I want buy one.
It's absurd. let's mark it down.
All the ai search platform have to find a way to share value back to content owners, or the whole eco system will collapse.
Good work! Context-awareness has huge potential. I don't think this demo hit the right mark, but it definitely shed some light.
Good read.
cool
Genuis!
I like the CRT-like filter effect.
Hmm... The key is to successfully decompose a big, hard problem into easier atomic sub-problems. However, the decomposition process itself is difficult, and this paper is not about that. They decompose a task using a…
wow....
I like the vibe.
Prompts are really an interesting way of programming, and we can actually express logic containing abstract adjectives like ‘happy’ and ‘unsatisfied’ in a somewhat arbitrary way.
Great!
"As an analogy, imagine that you could put your dog or cat into hibernate mode whenever you left on a trip. Your dog or cat might not notice, but even if they did, they might not mind. Now imagine that you could put…
RL doesn't need that much static data, it needs a lot of "good" tasks/challenges and computation.
Trained with 300 raw pairs directly from the ARC training set without using any data augmentation process, such as generating many more pairs with some kind of ARC generator? That's amazing.
"Note on "tuned": OpenAI shared they trained the o3 we tested on 75% of the Public Training set. They have not shared more details. We have not yet tested the ARC-untrained model to understand how much of the…
Off the topoc. I think, in the long-term , inference should be done along with some kind of training.
Past efforts leds to today's products. We need to wait to see the real imapct on the ability to ship.
It's amazing!
Fasciating. Language is a type of action evoloved for information exchaging, which maps latent "video", "audio" and "thoughts" into "sentences" and vice versa.
Cool! The real-time feedback will have enormous ramifications on the art creation workflows.
Asking models to do math is kind of an effecitve way to measure their capabilities, especially in reasoning and abstraction, which are quite important for problem solving.
The chain-of-thought works quite like the "System 2" introduced in <<Thinking, Fast and Slow>>, which is slower, more deliberative, and more logical.
I think the last paragraph quite makes sense. It seems "true" that some kind of reasoning capability emerges as LLMs get bigger, which makes those LLMs quite useful and blows a lot of people's minds at the beginning.…
I want buy one.
It's absurd. let's mark it down.
All the ai search platform have to find a way to share value back to content owners, or the whole eco system will collapse.
Good work! Context-awareness has huge potential. I don't think this demo hit the right mark, but it definitely shed some light.
Good read.
cool
Genuis!
I like the CRT-like filter effect.
Hmm... The key is to successfully decompose a big, hard problem into easier atomic sub-problems. However, the decomposition process itself is difficult, and this paper is not about that. They decompose a task using a…
wow....
I like the vibe.
Prompts are really an interesting way of programming, and we can actually express logic containing abstract adjectives like ‘happy’ and ‘unsatisfied’ in a somewhat arbitrary way.
Great!
"As an analogy, imagine that you could put your dog or cat into hibernate mode whenever you left on a trip. Your dog or cat might not notice, but even if they did, they might not mind. Now imagine that you could put…
RL doesn't need that much static data, it needs a lot of "good" tasks/challenges and computation.
Trained with 300 raw pairs directly from the ARC training set without using any data augmentation process, such as generating many more pairs with some kind of ARC generator? That's amazing.
"Note on "tuned": OpenAI shared they trained the o3 we tested on 75% of the Public Training set. They have not shared more details. We have not yet tested the ARC-untrained model to understand how much of the…
Off the topoc. I think, in the long-term , inference should be done along with some kind of training.
Past efforts leds to today's products. We need to wait to see the real imapct on the ability to ship.
It's amazing!
Fasciating. Language is a type of action evoloved for information exchaging, which maps latent "video", "audio" and "thoughts" into "sentences" and vice versa.
Cool! The real-time feedback will have enormous ramifications on the art creation workflows.
Asking models to do math is kind of an effecitve way to measure their capabilities, especially in reasoning and abstraction, which are quite important for problem solving.
The chain-of-thought works quite like the "System 2" introduced in <<Thinking, Fast and Slow>>, which is slower, more deliberative, and more logical.
I think the last paragraph quite makes sense. It seems "true" that some kind of reasoning capability emerges as LLMs get bigger, which makes those LLMs quite useful and blows a lot of people's minds at the beginning.…