or issue with your model and enable you to debug it quickly. Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

How You Can Enable Modern Enterprise Data Science with Armen Kherlopian of Genpact.-Guest speaker: Armen Kherlopian, Chief Science Officer at Genpact.-Nuro.AI, based in California develops autonomous delivery vehicles.-Ride sharing companies such as Uber and Lyft, feature in the discussion.🚀 You could sponsor today's episode. Learn about your ad-choices.💙 Show your support for HumAIn with a monthly membership.📰 Receive subscriber-only content with our newsletter.🧪 Visit us online and learn about our trend reports on technology trends and how to bounce back from COVID-19 unemployment.About HumAIn Podcast:The HumAIn Podcast is a leading artificial intelligence podcast that explores the topics of AI, data science, future of work, and developer education for technologists. Whether you are an Executive, data scientist, software engineer, product manager, or student-in-training, HumAIn connects you with industry thought leaders on the technology trends that are relevant and practical. HumAIn is a leading data science podcast where frequently discussed topics include ai trends, ai for all, computer vision, natural language processing, machine learning, data science, and reskilling and upskilling for developers. Episodes focus on new technology, startups, and Human Centered AI in the Fourth Industrial Revolution. HumAIn is the channel to release new AI products, discuss technology trends, and augment human performance.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

How Human Centered Design Can Create Inclusive Systems with Chris Butler of IPSoft.-Guest speaker: Chris Butler, Chief Product Architect at IPsoft.-Lyrebird, utilizes AI to enable creative expression.-Philosophie, deals with AI engagement sales, strategy, research, and design.-Kayak, is a metasearch engine and runs multiple travel search engines.-Kevin Kelly, is the author of the book: What Technology Wants.🚀 You could sponsor today's episode. Learn about your ad-choices.💙 Show your support for HumAIn with a monthly membership.📰 Receive subscriber-only content with our newsletter.🧪 Visit us online and learn about our trend reports on technology trends and how to bounce back from COVID-19 unemployment.About HumAIn Podcast:The HumAIn Podcast is a leading artificial intelligence podcast that explores the topics of AI, data science, future of work, and developer education for technologists. Whether you are an Executive, data scientist, software engineer, product manager, or student-in-training, HumAIn connects you with industry thought leaders on the technology trends that are relevant and practical. HumAIn is a leading data science podcast where frequently discussed topics include ai trends, ai for all, computer vision, natural language processing, machine learning, data science, and reskilling and upskilling for developers. Episodes focus on new technology, startups, and Human Centered AI in the Fourth Industrial Revolution. HumAIn is the channel to release new AI products, discuss technology trends, and augment human performance.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSArmen Berjikly is an entrepreneur who has dedicated his career to pushing the boundary of artificial intelligence with special focus on emotion and empathy to work with people as they are. He created the company called Kanjoya, which was acquired by Ultimate Software around three years ago. Today he has led Product Strategy for Ultimate Software in San Francisco, and is currently a Co-Founder and Head of Product at Motive Software.Episode Links:  Armen Berjikly ’s LinkedIn: https://www.linkedin.com/in/armenb/ Armen Berjikly’s Twitter:  https://twitter.com/armenberjikly?s=20 Armen Berjikly’s Website: https://www.motivesoftware.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:48) – Being people first. People building the organization, the employees and their philosophy with a level of trust, authenticity and value placed on (04:48) – Bringing your own understanding of the capabilities of new technology and the unmet challenges in the human resource space and where solutions are(06:00) – There's a lot of things that are still unmet needs, frustrations, gaps. And what you do is you start to come upon new technologies like artificial intelligence, which is not a solution in and of itself. (06:50) –Science fiction is going to become science fact, regardless of your position on that, it's just undeniable progress that's happened in the underlying hardware capabilities. (08:56) – Being people is the first step one, but just more expansively in the world of human capital, the responsibility is too great to bring empathy into the workplace and AI and NLP could do that(09:58) – Ethical considerations with some of these new capabilities within boundary boxes, with that philosophy, to pursue some of these goals of building better products, solving customer problems(10:57) – Support ethics and AI and build technology from within (12:18) – Technology will be the solution to the problems it has created, but that's a little backwards. Sometimes you need to be more thoughtful about the problems you're going to create before you create them.(14:15) – Companies have to embrace the boundaries and the direction of their artificial intelligence approach(16:28) – Transparency is essential in the tech industry. The cavalier approach is a no-go. If you try and retrofit ethics, try and retrofit morality and responsibility in your advanced technology portfolio, It's a little too late(17:14) – The greatest risk is that AI actually takes no risks. And it's a little bit counterintuitive to think that way, but what AI is, is really a bunch of formulas, It's a bunch of pattern recognition, a bunch of math,  and it is only as smart as the data it's seen before and what it could derive out of that data.(18:48) – We have unconscious bias machines that have the ability to have that bias identified, measured, and hopefully over time, ameliorated or potentially even eradicated. You can only get there if you have extremely diverse training inputs(22:49) – Decision-making support is the worthy goal of artificial intelligence. You have to enable it to work with us and understand our problems. And so that kind of gets into the boundaries that we're starting to push with new technology.(24:22) –The only data that we'll be looking at is data that was intended to be looked at(25:47) – If technology is trying to solve really big, interesting problems or help us make big decisions, and yet is not aware, sensitive and thoughtful about the fact that our emotions matter (26:52) – Being sensitive. When we look at a piece of data, it's not just how many words were said and a word count and a word cloud, which is sort of where things go to today, but we push forward and we say: how is this person feeling?(29:16) – We have zero interest and we are philosophically opposed to the idea of machines running companies and replacing people(29:57) – Let's build technology that works for us and change the situation that we've been subject to where we build the technology, then we end up being sort of subjugated by itAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSXena Ugrinsky has spent over the last 20 years of her career in technology enabled transformation. The last eight years of those have been focused on the application of data science for corporate performance management. She has a new book titled “Enterprise AI-Your Field Guide to the New Business Normal”.Episode Links:  Xena Ugrinsky’s LinkedIn: https://www.linkedin.com/in/xenaugrinsky/ Xena Ugrinsky’s Twitter:  https://twitter.com/QueenOfDataTech?s=20 Xena Ugrinsky’s Website: https://genrexconsulting.com/                                              https://www.pilotwaveholdings.