1/ This week's Q3 earnings call w/ $FB will likely go down as one of the biggest bets in history. IMO they'll spend >$170B over the next decade on building the metaverse. Since it's my largest position, I've been spending a lot of time reflecting. Attached are my "scratch notes"

OAI rate limit resets remind me of Uber promotions in 2012. "Refer a friend and get $20 off your next ride".

I'm hosting a pickleball / padel event in SF on Wed 6/17 with @elise_ai and @SapphireVC for AI engineers, builders, and founders! Come by for some friendly competition and good vibes 🎾 luma.com/l0cu9a2z

Re: $META.. 1. Below I believe is a summary of Facebook's medium term opportunities with AI 2. I actually don't think they need to be on the frontier to make make most of this a reality 3. It seems like they are "catching up" quickly and people will be surprised by end of 2026

Sarah Friar on the All-in podcast: "Our next big training run in the Fall will be on Vera Rubins"

the answer is.. very long (2-3 years).

Composer 2.5 being Pareto dominant in coding per CursorBench is important. This is after only a few weeks of supplemental training and/or RL in the Colossus 2 cluster.   The 1.5 trillion parameter version of Grok will likely be a much better base model than Kimi. We shall see.

The Uber AV thesis essentially boils down to one question.. "Will the technology commoditize faster than Waymo's 1st party network can get to scale?"

The Anthrophic Krishna Rao with @InvestLikeBest is great. Says they want to be a platform. Take Gates postulate that platforms capture small % of value for customers / ecosystem. iPhone - $200B rev = $2T in value Windows - $17B rev = $170B in value Anthrophic - $45B rev = $450B in value?

Having spent the past few weeks in Beijing giving talks and attending meetings, here are some quick observations as I wait for my flight to NYC to board: 1. The talk of the town has, of course, been the Xi-Trump meeting, but no one (not even usually well informed elite circle insiders) seems to know what it actually accomplished, other than a continuation of the detente that’s been in place for the past several months. That’s about as good an outcome as one could realistically expect, I suppose, but clearly a real “grand bargain” is not in the cards anytime soon. 2. The Chinese economy seems to be in a steady state, neither improving much nor visibly deteriorating like it was in 24-25. In that sense the government’s stimulus policies have had a positive effect, but the vast majority of industry people I talked to remain very pessimistic about domestic profits and consumption. The dominant sentiment is that the only way for major firms to generate profit growth is through direct overseas expansion. 3. That said, technological advancement is of course very real and quite impressive (although it’s not quite as visible in Beijing as it is in, say, Shenzhen). One interesting and very pleasant side effect of the EV revolution (paired with infrastructure investment) has been that Beijing is now a bike-able city again, given the sharp reduction in exhaust fumes on city streets and the expansion of bike lanes. Armed with a new bike, I could almost explore the city like I used to back in 2000. Hugely nostalgic feeling. 4. Academia is, in general, in a pretty dour mood. STEM subjects and the social sciences/humanities alike have seen very significant funding reductions over the past 2 years, but the latter have of course gotten the worst end of the deal. Political censorship also seems to be visibly ramping up again, with the sheer scale of perceived “red lines” snowballing to levels unprecedented since the early 1990s. As the recent Yang Nianqun incident suggests, administrative regulation of faculty members’ personal affairs has also expanded (i.e., consensual extramarital relationships between adults who were not in a direct teacher-student relationship would almost certainly have gone unpunished as recently as 5 years ago). 5. In general, it’s hard not to notice the steady increase in government presence in everyday life—in both positive and negative ways. The city feels safer and cleaner than it ever has been, and yet the layers of administrative review needed for just about any kind of professional activity have clearly proliferated on a vast scale (made less painful by the digitization of most government services and more uniform law abidance, but still more onerous than it used to be despite all that). 6. The most alarming thing, I suppose, is that general optimism (personal or socioeconomic) seems to be in particularly short supply among the younger generations. This is obvious even among the most intellectually gifted kids at Tsinghua and PKU, where the level of career anxiety seems to be at a level that I have never encountered before. Unsurprisingly, willingness to form families or plan ahead in general at the personal level is very low. All in all, it was, as always, a very informative couple of weeks. The stay was also made much more pleasant by the fact that I managed to do it before Beijing becomes brutally hot. I look forward to being back more often in the near future.

Codex with Computer Use is magical.. feels a lot like ChatGPT in 2023. Constantly have to stop myself midway through a task with "oh, Codex can do this".

OpenAI and Anthrophic already have an army of FDEs, I believe they typically refer to themselves as “SaaS companies”.

Impressive growth persistence by Google's Gemini

People talk, listen, watch, think, and collaborate at the same time, in real time. We've designed an AI that works with people the same way. We share our approach, early results, and a quick look at our model in action. thinkingmachines.ai/blog/int…

xAI reselling its excess capacity?

One of the easiest ways to forecast job loss from AI is to just look at automation in general.

Am I understanding correctly here? Says they’re selling compute / chips to competitors so they can fund their first party initiatives like Gemini? Google isn’t capital constrained? Is there some 3D chess here I don’t understand? Is he just going rogue? Seems bizarre.

OAI / @gabeeegoooh cooked with Image-2. Looks a lot less like "AI Slop". Previous gen vs. Image-2. Same prompt.

Many folks seem to be confused, and think the collapse of the CS major graduation numbers at Berkeley could be linked to the "AI is taking SWE jobs" hysteria narrative. Here's the easiest way to see that this is false: the timeline doesn't fit. The graduating class in 2027 (first small CS cohort graduating) has students who arrived on campus as freshmen in Fall 2023, with freshman admission targets set (i.e. shrunk) by the university in Fall 2022. So, the hysteria narrative obviously doesn't match the timeline; ChatGPT didn't even come out until November 2022. Now consider the plot below; orange curve is what % of bachelor's degrees are CS degrees each year at Berkeley, and blue curve is what % of applicants applied to be a part of that graduating year, intending to be a CS major in their application (combining both junior transfer and freshman applicants). In other words: * orange measures CS graduate production * blue measures CS demand (via % of all applications to the university) What do you notice? The collapse in orange (CS grads) isn't because of a collapse in blue (demand). In fact it's the opposite: orange collapsed at a time when blue was going up. 1/

$CRM.. "23,000 customers out of the total base of 150,000 to build custom autonomous agents for use in workflows" - WSJ Let's assume 1/2 are not "real" paying customers. 8% penetration after 3 years? Brutal.

Jensen vs. Dwarkesh; there isn't even clear agreement on what we're trying to accomplish? Are we trying to hobble or completely stop China's progress? Prevent cyber and military capabilities? Reduce economic chokepoints? SOTA or inference? What timeline, 5, 10, or 20 years? Etc