Technology
Business
Second Brains and Soft Skills for Staff Engineers. Augment, Stay Human.
AI can't replace you. But you need to adapt how you work. Augmented Engineers invest their time in learning, thinking, creativity, and soft skills. They leverage AI tools for what LLMs are good at - distillation, retrieval, boiler plate generation. While they focus on amplifying their unique, human strengths - thinking, creativity, empathy. Hosted by Chris Lettieri, a Staff Data Engineer optimizing large time series datasets for deep learning, the Bits of Chris Podcast is the show for Staff+ engineers interested in deep learning, soft skills, building their second brains, and amplifying their humanity to future-proof their careers. Follow along to become an Augmented Engineer. Remember - Augment, Stay Human. bitsofchris.com
Total 47 episodes
1
01/11/2024

Impactful Listening & Effective Onboarding | Sophia Sithole, Founder Ofstaff

In this episode, I talk with Sophie Sithole about her journey building Ofstaff, an AI-powered onboarding and performance management solution. We explore the challenges of effective employee onboarding, and get into a deeper discussion about customer development, active listening, and handling vulnerability in business.Key LessonsEffective Onboarding* Alignment and clear expectations between all parties are crucial* Communication is fundamental at every stage* Both employer and employee have important roles to play* First few weeks are critical for successProduct Development & Customer Research* The "Mom Test" approach: Focus on learning about the customer's world rather than pitching your idea* Distinction between product-market fit ("painkiller vs vitamin") and go-to-market fit (how to sell/distribute)* Importance of seeking to invalidate assumptions rather than validate them* Value of looking for specific examples when customers claim something is usefulEffective Listening & Research* Pay attention to when people pause to think - it often indicates deeper insights* Ask for specific examples to validate claims* Focus on understanding impact across teams/organization* Practice active listening and genuine empathyHandling Vulnerability in Business* Embrace vulnerability as a pathway to learning* Focus on the "why" behind what you're doing* View challenges as learning opportunities* Balance passion for ideas with openness to pivotLinks* Ofstaff* https://www.linkedin.com/in/sophiasithole/ Timeline[00:01:00] - Exploring how alignment and expectations are crucial for successful onboarding [00:04:00] - Discussion of shared responsibility between employer and employee in onboarding [00:06:00] - Introduction to UpStaff and its focus on sales team onboarding [00:09:00] - Deep dive into how AI can distill and personalize onboarding data[00:13:00] - Exploring AI-powered course recommendations and learning pathways[00:16:00] - Discussion of bootstrapping journey and product development [00:17:00] - Understanding the difference between product-market fit and go-to-market fit [00:20:00] - Introduction to the "Mom Test" and effective customer research [00:25:00] - Importance of empathy and active listening in customer discovery[00:30:00] - Discussion on why seeking to invalidate ideas can be more valuable than validation[00:32:00] - Exploring vulnerability in business and product development [00:35:00] - Wrapping up with insights on learning mindset and personal growth This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
37m
19/10/2024

I just built my first Neural Network: Here's my framework for learning in public

I recently joined a research team building time series Transformer models and have become infatuated with the field of deep learning.As a former trader, turned data engineer, I am now trying to understand the AI side of things. And this week I just hit my first significant milestone: building my first neural network from scratch, using no machine learning libraries. Today, I want to share this milestone and offer you my framework for how I decided to learn deep learning in public.(Here’s my GitHub repo and the XOR neural network).The Key: Invest in the basicsKnowledge compounds over time.When you understand the basics well, you gain the freedom and flexibility to explore more advanced concepts creatively.You have a strong foundation to build upon.Taking the time to stop your task and go look up something you don’t quite know, especially if it’s something foundational that you will see again, is an investment in your future self.This is the key concept to understand to unlock the value of life long learning.When you see the compounding effect of knowledge - you look for opportunities to know something well, to learn it deeply.Slow down, and focus on the fundamentals.Why I love learning in publicI've chosen to share my notes and code for this learning project on GitHub.This "learning in public" approach is better than learning on your own, but it requires a little more time in sharing what you do. It offers several benefits:1. Accountability: Sharing your work creates a forcing function, encouraging you to go the extra mile in understanding and polishing your knowledge.2. Continuous improvement: When you know you'll be sharing your learnings regularly, you start to notice learning opportunities in your daily life.3. Networking: By putting your work out there, you connect with like-minded individuals, potential mentors, and future colleagues. My previous writing actually played a role in landing me on my current AI research team.4. Knowledge retention: Externalizing your notes, whether in a private second brain or a public GitHub repo, helps solidify your understanding and creates a valuable resource that gets exponentially more valuable as you use it.My framework for learning in publicInspired by Scott Young's book "Ultralearning," here’s my framework for difficult learning projects:1. Set a big, exciting goalStart with a project that genuinely excites you. For me, it's building deep neural networks for financial data, leveraging my background in day trading. Your goal should be challenging enough to push you out of your comfort zone but aligned with your interests and expertise.2. Break it down into milestonesDivide your big goal into smaller, manageable milestones. My first milestone was implementing a basic neural network from scratch to solve the XOR problem. Having these intermediate goals helps maintain motivation and provides a sense of progress.3. Focus on a few high-quality sourcesAvoid information overload (and the stress that comes with it).Choose 1-3 reliable resources and stick with them. Even when things get difficult.Ignore everything else.4. Balance theory with practiceAdopt a "just-in-time" learning approach instead of drowning in prerequisites. Start with what excites you most, and fill in knowledge gaps as you encounter them. This approach maintains motivation while ensuring you still build a solid understanding as you go.When you're not actively coding or building, practice active recall by explaining concepts in your own words. This technique, inspired by the Feynman method, helps identify areas where your understanding is lacking.But it also provides a sense of action when you are studying theory.5. Be consistentPractice daily, even if it's just for 5-30 minutes. I aim for six days a week, taking Sundays off. Promise yourself at least 5 minutes, this will get you past that initial wall of getting started.My first neural network: A brief reflectionImplementing a neural network from scratch to solve the XOR problem was immensely satisfying. While the network itself is simple, the process of building it deepened my understanding of the core concepts behind neural networks.The journey wasn't always linear – I often found myself circling back to revisit concepts I didn't fully grasp at first. But this persistence paid off, and looking back, it's amazing to see how much I've learned in just a few weeks.Again if you are interested in the actual path I took, follow my deep learning work on GitHub.Start your own learning in public projectIf there’s something you want to pursue, give this framework for learning in public a try.* Start by identifying your exciting project and break it down into milestones. * Find 1-3 resources, and focus on these.* Commit to 5 minutes daily practice - balancing learning with doing.Remember, knowledge compounds over time. The key is just to consistently build on what you have.Thanks for reading and happy learning! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
13m
11/10/2024

