AZ👾
1.5K posts
AZ👾
@contrarycap5
There are no solutions. There are only trade-offs.
Katılım Nisan 2023
1.9K Takip Edilen1.6K Takipçiler
I'm traveling the world for a bit, starting with China but then hopping around the globe, anywhere. Open to any adventure. No plans, only a backpack. Hoping to meet & get to know humans from all walks of life. The pic is from a long hike on the Great Wall. For me, as a fan of history, this was an epic experience.
In China, first I'm visiting a few big cities & talking to engineers at the heart of China's AI revolution. After that, if feeling crazy enough, I'm hitchhiking (first time) across rural China for a few weeks. Hitchhiking because I think it's the best way to meet rural folks who I would otherwise never get the chance to meet. I hope to do the same in US and other places.
I have a request, if you have a travel recommendation, fill out the form(s) below if you feel like it. Or share with folks who might have advice about such travel.
Form 1 - travel recommendation:
If you can, recommend to me an interesting place I should visit anywhere in the world. For this, fill out form 1. Not touristy stuff, but something off the beaten path, that tourists may not know about, but is legendary. It could be as remote as meeting a herder in the mountains who is a local legend. Asia, Middle East, Europe, India, South/North America, Africa, Australia, anywhere. In China, I'm hoping to visit maybe Heibei, Shanxi, Shaanxi, Gansu, Sichuan, Yunnan, etc, so recommendations for spots to visit are helpful.
Form 2 - coffee:
If you want to grab a coffee with me anywhere in the world, fill out form 2 (please don't use form 1 for that).
Anyway, I hectically tossed stuff in backpack. Realizing I don't have a clear plan of any kind, which is probably the only way to do it. LFG.
Love you all ❤️
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AZ👾 retweetledi
AZ👾 retweetledi
some thoughts on the shape of foundation labs
1) epoch ai estimated anthropic @ $9m in revenue per employee and openai @ 5.6m in revenue per employee
2) these rates would be the highest among public technology companies; but, i'm not sure how valuable it is to look at on its own
3) the closest equivalents are quant firms like jane street @ $12m and hudson river @ $9m and energy infrastructure companies like valero energy @ 13m
4) revenue per employee is a complicated measure because a lot of it depends on accounting and different firms consider different things revenue
5) but, quant shops have high revenue per employee because they have a lot of revenue on top of a small number of specialized, expensive researchers
6) and, oil refineries have high revenue per employee because they can process a lot of oil with small number of employees, using very expensive tooling
7) foundation labs feel like a combination of these two things
8) like quant shops, they have a small number of very highly paid researchers and, like energy infrastructure companies, each employee is very heavily capitalized
9) traditional technology companies don't capitalize their employees very heavily; claude estimates nvidia spends $100k in r&d opex per employee per year, apple $80k per employee per year
10) in contrast, openai will probably spend ~$35bn in r&d compute this year with ~5000 employees; this would imply openai will spend ~70x what traditional tech companies spend in r&d opex per employee
11) now, in practice, this r&d opex spend is concentrated on a small team of core researchers and this would make the comparison even more stark
12) in this respect, they really are a new kind of tech business; they are not quite like hyperscalers, saas, ad-tech, e-commerce or hardware companies, etc...
13) they have unrivaled tam, distribution like plg saas, lower gross margins, an employee base more like quant shops, unique r&d dynamics, and capital requirements that if you squint sometimes look like a hyperscaler
Epoch AI@EpochAIResearch
Anthropic and OpenAI earn more revenue per employee than the top public tech companies, both now and at their IPOs. Anthropic: ~$9M OpenAI: ~$5.6M Top public co. (Nvidia): ~$5.1M
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I guess what you are saying is bulk-data problems are solved but for longer-horizon physical tasks it will require solving the long-tail problem. However, the difference between robotics and FSD is not all robotics tasks need the same number of nines (for tasks that don't risk human fatality as an outcome)
Also the breakthroughs in Fan's video are tackling some of the problems you state. The DreamDojo world model is video prediction conditioned on actions. It will inherently teach/learn physics bc in order to predict the next frame, the model has to know what actions to do the world
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I’d push back a bit and say the world model itself isn’t free. You need real-world data to build a high-fidelity simulator in the first place, and sim-to-real is incredibly hard. Running more compute on a flawed world model just produces more flawed data faster. This is basically the march of 9’s problem.
