I expect that software will continue to get optimized, and we’ll see new algorithms that are more efficient than what people are doing currently. However, it’s possible we’ll start seeing hardware specifically built for models as well. For example, there’s already a startup that uses ASIC chips to print the model directly to the chip. Since each transistor acts as a state, it doesn’t need DRAM and the whole chip requires a small amount of SRAM which isn’t in short supply right now https://www.anuragk.com/blog/posts/Taalas.html
The limitation with this approach is that the chip is made for a specific model, but that’s not really that different from the way regular chips work either. You buy a chip and if it does what you need, it keeps working. When new models come out, new chips get printed, and if you need the new capabilities then you upgrade.
You can see how absurdly fast their hardware version of llama 3 is here https://chatjimmy.ai/
I expect that software will continue to get optimized, and we’ll see new algorithms that are more efficient than what people are doing currently. However, it’s possible we’ll start seeing hardware specifically built for models as well. For example, there’s already a startup that uses ASIC chips to print the model directly to the chip. Since each transistor acts as a state, it doesn’t need DRAM and the whole chip requires a small amount of SRAM which isn’t in short supply right now https://www.anuragk.com/blog/posts/Taalas.html
The limitation with this approach is that the chip is made for a specific model, but that’s not really that different from the way regular chips work either. You buy a chip and if it does what you need, it keeps working. When new models come out, new chips get printed, and if you need the new capabilities then you upgrade.
You can see how absurdly fast their hardware version of llama 3 is here https://chatjimmy.ai/
That is indeed absurdly fast.