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:39) –At first technology was process optimization. Then there were better individual tools for doing analysis. So there you have spreadsheets. Analytics began to enable in the second phase the ability to do things like driver based forecasting trending analysis. And the third phase and the one that we find ourselves in today is the beginning of applying truly modern mathematical methods in the form of data science to technology(06:41) – Technology isn't the hurdle anymore, it's people, it's process, it's culture, it's organizational structure. (08:23) – Spreadsheets are too deeply ingrained in how business works (10:58) – Siloing of functions was causing a bottleneck of data that prevented executive teams from having the right information at the right time at their fingertips to make a decision(13:15) – Analytics application proliferation have become more accessible to the business community, then the IT organization completely loses control of their tech portfolio and managing costs(16:56) – The things that have to change in an organization to become an intelligent enterprise don't involve technology at all. You have to consider the people and a culture of inclusiveness that moves away from information as power to empowering everyone with the information(20:09) – Our traditional organizational structures need to be rethought. And it starts at the top with re configuring the responsibilities of the C-suite(23:15) – AI as a whole is not going to be the new spreadsheet, AI as a whole describes the transformation of applied data science(24:23) – Organizations fall into three categories: organizations built up and architected as a data company, traditional organizations that have been early adopters to solve something or to embed it in their product, and the ones that don’t know what is the right way to get started in data science(32:43) – Organic transformation: when you change people, you change the entire organization(34:00) – The winners in this race will be transforming so that their organizations are truly data-driven. If you miss this boat, you won't exist as a companyAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSMark Sears is the Founder and CEO at CloudFactory, a global leader in combining people and technology to provide a cloud workforce solution for data labeling. Their managed teams have experience with 150+ AI projects and can process data for machine learning and core business functions with high accuracy using virtually any tool, even customer-built tools. As an impact sourcing service provider (ISSP), CloudFactory creates economic and leadership opportunities for talented people in developing nations. Trusted by 140+ companies, They annotate data for 11 of the world's top autonomous vehicle companies and process millions of tasks a day for innovators including Microsoft, Drive.ai, Ibotta, and nuTonomy. They’re on four continents, with offices in the U.K., U.S., Nepal, and Kenya. His innovation drives the vision of connecting 1 million people in the developing world to online work. More than just connecting people to work CloudFactory works to develop leaders worth following men and women of high character and high competency who serve their communities. Episode Links:  Mark Sears’ LinkedIn: https://www.linkedin.com/in/msears/ Mark Sears’ Twitter:  https://twitter.com/marktsears?s=20 Mark Sears’ Website: https://www.cloudfactory.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:29) – Some good  talent is not well-connected in the global economy. CloudFactory built a technology platform to coordinate these really talented young people to connect them to the global economy(05:22) – Becoming really efficient and effective with training(05:47) – Hybrid workforce. Some of our workforces are working distributed. Some of them are working in one of our managed offices(06:52) – The Pomodoro technique for productivity(09:29) – CloudFactory exists to connect a million people to online work and we exist believing that talent is equally distributed around the world, but opportunity is not. So it starts and it ends with making sure that we are trying to create good opportunities(12:04) – It's that human in the loop that has both sides of training and augmenting that you see a huge amount of need for scalable people, people who can really do high quality work within a very tech forward friendly way.(13:39) –  Advantages related to data which is being touched by humans in the loop. When you do that at scale, because you're a tech company, you need access to a large, scalable high quality workforce(18:31) – Tool agnosticism: Customers want to own the data work tools(25:45) – Setting people up for success and selecting the right profiles and personas of people that can really get over the hump and join the digital economy(27:15) – Kathmandu and Nairobi have fully digital and English proficient talent and they are hungry and looking for opportunities to really grow and also to connect (30:05) – From the smaller startups to the biggest companies in the world, everyone's recognizing that the world is more connected than ever, and talent is all over(31:47) – Trying to train up your AI and fill the gaps of your AI and technology with inserting humans in the loop(34:22) – CloudFactory is a custom partner and is working on many different applications and ideas(36:12) – It’s becoming very effective and also more enjoyable for people to have the flexibility of being able to work from anywhere(38:26) – There's no question that the future of work is human and machine intelligence finding the right mix of bothAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSDan O'Connell is the chief strategy officer for Dialpad, and also is a member of the board. He previously was also the CEO of a real-time speech analytics and natural language processing startup TalkIQ, which Dialpad acquired about a year ago. He has held leadership positions at Google and AdRollEpisode Links:  Dan O’Connell’s LinkedIn: https://www.linkedin.com/in/droconnell/ Dan O’Connell’s Twitter:  @DialpadHQDan O’Connell’s Website: https://www.dialpad.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:22) –TalkIQ where we're building a real speech recognition engine(03:25) – Dialpad sell is designed specifically for sales organizations(05:01) – Political Marketing: Now you can use these technologies to actually quantify voters’ data(06:02) – Speech recognition and natural language processing now help you understand what's happening in those conversations and really unique ways that are going to allow you to drive better decision-making(06:58) – Google, Amazon, Microsoft, Apple,  about voice, they're really focused on consumer devices(10:31) – There's definitely a trend to more businesses being more open to having remote employees or just teams really spread throughout the world. These technologies are allowing that to actually happen(10:56) – There are definitely opportunities to build remote teams. It presents a really difficult challenges around culture and connectedness as well transforming industries(15:16) – We don't have the winning VR app yet(17:15) –  5G is going to be the game changer that we all hope it to be and expect it to be(22:09) – The beauty of open source software and places like GitHub is that you can go and learn and it doesn't cost you anything(26:56) – The landline is dying, but the telephone is not. They're trying to hold on to some of these services perhaps because of some business pressure(28:50) – People want the freedom of mobility(32:48) – AI speech recognition and LP, use these technologies to augment in-person experiences(35:40) –  if you're running a fully remote team, you really have to focus on over communicatingAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSJeremy Kaufmann has a wide variety of experiences. He started his career as a statistician and economist at the New York Federal Reserve and became very interested in looking at healthcare outcomes research. So he took his love of data, gained SAS experience at Salesforce, and then took that today to Scale Venture Partners, where he has focused his last three and a half years in the world of AI and machine learning.Episode Links:  Jeremy Kaufmann’s LinkedIn: https://www.linkedin.com/in/jeremy-kaufmann-42171370/ Jeremy Kaufmann’s Twitter: https://twitter.com/jkauf_mann?s=20 Jeremy Kaufmann’s Website: https://scalestudio.vc/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:39) – KeepTrucking integrates the mobile phone into the trucker workflow(04:26) – Cognata: a machine to  train the vehicles (05:34) – Investing in the broader world of AI is all about understanding timing risk(07:30) – Cognata corner cases: making a left-hand turn, an attempt to derive pedestrians’ intents, when to slam the breaks(09:23) – Solvvy,  a company in the conversational AI space not only answering questions, but automating actions.  (11:51) – Deflecting questions at the origin to reduce costs to respond to questions, and increase the percentage of times that a given action is taken(15:16) – TechSee, an example of international investment. Self-serve and installation, is going to be the future(18:54) – Look for verticals and industries where the promise is highest: customer pain points and ROI(20:14) – AI is fundamentally a probabilistic technology and not deterministic, meaning it's going to make errors and business buyers aren't necessarily comfortable with buying a product that's going to make errors(21:02) –  Proprietary data advantage and building a sustainable data moat. Talent as a differentiator in some of these companies.(24:14) – The world of AI to date and deep learning is all about massive quantities of data(26:01) – Overcoming Cold Start: Beging with SAS, then go to AI, publicly scraping data, offering deals and price discounts(28:19) – The real world is full of  these human complexities around gathering data. So the ability to simulate it is going to be one of the major trends for 2019 and 2020(31:43) – It's all about the business case and the economics, not only about the AI(36:05) – There are many cool technologies and robots can do different things, but it's really about where are the robots going to be most reasonable and cost-saving and business productivity driving(36:53) – The sales process in selling an AI product is hard because AI is somewhat of a black box. It's not very explainable(38:27) –  AI data moats and data network effects are not always going to drive long-term success of a business(43:59) – Conversational AI: improvements in natural language understanding and the ability to handle multi-step conversations while maintaining stateAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSEddan Katz has previously served as international affairs director at The Electronic Frontier Foundation, where he worked in advocacy initiatives at an international multi-stakeholder decision-making bodies in cyber crime, data privacy, intellectual property and freedom of expression. He was also the first executive director of the information society project at Yale law school, where he taught cyber law and he founded the Access to Knowledge initiative. Eddan has a JD from UC Berkeley, has a BA in philosophy from Yale and today he's working at the World Economic Forum on artificial intelligence and machine learning.  Episode Links:  Eddan Katz’s LinkedIn: https://www.linkedin.com/in/eddankatz/ Eddan Katz’s Twitter:  https://twitter.com/eddankatz Eddan Katz’s Website: https://www.weforum.org/centre-for-the-fourth-industrial-revolution/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:52) –The decentralized nature of our communications makes things connected together in a way that they haven't been before. And that complexity between the physical environment and the digital environment means that more and more of our daily lives are impacted by the structure and rules around how digital context and the digital network environment is governed(03:56) – The international aspects reflect the fact that our communications and our trade and our products and services don't obey the same physical borders as we're used to in other contexts(05:01) – There is a possibility of establishing some privacy norms in the US. US law is oriented towards strong privacy protection in different arenas, data privacy as a whole(07:30) – The Generation AI project is run by the World Economic Forum and the center for the Fourth Industrial Revolution, in partnership with UNICEF in regards to policy development, with developmental education and science and researchers who are working on the latest research in regards to how children can actually benefit from algorithmic and precision education(10:44) – Facial recognition project as a center for the fourth investment solution. Authentication and after the fact crime-fighting. Transparency as to how the processes are being designed and where the data goes(14:34) – People need to understand what AI is and what is different about aggregated data and artificial intelligence, machine learning and deep learning(16:28) – Understand the implications of false positives and other ways in which there are errors in information application before it gets deployed publicly (18:58) – New legislations can create havens where certain types of activity can take place. It’s important to think globally and think about harmonizing norms on a greater level(20:32) – We're developing guidelines for government procurement officials for the ethical and efficient purchasing of AI systems and algorithms(23:55) – Diversity is a key principle that makes up ethical design of AI systems an important point to carry.(25:16) – It's crucial for us to maintain the space where responsibility can still be assigned when it is divorced from human judgment and interaction becomes a unique problem(27:53) – AI in military weaponry, when divorced from the actual intent and the context of conflict, is particularly dangerous. (32:42) – There is an opportunity to move towards new and innovative uses of our emerging technology without having to consume the structures of what's already in place(33:59) – Teaching AI ethics and the responsible use of AI and social and economic considerations, and integrate that into engineering and computer science graduate programs(37:11) – We had the different stages of technology development and the one that we're currently in integrates the physical, the biological, the computational in this way, where the convergence is creating all sorts of exciting opportunities, but also social and economic challengesAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSNoelleSilver is NPR’s VP of Digital Technology. Her background includes founding the AI Leadership Institute in 2015, an organization that empowers and inspires organizations globally to begin thinking more deeply about AI offering executive workshops for defining AI Strategy, Creating an AI-Ready Culture, and more. She has founded other organizations like VoiceSkills Inc and Lady Coders. She also held program management roles at Microsoft, Red Hat, IBM and worked at Amazon in various roles within their Web Services and Alexa product lines for over 6 years. She describes herself as an evangelist that is passionate about helping women in technology rock their careers without sacrificing happiness, harmony or love. She is also excited about Conversational AI (Alexa), Mindful Leadership, work-life harmony and empowering women in tech to achieve more.Noelle LaCharite’s LinkedIn: https://www.linkedin.com/in/mindfulleadership/Noelle LaCharite’s Twitter: https://twitter.com/unitygirl Noelle LaCharite’s Website: https://about.me/noellelacharite Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:34) – Microsoft has developed a core bot, called Service Bot Framework, a single bot allowing to write once and then have it deployed on Alexa, Cortana and Google within just a few minutes(04:14) – The quick switch from text to voice. Text is a bit more mature from a natural language perspective(07:57) – Humans only need to look at the output of a model and make small verifications regarding meaning and intentions, which used to take a very long time for a human to actually manually translate, and now they're just reviewing, editing, iterating on, as opposed to building that translation from scratch(07:43) – There's a totally different kind of human benefit to language learning than just that transactional thing that AI can assist with today(11:40) – Making voice integration ubiquitous(14:49) – Unified Speech Services, the combination of speech to text, text to speech, speech authorization, and authentication. All these different services were unified into a single model(24:00) – Microsoft's Conversation Learner, cognitive services and applied AI to identify what that speaker is saying and attribute it like in a transcript, in real time(18:38) – This is not a new technology, but the fact that there have been efforts to democratize it and make it accessible as a web service is quite new(19:59) – AI is increasing the velocity of our technology and what we're able to do with it. We do have to be careful, but it's great(21:21) – The space of AI and networking opportunities: Voice Of The Car Summit, Voice Of Hospitality, Voice Of Banking Summit(26:36) – Participatory AI: AI Business School and AI school(31:19) – Democratizing things that used to be reserved for 1% of the 