This GAN was trained on chinese characters(fonts) and it is fairly close to them (If you do not look too closely). Clearly it does not look like a font, but I run out patience to train it further. I let it run for about 100h (209k iterations). #100DaysOfMLCode
@_skzv "We gathered 100 ML engineers to compete in building the next ChatGPT. Each person starts with only 1 GPU. To get more they need to eliminate other players or complete a physical challenge.
Let's see who will become the next OpenAI"
@paradite_ Yes, but what about ideas that are novel to you, but are known in some small community. You can get inspiration from any source of knowledge and LLMs are great at fuzzily browsing this knowledge. Plus combination of known ideas can make a novel idea.
@yoavgo They have their own solution: LeapSpace, which is a "research-grade AI-assisted workspace". If they advertise this right, they might convince administration to force everyone to use their "responsible" AI.
@jon_stokes This also goes against the core ethos of machine learning folk. General models eventually beat specialized models. So why specialize.
That's why everyone wants an omni model or why they combine the coding model and reasoning model with chat model.
@ElliotGlazer The sentence "I am lying." is a non-self-referential statement about a person. Only if you make an inference that the sentence itself has to be a lie you get a contradiction. For example If you just think to your self "I am lying." during a conversation, then there is no paradox.
@segyges What about fitting it in a collection of minds? Something like distributed understanding.
Also we can understand things by fitting in only the currently relevant part of the thing. You have a potential to understand every part, but you have to choose the specific part in practice
@pfau This is not complete science-fiction. To some degree people operate like that inside companies and institutions. Employees don't pay for things, they convince the management to either buy/give things or reasign/hire people.
@pfau For example we still haven't reached robotics bubble. From the looks of it frontier labs just figured out how to get a scalable data hose. So capabilities and investment in robots will probably grow even more.
@pfau They can, if we ride it out till AGI, but then the concept of money and investing maybe stops making sense. They might always be new better ways of doing things enable by improving AI. So I think we are early in the bubble territory.
@sureailabs Don't be embarrassed. Its not offensive.
I rationalize having bad username by thinking that anybody, who will engage with me does it despite the username. Plus such a name is more memorable, which is a valuable resource on the internet.
@yoavgo Those more creative parts might be optimizable. For example new concepts usually make understanding easier. So we can train the AI to create text that given to LLM will shorten the COT for a wide range of problems.
@jon_stokes If they were to believe that AI has some divine origin, then it would make sense. Be it a trial given by God or a kind of divine messenger, depending on the flavor of AI psychosis.
@yoavgo What do you mean by local? Depending on how you position things a local search can as powerful as a global search. If you pre arrange things so that answers are near the queries, then you don't need global search. Just like it is with a binary search tree.
@yoavgo We will see if it is useless math. There could be a chance, it will unlock a lot of discoveries using algebraic geometry, because people will starting looking. Fermat's Last Theorem also solved useless math, but the tools developed for it were useful.
@pfau Probably. Human created texts will increase in value, so companies/people will preserve them. I imagine that Google, Facebook and OpenAI has a stockpile of internet data. Most of it will make it to the end as long as there will be no technological collapse.