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317070

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www.youtube.com 1mo ago

Reinventing Entropy – Compression and Intelligence Part 1 [video]

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www.sciencedirect.com 8mo ago

Weak recovery of insectivorous bird population after neonicotinoid ban in France

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mrsteinberg.com 10mo ago

The Asshole Filter

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www.caltech.edu 10mo ago

Artificial Intelligence Helps Boost LIGO

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deepmind.google 10mo ago

Using AI to perceive the universe in greater depth

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ai.google 1y ago

Google AI – Our Principles

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www.biorxiv.org 2y ago

Coronavirus can cause 100% mortality in hACE2 mice, risks spill over into humans

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econgoat.ai 2y ago

Who Is the Greatest Economist of All Time? A Generative Book

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www.youtube.com 2y ago

OpenAI’s ChatGPT Is the Whole Game Studio [video]

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www.engraved.blog 3y ago

Building a Virtual Machine Inside ChatGPT

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theanarchistlibrary.org 4y ago

Comité Liquidant Ou Détournant Les Ordinateurs (C.L.O.D.O.) (1983)

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deepmind.com 4y ago

Controlling the nuclear fusion plasma in a tokamak with reinforcement learning

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www.wired.co.uk 4y ago

DeepMind Has Trained an AI to Control Nuclear Fusion

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www.nature.com 4y ago

Burning plasma achieved in inertial fusion

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www.theguardian.com 4y ago

CIA officials under Trump discussed assassinating Julian Assange

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www.nature.com 5y ago

Highly accurate protein structure prediction with AlphaFold

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www.youtube.com 5y ago

From Motor Control to Team Play in Simulated Humanoid Football

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www.youtube.com 5y ago

Computer Animated Hand (1972) – First polygonal 3D animation

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engraved.ghost.io 5y ago

Why machine learning algorithms are hard to tune and how to fix it

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arxiv.org 5y ago

Switch Transformers Scaling to Trillion Parameter Models

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twitter.com 5y ago

Citing Assange's mental health, judge rejects the US's extradition request

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finance.yahoo.com 5y ago

Google Waives $1.5B DeepMind Loan as AI Costs Mount

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investors.pfizer.com 5y ago

Vaccine Against Covid-19 Successful in Interim Analysis from Phase 3 Study

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www.theguardian.com 5y ago

Nobel laureates call on UK to back infecting volunteers with Covid for vaccine

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www.icij.org 5y ago

An ICIJ investigation reveals role of banks in industrial-scale money laundering

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adolos.substack.com 5y ago

What I would do with GPT-3 if I had no ethics

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eu.freep.com 6y ago

ICE arrests 90 more students at fake university in Michigan

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www.theguardian.com 6y ago

Smartphones are worse than nuclear weapons

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www.swissinfo.ch 6y ago

Switzerland’s first crypto banks receive licences

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www.reddit.com 7y ago

About Alphastar

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Count Binface 10 days ago

Those other parties all declined to compete in this by-election. They want Farage to stand to the rule of law on his corruption, and not endorse this procedural manoeuvre.

The timing of this by-election is also such that, were there an actual race, Farage would likely get his propaganda on the front of the newspapers throughout the summer months while everyone else in politics is on holiday.

"Ethnic Chinese" is a term covering 1.45 billion people. I don't even know where one would find a definition for "ethnic English", but if you take the NHS' "ethnic British" which ridiculously excludes even Irish heritage, I can see how you'd come to 50%.

A reasonable comparison would be to look at "Ethnic European", covering roughly 1.2 billion people.

london's trust level and prosperity have become a shadow of their former selves

As someone who traveled the world a bit and lived for a decade in London, I'd beg to differ without further elaboration.

A datapoint that points to the contrary:

- Singapore pre-1965 was a low trust, racist society. The tensions were so bad that in 1964 there were racial riots.

- Today, after a lot of immigration, within 1-2 generations, Singapore became a high-trust society.

Similar stories in South Korea and Taiwan. In all 3 cases, the trust came recently, within 1-2 generations, and from different approaches of the state. They combine high institutional trust and the economic prosperity with medium-low interpersonal trust.

I probably get there, but I have young kids.

But yes, these are averages between 1 person having 12 weeks and 12 people with 1 week. It's most likely power law distributed, so the average will feel weird.

There are people with cancer, severe car crashes and other horrible but temporary medical conditions in this average.

My portable CO2 monitor goes off. You can set a levels of warning on the aranet. It is a very quiet, non-disruptive alarm, but an alarm nonetheless.

I agree with OP. I don't always carry it along, but it has been a massive boost to my productivity.

Well if it was the data that was copied, nobody would be using LLMs. The data-generating process is the thing that would be copied.

That's why we do appreciate the nth artist making classical or techno music.

Right, and what happens at that limit is most exciting! A model that has a cross entropy at that limit for a data stream of text, produces a stream of text that is both theoretically and practically indistinguishable from the original stream.

And so if the datastream has been produced by something intelligent, the resulting model is indistinguishable from that intelligence. That is the whole compression idea behind artificial intelligence.

