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Gianfranco's Best of February 2024 Reading List
Gianfranco Filice
March 02, 2024
Welcome to the February 2024 edition of my monthly reading list.
This month, I've curated my favorite essays I read this month across Meaningful Retrospection, Artificial Intelligence, Finance and Economics, Society and Technology, Fintech, and Web3.
Meaningful Retrospection
You Don’t Need More How-To Advice — You Need a Beautiful and Painful Reckoning (Tim.blog)
Excerpt: “It’s an epiphany that turns a nice-to-have into a must-have. It applies to fat loss, to getting your finances in order, your relationships in order, and your life in order. No matter how many bullet points and recipes experts provide, most folks will need a Harajuku Moment to fuel the change.”
For the Person Who Has Everything (What's Important)
Excerpt: “Steering wheel mindset may even help us discover the magical place where what only you can do meets what the world needs. I think what most people, especially hyperagents, really want is reconnection to purpose. It’s immediately obvious when you meet someone on the right path for them. They become less comparative, less acquisitive and less anxious. Not only is their daily flow intrinsically desirable, it’s also meaningful because they can see how it serves the whole tribe. This is the big payoff.”
Small Differences and Consistent Compounding (Outlier’s Path)
Excerpt: “If you start out with $100 at the beginning of the year and can consistently compound 1% every day, you’ll have $3778, which is 37.78x! Compounding is also powerful in the opposite direction, as (1 – 1%)^365 = 0.03, which means you are left with almost nothing!”
Artificial Intelligence
AI Could Actually Help Rebuild The Middle Class (Noema Magazine)
Excerpt: “Artificial Intelligence will not in general [automate] high-stakes tasks, like catheterization. But it can enable workers with an appropriate foundation of expertise to level up. AI can extend the reach of expertise by building stories atop a good foundation and sound structure.”
The Modern AI Stack: Design Principles for the Future of Enterprise AI Architectures (Menlo Ventures)
Excerpt: "The modern AI stack, which is currently being shaped, is driving enterprises to reconstruct their tech stacks as machines become increasingly capable of reasoning, creation, and creativity. The key layers of this stack include the compute and foundation models, data, deployment, and observability, and in 2023, enterprises spent over $1.1 billion on this modern AI stack, making it the largest new market in generative AI."
Ten Noteworthy AI Research Papers of 2023 (Sebastian Raschka's Magazine)
Excerpt: “Orca 2 aims to teach 'small' (i.e., 7B and 13B) LLMs various reasoning techniques (like step-by-step reasoning, recall-then-generate, etc.) and to help them determine the most effective strategy for each task. This approach has led Orca 2 to outperform similar-sized models noticeably and even achieve results comparable to models 5-10 times larger.”
Wrestling with AI (Digits to Dollars)
Excerpt: “Setting aside all the noise, and there is a lot of noise, what we have seen over the past year has been the rise of Transformer-based neural networks... This is important because it opens up the problem space that we can tackle with our computers."
THE AIPOCALYPSE WE SHOULD BE WORRIED ABOUT (Digits to Dollars)
Excerpt: “The most glaring problem is at the edge. As much as users today seem taken with generative AI, willing to pay $20+/month for access to OpenAI’s latest, the case for having that generative AI done on device is not clear."
The Case for Open Source AI (Air Street)
Excerpt: “In short, we believe that the story of technology is one of a struggle between openness and its enemies. Between research teams or companies that support collaboration and open standards versus powerful gatekeepers."
Scaling ChatGPT: Five Real-World Engineering Challenges (The Pragmatic Engineer)
Excerpt: “Our big challenge is that self-attention scales quadratically, meaning that the more tokens we generate, we need quadratically more operations (about ~10,000 operations for the 100th token, but about 1,000,000 for the 1,000th.) How can we improve performance?”
Finance and Economics
Where Do Interest Rates Come From? (The Diff)
Excerpt: "But in the long run, rates are a matter of supply and demand, and that supply and demand is heavily influenced by where the average person is in their spending lifecycle, and by whether or not the number of people is growing."
The Business of Check Cashing (Bits About Money)
Excerpt: "The reverse of a check contains a small area where you can 'endorse' the check. This means signing it and optionally leaving the bank an instruction as to what to do with the check... One common endorsement historically is that you can endorse a check to another person, i.e. instruct the bank to make payment to the person you nominate, not to you."
What is Alternative Data and Why Does It Matter? (The Diff)
Excerpt: "What's changed in the last decade-and-change is the proliferation of datasets—anonymized card transaction data, web-scraping outputs, marketers' databases, regulatory documents, point-of-sale data, coupon tracking, industry-specific price feeds, etc.—and the tools needed to ingest and analyze them."
Society and Technology
Lessons from History - The Rise and Fall of the Telecom Bubble (Fabricated Knowledge)
Excerpt: “One of the scariest comparisons to the Telecom bubble is the doubling demand every 100 days comparisons. OpenAI in 2018 said that demand for training is doubling every 3.5 months...”
What Can be Done in 59 Seconds: An Opportunity (and a Crisis) (One Useful Thing)
Excerpt: “When a middle manager writes a weekly report on the status of a major initiative, the report may not be the point... But now every employee with Copilot can produce work that checks all the boxes of a formal report without necessarily representing underlying effort.”
All My Thoughts After 40 Hours in the Vision Pro (Wait But Why)
Excerpt: “The plan was clear. I went home, told my wife that I would be deeply ignoring her and our baby for the week, and spent twelve hours a day in the headset for four straight days...”
Thinking incrementally about SaaS (Buck on Software)
Excerpt: “One mental model of a SaaS business is that it is a big incremental revenue generating machine... Good SaaS machines are investment constrained - if more dollars are poured in, more dollars come out the other side.”
Fintech
Embedded Finance in Crisis (Simon Taylor's Fintech Brain Food)
Excerpt: "Since the global financial crisis, we've implemented regulations worldwide to ensure banks can absorb losses... The banks look at Fintech companies collecting billions in deposits, lending into the 10s of billions, and wonder, won't this lead to some financial crisis?"
Payday in 1,000 words (MTB Notes)
Excerpt: "The payfac and PFaaS trends exemplify the effect of software on financial services and other industries: it lowers fixed costs and enables new distribution channels, pushing the service closer to the end user in a more integrated, user friendly, and cost effective way."
The Next Great Consumer Fintech Company (Simon Taylor's Fintech Brain Food)
Excerpt: "In the case of Hispanics and Latinos, one foundational need is financial services in their primary language (a fairly obvious idea) and another is providing simple, transparent products that cater to a population that, on average, is less educated.”
Affinity Marketing and the Latino American Fintech Opportunity (Chaos Engineering)
Excerpt: "In the case of Hispanics and Latinos, one foundational need is financial services in their primary language... and another is providing simple, transparent products that cater to a population that, on average, is less educated."
Web3
Review: Chris Dixon’s Read Write Own (Citation Needed)
Excerpt: "Dixon has found the solution to the internet's Big Tech sickness: blockchains. "While plenty of people recognize their potential—including me—much of the establishment disregards them," complains a general partner at one of the most powerful venture capital firms in the web space. Now, if we would all just be so kind as to ignore the last fifteen years since blockchains' inception — during which innumerable companies have flailed around trying to find any possible use case beyond the manic speculation."
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