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Alan
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Alan
@0imalan
curr: paxmod. prev: prod and eng @ amazon, anduril, lyft, toyota research, DoD. I like robots and aerodynamics.
Australia Katılım Ocak 2024
814 Takip Edilen334 Takipçiler
Haha we called the “continuous learning machine” the “active learning loop”. Good times.
Nicholas Charriere@nichochar
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@loveDoges111 This is why woman need to have human babies… wtf is this..
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SaaS founders at end of month looking at their token costs.
Mesh🇧🇧@rahsh33m
I understand the calculations lol
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The end game for software is on demand ephemeral software as Karpathy says. There is decreasing incentive to buy apps like this. Not sure what this means for competition.
@levelsio@levelsio
This took 24 minutes Back when I did 12 startups in 12 months in 2014, it took me at least a month to make a new startup and I didn't even finish it And they were in fact as basic as this kind of, because they were MVPs too! If 'd ship every day and I sleep 8 hours I have 24-8=16 hours * 60 minutes = 960 minutes per day. And it takes 24 minutes per startup with AI to build an MVP So theoretically you can build 40 ideas per day, and if you work 6 days a week that's 1,000 per month and about 12,000 per year So a decade later, you can now build 12,000 startups in 12 months
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The <script> element was introduced with HTML 3.2, which was published in January 1997. This was the beginning of the end for the internet.
Artur Chakhvadze@norpadon
Can we please not do this? I want as little JavaScript on the websites I use as possible. The best designed and engineered website in the world is mobile Wikipedia. Everyone should emulate it
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@paulsaladinomd I remember when told people not to eat broccoli hahaha wtf get blocked
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Meat and potatoes have always been elite.
You father knew this, your grandfather knew this...
You could almost live on these two foods.
Throw in a little fruit for vitamin C, what else do you need?
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This guy is such a whiny dude
Elon Musk@elonmusk
Probability of me getting a fair trial if this is how the judge dresses is 0.0%
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Ask yourself why meta is the company doing research like this.
AI at Meta@AIatMeta
Today we're introducing TRIBE v2 (Trimodal Brain Encoder), a foundation model trained to predict how the human brain responds to almost any sight or sound. Building on our Algonauts 2025 award-winning architecture, TRIBE v2 draws on 500+ hours of fMRI recordings from 700+ people to create a digital twin of neural activity and enable zero-shot predictions for new subjects, languages, and tasks. Try the demo and learn more here: go.meta.me/tribe2
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Terence Tao is the greatest living mathematician.
Fields Medal at 31. Solved problems that had been open for a century. Widely regarded as the sharpest analytical mind alive.
And he just told you the thing your entire career is built on is now worthless.
Tao: “AI has basically driven the cost of idea generation down to almost zero.”
For five hundred years, the idea was the prize.
The theory. The hypothesis. The flash of insight a physicist chased for twenty years in a lab before it landed.
That was the bottleneck. That was what tenure rewarded. That was what Nobel committees were looking for.
Gone.
A model can generate a thousand candidate theories for a scientific problem in an afternoon. Not noise. Not garbage. Plausible, structured, publishable-grade hypotheses.
A thousand of them. Before dinner.
The idea used to be the scarcest resource in any room.
Now it is the cheapest.
But Tao went somewhere most people are not ready to follow.
Tao: “Verification, validation, and assessing what ideas actually move the subject forward… that’s not something we know how to do at scale.”
Sit with that.
We automated creation.
We did not automate truth.
We can produce ten thousand explanations for a phenomenon.
We cannot tell you which ones are real.
That is not a gap. That is a chasm.
And it is the most important unsolved problem on Earth right now.
Tao: “Human reviewers… they’re already being overwhelmed actually.”
The entire scientific apparatus was built for a world where a single paper took months to produce.
Peer review. Journal boards. Consensus forged over years of replication and debate.
That infrastructure was never designed for what just hit it.
Journals are flooded. Reviewers are buried. The filters that separated signal from noise for decades were engineered for human-speed output.
They are now absorbing machine-speed volume.
And they are cracking under it.
Tao compared it to the internet.
The internet drove the cost of communication to zero. That did not produce clarity. It produced an ocean of noise with islands of signal buried somewhere inside.
AI just did the same thing to knowledge itself.
Infinite generation. Zero verification.
The person who can produce ideas has never mattered less.
The person who can prove which ideas are true has never mattered more.
That is the inversion nobody is processing.
Every company, every lab, every institution is racing to generate more. Faster models. Bigger outputs. More theories. More code. More content.
Nobody is building the system that tells you which of those outputs are actually correct.
And that is the only system that matters.
Whoever solves verification at scale does not win a market.
They become the filter that all of science, all of engineering, all of human discovery flows through.
The bottleneck of the last five hundred years was producing the answer.
The bottleneck of the next fifty is knowing whether the answer is real.
And right now, according to the greatest mathematician alive, we do not know how to do that at the speed the machines demand.
That is not a research problem.
That is the race beneath the race.
And almost nobody has entered it.
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@__tinygrad__ Mac mini m2
Model: qwen3.5 9B
Tok/s: enough that it doesn’t matter really
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To anyone using local LLMs, what hardware do you have, what model are you using, and what tok/s are you getting?
Franci Penov@francip
@LottoLabs @max_paperclips I want to see numbers of tinygrad vs llama.cop
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Gstack shows the value of specific knowledge (as @naval calls it). There is incredible leverage in asking the right questions which essentially what gstack helps you do.
Garry Tan@garrytan
GStack is your personal AI coding toolkit, I'm dropping multiple new features per day right now
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@ChombaBupe Hm listen to chomba because he’s vibe coded a few web apps or listen to world most influential mathematician.
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Honestly, no disrespect but if the interview starts with comparing a language model (LM) to a human I consider everything that follows afterwards a waste of time to listen to.
Dwarkesh Patel@dwarkesh_sp
The Terence Tao episode. We begin with the absolutely ingenious and surprising way in which Kepler discovered the laws of planetary motion. People sometimes say that AI will make especially fast progress at scientific discovery because of tight verification loops. But the story of how we discovered the shape of our solar system shows how the verification loop for correct ideas can be decades (or even millennia) long. During this time, what we know today as the better theory can often actually make worse predictions (Copernicus's model of circular orbits around the sun was actually less accurate than Ptolemy's geocentric model). And the reasons it survives this epistemic hell is some mixture of judgment and heuristics that we don’t even understand well enough to actually articulate, much less codify into an RL loop. Hope you enjoy! 0:00:00 – Kepler was a high temperature LLM 0:11:44 – How would we know if there’s a new unifying concept within heaps of AI slop? 0:26:10 – The deductive overhang 0:30:31 – Selection bias in reported AI discoveries 0:46:43 – AI makes papers richer and broader, but not deeper 0:53:00 – If AI solves a problem, can humans get understanding out of it? 0:59:20 – We need a semi-formal language for the way that scientists actually talk to each other 1:09:48 – How Terry uses his time 1:17:05 – Human-AI hybrids will dominate math for a lot longer Look up Dwarkesh Podcast on YouTube, Apple Podcasts, or Spotify.
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Julian PERFORMS Ancient Meditation practice and his response is surprising...
Dr. K walks Julian through the Yogic Ashram (1-4 ) practice.
WAIT UNTIL END...
@HealthyGamerGG
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The hype around this just shows how useless twitter/x has become.
Okara@askOkara
Today we're introducing the world's first AI CMO. Enter your website and it deploys a team of agents to help you get traffic and users. Try it now at okara.ai/cmo
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