I got that same answer multiple times from ChatGPT, as you can see in my post. Immunosuppression doesn't equal deprogramming the immune system. It's like comparing a hammer to a scalpel. It also doesn't answer my question why exactly gradual desensitization can't cure autoimmune disorders. I wanted to know the exact science behind those two things, down to the molecular level. Basically, I wanted to keep asking why until it gave me a complete understanding of biology. My problem is that ChatGPT wouldn't go into lower levels of detail, and instead got stuck repeating these same ultra high level summaries. The best way I can describe it is ChatGPT would be great at writing medium articles, but not great at talking about bleeding edge research.

By all means, show me the right prompt

I can tell just by looking at the jpeg-ness of the image

Why do you need probabilities? You'd be better off spending more time on making your model more accurate period, even if it can be confidently wrong sometimes.

Yeah, we're at the point where models are improving faster than we can evaluate them lol

ChatGPT came out after this paper was written. We're at the point where models are improving faster than we can evaluate them lol

You don't build your own network. You define your problem, and choose the best network for that problem. For instance, is your problem a classification problem? Then find an off the shelf classifier to use.

> MF8

I've never heard of this and google isn't being helpful. Any links?

Has anyone checked to see if training fundamentally needs all that precision? Intuitively, I can understand why it works better that way, but if a model can be converted to int8 after the fact without taking a huge hit in accuracy, then I don't see why an optimizer couldn't find that int8 network in the first place.

Moore's law is all about hardware lol. But yeah, your intuition about smartphones is correct, Moore's law has slowed down.

What's the theory behind PTQ? As in, if quantization can preserve accuracy and create a massive speed up, why wouldn't you train on int8 to begin with? Speeding up training allows you to use even more parameters, or cut costs.

Unlike internet commies, I have a job. I posted my reply now. Check it out, you might learn something.

>First of all, I'm going to need you to define capitalism

Capitalism is an economic system, and all economic systems are defined by a set of rules. The rules of capitalism are: You can't steal or harm another person's private property, and you can't break a contract. This is in contrast to, for instance, Chinese communism under Mao, which had a rule that stated you can't own farmland and that all farmland would be owned by the community. This led to a scarcity of food, because no one had an incentive to produce much food, because any food they produced would be split up equally among the community. There was actually a small community who agreed to privatise their farmland such that the owners of the land got to keep all the food that they produced. Basically, they reinvented capitalism by creating private property. That town ended up producing so much food that China eventually adopted capitalism as their main economic system after Mao died, and the rest was history.

>Automation has reduced scarcity more than any industrial paradigm in history. Automation is possible both with and without capitalism.

Things don't just magically happen. Individuals have to make things happen. Individuals are guided my incentives. So you can't just say "industrial paradigm" like it's a magic wand. It doesn't mean anything. If there's an incentive to be more efficient, then sure, there will be automation. But if there is no incentive, there will not be automation. So when you say "automation is possible with and without capitalism", you need to be specific. Which exact economic systems have an incentive to create automation? Certainly not communism where things are collectively owned as we saw in Maoist China.

>Capitalism means the primacy of capital and capital holders as the decision engine of the economy - i.e., capital holders control the means of production and hold sway over the rules of the game

By that definition, you could argue that the chinese farmers which collectively owned their community farm were all "capital holders". So that's not a very good definition. Your definition also doesn't allow us to make predictions about how individuals would behave in such a system, which is the goal of any science. This is why in economics, economic systems are defined in terms of rules. It's way less ambiguous and allows economists to make predictions. Did you take microeconomics in college? It's a really good course.

>But capitalism has literally negative interest in eliminating scarcity...

And yet despite all that waste, global poverty has never been lower: https://ourworldindata.org/grapher/share-of-population-living-in-extreme-poverty-cost-of-basic-needs?country=~OWID_WRL

So clearly there's more to the story for each of your points. Food spoils, logistics is expensive, etc etc.

>and keep supply low by supporting restrictive zoning laws that forbid the construction of multi-family residences like apartments and condos.

When the government creates new rules and regulations that restrict the free market, blame the government, not capitalism. Also it's weird you're blaming companies on zoning restriction when the most famous NIMBY city is San Francisco and the people who live there.

>it sounds like capitalism is the very source of most of the scarcity in both of these cases.

"Source". Scarcity is the default. Things don't exist unless individuals make them exist. So the fact that there's so much food as there is right now is proof that capitalism has reduced scarcity. And again, global poverty has been dropping significantly.

>Then explain why insulin costs $5 to make and $300 to buy, smart guy.

Because the FDA makes it very expensive to do business. You can create insulin at home, but you'd go to jail if you tried to sell it to anyone without approval from the FDA. I could also say "explain why coffee cups are so cheap compared to insulin, smart guy." In general, when there's one-off expensive things it's usually caused by the government

>Capitalism is not "everything our economy makes".

Right, capitalism is private property and contracts. Those two simple rules happen to incentivise individuals to go out into the world and create everything the economy makes. But in the context of comparing different economic systems, it's pretty fair to say the capitalism is everything our economy makes as a shorthand.

>Capitalism is not "freedom"

Right, because capitalism is simply the enforcement of private property rights and contracts. But compared to other economic systems I'd argue it's one of the most free economic systems possible.

>Capitalism is not even "free markets"

Well, you can't have free markets if you don't have private property and contracts, so it sort of is.

>capitalism is unsustainable.

That makes no sense lol. Capitalism has reduced scarcity more than any economic system in history, and it's well on it's way towards creating post scarcity. Aside from inflation caused by government, capitalism has caused the price of everything to reduce dramatically. And as automation increases, the price of things will continue to fall. When the cost to produce something finally reaches 0, that good or service can be considered post-scarce and will be infinitely abundant. All thanks up capitalism.

How would resources get concentrated when they're being made more and more plentiful? Just doesn't add up.

Commies get out

They shouldn't

Why would you want this to work on windows?

>I mainly did NLP work for 3 years

Did you apply to an NLP job? Machine learning skills aren't transferable. "ML engineers" don't exist. You can be an NLP engineer, a computer vision engineer, a data scientist(they work with tabular data and probably use pandas), and I'm sure you can be whatever the stock market guys call themselves. But you absolutely can't be all of them just because you know one of them.

However, I'm positive it wouldn't take long for them to train you on their domain if all they're doing is pandas. So it's weird they're being selective.

5.75

English uses decimals not commas

If an architecture of more scalable, then it's the superior architecture.

>Are transformers really architecturally better than LSTMs or is their success mainly due to the huge amount of compute and data we throw at them?

That's like asking if B-trees are actually better than red black trees, or if modern CPUs and their large caches just happen to lead to better performance. It doesn't matter. If one algorithm works theoretically but doesn't scale, then it might as well not work. It's the same reason no one uses fully connected networks even though they're universal function approximators.

Have you tried rewriting these in rust?

Does it support SupCon? That's the only network I've had any success with in production