1% tech companies or Silicon Valley, or those very large companies in the Fortune 500(32:04) –AI not only solves business problems or tech problems, but now AI can help everyday problems. AI can help music, art, fashion. Collaboration between MIT and Met with AI(36:30) –Giving back to the community: Lady Coders and Woman in Tech initiativesAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSBrian Frumberg is the Founder of VentureOut, which launched in 2012 while working at Gotham Ventures, an early-stage venture capital fund. Its mission is to help bridge the gap between the innovators around the world and the endless opportunities available to them in the New York, the most collaborative and diverse tech ecosystem in the world. He’s also a proud advocate of of the New York City's vibrant technology community, as a speaker, mentor, a Co-Founder & President of the NYC Innovation Collective, member of the FWD.us Innovation Council, and as the Founder of the Chaminade Alumni Entrepreneurs Association. Through VentureOut, the NYC Innovation Collective and FWD.us Brian connects with thousands of thought leaders, entrepreneurs, investors and aspiring innovators from across the planet.Episode Links:  Brian Frumberg’s LinkedIn: https://www.linkedin.com/in/brianfrumberg/ Brian Frumberg’s Twitter:  https://twitter.com/BrianFrumberg Brian Frumberg’s Website: https://ventureoutny.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:56) –CzechInvest is an innovation platform and an accelerator trying to create more efficiency in the global venture ecosystem, by providing opportunities for the most promising innovators and startup founders around the world to gain access to all the opportunities available for them here in New York City and the broader US ecosystem. (03:36) – The venture ecosystem, both in New York and around the US, needed a bit of education on how they should be considering foreign startups in the same way they consider startups that maybe don't today meet their criteria(08:06) – The idea of immigration reform is important. There's not a pathway for entrepreneurs to be able to get to the US market. The instance of entrepreneurship among immigrants is two to three times that of native born Americans(11:07) – Almost all the capital lives in the US and it doesn't invest outside the US(12:35) – VentureOut creates opportunities for companies to get access to the biggest consumer and enterprise marketplace and the biggest venture funding ecosystem on the planet, bringing them to the US(14:31) – Immigration reforms and the work of Fwd.us. We should be focused on this competition for talent, on creating pathways for innovators and doctors and people that have higher degrees in STEM fields to be able to come to the US(20:58) – Should the US have policies more similar to what you see in Europe, it would enable so many more women to be active in the workforce and it would add over 10 years over a trillion dollars to the US economy(26:13) – The EDC is technically a nonprofit that manages both the real estate portfolio of New York City, which is 80% of the work of the EDC, as well as the economic development work to try to diversify the economy of New York away from its real reliance on financial services and Wall Street into other industries that they viewed as the industries of the future, like tech and innovation(36:28) – Within the startup practice of sector programs, VentureOut has been running AI programs with the NYU Future Labs for the last couple of years. It is a very AI machine learning driven program, trying to help these companies blow up their network of real thought meters, and advisors and corporates and investors in the AI ecosystem in New York CityAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSDr. Michael Capps is a well-known technologist and CEO of Diveplane Corporation. Before co-founding Diveplane, Mike had a legendary career in the videogame industry as president of Epic Games, makers of blockbusters Fortnite and Gears of War. His tenure included a hundred game-of-the-year awards, dozens of conference keynotes, a lifetime achievement award, and a successful free-speech defense of videogames in the U.S. Supreme Court. Mike began his career with postgraduate degrees at UNC, MIT, and the Naval Postgraduate School; for his research in VR, he was featured in SIGGRAPH’s historical documentary on computer graphics. He remains a regular host of multiple television series on the Discovery and Science Channels. Episode Links:  Dr. Mike Capp’s LinkedIn: https://www.linkedin.com/in/mikecapps/ Dr. Mike Capp’s Twitter:  https://twitter.com/solidfog?s=20 Dr. Mike Capp’s Website: https://diveplane.com/  Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:33) –Gaming is a hobby industry that has turned into a massive industry. A really interesting space dealing with rapid onset of AI, just like every other technology businesses(03:15) – Explainable AI and understanding AI and for consumers this is often quite challenging. The education systems in China or Finland put base level understanding of what AI is and what it can do (04:20) – Academic pursuit is important, but it comes down to a mix of nurtured talent and a set of skills that you could get at home, and that shifted into world design(06:45) – There's AI already built into the unity engine that you can use to drive avatars. It is a “democratization of capability”(09:49) – Dr. Capps’ advises: Get enough sleep and ‘throw away the first pancake’(12:23) – Educational games open up the technology to academia, to use for nonprofit projects. The focus at Epic isn't uneducation, but to facilitate more user created content(14:05) – Education comes from engagement, and if you don't understand what engages people, you can't educate. It's understanding what it is that is going to connect with that audience(14:46) – Diveplane: trying to build an open framework for interchange in VR, AI and super intelligence. Chris Hazard’s tech is specifically designed to explain step by step why it worked and then help figure out how to beat that, and we apply it to the commercial sector(17:38) – Empowering consumers is based on the best data we had with no intention of bias. It'll show the most important features, not overall a data set. It technically catches the bias that's happening systematically inside of a system and then try to provide contra positives(21:08) – Facial Recognition Systems are not perfect and they tend to have clustered errors. Banning this technology might be making a mistake in the name of freedom against security(23:43) – Data itself isn’t the problem, but the use for good or ill(25:15) – Diveplane has traceable auditability in their technology, but their focus is on human understandability(29:59) – Games are just one example of an adversarial approach to machine learning(33:28) – Cannons are maybe less hackable than certain neural nets. When you can really generate creative ideas mathematically it's a dramatically beautiful framework(36:18) – Synthesizing entirely new data sets to train up a machine learning model and then generate new data points that could theoretically be within it and what that lets us. A clean private data out of a data set(38:41) – We're so rapidly grabbing onto technology solutions that seem to work and as soon as it works enough, it's thrown into production(41:06) –The paradigm in Cybersecurity will not shift to AI powered defense being better than AI power to tech Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSAlberto Todeschini is a Faculty director, consultant and lecturer in artificial intelligence. He has supervised over 150 projects covering a wide variety of industries and techniques, with a special focus on sustainability in energy and water. He also works with the University of California, Berkeley, GetSmarter, and aivancity. Episode Links:  Alberto Todeschini’s LinkedIn: https://www.linkedin.com/in/atodeschini/ Alberto Todeschini’s Twitter:  Alberto Todeschini’s Website:  https://www.ischool.berkeley.edu/people/alberto-todeschini Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:59) – Cultural difference in cultural attitudes about privacy and concerns that exist in some locations in Asia(02:51) – Difference in attitudes to freedom of speech in Europe and in the US: Americans value freedom of speech less, and it's something similar with privacy. To take privacy seriously on a global level we need to talk to