manux

In Canada, all three major AI research centers use clusters created with public money. These clusters receive regular additional hardware as new generations of GPUs become available. Considering how these institutions work, I'm pretty confident they've considered the alternatives (renting, AWS, etc). So that's one data point.

The intent behind media matters but isn't all that matters. How people might interpret something is important (albeit often unpredictable).

I think the symbolism of "let's crush all remaining vestiges of creative culture" is a pretty obvious _potential_ interpretation from a _non-trivial amount_ of people. In that sense it is an interpretation that matters for our present discourse, even if it isn't the interpretation that the creator of the ad intended.

Demis now has a load of people reporting to him who previously were rooting for his failure

Having been in both places (Brain and DM), this feels so far from what I experienced that I must ask, what are you basing this on?

I know, the CAQ is full of xenophobes, and it can suck not looking white in Quebec (although much less so in Montreal). I'm skeptical that it drives rent prices in any detectable way.

Not really no, there's been a bump which studies seem to agree is an aftereffect of COVID, but the media is also paying more attention to it. There's always been some amount of shootings and stabbings in Montreal, and 99% of Montreal is safe during night time.

https://www150.statcan.gc.ca/n1/pub/85-002-x/2021001/article... https://spvm.qc.ca/upload/02/2021_Activity_Report_SPVM_EN_VF...

Wow, what a take. I seriously doubt that people in Montreal/Quebec are more or less xenophobic than the average North American; if you have data supporting this I'd be happy to change my mind.

Also please be more skeptical of thoughts of the form "X is Y because of hot take Z". Reality is complex and things have many causes. Montreal has a long history of doing city planning differently than other cities in Canada.

maybe things just move so fast

This is definitely the case in DL (and I'm assuming elsewhere too but I wouldn't know).

I've lost count honestly, running 1-2 year old paper github repos with some detail missing (like the Python version!) that make it non-trivial to run as is. Libraries make undocumented breaking changes, wrong pickle format, authors used a nightly version which didn't make it to a tagged version, and so on.

This perhaps says also something about the CS (versus software eng) background that most people engaging in DL publishing have.

Yeah! This kind of reasoning is why it's exciting to think that we could use the GFlowNet machinery to construct latent representations--ones that map more directly to the notion of "beliefs" that we're used to think about as humans, something "discrete" and relational.

Concretely what this could mean is using these tools to generate causal hypotheses, like what's been done here: https://arxiv.org/abs/2202.13903

What the permutation invariance gets you is that the model doesn't arbitrarily prefer one (graph) configuration over another, but this seems tangential. The difference between this and RL is in what we do with the reward:

- RL says, give me a reward and I'll give you its max.

- GFlowNet says, give me a reward and I'll give you all its modes (via p(x) \propto R(x)).

Yes you would ideally have a loss (well, a reward/energy) that is invariant and operates e.g. directly on the molecule rather than on some arbitrary ordering of the nodes.

I think the inspiration came to me from looking at SumTrees and from having worked on Temporal Difference learning for a long time. The idea of flows came to Yoshua and I from the realization that we wanted some kind of energy conservation/preservation mechanism from having multiple paths lead to the same state.

But, yes in the moment it felt like some very serendipitous insight!

Yes, although they may not be ideal unless you're able to define a "distance" between a proof that the agent is proposing and whether that proof is correct (i.e. unless you're able to define a reward or energy function).

It may be possible to infer/learn a score from existing proofs though. We have a paper that manages to both learn a flow and an energy function (the score) from data: https://arxiv.org/abs/2202.01361

I don't know much about theorem proving though. Can some value be attributed to partial proofs?

Hi, first author of the original NeurIPS paper here! Someone just shared this HN post with me. I'll go through the comments but happy to try to answer questions as well.

Yeah the "net" in GFlowNet refers to how the underlying state is interpreted, not to an architecture. It is a way to train generative models, on any kind of discrete data (like graphs).

Source: am first author of original GFlowNet paper.

It's quite likely some people will come out of reading this thinking we should stop sending people to grad school. Shouldn't we instead take this as a signal that it needs improvement?

Grad students are one of the very few subpopulations of humanity allowed to take on extraordinary epistemological risks; a kind of immune system of our civilization. I'm not even talking about some elusive notion of "progress", just [intellectual] societal health. It would feel to me like a tremendous loss if we let go of such a component of society.

A more nuanced take on this: https://www.youtube.com/watch?v=21NxJS_zYDY

Getting China to stop coal would be more effective than getting the USA to stop beef.

Fighting climate change is not a game of "what would be more effective" and ranking solutions (especially in between countries), it's a game of "what are ALL the things we can realistically do". Both _must_ be done.

