Sending a simple transaction like this costs a couple cents though, which they could in theory bill to the developer as well. Setting the threshold at 100 is probably more to accrue additional interest on Steams bank accounts.
Sending a simple transaction like this costs a couple cents though, which they could in theory bill to the developer as well. Setting the threshold at 100 is probably more to accrue additional interest on Steams bank accounts.
I won’t pretend I understand all the math and the notation they use, but the abstract/conclusions seem clear enough.
I’d argue what they’re presenting here isn’t the LLM actually “reasoning”. I don’t think the paper really claims that the AI does either.
The CoT process they describe here I think is somewhat analogous to a very advanced version of prompting an LLM something like “Answer like a subject matter expert” and finding it improves the quality of the answer.
They basically help break the problem into smaller steps and get the LLM to answer smaller questions based on those smaller steps. This likely also helps the AI because it was trained on these explained steps, or on smaller problems that it might string together.
I think it mostly helps to transform the prompt into something that is easier for an LLM to respond accurately to. And because each substep is less complex, the LLM has an easier time as well. But the mechanism to break down a problem is quite rigid and not something trainable.
It’s super cool tech, don’t get me wrong. But I wouldn’t say the AI is really “reasoning” here. It’s being prompted in a really clever way to increase the answer quality.
It’s not a direct response.
First off, the video is pure speculation, the author doesn’t really know how it works either (or at least doesn’t seem to claim to know). They have a reasonable grasp of how it works, but what they believe it implies may not be correct.
Second, the way O1 seems to work is that it generates a ton of less-than-ideal answers and picks the best one. It might then rerun that step until it reaches a sufficient answer (as the video says).
The problem with this is that you still have an LLM evaluating each answer based on essentially word prediction, and the entire “reasoning” process is happening outside any LLM; it’s thinking process is not learned, but “hardcoded”.
We know that chaining LLMs like this can give better answers. But I’d argue this isn’t reasoning. Reasoning requires a direct understanding of the domain, which ChatGPT simply doesn’t have. This is explicitly evident by asking it questions using terminology that may appear in multiple domains; it has a tendency of mixing them up, which you wouldn’t do if you truly understood what the words mean. It is possible to get a semblance of understanding of a domain in an LLM, but not in a generalised way.
It’s also evident from the fact that these AIs are apparently unable to come up with “new knowledge”. It’s not able to infer new patterns or theories, it can only “use” what is already given to it. An AI like this would never be able to come up with E=mc2 if it hasn’t been fed information about that formula before. It’s LLM evaluator would dismiss any of the “ideas” that might come close to it because it’s never seen this before; ergo it is unlikely to be true/correct.
Don’t get me wrong, an AI like this may still be quite useful w.r.t. information it has been fed. I see the utility in this, and the tech is cool. But it’s still a very, very far cry from AGI.
This is true, but it’s specifically not what LLMs are doing here. It may come to some very limited, very specific reasoning about some words, but there’s no “general reasoning” going on.
I think you might be looking for this? https://addons.mozilla.org/en-US/firefox/addon/side-view/
Someone already figured out how to “unlock” the full thing.
Larian are now the proud owners of the “Daddy Halsin” mod. Truly an asset to their IP!
I probably change the brightness setting the most. Why is it all the way at the top of the settings, the furthest out of reach it could be?
Android can be degoogled, e.g. GrapheneOS. If you’re focused on privacy then that’s the way to go.
Although Google is worse than Apple when it comes to privacy, Apple is still pretty bad.
697? Geez that’s… Not great.
Sure, but even Epic exclusives aren’t any cheaper than the games on Steam. These savings directly go to the game developer/publisher, not the consumer. This means there’s no incentive for the consumer to switch to Epic other than exclusive games, which is a pretty poor reason to switch away from a well-established platform.
It’s slightly cheaper for developers to put their games on there. But that sucks as a business model, because game prices aren’t any lower so for the end user it doesn’t matter. And on features, Epic just loses every matchup against Steam.
Both WhatsApp and Signal show the same amount of chats to me (9 for both). WhatsApp does show a small sliver of a tenth chat, but it’s not really properly visible. There is a compact mode for the navigation bar in Signal, which helps a bit here.
From what I can see there’s slightly more whitespace between chats, and Signal uses the full height for the chat (eg same size as the picture), whereas WhatsApp uses whitespace above and below, pushing the name and message preview together.
In chats the sizes seem about the same to me, but Signal colouring messages might make it appear a bit more bloated perhaps? Not sure.
Shareholders can demand external audits under threat of selling the stock. There’s plenty shareholders can do (and have done in the past). They don’t just sit idle and not do anything you know.
Shareholders seek to maximize profits. If that includes a lawsuit to squeeze out even more investments, then why not?
They never bothered to check if Boeing did what they had to do security wise. Only once it threatened their profits they sprang into action.
⛤
I think the current logo would work fine as a unicode character. I dislike the three anuses for a logo.
I doubt it’s looking anything up. It’s probably just grabbing the previous messages, reading the word “wrong” and increasing the number. Before these messages I got ChatGPT to count all the way up to ten r’s.
Plenty of fun to be had with LLMs.
Seconded, Divinity is great!
https://github.com/cheeaun/phanpy?tab=readme-ov-file#easy-way
It’s fairly literally just a download-and-run kind of deal it seems. Does seem pretty trivial.