people from around the world and understand that population density, economic growth, and other factors are very important(05:27) – One of the challenges about AI being merged into business is interpretability. If you can't interpret and explain your algorithms to your investors, you may have a hard time. You may choose something that works a little less well, but it is a lot easier to interpret(10:13) – There's a certain technical proficiency that doesn't have to be extraordinary. Involving the experts to solve real problems(14:56) – The dangers of AI. Weaknesses in classification systems susceptible to attacks, either by misfire or potentially more vicious. We are moving into a world with hundreds of millions, billions of gadgets that do machine learning in houses, in hospitals, on army bases(21:01) – Generative Adversarial Networks and a way to be protected from attacks(25:45) – Fake News.We are not going to be able to trust our unaided human consensus with anything that comes to us digitally(29:43) – There's more time and ability allowing us it's increasingly feed different types of data into a single system. That's why the overall system works better to feed different modalities of texts into data, into our algorithms and for users, it will get richer products and richer experiences(34:03) – Augmented human intelligence. Creating experiences where data science and machine-driven learning is able to augment user experience and create better solutions for societyAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSDr. Travis Dirks is CTO at XLabs, building moonshots powered by artificial intelligence (AI), quantum & neurotechnology. Prior to XLabs, Travis was co-founder and chief science officer of Seldn, an AI that could accurately predict rare global socio-economic disruptions in 12 countries. Travis led the team at Seldn to predict ‘black swans’ such as labor strikes, jumps in commodities & currencies, and societal riots four months before they happened with 95% accuracy. He connects complex science and math to challenging business problems and designing new software solutions with AI. Travis has pioneered several AI algorithms and new approaches to engineering moonshots and novel breakthroughs, including ‘Mental Model Arbitrage’. Prior to Seldn, Travis co-founded and led Rotary Gallop – a machine learning fintech firm that applied game theory to corporate control (for M&A, hostile takeover, and activist situations). Travis’s analyses and quotes have been heavily featured in popular media, including the Wall Street Journal and New York Times. Travis received his PhD in Nanotechnology from the world’s leading institution for condensed matter physics, University of Illinois at Urbana-Champaign, and holds a B.S in physics from Purdue University.  Episode Links:  Travis Dirks’ LinkedIn: https://www.linkedin.com/in/travisdirks/ Travis Dirks’ Twitter:  https://twitter.com/TravisDirks Travis Dirks’ Website: https://www.travisdirks.com/   https://xlabs.ai/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:49) – For XLabs, moonshots are those startups which change your perception of what's possible. It should push out the boundaries of possibility(02:58) – XLabs’ goal over the next 10 to 15 years is to develop start-ups in each theme to change the aspects of the world in three categories: amplifying genetics, creative destruction of the internet and culture as a technology(04:16) – Uber, self-driving and state-of-the-art technology to shy away from uncomfortable things and interact as people.(07:01) – XLabs trends include X-core, a metal learning AI engine pipeline that learns to build other AIs and genetics data to predict cancer(08:56) – Mental Model Arbitrage is essentially the idea of going to other fields, intentionally seeking out their best ideas, their best models, their best tools, intentionally generalizing them to see where else you can apply them(11:17) – AI is on the verge of great things that don’t happen as fast, because of trying to show that an algorithm could do what someone thought it would do as opposed to being built with the assumption that it will do its job(12:50) – AI is essentially the attempt to duplicate things that come easy to human beings. We're more interested in the space of things that are not easy for humans or computers, and it’s called Amplified Intelligence(15:54) – X-core is really an evolution. Rebuilding in a more general way an engine that allowed us to make stunning predictions about rare events such as labor strikes, commodity prices, violence break outs through complexity physics or “mining of human knowledge”(18:39) – Why investment in research for moonshots is not as high(21:42) – The XLabs purpose for a moonshot company in a nutshell: be driven, develop something relevant to AI, machine learning or cloud computing, breadth of interests and  surprisingly rare skills(23:37) – The allegory of the showman and the artist in the entrepreneurial scene(29:41) – Dirks’ recipe for achieving great thingsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSTara Chklovski is CEO and founder of global tech education nonprofit Technovation (formerly Iridescent). Prominently featured in the award-winning documentary Codegirl, Forbes named Chklovski “the pioneer empowering the incredible tech girls of the future” and Discovery Science Channel named her its first “CEO Science Super Star Hero” for her work encouraging the next generation of innovators, problem solvers, and game changers. A frequent advocate for STEM education, she’s presented at the White House STEM Inclusion Summit, SXSW EDU, UNESCO’s Mobile Learning Week, and led the 2019 education track at the UN AI for Good Global Summit. Since founding the organization in 2006, Technovation has welcomed more than 130,000 children and parents, and 14,000 mentors, to participate in its programs in 100+ countries.Episode Links:  Tara Chklovski’s LinkedIn: linkedin.com/in/iridescentTara Chklovski’s Twitter: TaraChkTara Chklovski’s Website: https://www.technovation.org/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:32) – The AI Family Challenge is the first program for children and parents. Families can gain a better sense of how their world is being shaped by AI and in a very practical way, bond together and learn about different AI technologies(03:39) – Communities that are not empowered by technology can still have the best ideas, even without the software being at their hands. These are people that are curious about their world.They’ve heard about AI, but not in a way that is accessible or that invites them to be part of the conversation(06:32) – Encouraging the entrepreneurial mindset in these communities around the world to replicate innovation, where each individual can have a stronger voice, can have a stronger influence, a stronger sense of agency(08:06) – These communities are very similar, despite pretty large differences in socioeconomic status: very low human development indexes. But the interesting commonality is that each one of these participants are risk takers. Very few people would sign up for an AI education competition(10:00) – Over 95% of the parents think that their child is capable of creating something that's AI based in the future(12:29) – Technovation challenge is a program running for nine years across more than a hundred countries, for girls who find problems in their communities and create mobile apps to solve them. They work not with their parents, but with mentors (13:38) – Around 50% of its effort goes into collaborations with the local government, which provides some degree of support in terms of infrastructure or access to the internet, or the data is not that expensive.10% of these efforts are in countries where there's absolutely no support system(16:10) – Iridiscent’s mission is to work with groups that have typically not had access to resources and opportunities and to empower them, that they can be leaders, but using technology, which is an amplifier(16:39) – Diversity of thought is the key. Intellectual diversity and the perspectives that you bring and the training and the experience that you've had(17:57) – Hiring, retaining and attracting talent that can be intellectually at the same caliber. No matter their background, especially from other privileged countries and frontier communities. It's not about whether you're black or brown or white but how to build or develop self-driven learners(19:51) – Self-motivated learning and how you drive resilient, long-term interest in technical content (22:11) –The keys to self-motivation: exposure to someone who you respect, experience, excitement and video games, energy (28:30) – It takes a tremendous amount of effort to find these partners, to train them, to run the program on the ground, to build a sense of community and then to come back next year and to continue the momentum. This is a complex social issue with multiple factors.