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@aishwaryad07 White: Smith-Morra Gambit Black: KID, Benoni, Najdorf

JUST IN: ALL THE TOP INVESTORS IN THE WORLD JUST UPDATED THEIR PORTFOLIOS HERE’S EXACTLY WHAT THEY’RE HOLDING AND HAVE BEEN BUYING 🧵⬇️

The latest 𝕏 algorithm has been published to GitHub github.com/xai-org/x-algo…

@Evan_ss6 U dropped this king 👑

QQQ LEAPS up 115% in 2 weeks

#2 across all new releases in Canada.

"AAA graphics aren't possible in the browser" Hold my beer 🍺

The 'inequality life expectancy gap' is going to widen DRAMATICALLY over the next years, more and more. We are learning so much about the unhealthy ways that have become default in 'modern life'. Having followed much of the health research for the last many years, I've become consious to the fact that the world around us in cities is not built for health whatsoever. There are SO many constant things we are exposed to that are disrupting our bodies, from what we wear and what we eat/drink, what we put on our skin, what we breathe.. And that is just on the MINUS side. Ie the cost many average people are paying compared to what a natural life would be. Add on top of that the potential PLUS side. Optimization protocols that are being discovered more and more that make our cells work in *better* than natural ways, age slower, more efficient mitochondria etc. The floor on both MINUS and PLUS will rise much slower for the average person that for those really looking and focusing on this aspect, that will find the pockets of information and access to keep themselves healthy as they age. It is not simply resources, it is even just the KNOWLEDGE because a lot of these improvements are free/low cost and just a matter of having enough mindspace to look at it. Rich people will have more people around them talking about these things to hear about it from word of mouth. Youtube, podcasts, Twitter one of the few equalizers of this inequality- but have to follow the right people. Thing is if you have good judgement to follow the right people you will automatically anyways get richer, hence the (poor + healthy) quadrant will remain almost empty.

I've tweeted about this before but it's a good reminder The founder of Tik Tok was running out of money trying to build an education start up. One day, he looked at the people on his train. Eyes blank. None of them were learning the next day he pivoted to brain rot and won

You're not depressed. You just don't have a quest. you need to be quest maxxing. Here are 25 side quests to start immediately:

great article, mostly focused on coding agents but applies elsewhere impo. aligns w a lot of my prior thoughts: - agents need scaffolding, not just smarter models - failures should become durable improvements - tools/functions should be small, reusable, and logged - execution environments matter - tests and deterministic checks are essential - memory should live outside the model - agent systems should improve through use

actually pretty cool, if it works in a way where settlement happens via stablecoins on chain. tournament operators can vet action sellers and distribute payouts directly to onchain pool. players don't care about transaction size/volume when thats the main hassle in selling to multiple counterparties. more interesting use case would be for icm/chip value shares being bought and sold in late stages of tournaments. these trition final tables are being played for too much money to begin with for the average person playing anyways. with that being said the current ui isn't great you can't really tell what you are even buying and i can see it being exploitative as hell as im guessing most jupiter users don't know much about player edges. would bre pretty interesting if they offered users ability to offer short shares of players as well.

While everyone was busy chasing $NVDA they ignored $SNDK at the lows. While everyone was busy chasing Bitcoin they missed $HOOD at the lows. While everyone was chasing $GOLD they missed Semis. And while everyone is chasing Semis and Memory they are missing something else.