Domain Expertise and AI Tools for Data Analysts | Meghan Maloy, Staff Analytics Engineer

Key Lessons* Real-world experience and domain expertise can be your edge as a data analyst. Understanding the domain leads to better understanding the data.* AI can’t replace data analysts who understand the context of their data and have the communication skills to share results.* Using AI tools effectively requires clear & specific prompts while also understanding the limitations of LLMs.* Why Staff Level is hard to define and how to handle it.* NYC Open Data is a great way to explore some real world data.Links* Upcoming NYC Open Data Classes* How I Learned to Understand the World by Hans Rosling* How not to be ignorant about the world Timeline[00:00:00] Introduction to the Bits of Chris show and guest Meghan Maloy, staff analytics engineer at Datadog.[00:00:58] Discussion on using New York City open datasets to investigate real-life experiences.[00:02:19] Meghan shares an example of investigating traffic light timing changes in her neighborhood using open data.[00:05:33] Exploration of 311 data sets and their applications in understanding city complaints.[00:08:14] Meghan discusses her presentations at meetups using New York City open data.[00:09:34] Conversation about approaches to exploring data sets and asking questions.[00:12:54] Discussion on consuming information and book recommendations, including "How I Learned to Understand the World" by Hans Rosling.[00:17:21] Insights on the importance of domain expertise for data analysts and understanding data collection methods.[00:23:14] Meghan shares her experience transitioning to a staff-level role and finding impactful work.[00:27:23] Chris and Meghan discuss the challenges of measuring performance and impact at higher-level roles.[00:31:58] Conversation about the impact of AI and LLMs on the future of data analysis roles.[00:37:52] Discussion on using AI tools, including ChatGPT, Perplexity, and Claude, for various tasks.[00:44:38] Insights on the importance of specificity in prompts when using AI tools and interacting with colleagues.[00:50:34] Meghan shares her experience during a three-month sabbatical and the benefits of work-life balance.[00:53:53] Information about New York City Open Data training sessions and the Open Data Ambassadors program. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
55m
27/09/2024

Pilot Life, Basics of LLMs, and AI for Beginners | Greg Lettieri, Corporate Aviator

Today I’m joined by my brother Greg Lettieri, a corporate aviator with over 15 years of flight experience.We discuss the role of automation in flying, life as private jet pilot, the basics of LLMs, and how to handle FOMO around AI (hint - you’re not too late, just experiment).Enjoy!Key Lessons* Consistency is crucial, whether it's maintaining fitness while traveling or pursuing a long-term goal like writing a book.* While automation plays a significant role in aviation, human pilots are still essential due to the need for discretionary input and handling unexpected situations.* AI, particularly large language models (LLMs), can be powerful tools when used to augment human capabilities rather than replace them entirely.* The most effective use of AI for many people is in tasks like distillation, summarization, and enhancing search capabilities.* It's not too late to start learning about and experimenting with AI, as we're still in the early stages of understanding its full potential and applications.Links* https://perplexity.ai Timeline[00:00:05] Introduction to the episode featuring Greg, a corporate aviator with over 15 years of experience.[00:00:37] Greg discusses his experience flying high-profile clients and the nature of private jet life.[02:24] Explanation of the two-week on, two-week off schedule in corporate aviation.[03:40] Discussion on the unpredictability of private jet schedules and waiting for clients.[07:27] Greg shares his strategies for staying healthy and maintaining routine while traveling frequently.[11:45] Conversation about automation in aviation and why human pilots are still necessary.[14:37] Greg explains how autopilot works and when manual flying is required.[17:24] Discussion on the importance of maintaining manual flying skills to prevent skill atrophy.[18:51] Chris introduces the topic of AI and the risks of over-reliance on technology.[21:00] Greg shares his limited experience with AI and expresses interest in learning more.[21:38] Chris explains the basics of how large language models work.[24:53] Discussion on practical applications of AI, such as summarization and enhanced search capabilities.[28:48] Conversation about the financial applications of AI and its potential impact on jobs.[31:29] Chris and Greg explore potential uses of AI in aviation, particularly in expense management and flight planning.[32:20] Discussion on the fear of missing out (FOMO) surrounding AI and new technologies.[34:13] Chris reassures Greg that it's not too late to start learning about and experimenting with AI. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
34m
14/09/2024