I fail to see how this is the case, but perhaps I'm missing the point you're trying to make? What you're referring to is about colonialism, whereas here the USA is very much incentivized to work within its own borders, on its own food industry. It just so happens that climate change is a global problem as well, and the USA being a large rich country it has more causal influence on the outcome of climate change.

...and the USA is a large country of >300M people. It must lead in humanity's work towards reducing GHG. What is your point exactly?

Well you did say that

almost everyone seems to believe that real incomes have totally stagnated.

suggesting that this is a false belief. I think this can easily be interpreted as you saying "inflation is fine" (even though that may not have been your intention).

massive ocean container ships, coal plants, the extraction of every type of ressource

but all these things... serve consumers. Container chips contain goods that people buy, that required resource extraction and transport.

Inefficiencies aren't always bad.

Efficiency, for example, is often the opposite of robustness. Many companies have learned that the hard way when COVID hit, even though they had an efficient supply chain and production pipeline, it was not robust.

What about the self-censorship of our neo-cortex telling us not to insult other people? Is that bad too?

Expression, and respectful expression, is a very nuanced and complex topic. This dramatic post presents the far end of the spectrum where every word can lead one to be fired. The truth is somewhere in the middle.

Here's an analogy: laws vary from country to country, from state to state, city to city.

But we understand the principle of law-making, what laws mean and how they're applied. This is fairly uniform. What really changes from place to place is the content of those laws.

AI ethics and AI safety are attempting to give us a set of "law-making" rules but for AI. We get to decide (democratically ideally), in countries, states, cities, what "ethics" (what laws) we want, but AI Ethics as a field gives us tools to achieve that regardless of what the ethics/laws are.

For example, how do we encode the trolley problem in self-driving cars? We could decide democratically that cars should act and kill 1 instead of 5. Or the opposite. But then how do we translate that into ifs and else? No one really knows how to do that.

The real problem with ethics is that it's not a science

This is simply untrue. The goal of AI ethics research is (also) to build algorithms where one of the _inputs_ is a set of ethics. It doesn't matter what those ethics are. It just so happens that the "set of ethics" currently fed in tends to have a particular flavor ("woke liberal" ethics), which you seem to disagree with. Finding the algorithms matters, and it's likely that the standard ethics put in are going to come from some dominant ideology, but we still need the algorithms if we are to understand how to make AI that aligns with humanity's interests (however they are defined).

I'd call that computer science.

it's mutating at a breakneck pace

I agree that it's changing faster than a century ago, but I don't think "breakneck pace" is a fair qualifier. Lots of people comfortably adapt to new norms and change how they behave without significant effort.

the two minutes hate outrage machine.

This phenomenon existed long before the internet. Heck, I'd bet long before writing was invented. Gossip in large social groups doesn't seem like something particularly new.

I still think this has nothing to do with "self-censoring out of fear" being a Bad new thing. You _should_ self-censor if you think you're being offensive. If the author of the article really wanted to harp on the fact that predicting what is offensive is hard, then perhaps that should be the focus of the article. I don't think pushing the "fear" narrative is useful nor healthy.

The Culture series by Ian M Banks has an interesting take on this, if this kind of sci-fi interests you!

Self-censoring is part of the frontal cortex's normal function.

I only hear this word 'self-censorship' brought up as a boogeyman. If people have an axe to grind against some part of mainstream culture, why not just say it out loud instead of priming their readers with FUD? (fear, uncertainty, doubt).

I think you're missing the point I'm trying to make, which is that developing "fair" algorithms, is not about developing algs that are e.g. pro-white-black equality, it is about developing algs that have option of equality built-in. It is then up to the user of the algorithm (you, Google, whoever), to "input" what or who should be equal.

It just so happens that currently the "input" is racial and gender equality. That's a societal choice, and one that is likely to change if e.g. racial equality is achieved and some new inequality arises. Maybe eye-color-based discrimination, who knows.

More generally than "equality", AI Ethics research gives us tools to analyze current methods and see where they fail to meet our ethical standards.

History has shown us that defining ethics and writing them down merely spreads falsehood

Humans have been trying to improve their own condition for as long as there have been humans. Collectively defining acceptable behaviors is a never-ending task. Does that mean we should not undertake it? Absolutely not!

Writing down ethics isn't about spreading falsehoods, it's about cooperation. Cooperation involves compromise:

AI Ethical research can never be an accurate representation of the majority of humanity - or even the majority of its users! If it can it is not sustainable for any long period of time.

Laws can never be an accurate representation of the majority of humanity - or even the majority of its users! If it can it is not sustainable for any long period of time.

Culture can never be an accurate representation of the majority of humanity - or even the majority of its users! If it can it is not sustainable for any long period of time.