Getting from 90% → 99% → 99.9% reliability each takes roughly the same effort as the prior step, because the failure modes get progressively weirder and longer-tail.
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What is different in the robotics paradigm is that more compute will create more training data, as data is just the byproduct of running compute on the world model
Jim Fan@DrJimFan
I promise this will be the best 20 min you spend today! Robotics: Endgame, the sequel to my last year's Sequoia AI Ascent talk, "Physical Turing Test". I laid out the roadmap for solving Physical AGI as a simple parallel to the LLM success story. Be a good scientist, copy homework ;) And stay till the end, more easter eggs and predictions for your polymarket! 00:30 DGX-1 origin story at OpenAI, I was there in 2016 signing with Jensen and Elon. Heading to the Computer History Museum! 01:42 The Great Parallel 03:31 Robotics, the Endgame 03:39 Why VLAs fall short 04:32 Video world models as the 2nd pretraining paradigm 06:09 World Action Models (WAM) 07:46 Strategies for robot data collection and the FSD equivalent to physical data flywheel for robot manipulation 11:06 EgoScale and the Dexterity Scaling Law we discovered recently 14:00 Physical RL: bridging the last mile 15:39 DreamDojo: an end-to-end neural physics engine for scaling RL in silico 17:00 Civilizational Technology Tree and my predictions for the near future. Spoiler: it's closer than you think. Thanks to my friends at Sequoia for inviting me back to AI Ascent this year! I had a blast! Last year's talk is attached in the thread if you missed it.
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@arian_ghashghai @credistick Lots of parallels to previous crypto cycles of low float high val
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Both founders and VCs are currently assuming that "getting rich off secondaries" will be a permanent state of the private market vs a temporary one (inherently a risky position imo), and thus private market exits are what need to be optimized for
Since private market valuations have very little correlation with actual business performance i.e. companies that raise a lot and spend a lot to turn over a lot (most unprofitably) are almost always valued more highly than a lightly VC-funded business with positive FCF. Pair this with the often-repeated idea that only 10 or so private companies matter, you end up with:
> primary focus of the business becomes how to be popular with private market investors (as they are your supposedly only source of liquidity)
> startup founding devolves into a status game (and attracts many fitting participants i.e. grifters etc)
> bad assets get dumped onto unknowing idiots downstream (or just the one that gets caught holding the bag)
Feels like an unsustainable prevailing setup for the entire venture asset class
Preston@metapreston
Current meta: VC's and founders getting rich off of secondaries. No need to exit
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AZ👾 retweetledi
We are quickly approaching a tipping point where geriatric non-tech billionaires will be tempted to yolo half of their immense fortunes at GPU clusters dedicated to solving whatever pet disease they happen to be worried about as a far more compelling gambit vs the giving pledge or another university building.
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My surprise is not that the number of travel agents has fallen, but that it's only down 50% in the last 25 years.
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@ccbaker2023 @poolnoodle93 At least she wasn’t the cashier at Four Horsemen
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@poolnoodle93 The other day I stopped in a wine store off the Bedford L that had a big vinyl collection. I made a James Murphy joke to the cashier and she had never heard of him. This was literally around the corner from Four Horsemen
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walking on bedford avenue on a saturday feels surreal in 2026. there is no history left and not even a hint of nostalgia. the people have completely turned over. you might as well live in richmond, va or any other tier two city and find yourself more connected to place.