Start your Second Brain: A Quick Guide for Staff Engineers

Staff Engineers!Are you overwhelmed by the constant need to learn & adapt?AI's making it worse, right?Time to build your Second Brain! 🧠Here's a quick start guide:* Pick ANY note-taking app (I use Obsidian)* Create 3 folders: * Inbox: Quick capture - save anything worth keeping. * Reference: Curated highlights from your sources - only what resonates.* Notes: Think & write in YOUR words from your reference.* [Optional] Add 2 more folders: * Projects: Track tasks & ideas per role or project area. * Journal: Brain dumps & life homeworkRemember, the goal isn't just to collect info - it's to facilitate LEARNING. 🎓AI + Your Second Brain = Augmented EngineerOnce you've built your knowledge repository, use AI to supercharge it through distillation (not generation).Don't let information overwhelm you. Start your Second Brain today and let your knowledge compound over time! 💪Key Lessons:* Building a "second brain" through structured note-taking can significantly enhance your ability to learn and adapt in a rapidly changing industry.* The primary goal of a second brain is to facilitate understanding, not just collect information.* A simple strategy for starting a second brain involves using three folders: Inbox (for quick capture), Reference (for curated highlights), and Notes (for personal insights).* Linking ideas across different notes can lead to novel insights and help trigger memories of valuable past information.* Combining a second brain with AI tools can create a powerful system for distillation and problem-solving.Links:Timeline:[00:00:43] - The challenge of keeping up with rapidly changing technology and the importance of continuous learning[00:01:25] - The purpose of a second brain: facilitating understanding and learning[00:02:11] - Simple method to start a second brain: choosing a note-taking app and creating three folders (Inbox, Notes, Reference)[00:03:20] - The importance of making capture easy and friction-free[00:03:56] - Explanation of the Reference folder for curating highlights from various sources[00:04:46] - Discussion of the Notes folder and the importance of writing in your own words[00:05:35] - Recap of the simple three-folder strategy for second brains[00:05:58] - Introduction to a more advanced method with additional folders for Projects and Journals[00:07:44] - Combining various note-taking systems (Zettelkasten, PARA, GTD) into a five-folder structure[00:08:54] - The potential of combining a second brain with AI for powerful information processing and problem-solving[00:09:33] - Encouragement to get started with a second brain and invest in learning tools This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
9m
10/09/2024

Deploying AI Models at Scale | Eugene Weinstein, Engineering Director @ Google

Today I sit down with Eugene Weinstein, a speech recognition researcher and Engineering Director at Google where he leads an organization that productionizes speech recognition technology across various Google products.We discuss the evolution of speech recognition, the impact of Transformers, and the challenges of deploying models in production. This episode is packed with insight.A few things I learned from Eugene:* Build the model factory. Be able to pre-process your data, tune a model, and evaluate the model for accuracy and load testing as automated as possible.* Good data is key, but it's hard to get. Eugene shared how even Google struggles with data quality issues and ways to think about handling them.* How the Transformer architecture changed everything. Eugene breaks down why it was so impactful.* Scaling AI is an art. The trade-offs between speed and accuracy are constant battles and often need a bit of experience to get it right.* The benefits of cross-functional collaboration between engineers, researchers, and domain experts. Especially with finding data quality issues.My favorite quote:"If adding more data hurts your model performance, it's a red flag. But how do you catch it? There's no substitute for actually looking at your data." - EugeneKey Lessons* The importance of data quality and preprocessing in AI model development, including the need for manual inspection and automated checks.* The challenges and strategies for productionizing AI research, including optimizing for speed vs. accuracy and managing hardware resources efficiently.* The value of cross-functional collaboration between data engineers, researchers, and domain experts to improve AI model development and deployment.* The evolution of speech recognition technology and how recent advancements like transformer architectures have impacted the field.* The process of scaling AI models from research to production, including the importance of robust evaluation and testing frameworks.Links* https://huggingface.co/* https://github.com/run-llama/llama_index* https://www.langchain.com/* https://ai.google.dev/gemma* https://deepmind.google/technologies/gemini/project-astra/Connect with Eugene* https://www.linkedin.com/in/weinsteineugene/* https://research.google/people/eugeneweinstein/Timeline[00:00:00] Introduction of Eugene, his background at MIT and Google[00:01:26] Eugene's early work in speech recognition and computer vision[00:02:58] Discussion of Google's scale and the evolution of machine learning techniques[00:04:38] The impact of neural networks and deep learning on speech recognition[00:07:53] Explanation of transformer architecture and its significance[00:09:00] Convergence of different AI modalities and increased accessibility of AI technologies[00:14:55] The process of taking AI research to production at Google's scale[00:19:03] Importance of data quality and preprocessing in AI model development[00:21:54] Discussion on the value of domain expertise and cross-functional collaboration[00:25:36] Signals for identifying data quality issues and the need for data checks[00:31:17] Challenges in model deployment, including speed vs. accuracy trade-offs[00:34:51] Optimizing hardware utilization for AI model inference[00:37:56] Decision-making process for model selection and deployment[00:39:47] Explanation of the model tuning process and parameter optimization[00:42:01] Importance of software engineering discipline in productionizing research code[00:43:56] Building an efficient pipeline for testing, training, tuning, and evaluating models This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
46m
23/08/2024

AI in the Classroom: From Teachers to Facilitators | Shawn Cryan, Educational Systems Coordinator

