Dataflow matrix machines (by Anhinga anhinga)

Vernor Vinge

2024-03-23T01:09:56Z

Vernor Vinge died at 79 on March 20 (due to long decline from Parkinson's disease):

en.wikipedia.org/wiki/Vernor_Vinge

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GreaterWrong viewer for LessWrong; Conjecture.dev

2023-02-23T03:44:58Z

I am reading more and more LessWrong in recent months (mostly, after the Simulator theory by Janus (work done while at Conjecture) has been posted there in September).

I still think the Simulator theory is probably the single most important research breakthrough of 2022.

These days LessWrong is dominated by writing related to AI safety (the topic is made particularly acute by the recent progress in LLMs: ChatGPT and even more capable Bing Chat; no consensus whatsoever, of course, but I do think that GPT-3 release in May 2020 is, in some sense, an equivalent of the nuclear fission discovery on 19 December 1938, and that ChatGPT performance (+ Bing Chat clearly drastically enhanced capabilities even compared to that) is, in the same sense, an equivalent of the first working nuclear reactor on 2 December 1942, if one goes by "AI today is what nuclear energy has been back then" analogy).

So, one thing which might be useful is that there is GreaterWrong alternative viewer (which looks different from LessWrong default viewer and which can be visually tuned in terms of presentation style; also different default front page for the site if one uses GreaterWrong). Which viewer is better might depend on your device (display, browser, etc).

Another thing, Conjecture people tend to produce some of the best, most interesting articles there.

I'll put a few links into the comments.

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New Year resolution

2023-01-08T05:42:26Z

To read my https://twitter.com/home more regularly (that's absolutely the best source of info at the moment).

A small fraction of today's catch:

New work by Janus

A new involved take on AI safety/alignment

(What's the right way to organize all that information?)

Links are in the comments (I think the new work by Janus is more important even for alignment, and is just overall more important of the two topics of this post)...

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update on AI progress and AI safety

2022-12-04T16:18:56Z

AI-safety-wise, the write-up, My AI Safety Lecture for UT Effective Altruism by Scott Aaronson is very nice reasonably objective and theory-friendly overview of the current state of AI safety as a field of science.

AI-progress-wise, ChatGPT based on roughly speaking GPT-3.5 has been released recently, with people doing tons of interesting things with it, including meaningful writing and software generation... This seems to be another major step-up.

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Conferences; research updates

2022-11-17T01:44:04Z

This week, Nov 17-18, Thu-Fri, 8am-11:45am Boston time, "Quantum physics and the first-person perspective": www.essentiafoundation.org/quantum-physics-and-the-first-person-perspective/seeing/

JuliaCon 2023, juliacon.org/2023/ the call for proposals is posted, deadline Dec 18: pretalx.com/juliacon2023/cfp

I've spent more quality time focusing of two breakthroughs in understanding the nature and the behavior of machine learning models which came from the "penumbra" of "prosaic alignment" start-ups and which I wrote about in my previous two posts.

"Grokking is (more or less) solved." I took brief notes between Oct 21 and Oct 23: github.com/anhinga/2022-notes/tree/main/Grokking-is-solved

"Generative autoregressive models are similators." I took extensive notes between Oct 5 and Oct 23: github.com/anhinga/2022-notes/tree/main/Generative-autoregressive-models-are-similators

I am continuing to develop thoughts related to these topics, I am going to gradually write more about those topics in the comments.

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Generative autoregressive models are similators

2022-09-21T07:25:52Z

Вот, наконец, кажется возник правильный подход к пониманию природы моделей вроде GPT-3 и разнообразного волшебства, с этим связанного:

www.lesswrong.com/posts/vJFdjigzmcXMhNTsx/simulators

Он говорит, что надо перестать думать про эти модели в терминах более старых AI-систем.

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OpenAI posted its approach to alignment research

2022-08-25T13:43:11Z

openai.com/blog/our-approach-to-alignment-research/

"Our approach to aligning AGI is empirical and iterative. We are improving our AI systems’ ability to learn from human feedback and to assist humans at evaluating AI. Our goal is to build a sufficiently aligned AI system that can help us solve all other alignment problems."

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Our understanding of major AI risks is exactly at zero

2021-07-31T19:09:18Z

astralcodexten.substack.com/p/updated-look-at-long-term-ai-risks

The main takeaway is that no scenario is considered as much more likely than others by the best experts, and they all look more or less equally likely except for the "scenario not listed here" (which is rated as somewhat more likely than the listed scenarios).

Also people seem to be very optimistic for some reason (perhaps, they secretly believe in a benevolent G-d or benevolent aliens keeping an eye of us; otherwise their optimism is difficult to explain).

Scott Alexander summarizes the takeaways interesting for him as follows:

======= QUOTE =======

1. Even people working in the field of aligning AIs mostly assign “low” probability (~10%) that unaligned AI will result in human extinction

2. While some people are still concerned about the superintelligence scenario, concerns have diversified a lot over the past few years

3. People working in the field don't have a specific unified picture of what will go wrong

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GitHub Copilot ("we are getting there")

2021-06-29T16:23:30Z

github.blog/2021-06-29-introducing-github-copilot-ai-pair-programmer/

"Today, we are launching a technical preview of GitHub Copilot, a new AI pair programmer that helps you write better code. GitHub Copilot draws context from the code you’re working on, suggesting whole lines or entire functions. It helps you quickly discover alternative ways to solve problems, write tests, and explore new APIs without having to tediously tailor a search for answers on the internet. As you type, it adapts to the way you write code—to help you complete your work faster.

Developed in collaboration with OpenAI, GitHub Copilot is powered by OpenAI Codex, a new AI system created by OpenAI. OpenAI Codex has broad knowledge of how people use code and is significantly more capable than GPT-3 in code generation, in part, because it was trained on a data set that includes a much larger concentration of public source code. GitHub Copilot works with a broad set of frameworks and languages, but this technical preview works especially well for Python, JavaScript, TypeScript, Ruby and Go."

If you are using Visual Studio Code often, it might make sense to try to sign-up for the technical preview phase...

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