>Sure, Baby Driver made $300m on a $40m budget. But for pure profit maximization you are better off making a billion dollars on a $500m budget.
Lol no you're not. $1B off a 500M production budget would be a disaster bordering on a flop. You've not taking marketing into account. You've not taking having to split earnings with theaters into account. Baby Driver is the more desired outcome 10/10.
It's just a poor point. Cats are a bad analogy anyhow because there is no cat language. You can't actually speak to them or have a drawn out discussion. But you can with humans and many have inspired thousands or even millions to action doing just that, no super-intelligence required.
Yeah the whole thing is strange. He does such a good job in the first bit outlining all the reasons for caution that I was intrigued to see what he had to say against it, but it's just one bad argument after another. Even Hawking's cat is bad. Make some money and pay someone to get the cat in the box.
Paying someone to physically force the cat in the carrier is missing the point. Compared to the cat, Hawking is a super intelligence. But all that intelligence isn't able to get him to speak cat and give the cat a reason to get inside the carrier of its own volition.
Who said anything about physically forcing the cat in the box? The point of Hawkings cat is is the lack of physical embodiment for AI. So get someone else to do it. Millions of people put cats in boxes without any force just fine. Or do you classify it as 'force' because it went beyond speaking? You can't actually speak to cats (unlike humans) so acting like anything more than words is brute force is strange.
Who was Hitler to most people ? Just a persuasive powerful voice on the radio, or words on a paper. So not even two way communication and yet he inspired armies that killed millions. Hawkings wouldn't even need to pay anyone. There would be plenty of people willing to get the cat in the box for Stephen Hawkings.
ChatGPT is the 5th most visited site (as well as has nearly a billion weekly active users) and none of the competitors are even close. In the consumer space, Gemini is doing well but Claude is not even in the same galaxy. OpenAI is undoubtedly the leader in consumer LLMs and by a large margin. I'm sure there are mixups, but if someone is telling you they're using chatGPT, they almost certainly mean they're using chatGPT.
The consumer market is worthless though. Consumers will never pay, so the only revenue option is ads which barely, if even at all, pay for inference costs.
Ads implemented remotely competently would be worth a lot of money and more than pay for inference. Inference is cheap, especially outside token expensive ordeals like agentic coding.
Maybe. To really make money on ads they would need to embed them directly into the chat I think. Banner ads arent worth enough I think and google is able to make so much off them largely because people are already looking to click a link when they search something. People would just ignore them with genAI.
Maybe Im projecting my distaste for being psychologically manipulated, but I dont think users would continue using a genAI that embeds ads directly into the response when they can just switch to gemini where they only see banners.
I’m pretty sure Gemini would be the leader in consumer LLMs considering it’s on every single search result. Every single google search is also usage of gemini.
Google stuffing things in the search results of existing users does not mean active participation or usage. (Not that I'm saying it's not getting used but it's just a feature of google search, and only a fraction of the kind of queries llms get anyway)
People use LLMs for a lot of things. Different kind of search is only one of them. AI mode is not stopping people from using ChatGPT because it's just a subset of consumer LLM queries.
Fatal Familial Insomnia is an incredibly rare prion disease that causes widespread neurological destruction. It's not remotely a normal brain that has chosen not to sleep. It's such a highly non-trivial deviation of the brain that we've only identified a few dozen families in the entire planet that suffer from it. At this point, quite a lot of things have already gone wrong in your brain.
There is quite literally no prion disease that isn't fatal.
Sleep does a lot of very important things that we probably wouldn't live long without, but it really is unclear to what extent sleep is necessary for them. If we had enough knowledge, could we trigger all the things sleep does without invoking sleep itself ? Perhaps sleep is just a very convenient mechanism.
Anthropomorphization is not inherently wrong, and in some instances, it actually lets you reason better about about complex behavior than whatever convoluted (and often wrong, especially in the case of giant neural networks) mechanistic description one might conjure.
> This whole thread is an overreaction. 302 comments about code that does not work. We haven’t committed to rewriting. There’s a very high chance all this code gets thrown out completely.
Is your reading comprehension poor? Where in that does it say it had no chance of being merged? Do you understand what an experiment and what the purpose of an experiment is ?
Of course he's not writing a legal contract, but to go from saying:
> This whole thread is an overreaction. 302 comments about code that does not work. We haven’t committed to rewriting. There’s a very high chance all this code gets thrown out completely.
And then fully merging into main in under 18 days is quite extreme
>It's clearly not yet a tool that can deliver new math at a scale.
What is at scale here exactly ? This is the most impressive so far, but it is one of several such advances in the last few months, all of which were with publicly accessible models.
LLMs have been trained on a lot more data than any single human (text wise at least) for years now and these sort of results have only been possible for the latest crop of models in the past few months. Models get better as they get better.
The argument is whether models of today, suitably trained on pre-17th century data (if comparable quantity was available) would be able to "invent" calculus et cetera.
If we believe today's models are sufficiently capable to have been able to do so, why are we not getting these types of results today compared to the entire world knowledge and especially math?
Are research mathematicians simply not prompting LLMs in the right way?
Lol no you're not. $1B off a 500M production budget would be a disaster bordering on a flop. You've not taking marketing into account. You've not taking having to split earnings with theaters into account. Baby Driver is the more desired outcome 10/10.
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