Key Lessons* AI can free up time for higher-order thinking tasks and more creative, human-centric activities in various professions, including teaching and software engineering.* AI in education can enhance individualized learning, allowing teachers to become facilitators rather than just content providers.* Educators using AI tools like ChatGPT can create customized curriculum content and assessments from sources they curate and vet.* How Shawn & I use AI with our kids outside of school.DescriptionIn this episode of The Bits of Chris Show, host Chris Lettieri talks with educator Shawn Cryan about the transformative potential of AI in education and everyday life. The integration of AI in education and daily life offers exciting possibilities for personalized learning, increased efficiency, and enhanced human creativity. As we adapt to these technologies, we have the opportunity to focus on higher-order thinking and more meaningful human interactions.By listening to this episode, you'll gain valuable insights into the practical applications of AI in education and beyond, helping you prepare for a future where human skills and AI capabilities work in harmony.Here's what you'll learn:AI Revolutionizing Education:* The shift from traditional teaching to personalized education using AI* Introduction to Khan Academy's AI tutor, Khanmigo, and its potential impact* How teachers are evolving into facilitators rather than just content providers* Unlocking higher-order tasks like project-based learning through AI assistance* The move from teacher-centered to student-centered learning environmentsAI-Powered Curriculum Development:* Creating social-emotional curriculum online during the pandemic* Using AI tools like ChatGPT for basic level information and content creation* The importance of vetting AI-generated content* Exploring content vendors for schools and their role in education* Sean's experience with "We Are Well" curriculum based on TED-Ed contentMaximizing AI Effectiveness:* The power of using AI on curated, personal data sets* Creating embeddings with your own data for more nuanced results* ChatGPT's strengths in common knowledge vs. the need for specialized data in niche areas* Understanding Bloom's Taxonomy and its application in AI-generated assessments* The potential of chaining prompts or using an ensemble of AI models for sophisticated resultsAI in the Workplace:* How AI is replacing certain tasks, freeing humans for higher-order work* Examples of higher-order tasks for software engineers* Emphasizing that AI is augmenting jobs, not replacing them entirely* The potential for AI to enable us to be more human in our workAI in Personal Life:* Creative ways to use ChatGPT with children for learning and play* Utilizing ChatGPT's image recognition for household tasks and family activities* The potential future of augmented reality glasses powered by language modelsResources* Shawn’s Portfolio* KahnmigoTimeline[00:01:15] Shawn introduces himself and his background in education and educational administration.[00:03:25] Discussion on Shawn’s career path and his role as an educational systems coordinator.[00:04:52] Exploration of current issues in education, including balancing academic success with nurturing environments.[00:06:50] Introduction to the topic of AI in education, mentioning Khan Academy's AI tutor.[00:08:00] Shawn explains the concept of individualized learning and how AI can facilitate it.[00:15:57] Discussion on content creation companies for schools and how they provide educational materials.[00:19:00] Shawn shares his experience creating his own health curriculum using AI tools.[00:22:28] Chris introduces advanced AI techniques, including injecting personal data into language models for better results.[00:25:30] Explanation of how to use ChatGPT with personal data sets to enhance its usefulness.[00:31:18] Discussion on using AI to create better assessments and project-based learning opportunities.[00:34:35] Introduction to Bloom's taxonomy and how it can be incorporated into AI-generated assessments.[00:35:30] Exploration of using multiple AI models together (ensemble of LLMs) to create more sophisticated educational tools.[00:39:30] Shawn and Chris share personal experiences of using AI in parenting and engaging with children.[00:42:19] Discussion on potential future applications of AI, including augmented reality glasses for real-time information. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
44m
17/08/2024

Handling Work Stress with Awareness & Homework for Life | Quick Bits #2

In this episode, learn how your personal values and Homework for Life can help you spot problems in your day-to-day faster.I share how I overworked this week but thanks to self-awareness I quickly corrected course. I then provide an example in my 11 years of marriage of how awareness again helped me break out of toxic mindset.Key Lessons* The importance of self-awareness in managing work stress and maintaining work-life balance.* How articulating personal values can serve as a compass for decision-making and prioritization.* The value of daily reflection exercises like "Homework for Life" in identifying patterns and improving personal growth.* Recognizing and addressing internalized expectations that may negatively impact relationships.* The benefits of open communication and self-reflection in breaking negative patterns and fostering personal development.Links* Homework for Life TED Talk* Storyworthy by Matthew Dicks* The Pathless Path by Paul MillerdShow Notes[00:00:09] Discussing the challenges of pre-vacation work intensity and the importance of not overworking[00:00:57] Recognizing the signs of overworking and its connection to fear and imposter syndrome[00:02:10] The importance of awareness in managing work stress, derived from daily value reminders and the "Homework for Life" exercise[00:02:29] Explaining the concept of writing down personal values as a decision-making compass[00:03:33] Identifying physical and emotional signals of work-related stress[00:04:40] Introduction to the "Homework for Life" exercise for daily reflection and awareness[00:06:52] How self-reflection and awareness helped in quickly identifying and addressing negative work patterns[00:07:22] Discussing a personal mistake of feeling entitled due to being the breadwinner[00:08:51] The importance of recognizing different perspectives and contributions in a relationship[00:09:17] Encouraging listeners to increase self-awareness through reflection and writing This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
10m
10/08/2024

Augmented Intelligence for Engineers, Feynman Technique, FX Carry Trade | Quick Bits #1

Augmented Intelligence for Engineers[00:00:53]* How to adapt to AI as a Staff Engineer* Use AI as a tool, but stay human and keep doing the work.* Let it free you up to focus on learning, thinking, creating.* Don’t use it to write for you - writing is the best way to improve your thinking.* Using AI for learning and augmenting your thinking* Focus on AI for distillation to go faster rather than for generation* Summarization, searching - process information faster* Amplify your human strengths by still doing the thinking and the work* I use Perplexity.ai for search nowFeynman Technique[00:04:58]* Explain something in simple terms with no jargon to show you understand it well* Iterate through writing it down, teaching it someone, and filling the gaps* Simple is a sign of expertise* Boil a complex topic down into it’s simplest form to learn something deeplyFX Carry Trade[00:06:30]* Currencies are traded in pairs. You buy the “base” pair and sell the “quote” pair.* The carry trade profits from being long a higher yielding base pair and simultaneously short the quote pair.* The USD was yielding close to 5% while the JPY was much lower near 0.25%, so investors holding the USD-JPY pair profit from the difference here.* This week the Bank of Japan raised rates again and the FED hinted at cutting rates, so the carry trade suddenly looked less attractive.* Research paper on Carry TradePersonal Growth[00:09:23]Quote from Sahil Bloom:When you're on your journey to growth, some people won't like it. They'll tell you to be realistic, laugh at your ambitions, and say things behind your back.Recognize one truth: This is fundamentally not about you.Your growth, focus, and improvement are exposing something in them: Their insecurities, their fears, their lack of ambition.You can show them empathy and love, but ultimately, you are not responsible for how your journey to self-improvement makes others feel.* Sahil’s newsletter* It’s hard trying new things, but your vulnerability muscle grows* Do what you want, you’ll find supporters but don’t get discouraged by lack of support Brilliant App[00:12:12]'* Duolingo for the sciences* Brilliant (not an affiliate link) This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
12m
09/08/2024