(29:22) – All these different countries that have gone through a common experience. And that's the power of technology. That brings people together that would never have come together.(32:35) – Ethics involves thinking deeply about the product that you're building. Developing your own self awareness. Normal human individuals who would never be product innovators and developers are now being asked to develop products that go and touch many people. (36:47) – The partnership between humans and AI needs to be a global conversation. Empowering participants to be more creative, more innovative. To support students in thinking more creativelyAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSJed Dougherty is the VP of Field Engineering at Dataiku. He specializes in helping companies construct enterprise-grade data platforms and has helped teams around the world build successful production infrastructures across the various clouds and on-prem. He holds a master’s degree from the QMSS Program at Columbia University and Degrees in Mathematics and Political Science from Arizona State.Episode Links:  Jed Doughtery’s LinkedIn: https://www.linkedin.com/in/jediv/ Jed Doughtery’s Twitter:  https://twitter.com/dataiku Jed Doughtery’s Website: https://www.dataiku.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction.(02:03) – Making AI and Data Science relatively easy to use instead of limiting it to a few smart dudes encourages a more evenly distribution of the power that comes from it.(03:27) – Google and Amazon want to keep control of the actual algorithms. (04:37) – No big company in America, except Google, Amazon, Facebook and Netflix is able to hit the median income for their data scientists these giants have, which means they have a different pool of talent to pull from.(07:22) – Universal Basic Income as a solution for a feasible future of jobs being replaced as a result of automation.(12:27) – Empathy mapping to design AI systems to be diverse, inclusive and trained for multiple scenarios. AI has been about prediction and not an explanation of these predictions. Models should be more explainable than accurate.(13:02) – Some of the new product lines for the explainability of an AI built by Google and Amazon .(17:08) – Pushing the power back to the user immediately to empower them to have decisions driven by AI. (11:53) – AI governance and ethical decision-making. If you don't have people connected to the things you're trying to predict, it's easy to miss a trend to assume that you have complete data when you do not.(20:29) – Fair AI systems: labels are generated by humans, which means they have all the failures and foibles of our current society. Pushing those into a model makes that model exactly as good as our current society or worse. (23:06) – We overestimated human enthusiasm for autonomous driving.(28:51) – Computer centralized systems are weak. If Google, Amazon and Facebok were one single company, they would have this complete idea of your life and be able to predict every moment of it and say, how much of a worthy individual you were to society.(32:35) – In NYC, people from all walks of life run into each other, touch each other accidentally. Nobody owns New York. You have the people who are gonna be affected by AI, the business knowledge and a growing tech base of folks who can implement technology. NYC could be the center of machine learning.(36:22) – Linux command line is running 99% of the servers in the world right now(38:32) – Knowledge to become tech-relevant: this is such a new industry that 10 years at school, you may have learned 5% of the industry.(43:03) – Humans and the machines. Things from an ethical perspective or a human perspective combined with technical knowledge.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSJohn Spence is an author, international executive coach, professional development educator, virtual trainer, strategic planning facilitator, keynote speaker and developer of online learning programs. John is recognized as one of the top business thought leaders and leadership development experts in the world and was named by the American Management Association as one of America’s Top 50 Leaders to Watch along with Sergey Brin and Larry Page of Google and Jeff Bezos of Amazon. As a consultant and coach to organizations worldwide, from startups to the Fortune 10, John is dedicated to helping people and businesses be more successful.Episode Links:  John Spence’s LinkedIn: linkedin.com/in/johnbspenceJohn Spence’s Twitter: AwesomelySimpleJohn Spence’s Website: https://johnspence.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction.(03:45) –  Technology is impacting not only the financial industry, but every industry there is.(04:41) – Major trends that are impacting business: computer speed, which leads to big data, Artificial intelligence, robotics, virtual reality, augmented reality, synthetic medicine, genetic decoding and recoding.(06:57) –Technology is evolving. A lot of industries are taking off virtual reality, augmented reality, AI and FinTech.(07:45) – Monsanto: from agriculture and farming to Big Data.(09:09) – Ubers for harvesters in Australia. Get on the app, order the harvesters, the harvesters are brought to the field and they're all autonomous.(11:00) – All strategy is just valued differentiation, multiplied by disciplined execution.(11:30) – Bring something unique and compelling to the marketplace that your target customer wants to buy, impossible for your competition to copy and that you can execute on flawlessly and consistently.(11:53) – Required criteria for success in business: the quality of the people in your company, the relationships you have with your customers, the strength of your brand, the data you have collected on your customers in the industry with the caveat of how well you deploy that data.(13:08) –  Data that will allow to significantly increase competitive advantages in the marketplace.(14:33) – Businesses are going to change through automation, through AI, through big data.(15:25) – Intelligence Quotient, Emotional Intelligence and Agility Quotient.(19:15) – All the technology, all the leadership, all the business models, all the strategies are focused on one thing only, to satisfy your customer. (28:58) – The three wheels of the Hedgehog Concept: high technical expertise, passion  and a strong economic driver in the marketplace.(24:10) – “Adjacent news” to anticipate the market.(29:42) – Technology is going to outrun our ability to keep up with it.(33:35) – Younger people coming into the marketplace look for stability, dignity and purpose.(39:13) – Committing yourself to Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSKristen has been ranked #8 Global LinkedIn Top Voice in Data Science & Analytics. She has 10 years’ experience in data science delivering innovative and actionable machine learning solutions across the eCommerce, healthcare, & utility industries. Kristen is currently an instructor at UC Berkeley Ext. teaching Practical Data Science in collaboration with Emeritus Institute of Management, holds an MS in Applied Statistics from Worcester Polytechnic Institute and a BS in Mathematics.Episode Links:  Kristen Kehrer’s LinkedIn: https://www.linkedin.com/in/kristen-kehrer-datamovesme/Kristen Kehrer’s Twitter: DataMovesHer Kristen Kehrer’s Website: https://datamovesme.com Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:39) – Remote learning environments are the world of Work 2.0(03:33) – Many people believe Data Science means working remotely, but you need to build reputation and experience first(05:41) –Education and work are moving towards remote environments but we’re not completely there yet(08:18) – Working remotely simplifies busy schedules. It's a model that works for people and the lives that they've built(11:49) – Without diminishing the experience of being able to learn on campus and build real relationships, online learning is very useful for professional development (13:46) – Saving for future education requires financial advice, considering the college admission scandal and changing world conditions(17:21) – Models must be interpretable. AutoML does not allow to set parameters(18:38) – Some tasks can be automated by interpreting these AutoML models and some others should be done manually, depending on the factors to be determined by them(19:29) – Dehumanization by automation: products that we're using each and every day implementing AutoML or auto AI solutions.