Andrew Trask @iamtrask
@openminedorg, @GoogleDeepMind ethics team, @OxfordUni phd candidate, @UN pet lab, @GovAI_, creator of #GrokkingDeepLearning, NALU, and sense2vec youtube.com/watch?v=4zrU54… Oxford, UK Joined November 2012-
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I wrote #beginner level book teaching Deep Learning - its goal is to be the easiest intro possible In the book, each lesson builds a neural component *from scratch* in #NumPy Each *from scratch* toy code example is in the Github below #100DaysOfMLCode github.com/iamtrask/Grokk…
1. What are the ethical and societal implications of advanced AI assistants? What might change in a world with more agentic AI? Our new paper explores these questions: storage.googleapis.com/deepmind-media… It’s the result of a one year research collaboration involving 50+ researchers… a🧵
After ~5yrs of work, @emmabluemke, Teddy Collins, @bmgarfinkel, @KEricDrexler, @ClaudiaGhezzou, @IasonGabriel, @AllanDafoe, @wsisaac, and I have published an updated paper. This work is co-authored by an extraordinary team I'm grateful to know, and I expect to work off this…
fun fact in #disinformation research: filtering out disinformation is a solved problem — has been for 1000s of years however, disinformation’s solution creates major problems for liberalism and democracy that’s the *real* #disinformation problem 1/🧵 IMO, @karpathy’s post is…
fun fact in #disinformation research: filtering out disinformation is a solved problem — has been for 1000s of years however, disinformation’s solution creates major problems for liberalism and democracy that’s the *real* #disinformation problem 1/🧵 IMO, @karpathy’s post is…
Fwiw - if you're new to reading AI papers 👇 The tipping point for me was when I spent 4 weeks reading one paper per week. (two or three of them were @RichardSocher's back in ~2012) For each paper, I read each sentence and wrote 1-2 paragraphs about it, summarising its…
Fwiw - if you're new to reading AI papers 👇 The tipping point for me was when I spent 4 weeks reading one paper per week. (two or three of them were @RichardSocher's back in ~2012) For each paper, I read each sentence and wrote 1-2 paragraphs about it, summarising its…
i wrote #beginner level book teaching #deeplearning its goal is to be the easiest intro possible each lesson builds a neural component *from scratch* in #NumPy each *from scratch* toy code example is in the #Github below #100DaysOfMLCode github.com/iamtrask/Grokk…
Excited to share I've moved to the @GoogleDeepMind ethics research team — and I'm honored to have played my small part in the Gemini release from that new post! Lots of multi-modal features coming to an app near you!
Excited to share I've moved to the @GoogleDeepMind ethics research team — and I'm honored to have played my small part in the Gemini release from that new post! Lots of multi-modal features coming to an app near you!
Before getting into AI, I attended undergrad at Belmont University, where I studied commercial music and music business. It's one of the top schools for this. In the "AI threatens art" narrative, something is forgotten. Art's beauty is grounded in its ability to tell stories of…
Before getting into AI, I attended undergrad at Belmont University, where I studied commercial music and music business. It's one of the top schools for this. In the "AI threatens art" narrative, something is forgotten. Art's beauty is grounded in its ability to tell stories of…
There's a nuance of this take I disagree with. It's not *quite* "more data" -> "more quality". It's actually "more structure" -> "more quality" Ex: I could generate 100 billion petabytes of data about how to convert Celsius to Farenheit But that wouldn't help with driving cars…
There's a nuance of this take I disagree with. It's not *quite* "more data" -> "more quality". It's actually "more structure" -> "more quality" Ex: I could generate 100 billion petabytes of data about how to convert Celsius to Farenheit But that wouldn't help with driving cars…
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368 Followers 76 Following Driving positive futures for humanity. We curate high-impact sci-tech resources, interview experts, and host events to foster collaboration. #Xhope 🌟Francois Chollet's mental model for LLMs: LLMs are stores of programs. Querying LLMs involves selecting a program from the latent program space and running it on your data. And the ability of LLMs to interpolate between these programs is what makes LLMs so flexible.