AI for Sales, Augmentation, and Learning | Account Executive, Ryan Burwell

In today’s episode I am joined by my long time friend and Account Executive at Johnson Controls, Ryan Burwell.We cover:* The basics of how AI and large language models work, so less technical folks can leverage these tools professionally.* Critical soft skills, such as empathy and effective listening.* How to use AI tools like ChatGPT to augment rather than replace human skills and thinking.* Speculation o the future of education with AI assistants providing personalized learning experiences.Show Notes:[00:01:33] Ryan's first job in New York: Cold calling sales at Yext, discussing the high-pressure environment and sales techniques.[00:03:32] Discussion on sales skills: The importance of confidence, empathy, and effective listening in sales and general communication.[00:07:51] Applying sales skills to life: How sales techniques can be useful in various personal and professional situations.[00:12:07] AI in sales: Exploring potential uses of AI and large language models in sales processes, including personalized outreach and data analysis.[00:17:52] Personal use of ChatGPT: Ryan shares examples of using ChatGPT for quick information lookups and generating reading lists.[00:27:26] AI and education: Discussing the potential impact of AI on MBA programs and self-directed learning.[00:29:46] Chris introduces the concept of "augmented learning": Using AI to enhance learning and thinking processes rather than replacing them.[00:32:21] AI in elementary education: Exploring how AI could provide personalized assistance to students and help teachers identify areas where students need extra support.[00:38:21] Technical discussion on AI compute demands: Chris explains the basics of how AI models work and why they require significant computational resources. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
41m
14/07/2024

34 - AI for Real Life: Augmented Creativity, Robot Hockey, and storytelling with my friend Frankie

Key ideas discussed in the podcast:* AI-generated content and its implications* The future of human interaction in a digital world* The role of AI in creative processes* The importance of human connection and authenticity* Adapting to AI while maintaining humanity* The potential impact of AI on trust and information consumption* The concept of “being augmented" and AI-assisted creativity* The uniqueness of human experiences and storytellingTimestamps:[00:00:44] - Discussion of an AI-generated George Carlin comedy special, raising questions about the future of content creation.[03:09] - Exploration of how AI might "break the internet" and lead to a resurgence of valuing in-person experiences.[09:18] - Explanation of how large language models work and the current limitations in AI technology.[11:25] - Introduction of the "augmented writer" concept, discussing how AI can assist in content creation.[20:07] - Reflection on what makes humans unique compared to AI, focusing on creativity and empathy.[24:40] - Discussion about the potential future of virtual reality and its impact on human interactions.[31:11] - Frankie shares his experience with transcendental meditation, highlighting the importance of finding personal practices for well-being.[33:14] - Final thoughts on adapting to AI while emphasizing the importance of staying human and embracing uniqueness.Summary:This podcast episode features a conversation between Chris and his friend Frankie, exploring the implications of artificial intelligence on various aspects of human life. They discuss the emergence of AI-generated content, its potential impact on trust and human interaction, and the challenges of distinguishing between real and AI-created media. The conversation goes into the technical aspects of AI, including how large language models work, while also exploring philosophical questions about what makes humans unique in the face of advancing technology.Throughout the episode, Chris and Frankie contemplate the future of human connection in an increasingly digital world, discussing concepts like the "augmented writer" and the potential for AI to both assist and challenge human creativity. They emphasize the importance of maintaining authenticity and human connection in an AI-driven world, encouraging listeners to embrace their unique qualities and experiences.Listeners will gain insights into the current state and future possibilities of AI technology, as well as thoughtful perspectives on how to navigate a world where the lines between human and AI-generated content are becoming increasingly blurred. The episode concludes with a call to focus on being better humans while adapting to the presence of AI in our lives. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
34m
09/03/2024

#8 - How to Start a Podcast in 10 Minutes as a Part-Time Creator

The moment I hit 'publish' on my first podcast episode, I stepped into a world I never imagined.I had no idea sharing my thoughts into a microphone could be this much fun.If you like to write but it feels slow, or if you’ve been interested in podcasting - ignore anyone telling you to not do it.And just give it a try!Here’s how I got started and why I think conventional advice is wrong.How to Start a Podcast in 10 Minutes* Buy a Microphone. I chose the Blue Yeti.* Pick a hosting platform. I used Substack because I’ve had a newsletter there. Any platform will do, you just need an RSS feed to submit to Apple or Spotify.* Pick a recording & editing tool. I use Descript now but Alitu looked interesting too.* Make the first episode. Write down a title, some key points, then hit record and go.* Publish. Don’t stress the details, just get started and produce something.You can always iterate as you go, the most important thing is to get going. Focus your time on creating the episode, not the little details. You’ll learn a lot from just doing and you can tweak things over time.Part-Time Creators Should Ignore Conventional AdviceMost advice on starting a podcast is too complicated or too negative and distracting.Influencers who make a living by monetizing their audience are playing a different game than the part-time creators who are doing this for fun. For them, niching down and building an audience is crucial to their survival. For you and me, we don’t need to worry about that.“Podcasting doesn’t have discoverability so don’t do it until you have an audience.”Nonsense.Part-time creators are playing a different game. We want to have fun, learn, explore, connect with fans, and maybe monetize in the future. But while in this period of self-discovery, just focus on have fun and making your art.If you think podcasting sounds fun, or you want to explore another medium, do it.You won’t regret giving it a try.The 30 Day ChallengeTry recording a solo podcast of 5-10 minutes every day for the next 30 days.Today was day 8 for me.You’ll learn so much and very quickly figure out if podcasting is for you.Let me know how it goes, have fun :) This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
9m
03/03/2024