(22:29) – There will always be a need for analysts who have business context and understand how variables interact(23:28) – Data science, the beginning of machine learning, is the foundation that helps get into more advanced algorithms(24:45) – Stop learning and start applying to positions. Get feedback from the market in order to know what skills or gaps you have on your resume that keep you from getting a job in the industry. Work your way up.(28:14) – We're living in a data-swamped life among devices, information and messages that are distracting (29:40) – Defining the role of a Data Scientist is quite complicated. People trying to get into the industry, data getting bigger, tools getting easier. Things are becoming more automated. Data is the ‘new oil’(33:41) – Data Science is going to focus the highest priority on the objectives that are going to result in the highest ROI(35:15) – A data-obsessed culture that wants every single decision to be made on data. And it does not need to be used for everything, if it's not actually going to inform what it is that we're going to doAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSLex Sokolin is Global Fintech Co-Head and Head Economist at ConsenSys. He is a New York & London entrepreneur with senior operating and board-level Fintech experience in blockchain, digital investing, and wealth management. He founded the Fintech practice at Autonomous, a financial services equity research firm, where he focused on artificial intelligence, blockchain, and mixed reality. Episode Links:  Lex Sokolin’s LinkedIn: linkedin.com/in/alexeysokolinLex Sokolin’s Twitter: LexSokolin Lex Sokolin’s Website: https://www.lexsokolin.com/Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:12) – Banking, investing, lending and insurance, which used to be intermediated by human beings, are now targeted by artificial intelligence companies. (04:09) – The digitization of all the industries from media to retail to now finance and healthcare.(05:14) –Machine Learning on top of large data sets. Services that used to be physical now have digital chassis that create data exhaust.(06:28) – Removing humans and running on autopilot makes it way cheaper and more accessible to manufacture a financial product. (09:12) – Mobile apps usage rises because phones are more distributed than banking services.(11:07) – 800 million or so users in China power the engine for the algorithmic decision-making for credit there.(12:30) – Free internet costs your data, your money or tracking of your behavior.(15:35) – Chinese model is successful because fixed costs of research and development are covered by government spending, and the U.S is fairly disadvantaged in that regard.(16:13) – Asymmetrical markets are controlled by very few players. Capitalism allows for that sort of selection mechanism to occur. The other option is decentralized direction, which is less profit-driven and more humanistic.(22:16) – Low marginal costs is the direction that we're moving towards from a macro level, driven by lower cost manufacturing and lower cost distribution.(24:05) – Finance jobs are threatened by automation.(28:40) – Encourage venture capitalism for innovation and risk-taking by the population.(34:36) – Distribution of wealth and income are getting more unequal because of unassailable structures of society.(38:21) – The internet age accentuates inequality. The large tech firms trend towards monopoly.(42:19) – Mental health tactics to keep at baseline(42:55) – A system that manufactures anxiety. Scientists develop newsfeeds to break down your behavioral defensesAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSBrett Greenstein is a Senior Vice President and Global Head of Artificial Intelligence at Cognizant. His experience in the Internet of Things, technology consulting, solutions in banking, healthcare, customer service, and retail with organizations include IBM and many Fortune 500 products.   Episode Links:  Brett Greenstein’s LinkedIn: https://www.linkedin.com/in/bretgreenstein/Brett Greenstein’s Twitter:  https://twitter.com/bretgreenstein?s=20Brett Greenstein’s Website: https://www.cognizant.com Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction.(04:12) –How technology immerses our lives and the internet reaches every corner.(05:51) – The chinese pace to adapt to changes in technology versus the slowness of the US.(07:57) – Technology integration might become a liability. (10:28) – IOT and technology as a game of forces between the US and China.(13:34) – 5G opens up massive potential for communications.(19:45) – HTML geeks are now strategists who use data and to make companies be more digitally centric, AI-powered.(24:00) – Cultural and transformational change of a business is inhibited by the power structures. (29:01) – The human touch to an AI system is critically important for its acceptance and adoption.(31:23) – AI is transforming industries.(40:55) – Breakthrough devices are going to be health-related. Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio]  Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSST. Scott Clendaniel is an Artificial Intelligence Pioneer with 35 years' proven track record of ROI improvements. He’s also a Guest Lecturer at Johns Hopkins University and University of Maryland, Harvard Innovation Labs’ Experfy, Artificial Intelligence course author and the Chief Data Officer of the Board of Directors at Gartner/ Evanta (DC region) Episode LinksT. Scott’s LinkedIn: https://www.linkedin.com/in/tscottclendaniel/T. Scott’s Twitter: https://twitter.com/Strat_AI?s=20 T. Scott’s Website: https://www.boozallen.com Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:43) – The pace of advancement has changed but problem solving leans more towards software development than problem solving itself.(03:18) – Deep learning can’t provide solutions unless data is applied beyond the models.(05:38) – Model building must be fully interpretable to be able to be fixed if needed(07:15) – Protecting the rights of consumers and increasing the requirements on transparency of the models.(12:55) – Ethics groups, reviewing policies and the “adverse impact test” for algorithms.(15:46) –Overestimating AI's impact in the future of work.(16:49) – Automation and augmented intelligence: humans using computers to solve existing problems, as opposed to being replaced by them.(21:22) – AI applications in specific industries for specific problems, focusing education on the good and the bad in AI.(25:10) – Sharing the "wealth of knowledge" about predictive analytics.. (27:09) – Open sourcing education so that anyone can learn how to build and use models that are going to impact them.(31:06) – New research on algorithms to find advanced sophisticated solutions to problems.(34:07) – Data in general and Artificial Intelligence, specifically, can be used in good ways or detrimental ways.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSJohn Lynn is the Co-Founder of Cela, an Accelerator in NYC. He has worked closely with acceleration at places like Studio Project and Techstars, which represent a new kind of educational model. John has been involved with many innovation, acceleration and incubator programs. Episode Links:  John Lynn’s LinkedIn: https://www.linkedin.com/in/jayeffelle/John Lynn’s Twitter:   https://twitter.com/jmlynn7?s=20 John Lynn’s Website: https://about.me/jlynn Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:41) – The trends and patterns in innovation are set by New York City as a tech capital.(02:37) –  New York City’s tech ecosystem invites more participation.(06:47) – New York City is the capital for crowdfunding.(11:01) – Better access to education make NYC a place for innovation.(12:59) – The rapid change and growth of NYC due to the rise of technology.(16:43) – The virtualization of education as a shift in Accelerators’ models.