How can you incentivize people to avoid this failure mode, or give them affordances to do something which is not that? One way would be to make it easy to track & share data about the training process. Perhaps using @iamtrask's Structured Transparency to mitigate misue risks?
@DanHendrycks @EvanHub A particular danger I see here is: any kind of outer optimization loop (even an informal process of R&D iteration) that takes “Not sneaky”-type linear directions as a loss term (while still having optimization pressure toward deception) will probably result in nonlinear sneaking.
📜 New paper unpacking Google DeepMind’s approach to safety evals for advanced AI models, with lessons learned to support the advancement of similar efforts by other actors in this space. Covers foresight, evaluation design, and the wider ecosystem. arxiv.org/abs/2404.14068
Grant's parody of Hallelujah is equally astonishing! youtu.be/NOCsdhzo6Jg?si…
@iamtrask Got my copy a few years ago, if you wanna build your intuition of DL from the ground up, this is definitely a great place to start!
Bookmark this. Pull the Repo. Visit the link. Do anything, just make sure to read this. Can’t thank @iamtrask ENOUGH for this. Thanks Andrew ! #neural #MachineLearning #deeplearning
I wrote #beginner level book teaching Deep Learning - its goal is to be the easiest intro possible In the book, each lesson builds a neural component *from scratch* in #NumPy Each *from scratch* toy code example is in the Github below #100DaysOfMLCode github.com/iamtrask/Grokk…
@_BGoldberg @sebkrier @lawhsw @maribethrauh @FranklinMatija @joelbot3000 @michaelklenk @ShannonVallor @merrierm @blaiseaguera @wsisaac James Manyika and all these fine folk ✨
14. Overall the paper was a huge undertaking spanning a wide range of disciplines and skill sets. Thanks to all the amazing contributors for your time, effort, and belief in this work—it’s been a pleasure to work with all of you! @Arianna_Manzini @verena_rieser @weballergy
13. If you’re interested in Definitions, Technical Foundations, Types of Assistant, Value Alignment, Well-Being, Safety, Malicious Use, Persuasion, Anthropomorphism, Appropriate Relationships, Cooperation, Access, Economic Impact, the Environment or Evaluation then jump in! ☕️
12. There's also a: – 2-page Executive Summary – 6-page summary in the Conclusion – Guide for different kinds of reader.
11. Finally, this is quite a *long* paper (some have said “book”) 😅📖 We have a blog here: deepmind.google/discover/blog/…
10. Fifth, we potentially stand at the beginning of an era of potentially profound technological and societal change—which means there's a window of opportunity to shape the design, use and purpose of advanced AI assistants. The paper contains over 50 suggestions...
9. Fourth, it’s hard to evaluate AI assistants using tools that focus only on model properties and outputs. We need to understand how people interact with assistants & how they could shape society over time. New kinds of holistic evaluation are needed: arxiv.org/pdf/2310.11986…
8. Third, millions of AI assistants could be deployed at a societal level where they’ll interact with one another and with non-users. Coordination to avoid collective action problems is needed. So too, is equitable access and inclusive design.
7. Second, increasingly personal and human-like forms of assistant introduce new questions around anthropomorphism, privacy, trust and appropriate relationships with AI. Safeguards are needed to support user well-being—and well-being needs to be understood in holistic terms.
6. Greater freedom and scope of action make it essential that AI systems embody the right set of values—respecting the needs of non-users and society more widely. An AI assistant is aligned if it does not *disproportionately* favor some actors over others e.g.
5. For advanced AI assistants, several things stand out: First, with autonomous and agentic technologies *alignment* is key—but this goes beyond following the instructions of intentions of a single user.
4. Yet, this new phase in AI technology also heralds a new phase in AI ethics—so sociotechnical foresight is key 🔮 We need to model the futures technology makes possible—based on existing social and technical analysis trends—and understand their implications 📈