#2 - How to Do Big Things Without Motivation

Key Points* Motivation is fleeting, you can’t rely on it* To do big things, you need consistency* You get consistent by making it a habit* You get a habit by starting small* You start small by taking the big thing you want and setting a process goal around the smallest unit of work you can do everyday* I then shared two examples of how this worked in my life:* Writing my first book* Transitioning from finance to tech* Time will pass no matter whatTranscript  Welcome back everyone. This is episode two of the bits of Chris' show. Thank you for joining me yesterday. I really appreciate it. I also appreciate some of the feedback I got in listening to myself. I noticed I already have a few things to work on. I think I said like, and so a bit too much, we're going to try to work on that today. But day two, I woke up and I'm not motivated to do this anymore. And I thought, oh s**t, this is going to be a long, 30 days. But that brings me to today's topic, how to do big things. When you're not motivated. I think motivation is fleeting. That's pretty obvious it comes and goes. And if you think you need to be motivated, you're not going to get much done. If you're waiting around for motivation to hit you. You're never going to go after the things you want to do. So motivation is not the answer with how to do big things. In my opinion, the answers to build consistency. Consisting meaning you show up every day and you just do the thing. There is a quote from bill gates that feels relevant right now. He said most people overestimate what they can achieve in a year. And underestimate what they can achieve in 10 years. Well, I think we could take that a step further. And just say most people overestimate what they can do in the short term. But underestimate what they can do in the long term. So, if you think about a to-do list for a single day or a week, You're probably overestimating what you can get done, but then if you zoom out to maybe a month, two months, or even a single year, You're probably underestimating what you can accomplish. And I have a few examples of this that I'll get to later. But if motivation is not the answer to doing big things, then how do you. Be consistent. And the answer there is. You make whatever you're doing a habit. So, how do you build a habit? There are some amazing books on this topic. I won't get into those today, but I think one or two pieces of advice on how to build a habit. The most important thing is to start small. Make whatever habit you're. Trying to do. A bite size, tiny step that, you know, you can succeed at every day. Because. If doing this podcast is Edie evidence. You can lose motivation very quickly. And so you need to just build it into your routine to find that consistency to power through those dips in motivation. And as you do more. As you get a little more success that motivation will come back and it might come back stronger and it will be easier at times, but it definitely ebbs and flows throughout any big project. So it's important to have whatever habit or whatever thing you're trying to do. Be small, something attainable, something you can do every day. So if our goal is to be consistent and we do that by building habit and the best way to build the habits by starting small, how do we start small? Well, you should take that big thing you're trying to do and try to find the smallest unit of work. That you can do every day. And make that goal a process-based goal, not an outcome based goal. So, for example, if you're going to write a book. Make your goal, a process oriented one. I don't say I'm going to write a hundred pages. And don't say I'm going to write 500 words even. The process there is writing a little bit every day, but just set a timer, make it really focused on just showing up and doing it. For example, when I wrote my personal finance book, my goal every day was to just write for five minutes. And I would say 70% of the mornings that I woke up. I did not want it right. And a lot of times I would just right for the five minutes and walk away, go do something else. But some of those days when I didn't want to write, I would write for five minutes and then I would keep going. And. That could have taken up to an hour, some mornings again, starting from that rolling out of bed, not wanting to do anything. So starting small can lead to. Some real powerful results. In the day-to-day. But it also just keeps you moving forward. And I think one of the biggest problems with a long project is. Humans. We want that instant gratification more or less, even if we are disciplined or thinking with the big picture. And so you have to. Give yourself these little wins to keep it going forward. Jerry Seinfeld has a famous story or method that he shares where he put an X on his calendar every day he was writing jokes or doing stand-up, something like that when he was coming up. He had a goal to just either perform standup every day or write jokes every day. And as long as he did, he put an X on the calendar and then his focus became just doing that every day. So he could put that X on his calendar and string together. Those successes. And I think that's really what you need to do when you're trying to be consistent and being consistent is the thing you need to do. In order to do big things. Another way you can start smallest trying to scope down your initial milestone. So again, with the example of a book, Instead of thinking you need to write a 300 page book. Just make your goal right now, writing the first chapter. And with that smaller scope, you get a little closer and as, and as you get closer to that finish line. The motivation tends to come back in my experience. So if you set incremental milestones, you can have maybe a more consistent distribution and motivation to make your day-to-day easier. You can always expand the scope later. So don't be afraid of scoping it down now. And you can have that longer term vision in mind as you work towards more intermediate milestones. So to recap. In order to do big things. We don't want to rely on motivation. We want to build consistency. To build consistency. You need to make. The thing you're doing a habit in your daily routine. And the best way to do that is to start small. By using a process oriented goal every day that you can achieve. And scope it down. And if you're thinking. You don't want to be patient enough, or if you're thinking. I need to get my big thing done now. And you bite off more than you can chew, or you take too big of a swing right away. You might regret it. And I would suggest you really heed the advice of starting small and scoping it down. Now I want to share two examples of how this has helped me over the years. I started to touch on the first one, which is writing that book. And it took me 10 months to write. But the key was doing it every day for at least five minutes showing up to right. Because as I said earlier, most mornings I did not want to write. And it would have been very easy for me to never make progress and just do other things. But because those days I didn't want to write. I moved the needle for five minutes. I was able to get closer to finishing a chapter or finishing a section. And seeing some progress and then motivation would tend to find its way back, making the next day easier. But also the magic of just getting started with that small process oriented goal of just doing five minutes. Would often lead to me doing way more than five minutes. But by making that barrier to entry super low. It became really easy to get those consistent wins. And I knew every morning, That's all I had to do. So it became easy to take some pressure off. And get a success that day. So I think when you do find that small unit of work, really make that process go for yourself. Just as small as possible, you can always do more than that. But make it small so you can build a habit, especially when you're starting out. Another example is when I left day trading to get into tech. That was a. Maybe a two year journey. And I knew the goal was in mind of, I wanted to get a job as a software engineer. But I didn't have a background in tech and I had only been. Coding at my trading job for maybe a year, year and a half or so. And that was all self-taught and there wasn't many people around me to help. Develop my engineering skills. So how to do a lot of that on my own, or with resources online. And the goal I had there every day was basically to spend one to two hours. Taking online courses or writing code in the morning before going to work. Back then I was a big proponent of the Pomodoro technique where you focus for 25 minutes and then you have a five minute break and you have a little timer running to track these units of work. And so I would measure my. Success in the number of Pomodoros I did focusing on learning something new. And it took a while. But after doing that for a year, year and a half, I started to get deeper into interview rounds. I started to actually have. This full computer science curriculum underneath my belt. And I started to do more interesting projects at work. So a year and a half of saying, let me get two to four Pomodoros of learning in every morning. And I had the skills to become a software engineer. And I think it was. Difficult because during that process, I didn't know when that was going to end. I didn't know when that jump was going to happen. And so that can be a challenge, but by making the goal something I could completely control and by making it relatively small of just learning for a certain period of time every day, That back then. I didn't have any kids, so it was easy to get an hour or two of time to myself. But by making, keeping things small, itallowed me to progress day over day, week over week, and then a year and a half later, I had a new career. You know, same thing with writing the book five minutes a day, 10 months later, I had a completed book that was close to 200 pages. And so to wrap up. Big things take time. Motivation is fleeting. If you need to do big things, you want to have small, consistent wins. Strung together over a long period of time. Your results will come from the compound effect of a lot of little wins. So start small. Focus on the tiniest bit of work you can do every day. And then focus on that process. Getting that done. And a month, a year, 10 years from now. You will surprise yourself because the thing is that time is going to pass no matter what. So you can look back and say, oh great. You know, five minutes a day for the past year. Now I have a book instead of a man I'm still waiting for that motivation to come. And with that. We're over the 10 minute mark that's episode two. Thank you so much. I appreciate your listening. Let me know how this is going, or if there's anything valuable you got from this episode. And we'll see you tomorrow. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
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02/03/2024