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@tomhschmidt I like my coffee like I like my accounting fraud, brewed in china and served here in america
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🎶 you know who we are 🎶
🎶 cuz we luckin all over the world 🎶
Tom Schmidt ＞|＜@tomhschmidt
The Luckin company is giving the Chinese data on me — that’s ok, I’ll still keep drinking that garbage
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@johnarnold This also happened to me with a full shoulder/labrum tear. Grateful to the younger doctor
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Many years ago I hurt my knee playing sports. I was referred to the orthopedist for one of the local pro teams. After keeping me waiting for 2.5 hours, he diagnosed a cartilage tear and recommended surgery. I was so mad at his manner and tardiness I left without scheduling.
The next week I got a second opinion from a much younger doc who was likely more current on the recent medical literature. He looked at the same MRI. He said he could do surgery now but his advice was to wait 30 days and see if it healed on its own. It did.
Medical reversal is when a practice that became widely used is later shown to be ineffective or even harmful. Examples like meniscus surgery show the need to keep gathering evidence. A not immaterial part of the practice of modern medicine doesn't improve health, and may be net harmful.
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@0xMentalIllness or countries dumping UST to shore up domestic currency
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How much of the treasury dumping is people chasing stocks for the Fourth Industrial Revolution?
How could you keep clients in bonds as the most profitable companies in the history of the world have half a trillion in unserved demand?
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AZ👾 retweetledi
yeah I'm really optimistic about DeepSeek now.
they will scale *aggressively* on Chinese compute, they will leapfrog every competitor.
Jensen wasn't speculating, he knew what is happening.
This will be V5. V4 is mostly preparation for migration. Kimi can have H1 2026.
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World Cup final tickets this summer are going for $15k a seat
Timothy B. Lee@binarybits
This essay by @alexolegimas is the best thing I've ever read on why AGI won't lead to mass unemployment. A compelling argument backed up by substantial empirical data.
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AZ👾 retweetledi
New newsletter: HOW THE 2020s BROKE OUR BRAINS
It's the Tragic Twenties, and Americans can't stop feeling like hot garbage.
- The UMich consumer sentiment survey is now at its lowest rate on record
- The Fed's job satisfaction survey is at its lowest rate on record
- Both the General Social Survey and the World Happiness Survey have found that happiness in the US plunged in 2020 and has since been mired at levels significantly below previous decades
You shouldn't assume that your favorite pet issue is the main culprit here. Conservatives might point to cultural changes, like the decline of marriage and religiosity, but those have been going on for decades. The left might reach for wage inequality, but that has actually narrowed in the last six years. This can't even primarily be about phones, since what's most clear in the data set is something that changed this decade, not last decade.
I spent a long time reading, talking to people, and doing my own research, and I think the most parsimonious explanation I can provide is this:
The Pandemic Never Ended.
This thesis has three parts.
TPNE 1: The biological antagonist of COVID gave way to the economic antagonist of inflation, and after decades of coming to rely on lowflation and meager wage growth for low-income workers, price levels have increased 3x faster this decade than in the previous 40 years, and economists simply have to accept that inflation makes people angrier than it used to. This isn't even a strictly American phenomenon. Around the world, incumbents have lost power faster than any post-WWII period, as affordability concerns bludgeon their electorate. The few countries where happiness levels have increased in the western world in the last 6 years have had some of the lowest levels of inflation.
TPNE 2: Institutions down, individualism up: The 2020s have seen trust plummet for practically every institution, along with growing distrust in strangers, and rising alone time and at-home time. At best, community offers a buffer in times of crisis. But today, the absence of community—and the triumph of a tech-enabled, hyper-introverted atomism—makes every crisis feel more existential and unsolvable. And that's a problem bc...
TPNE 3: The 2020s have been the permacrisis crisis decade. It's really been one fucking thing after another, hasn't it? Pandemic, inflation, interest rates, Ukraine, Gaza, Iran, AI. Meanwhile, phones give us constant contact with both the scary news cycle and the panic-inducing fears and anxieties of the commentariat.
Inflation makes today's life feel harder to live. The news cycle makes tomorrow's world scarier to live through. And the post-pandemic decline of institutions and acceleration of toxic individualism weakens our socio-emotional immune system to deal with all of it.
TLDR: The pandemic never ended, and it's left us with the Tragic Twenties.
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