Morals can never be an accurate representation of the majority of humanity - or even the majority of its users! If it can it is not sustainable for any long period of time.

Do you see the pattern? Things change, that's normal. We still have laws, and culture and morals, but we adapt them to our needs. Are you suggesting we should simply reject anything that changes? You won't be left with much.

I'm still very much interested in improving my own condition. That includes pushing people to behave in ways which I think would do that. People have different interests and their condition is often at odds with other people's condition. This is the foundational difficulty of living in a society of more than 1 individual. Yet we 8 billion humans still manage to be fairly successful at it. I wonder why?

Cultures and morals change. Does that make the morals of the past falsehoods? Of course not. They're just different perspectives on the human condition, probably best suited to the material conditions of the past.

Calling someone today is often seen as rude when a text would suffice. This is due to our material conditions, the ubiquity of cellphones.

It would be better to just admit ...

You're suggesting we should admit defeat? Give up and let Google maximize profit? AI is a wonderful tool that could improve the material conditions of most of humanity if used correctly. It could also be devastating. I'd rather it not be devastating, so I'm going to continue supporting people who try to do research into aligning AI with whatever ethics we collectively agree on.

I don't think we are actually better off morally now then 50 years ago

This is pretty sad.

Don't confuse your own cynicism vis-à-vis big tech with some nihilistic historical inevitability. The global improvement of the material conditions of people in the last 50 years have enabled us to start asking for ourselves what morals we actually want on a global scale, rather than this exercise being left solely to a self-interested elite.

Regardless of how better off morally _you_ think we are or aren't now, the space of collective possibilities is now immensely larger, whether you like it or not. That, is wonderful.

No, you're wrong. Ethics and morals do exist. Money exists. Ideas exist in our brain, functionally.

Are all these things _ideas_? Human creations? Sure. The universe is absolutely indifferent to us. But these _ideas_ have real-world impact, and I'm not indifferent to my own suffering.

Societies function at the scale they do right now because there is enough overlap in how I perceive the world and how another random human perceives the world so that even though we don't know each other, we can still cooperate [see e.g. 1 for great discussions on this] e.g. exchange money for goods.

[1] https://www.preposterousuniverse.com/podcast/2021/02/01/132-...

AI ethics cannot hope to remain in style for long

Again, you seem to be conflating "AI ethics" with a particular ethical stance, let's call it woke humanism, and you seem to think that the people who work on AI ethics work to enforce this belief on others. This is wrong. We're perfectly aware that humans have a variety of ethical preferences, see my previous post. Lots of people who work in "AI ethics" are definitely not woke humanists.

Accepted standards of 2 years ago, are already out of date.

I'm not sure what you're trying to say here. Um, sure we keep finding better algorithms... no one ever, ever, ever, has claimed that their paper is the ultimate algorithm and no no one will find better. But 2 years ago, killing a random person in the street was wrong. It's still wrong today, it was wrong 2000 years ago, and it's going to stay this way for the foreseeable future.

I'm lost for a solution

The research field of AI ethics exists because we don't know what the solution is!!! Come join us if you're so concerned.

Honesty is the basis of the whole of scientific inquiry

If you value honesty, then you should value research that tries to make ML models "honest", by revealing how they make the predictions they do and where that fails. I don't understand your antagonism towards ML FATE (fairness accountability transparency and ethics) research

if you're saying i'm a racist

I wasn't, sorry if that's what you interpreted.

The status quo however should be changed by people,not people with machines

I'm not sure I understand what this means. People/companies own machines (and ML models) and use them. So shouldn't we make sure that the machines' decisions align with what people/companies _want_ them to do? (i.e. that the people's ethics align with the ML model's ethical consequences; I'm 100% sure that people who deploy "racist models" don't do it on purpose or out of malice)

You can't call something ethical just because you think it should be; it must be argued out

On one hand this sounds like a strawman. No one thinks that something is ethical because someone randomly declared it so.

On the other hand... ethics are a human construct, and will continue to evolve as our culture evolves over decades and centuries. Shouldn't we construct ML models which are flexible in that they can align themselves with the ethics we collectively decide? We don't know how to do that yet!

Using AI to shut out some more of that argument will only create a universal standard, not necessarily the correct one.

You seem to be under the impression that the fields of AI ethics is dedicated to brainwashing people into some particular unpopular moral philosophy. This is simply untrue. Within the field of AI ethics there is a lot of diversity of thought and disagreement on how human morals should be "encoded" so that AI can "align" with these morals. And I'm using the plural of morals because obviously there will never be a humanity-wide consensus on ethics, and if AI is to be deployed in the world it needs to reflect this diversity.

Here's an example of AI people disagreeing if you don't believe me: https://jacobbuckman.com/2021-02-15-fair-ml-tools-require-pr...