#1 - 30 Days of Podcasting, Writing, and Joyspan

Episode Description* Expectations for the next 30 days* Reflections on writing for 45 days straight* Struggles finding a niche* Joyspan - the framework that fits all my interests* How to maximize your JoyspanTranscript Hello. I just think on. All right. I think so. Well, hello, everyone. Welcome to the first episode of the bits of Chris' podcast. I am not sure what I'm doing. So please bear with me. But for the next 30 days, I figured why not record myself speaking and try to figure this out. So here we are. I'm sure it's going to be. Bumpy and I'll make mistakes. And like I said, Not really sure what I'm doing. So we're just gonna learn as we go, please. Any sort of feedback or suggestions would be appreciated, even if you tell me I suck because then. I can think about it. What, what actually sucked? What, why didn't you like, how can I do this better? So let's get into it. My me try to speculate how I think this is going to go. And then maybe get into the reason why I'm going to do it for 30 days. And then I'll give a little context of where this all came from and what I learned from trying to write 45 days straight to start the new year and where we ended up. So one thing I think will happen is between this first episode and 30 days from now, We'll have 30 episodes, which has given me pretty cool. Assuming I don't give up halfway, which, because I'm telling you I'm going 30 days. I don't think I will give up halfway. If I do, you can call me out on it. But I do think the tooling and the scripting and the flow of the episodes and the structure is going to get so much better by the end of it. I also have no idea on how to take the show notes or how to organize things. So we'll see how that improves too. I don't have a logo yet. I don't have much of a name, I guess we'll just go with the bits of Chris' podcasts, but it should be fun. One thing I do know is I had a taste of podcasting at work earlier this week, and it was a blast. I started emceeing this community meeting and at the end. I decided to add a new segment with some feedback from folks. To interview a person. In that meeting live and that was so much fun. That I was like, this, this is a signal I need to talk more. I, I like doing this, so that's the one thing I do now. So even though I'm not qualified yet to really have a podcast, I know it's a lot of fun, so I really don't care. So I promise you over the next 30 days, I'm going to learn some stuff. This will get incrementally better, especially if you're giving me feedback. And it's also, I think, a fun way for me to explore ideas. I've had a lot of ideas and I've been trying to write more online. But writing is slow. And I think you have to be more polished when you write. But podcasting, like anybody can start one. You're just talking into a microphone and who cares if nobody listens, but at least you're getting your words and thoughts out there quicker. So I'm going to try for that sake, like exploring the ideas, maybe outlining future things I might want to write about. Or just giving me an outlet to talk. So I don't drive my wife crazy from talking too much. Or I think even chat GPT has had enough of hearing from me. With all my ideas and questions and things I want to explore. So I think this is going to go great. I'm excited to see what happens over the next 30 days. And let's just get into today's episode. So, as I mentioned earlier, To start the new year and actually even a little before then. I was writing every day online and publishing something short. And I did that for, I think, close to 45 or 50 days in a row. Where I would wake up generally had an outline in place from the night before. And I would write. 300 to 600 words. Try to quickly edit it and then publish it. And this was. Obviously new for me. I had been writing online for a few years, but very ad hoc, like maybe something once a month. Once a week, never anything this intense. And also rarely publishing it in a place where people could see it. So a big part of this challenge was to put it out on social media where you could actually get in front of readers. Forever. I just had it on a personal blog that I'm pretty sure. A hundred people a year might've came across from Google. If, if that, so this was actually more intimidating. I thought just like doing this today is because you're getting content right in front of people and sharing it. So that was interesting. But one thing. Doing this 45 day challenge was you get to go through ideas very quickly and you get to iterate on a bunch of stuff quickly, and you get feedback very quickly. And all that helps you figure out what you like. What you like to talk about? What's working like what other people like, and find interesting. And so I try to pick a specific niche. For that, and I kept changing it and I'm still sort of changing it. Some of the advice you get when you start writing online, if you want to build an audience is to get super specific and niche down. And the people that fit that niche will resonate so greatly with what you're saying, that they'll start following you or the internet will help you find those people. All those platform algorithms will bring you the exact people that are looking for the content. If you're speaking to them, Well, I find that very challenging because I have a lot of things I want to talk about. And a thing I've been struggling with for the past four months or so. Has been trying to put myself into one box and niche down to, to speak to a single. Audience or on a single topic. And I don't know if it's just me or if I haven't found it yet, but I can't do that. So. One thing, the writing for 45 days straight and what this podcast is, hopefully