(22:08) –  NYC has unique elements that make it a tech capital demographically and for business. (24:30) – All sorts of capital investments make NYC the best place at the best timing. (26:54) – The Global Accelerator Summit will be scheduled soon.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSDr. JT Kostman is a data scientist, mathematician, and psychologist. He is widely regarded as one of the world's leading experts in applied artificial intelligence and cognitive computing. JT has hunted terrorists for the U.S. intelligence agencies, tracked criminal networks for the FBI, advised the Department of Defense on analytic strategies and led social media analysis for the 2012 Obama campaign. In the corporate sector, he served as Chief Data Officer and member of the Executive Committee for Time Inc. and as Chief Data Scientist for Samsung. Prior to attending graduate school, JT served as a paramedic, police officer, deep-sea rescue driver and team leader of a U.S. Army Special Forces scout/sniper reconnaissance team. JT received a PhD in psychology from City University of New York an MS in psychology from Baruch College and did post-doctoral research on nonlinear Dynamical Systems Theory at Moscow State University of Economics, Statistics and Informatics (MESI)Episode Links:  Dr. JT Kostman’s LinkedIn: https://www.linkedin.com/company/protectedbyai/Dr. JT Kostman’s Twitter: jt_kostman Dr. JT Kostman’s Website: https://protectedby.ai/  Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(01:47) – The trends in the consumer space keep being 5G, virtual reality and quantum computing.(02:23) – Diversity is not just needed, but essential to our success. Most industries do little to truly accommodate,welcome, incentivize and attract a more diverse and more heterogeneous population into tech.(04:35) – Minorities portrayed in the media are editorial selections. The seats of power, keep being in hands of white males.(05:36) – We need to think beyond traditional concerns of gender, of ethnicity. We need to start talking about neurodiversity. We need to start talking about a difference of perspective. (06:26) – Fast growing demographics are not wholly represented within technology.(08:27) – Cognitive diversity needs to be transferred over into AI startups and AI applications. (09:57) – Diversity of thinking has really contributed to each of the organizations. And that's what we need need to be able to better communicate to the rest of the field.(211:57) – Brain power and diversity of cognitive thinking is it's going to start with humans, training humans in essence, to think diversity-first.(12:35) – Artificial intelligence and machine learning has, in its current incarnation, been coded by white men “teaching the machines to do what white men do”.(15:10) – The things that make us quintessentially human; Empathy, caring, wisdom, perspective, equanimity, patience. Let machines do what machines do, and let us be left to be human.(16:27) – The lost generation 2.0.(19:09) – Multiculturalism and neurodiversity.(20:12) – HR teams do not assess technical fit, but cultural fit. People who have a diverse perspective are not going to fit into that common mold.(24:52) – The Dunning Kruger effect and the skills assessed by the Industry. (26:41) – Symbiotech means people and the machines partnering most effectively, how in an almost transhumanist perspective of how do we work symbiotically with the machines so that both end up being able to do better.(27:28) – The Great Tech Debate, a dialogue with all the great thinkers, citizenry, consumers, whose voices will be included in these conversations. (28:43) – We should talk about technology. The implications, applications, ramifications, data privacy, the petroleum problem, the economic implications of artificial intelligence and the impact that will have on jobs.(30:05) – We need to reclaim the ability to actually hear other perspectives, other attitudes, other beliefs.(32:01) – AI is not going to run a mocking and kill us all. We need to stop worrying about silly things and take that same energy and worry about climate change, how joblessness is already impacting such a large segment of the population, the economic implications of artificial intelligence.(32:22) – We need to democratize talent more. That leaves us to worry about things like immigration and writing.(35:58) – We have to stop abrogating our responsibility to the leaders of the tech companies or to the politicians.(37:01) –Every citizen needs to know how to code. Technology is going to change the world and every aspect of it. “Edutainment”, something that teaches you and entertains you.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSSameer Maskey is the Founder & CEO at Fusemachines, a services and solutions provider on a mission to democratize AI. He is also an Adjunct Associate Professor at Columbia University. Sameer holds a PhD, a MPhil & an MS in Computer Science from Columbia University and a BS in Math & Physics from Bates College.Episode Links:  Sameer Maskey’s LinkedIn: https://www.linkedin.com/in/sameer-maskey/Sameer Maskey’s Twitter:   https://twitter.com/sameermaskey Sameer Maskey’s Website: http://www.sameermaskey.com/                                                 https://fusemachines.com/  https://www.fuse.ai/  Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction.(01:42) – Fuse.ai Scholarship program intended for underserved communities to democratize AI.(04:55) – AI should be a global opportunity. Lots of companies are trying to build AI systems and there's not enough AI talent.(06:30) – Neural networks have come back in full force with deep learning to build solutions in computer vision, NLP, and others.(07:46) – AI, ML and Deep Learning, made simple.(10:06) – Neural networks and the human brain functions. (11:24) – We’re still far from making computers use data to process it like a human being.(14:09) – Fusemachines is working on medical dental medicine delivery in Nepal, and  various language recognition systems, speech recognition systems and dialogue systems. (16:25) –In spite of research and advancements in translation systems, language learning is not redundant yet.(17:22) – New breakthroughs will be in language translation systems with data collected from the tech Giants.(19:04) –  Job automation will happen, so people should learn about AI, Machine Learning and computer science.(21:27) –  Self-driving cars will be transformational for the way we travel.(24:03) –  Chatbots are useful for reducing the customer service load, but cannot completely replace customer service reps. (26:29) – Global recession might slow down investments into AI-related businesses, but if otherwise, AI will keep pace with it, or actually outpace economic growth.(28:47) – Fusemachines and Fuse.ai  will have wide-world impact by training AI practitioners to solve some of the biggest challenges humans face.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSOliver Christie is the Co-Founder of Voltare Consulting. He has a degree in Mathematics, Economics and Fine Art from Peter Symonds College, Winchester, UK and a BFA in Fine and Studio Arts from University of SoutHampton. His experience includes working in the Financial, Media and Transportation sectors, and using technologies such as IBM Watson, Microsoft Azure, Google Tensorflow, H2O.ai and Intel.Episode Links:  Oliver Christie’s LinkedIn: https://www.linkedin.com/in/oliverchristie/Oliver Christie’s Twitter: https://twitter.com/OliverChristie?s=20Oliver Christie’s Website: https://oliverchristie.com/Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators  – Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:08) – Automation means men and machines working together.(05:55) – People’s skills and the need for a more human technology.(07:05) – Technical education for a more inclusive workforce.(10:57) – The need for Government policies to regulate optimization through AI.(15:56) – Building more human connections through Technology.(23:08) – People are a company’s best asset to leverage true changes through technology.(23:34) – Real success is not only technological advancements. Humans need connection, family and personal growth.(30:15) – Changing the model for automation to make it more human-centric. (31:55) – AI Transparency for consumer-focused products.(34:18) – Human-centric AI tools, Data and technology for human development.Advertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy