Ido Rosen @idorosen
#ai #ml #economics #neuroscience #trading #pilot #xoogler👨💻🤖🧠📈🛩🏳️🌈 (tweets my own. not advice. no endorsement implied.) ido.ai San Francisco, CA Joined February 2008-
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I often hear that evals are the most confusing part of creating LLM AI products. It's a shame b/c IMO, domain-specific evals are the most important part of an AI product! I've written a detailed blog post with real examples on how to do this (1/3) hamel.dev/blog/posts/eva…
There appears to be a mismatch between publishing criteria in AI conferences and "what actually works". It is easy to publish new mathematical constructs (e.g. new models, new layers, new modules, new losses), but as Apple's MM1 paper concludes: 1. Encoder Lesson: Image…
I'm releasing all the lectures and notes for an introductory course on Statistical Detection and Estimation I used to teach. The core material hasn't changed - it was an EE course, but it's as relevant today to AI researchers as ever before. Hope you find it useful. Covers: *…
I put up a mini-site today at citydensity.com to help you compare the world’s cities. You can see how many people live near a city, or use my favourite metric: "population weighted density" to get an accurate measure of how dense a city is to live in.
@karpathy is perhaps the most talented deep learning teacher out there, and his video lectures are always worth watching. Some minor addenda on the history of tokenization: While GPT-2 used sub-word tokenization pretty early, it was really shown to be important for handling…
@karpathy is perhaps the most talented deep learning teacher out there, and his video lectures are always worth watching. Some minor addenda on the history of tokenization: While GPT-2 used sub-word tokenization pretty early, it was really shown to be important for handling…
@Tim_Dettmers Yeah exactly. The trap is that the original creator has actually built it piece by piece and over time molded it, which creates an unintuitively large disparity between how easy they perceive it, and how easy fresh eyes perceive it, even when controlling for technical level.
Have you ever done a dense grid search over neural network hyperparameters? Like a *really dense* grid search? It looks like this (!!). Blueish colors correspond to hyperparameters for which training converges, redish colors to hyperparameters for which training diverges.
Folks, you don't need anything special to have python automatically drop you into the debugger if there's an exception -- this capability is already built in! Here's a complete demonstration of how to do it, including an alias you might find pretty handy:
The skills needed for developing new ML techniques have little overlap with the skills needed for applying ML effectively. A bit like how chip design has little overlap with software engineering.
I'd like to start 2024 with some thoughts on the state of optimization theory. To begin with, let me quote Nesterov's 2003 book: "The main fact, which should be known to any person dealing with optimization models, is that, in general, the optimization problems are unsolvable" 🧵
@dharmesh Vector embeddings *do not* magically solve search. In fact, the heavy lifting is in the step before you re-rank with semantic similarity search. Making a genuine improvement over BM25 or full-text search is hard.
What people think production ML is vs. what it actually is
The fact that most individual neurons are uninterpretable presents a serious roadblock to a mechanistic understanding of language models. We demonstrate a method for decomposing groups of neurons into interpretable features with the potential to move past that roadblock.
Interesting, I'd missed that Python gets a whole new generic syntax in 3.12 via the `type` statement. Looks very TypeScript-y. I think Ruff should be able to do automatic upgrades to this new syntax.
Folks, the time to run debirdify.pruvisto.org or fedifinder.glitch.me is now. You don't need to have an account elsewhere yet. Download the CSVs while you can, and you can import them later. go go go go
Tomorrow (Wednesday 6th) at @BlackHatEvents, we are presenting with @martinralbrecht, @DowlingBJ and @djwj_ our work on finding practically exploitable vulnerabilities in Matrix. Join us!! blackhat.com/eu-22/briefing… (and check our paper: nebuchadnezzar-megolm.github.io)
The 6 different ways of using a language transformer / LLM 1 Train from scratch 2 Feature-based: Train new model on embeddings 3 Finetuning I: Freeze all but output layer weights 4 Finetuning II: Update all weights 5 Zero-shot learning 6 Few-shot learning Anything missing? 1/6
Someday aliens are going to land their saucers in a field somewhere in New Jersey and everything is going to go just fine right up until we try to explain our calendar to them
Recently @twilio, which provides SMS verification services for Signal, suffered a phishing attack. Via Twilio, attackers may have accessed phone numbers & SMS registration codes for 1,900 Signal users. 1/
I am delighted to announce that the camera-ready version of my new book, "Machine Learning: Advanced Topics", is finally available online for free at probml.github.io/book2 (@mitpress will publish the hard copy in 2023.)
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798K Followers 964 Following Menswear writer. Editor at @putthison. Creator of @RLGoesHard. Bylines at The New York Times, The Washington Post, The Financial Times, Esquire, and Mr. PorterI installed @comma_ai in my car Their tagline is “make driving chill” which is accurate! I have pretty good confidence relying on it to drive most of the time, feels way “chiller” than Tesla autopilot (I haven’t driven the new FSD) It’s awesome that you can self install…
# scheduling workloads to run on humans Some computational workloads in human organizations are best "run on a CPU": take one single, highly competent person and assign them a task to complete in a single-threaded fashion, without synchronization. Usually the best fit when…
THE TECHNO-OPTIMIST MANIFESTO part 1 “You live in a deranged age — more deranged than usual, because despite great scientific and technological advances, man has not the faintest idea of who he is or what he is doing.” — Walker Percy “Our species is 300,000 years old. For the…
A few new CUDA hacker friends joined the effort and now llm.c is only 2X slower than PyTorch (fp32, forward pass) compared to 4 days ago, when it was at 4.2X slower 📈 The biggest improvements were: - turn on TF32 (NVIDIA TensorFLoat-32) instead of FP32 for matmuls. This is a…
95% of what we are doing in AI is stuff that's simple enough to explain to a child, made way over-complicated by mathematical-looking notation and unclear thinking. A short rant 🧵 using attention as an example.
Why Google Deepmind's Mixture-of-Depths paper, and more generally dynamic compute methods, matter: Most of the compute is WASTED because not all tokens are equally hard to predict
Should I proceed?
Thrilled to share we've raised $21.7m for @ColumnTax to scale up our fundamentally new tax filing product forbes.com/sites/igorbosi… It's been so much fun building the first-ever IRS authorized tax filing API with the amazing team here
i think it's a very good sign that the last three people to join Column Tax are all former founders
Apple says its latest AI model ReALM is even “better than OpenAI’s GPT4”. It likely is as GPT4 has regressed because of “alignment”. The ReALM war begins at WWDC 2024. Paper: arxiv.org/pdf/2403.20329…
@idorosen Thanks, Ido. We have yet to meet anyone who is envious of our minivan!
WTH! @Rainmaker1973 blocked me after I asked him to delete a post of MY video on X by someone who ripped it off TikTok. I didn't want to have to do it, but if @elonmusk's platform is this bad at protecting its creators I'll work up a little more action.
I often hear that evals are the most confusing part of creating LLM AI products. It's a shame b/c IMO, domain-specific evals are the most important part of an AI product! I've written a detailed blog post with real examples on how to do this (1/3) hamel.dev/blog/posts/eva…
3 paper deadlines, 3 awards nominations, one video deadline, one lecture to make and give, work to do for a group meeting, and policy feedback to give all by eod tmr thursday 😵💫 (and this is not an unusual amount of work). all for a chance at a non-contractor position someday...
TIL about binary vector search... apparently there's a trick where you can take an embedding vector like [0.0051, 0.017, -0.0186, -0.0185...] and turn that into a binary vector just reflecting if each value is > 0 - so [1, 1, -1, -1, ...] and still get useful cosine similarities!
There appears to be a mismatch between publishing criteria in AI conferences and "what actually works". It is easy to publish new mathematical constructs (e.g. new models, new layers, new modules, new losses), but as Apple's MM1 paper concludes: 1. Encoder Lesson: Image…