4 ms·

Also, the open source models are getting closer and closer to the (current) closed models. Hopefully more and more tinkerers are going to fuel this fire even f

Also, the open source models are getting closer and closer to the (current) closed models. Hopefully more and more tinkerers are going to fuel this fire even further, making it possible to run AI on-device with custom native chips.

toxik 3y ago
Which current public models do you think are getting to ChatGPT levels?
- tmikaeld 3y ago
  Llama 2 is very close to GPT 3, same with the new code Llama. That said, while it scores high, it's not as "generally" competent on most issues as GPT is, however, it's an exponentially smaller model and for that it does, it's really impressive.
- reacharavindh 3y ago
  I don’t particularly use ChatGPT in any serious capacity or for work. But, for my amusement and intellectual assisting needs, Llam2-uncensored and codewhisper models run using Ollama locally on my Mac has been a pleasure to use. Like most things, if you steer clear of all the hype there is a golden core of utility to be found. It sure is not just a party truck as the article daringly claims/questions it to be. The ones that make clever use of the foundational tool will stand to reap the benefits. Just like the ones that benefited from the spread of the internet.
- capybara_2020 3y ago
  Depends on what you want to do. For writing and RPG style interactions some of the LLama 2 based models are pretty good. Beauty is, even the 13B models work in those cases. So it works reasonably well on consumer grade hardware.
- Roark66 3y ago
  It is not really a fair comparison, because chatgpt is not just a model. There is clever output sampling, scoring, sub model selection based on prompt and more. While open source LLMs are "just a model" with the most basic (greedy) output sampling. To have real LLM comparison we would need access to pure chatgpt model's input/outputs. I wouldn't be surprised if certain open source LLMs like falcon-40b-instruct or llama2 have already surpassed chatgpt 3.5 models in quality. But as far as I know no one so far has taken a bunch of open source models and wrapped them in a service like chatgpt 4. Why? Because the main cost of running such service using open source code (assuming the service would be open source too) would be the cost of renting hardware. Consequently the barrier to entry for competition would be very low so no one would sink their life savings in a company like that. However, once it becomes possible to run multiple models like falcon-40B and llama2 (without quantization to 4bits) on a typical "high end pc" that will change. We will see open source projects that want to achieve a "chatgpt service" offline on consumer hardware. Why only then? Same reason why Linux was written once 386PC's became available. Could someone like Linus Torvalds write Linux 20 years before on their "university" or "company" computer? Sure, but except certain exceptions (gnu) most people engage in writing open source software they themselves want to run on their own hardware. Big companies know this and they know very well such developments will out compete them shortly (like Linux out competed unix) so they are already doing all they can to stop or slow it down. By talking about "the dangers of AI", by not releasing powerfull ai accelerators on the market (google's tpu). And so on. But it will happen. Give it 10 years. I

toxik 3y ago

Which current public models do you think are getting to ChatGPT levels?

tmikaeld 3y ago
Llama 2 is very close to GPT 3, same with the new code Llama. That said, while it scores high, it's not as "generally" competent on most issues as GPT is, however, it's an exponentially smaller model and for that it does, it's really impressive.
reacharavindh 3y ago
I don’t particularly use ChatGPT in any serious capacity or for work. But, for my amusement and intellectual assisting needs, Llam2-uncensored and codewhisper models run using Ollama locally on my Mac has been a pleasure to use. Like most things, if you steer clear of all the hype there is a golden core of utility to be found. It sure is not just a party truck as the article daringly claims/questions it to be. The ones that make clever use of the foundational tool will stand to reap the benefits. Just like the ones that benefited from the spread of the internet.
capybara_2020 3y ago
Depends on what you want to do. For writing and RPG style interactions some of the LLama 2 based models are pretty good. Beauty is, even the 13B models work in those cases. So it works reasonably well on consumer grade hardware.
Roark66 3y ago
It is not really a fair comparison, because chatgpt is not just a model. There is clever output sampling, scoring, sub model selection based on prompt and more. While open source LLMs are "just a model" with the most basic (greedy) output sampling. To have real LLM comparison we would need access to pure chatgpt model's input/outputs. I wouldn't be surprised if certain open source LLMs like falcon-40b-instruct or llama2 have already surpassed chatgpt 3.5 models in quality. But as far as I know no one so far has taken a bunch of open source models and wrapped them in a service like chatgpt 4. Why? Because the main cost of running such service using open source code (assuming the service would be open source too) would be the cost of renting hardware. Consequently the barrier to entry for competition would be very low so no one would sink their life savings in a company like that. However, once it becomes possible to run multiple models like falcon-40B and llama2 (without quantization to 4bits) on a typical "high end pc" that will change. We will see open source projects that want to achieve a "chatgpt service" offline on consumer hardware. Why only then? Same reason why Linux was written once 386PC's became available. Could someone like Linus Torvalds write Linux 20 years before on their "university" or "company" computer? Sure, but except certain exceptions (gnu) most people engage in writing open source software they themselves want to run on their own hardware. Big companies know this and they know very well such developments will out compete them shortly (like Linux out competed unix) so they are already doing all they can to stop or slow it down. By talking about "the dangers of AI", by not releasing powerfull ai accelerators on the market (google's tpu). And so on. But it will happen. Give it 10 years. I