"Memory is cyclical, everyone knows that, and the recent run up in memory names is an obvious bubble." That's the easy, reflexive view. But I think the people who hold it are missing the simple scale of what AI is doing to memory demand. The first clue that there might be more to the memory story came in January of this year when it came out that NVDA's next gen Rubin platform would require 16 TB of NAND per GPU, or 1152 TB per rack, and that required HBM bandwidth for the system would be 70% higher than what had been previously reported. That was the first time it became obvious to outside observers that memory would need to scale exponentially to keep up with already-known GPU demand. One under-appreciated fact is that while GPU compute has largely scaled with Moore's Law (doubling in compute ~every 2 years), memory density and speed hasn't. As GPU compute continues to scale, existing memory manufacturers must produce exponentially more chips. These chips will also need to be faster than ever, which introduces an incredible technical challenge: how can memory manufacturers find the required speed improvements that have eluded them for decades? When you combine this added technical complexity with an exponentially expanding demand for the product, memory starts to look less like the "commodity" everyone knows it to be, and much more like a high-margin proprietary chip. This hasn't even touched on memory's role in inference (compute needed for inference is expanding exponentially as well, and is highly memory-dependent), long context, etc. Agentic AI requires agents to pull massive amounts of data into their context, which increases the number of tokens per "turn" and also the amount of memory required to run them. True agentic systems will require both dramatically higher context, and also many more "turns" or iterations of each task (as they improve an output over and over until it reaches a target quality level). Longer context = more memory per workload, and more "turns" = more workload per output. To put a specific number on that, Micron SVP Jeremy Werner said recently on The Circuit that agentic AI is causing context length to grow 30x a year. Michael Dell recently framed the problem in extremely simple terms: H100 had 80GB of HBM; by 2028, accelerators could carry ~2TB. That is 25x more memory per accelerator. Over the same period, he expects roughly 25x more accelerators deployed. That's 25 x 25 = 625x more accelerator memory demand by 2028. Everyone knows memory stocks are cyclical, and they always look cheap right before the bubble bursts. But what if there are structural changes happening in the memory markets that could prove the consensus wrong? Does anyone remember another traditionally cyclical company that has rerated to a growth story due to the demand from AI? Hint: It's now the most valuable company in the world. Reminder: this is not a recommendation to buy or sell any securities. It's a framework for thinking about how the AI buildout may be changing the memory market.

AI is going to affect every aspect of our lives...but it can also prolong + improve life. Digital Biology feels like a catchphrase now but in 5yr or less, it will be a major sector as personalized medicine via AI augmented research pays off for everything from oncology to autoimmune conditions. $ABCL & $ABSI are two bets I've made in this space.

🚨 SOMEONE JUST KILLED THE REAL ESTATE INDUSTRY A guy scanned an entire house with his phone. Uploaded it. Now anyone on Earth can walk through it in a browser tab. No app. No VR. No agent. No appointment. Click → you’re inside. Every room. Every angle. Every shadow. Photoreal. The numbers are insane: - Agent fee on a $500k home: $15,000 - Cost to make this scan: ~$200 - Time to “tour” 50 houses: one evening - File size: smaller than a TikTok The science is wild too: It’s called 3D Gaussian Splatting instead of polygons (how games render), it uses millions of tiny glowing “splats” of color and depth. AI reconstructs reality from your photos. The result loads on a phone and looks like you’re THERE. The grift opportunity is even wilder: Freelancers are already charging $300–$800 per scan for realtors, Airbnbs, venues, car dealers, museums. One person + one phone + one weekend = a business. 100% Open source. Built on PlayCanvas.

The most egregious low-to-no-revenue dot-com bubble IPO, Webvan, had a peak market cap of $4.8 billion.

People keep confusing a bubble with “stocks go up and get overvalued”. A bubble is when when a prevailing trend and a prevailing misconception about that trend interact reflexively, each reinforcing the other until the gap between perception and reality becomes unsustainable. A bubble is not when everyone realizes that right now every iota of AI demand eventually, at some point upstream, must move through memory OEMs. Nor is it when estimates continue rising because things are better than expected. And it’s not just when stocks trade expensive to historical valuations. The reason behind the moves in the AI infrastructure layer so far have been simply that we don’t have enough. They’ve been driven by the fundamental reality more than the perception of the future. It’s why the bulk of the most bullish parts of this cycle have been lumpy and centered around earnings season when companies uniformly come out and confirm there’s still not enough. In the bubble, the reality is driven by the market - not the other way around. Everyone keeps saying “people are gonna freak out if it’s not a bubble!”. I think that’s silly, we have a transformative new technology that needs crazy capital to fuel it coming to fruition, that has and always will result in a bubble as long as we have financial markets. But if you want to call the top in a bubble, you need a much stronger view on what the misconception is and what negative catalyst forces broad perception to align with realizing it than you do on valuation.

Claude is telling you to play chess

@cynbahati Great post but what’s the counter thesis?

Mira Murati One of the smartest people alive (founder of Thinking Labs & ex OpenAI CTO) and casually stunning at the Met Gala Goals.