The limit is not a bug, it's a feature!

for LLMs, because in practice floating point inaccuracies (in particular after exponentiation) prevent values from being exactly equal.

In one thinking trace of 10k tokens, with fp16 or bf16 logits, I don't reckon a collision is rare? There are only 65k floating point numbers with that accuracy. And an agent can quickly rake up 100k tokens, so while not every token will have such a collision of equiprobable logits, it is not rare.

If RL was used to train the model, the model will have been trained on its own sequences. Those will have been generated with a temperature of 1.0. They must be, otherwise you would get a premature collapse or explosion of your entropy if the temperature was respectively lower or higher.

After that RL step, you want to stick to the RL distribution, and so keep a temperature of 1.0. Other temperatures will drive the model out-of-distribution.

That is why the sampling step for agents or thinking LLMs are usually kept at a temperature of 1.0.

Look at the softmax function and take the limit as T->0. It becomes a dirac-delta function.

In pure math, it does not always do that. It becomes a dirac-delta comb with equal weight on every maximum. There can be more than 1 maximum. Setting the temperature to zero turns into greedy sampling, but greedy sampling is not necessarily deterministic as you can have multiple equally optimal options.

so in principle, setting temperature to 0 _should_ result in deterministic outputs

It is a common misconception, but it is not true even in principle. If I have 2 or more logits which are equal to the maximum of my logits, I will sample uniformly random from them with any temperature, even zero. Sampling from softmax([1, 0, 1]) is still stochastic at temperature 0, because the limit is to sample uniformly from the first or the last element.

Anyway: "GPUs don't do deterministic matrix multiplications" is the biggest source of randomness in LLMs. GPUs put the associativity of the sums in matrix multiplications in arbitrary order, and this has a huge impact on the logits coming out of the neural network.

It's been used, along with every other divergence and distance you can think of.

In practice, which divergence you use doesn't seem to be very important. The KL is the one with the most theoretic foundation though, i.e. will work with infinite data. The important aspect seems to be that neural networks are Lipschitz bound, and that that is the most important constraint preventing collapse.

To get there, you often need to slow down your brain's electrical activity, moving from active Beta waves into Alpha or Theta waves through meditation or deep focus. This blurs the boundary between the inner "self" and the outer world.

Quantum Mysticism, a.k.a what if we write about spirituality as if we would report pop-science.

It's been a while since I came across one as flagrant as this article.

https://en.wikipedia.org/wiki/What_the_Bleep_Do_We_Know!%3F

If you want to read more: the concept is called "the dual state" [1] after the eponymous book [0]

I agree that the phrase is somewhat contradictory, but it is the best way to describe what was going on. As long as you were within the confines of the normative state, you experienced a rule of law. But as soon as you stepped into the prerogative state, anything could happen. So a "rule of law", except that it didn't apply to everybody, but only to most people. And importantly, the existence of the prerogative state is mostly hidden when you're in the normative state (so unlike a king, which everybody knew was outside of the law)

[0] https://en.wikipedia.org/wiki/The_Dual_State

[1] https://en.wikipedia.org/wiki/Dual_state_(model)

Not sure if it matters, but that is at least not true for nazi-style fascism. In there, they had a very strong rule of law for most people. But, there was a dual, a parallel system where there was no law at all, it operated outside of the legal system. You could win a trial and be exhonorated, only to be taken away by the gestapo at the door of the courtroom.

It was important for the nazis to keep businesses running, and have most people continue their lives without noticing major changes. Most people would not come into contact with the second system, and barely knew it existed. But if you entered the second system, you often would not come out alive.

This way, they could transit into an authoritarian system without hurting the economy. They knew this and planned it, and it turned out to be correct.

A theory that skips the parameter space, and understands grokking theory, comes up with an unexplained update rule, which notably works on a per-parameter level by dropping the updates for most parameters.

I suspect there is going to be a lot of handwaving to actually go from eNTK to that new update rule.

I also doubt it helps in the non-grokking regime, given the focus of the theory, which is where all the practical applications I have ever heard from live.

Don't get me wrong, I did enjoy reading this essay. It's well written and reasonably argumented without going into details.

Source: I write transformers for a living.

There is a piece of knowledge you seem to be missing. Yes, a transformer will output a distribution over all possible tokens at a given step. And none of these are indeed zero, but always at least larger than epsilon.

However, we usually don't sample from that distribution at inference time!

The common approach (called nucleus sampling or also known as top-p sampling) will look at the largest probabilities that make up 95% of the probability mass. It will set all other probabilities to zero, renormalize, and then sample from the resulting probability distribution. There is another parameter `top-k`, and if k is 50, it means that you zero out any token that is not in the 50 most likely tokens.

In effect, it means that for any token that is sampled, there is usually really only a handful of candidates out of the thousands of tokens that can be selected.

So during sampling, most trajectories for the agent are literally impossible.

We, westerner, want our values to prevail.

This comes to the core of the issue, and is where I think the disagreement comes from. Many Westerners in fact do not want "Western" values to prevail.

Why? For me those values have led to outcomes so horrendously antithetical to _my_ values, that I would not wish them for the rest of the world. Even worse, this Western centrism has led to jingoist conclusions for at least 400 years.