Combining mechanistic interpretability with economic game theory, Risk Tokens would price inference based on internal reasoning patterns and risk assessment, making attacks on AI safety potentially economically irrational.
As narratives increase in value, a new generation of companies build on the power of perception, while markets race to fill every speculative void.
The progression of building Applied Research Organizations and how venture capital may be changing science and research development forever
Observing what the rapid rise of conviction in AI disrupting robotics says about technological forecasting, company building, and investing in 2024.
Analyzing where we are in the current AI cycle and navigating the meta-moats over the short to long-term that impact company building.
I recently re-read three fantastic (and imo canonical) older crypto posts that shaped a lot of how people think about value capture in crypto (Fat Protocols, Thin Applications, and Crypto Tokens and the Coming Age of Protocol Innovation). via Power Laws & Normal Distribution in Crypto The original fat protocol thesis is well understood in terms of L1 value accrual, but it also meant that you...
What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle. Marvin Minsky The Frontiers of Increasing AI Performance There has been a lot of work done on pushing the performance of machine learning with the structure of transformers + scaling in the past few years. Alongside this, AI...
I kind of thought of the UI as the product and then machine learning came along and the Machine learning was there to sort of help the UI and that shifted completely. Now AI is the product and the UI is there to to help the AI to capture better signal. — Gustav Söderström, Co-President, CPO & CTO at Spotify, Source It’s very clear that some version of the future includes a world where...
I believe one of the most damaging pieces of advice to proliferate in the tech world over the past few years has been “being early is indistinguishable from being wrong”. There are many reasons why this is true in theory but as I’ve talked about for years, at this stage of technology development and penetration, whether you’re a technologist or capital allocator, if you’re not too early, you’re...
How business models differ in Open-Source AI versus traditional OSS + thoughts on how Brand Moats are increasingly important in AI broadly.
When an area becomes consensus but is still somewhat novel or hard to parse for investors, they often try to distill companies into very clear-cut and easily “findable” metrics in order to make decisions. In many cases, this wave of chaos, rapid change, and complexity pushes investors to retreat into discussing a constant in startups; Founders. And as one searches for Founder-Company...
AI companies today find themselves in multiple cycles of R&D and commercialization, making an implicit bet that the millions or billions of dollars spent on R&D will eventually lead to market domination and massive scale years from now. This pushes these companies into a dark forest they must navigate
What tracking changes in narratives tells us about conviction, depth, and emotions during times of exuberance and volatility
Navigating go-to-market, product, and customers during the most dangerous phase of an emerging category.
Power laws rule everything around us. This is a core principal of what we have largely come to learn in a world dominated by this narrative, which has also helped proliferate the concept of Asymmetric Upside. Within traditional tech/Web2, due to the compounding nature of moats (most notably network effects) and duopolistic markets, it is often assumed that outcomes follow a colloquial power law...
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