can help me explore is what's most fun for me to talk about. Now I've definitely narrowed it down to a lot of topics. And I think. If you're interested in writing or creating content, you don't want to just. Sit. In your room and plan and think about it. I think you need to balance what I've called the learn. Do reflect or learn, do think cycle. Where you consume some information, but then you spend equal time doing, like using that information, whether that's creating or writing code. And then you spend a little bit of time reflecting, like thinking about the process. Thinking about what it means, thinking about what you like. And so with the 45 day writing challengeI was so busy doing, I didn't have much time to consumer reflect. And I think that was good because it jolted me out of a cycle that most of us are in, I think, which is. We consume way more than we produce. And once you get going with the PR producing, you learn a lot and you start to figure out what, what you do like to talk about what you do have a lot to say about. And we'll get into that journey, but that's what I want to use this podcast to explore is. A lot of these different topics. But ultimately where I'm at today is. I'm a staff engineer at a data company, mainly focused on data analytics. I'm a former day trader. And I w. Years ago, wrote a small book on the basics of personal finance. And I find this money part of myself. I just really enjoy talking about investing, trading money and I've put that on the back burner for a long time. While I focus on growing my tech career. But it keeps coming back. And I think that's a signal that I should pay more attention to that part. So the topics I kind of have in mind for the rest of this podcast are things around money trading and investing, especially at the intersection of data and data engineering, which is what I do for work now., especially around like cryptocurrency markets and web three, because the technical nature of those different platforms and the different tokens that are being created are really fun or interesting to me. Also have a couple ideas around work-life balance and being a parent, how that ties into work. I have this concept of work from home fire for financial independence, remotely employed instead of financial independence retire early. I want to explore that. I'm not really sure what that means, but it just, it sounds catchy to me and I like the idea. For work and for more engineering focus stuff, I've been thinking a lot about how to adapt to AI. And so I've been calling my philosophy there, the augmented engineer, which basically is stating AI as a tool, we should focus on investing in skills that AI can't replace, like our thinking and our soft skills and communication. So I hope to explore more of that. And then ultimately in looking at these different. Ideas in these different pockets of. Specialization that I was considering writing about. They all sorta overlapped around this thing of making more money or making more time. And I started to reflect on why that was or what am I trying to get at? And that's what led to this idea of my life philosophy being to maximize my joy span. Joyce man, being the amount of moments in time over your life that you're spent in a state of joy. Joy being when you lose track of time, when you're in that flow state, when you're doing an activity that fully absorbs you. And when you're spending time with people where you just lose track of time. So spending quality time with loved ones, for example, That's what I've defined as joy and. That's the philosophy I was. Sort of trying to define. And how all these different pieces fit together. It made sense to me. So the joist fan philosophy won't get into too much, but that's the basis of it. And there was three pillars of how to maximize your joy span. One being to make more money. And then within that make more money pillar. You can grow your career. You can invest money. And you can do complimentary projects that could become income-producing assets, but at worst are teaching me new skills or fun stuff for you to learn. The second pillar was to make more time. And this is around productivity, longevity. And using money to buy back time, whether that's upgrading something or hiring things out. And lastly was to make more joy. And the way to do this was to explore your actual hobbies, figure out what you like, try to find your eeky guy. And what you enjoy doing? As well as nurturing relationships. So you have a strong bed of relationships, strong families, strong friendships. To enjoy life with. And then doing a bit of mindfulness. So you're aware of when you're outside the present moment and when you're removing yourself from the ability to be lost in flow and enjoy the moment. And so that framework. Maybe isn't my. Like purpose in life, but it felt. Very complete and that all these ideas I had that I wanted to write about. Fit inside different buckets of that. So I liked it as a central theme to tie together what I want to talk about and write about. And that's what we're going to be exploring over these next 30 days. So thank you for listening. This is getting a little bit longer than I want. I think most episodes should be in that 10 to 15 minute range as I figure this out. If you made it this far. I'm truly honored for you to have spent your attention on my voice. And what I have to say. So thank you. But really any feedback is welcome. Good. End bet. I am just in this to learn, so I won't take it personally. So please. Any sort of signal would be useful. And I hope. To see tomorrow. Thank you for listening. Cheers. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit bitsofchris.com
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