Predictions about the potential impacts of generative AI may be hugely overblown because of "many serious, unsolved problems" with the technology according to Gary Marcus, one of the field's leading voices.
Which modern Mac are you talking about and how much does that cost? Again, I doubt any of the opensource 30B models can compete even with ChatGPT 3.5. Which is the point I started with earlier.
Seems to me like you are riding this whole efficiency thing on nothing more than hopium.
I actually work with this stuff daily and there is a number of 30B models that are exceeding chatGPT for specific tasks such as coding or content generation, especially when enhanced with a lora.
airoboros-33b1gpt4-1.4.SuperHOT-8k for example comfortably outputs > 10 tokens/s on a 3090 and beats GPT-3.5 on writing stories, probably because it’s uncensored. It’s also got 8k context instead of 4.
Several recent LLama 2 based models exceed chatgpt on coding and classification tasks and are approaching GPT4 territory. Google bard has already been clobbered into a pulp.
The speed of advances is stunning.
M- architecture macs can run large LLMs via llama.cpp because of unified memory interface - in fact a recent macbook air with 64GB can comfortably run most models just fine. Even notebook AMD GPUs with shared memory have started running generative AI in the last week.
Which modern Mac are you talking about and how much does that cost? Again, I doubt any of the opensource 30B models can compete even with ChatGPT 3.5. Which is the point I started with earlier.
Seems to me like you are riding this whole efficiency thing on nothing more than hopium.
I think at this point we are arguing belief.
I actually work with this stuff daily and there is a number of 30B models that are exceeding chatGPT for specific tasks such as coding or content generation, especially when enhanced with a lora.
airoboros-33b1gpt4-1.4.SuperHOT-8k for example comfortably outputs > 10 tokens/s on a 3090 and beats GPT-3.5 on writing stories, probably because it’s uncensored. It’s also got 8k context instead of 4.
Several recent LLama 2 based models exceed chatgpt on coding and classification tasks and are approaching GPT4 territory. Google bard has already been clobbered into a pulp.
The speed of advances is stunning.
M- architecture macs can run large LLMs via llama.cpp because of unified memory interface - in fact a recent macbook air with 64GB can comfortably run most models just fine. Even notebook AMD GPUs with shared memory have started running generative AI in the last week.
How much does this cost?
You will answer any and every question but this.
My points still stand