| ▲ | h14h 2 hours ago | ||||||||||||||||
I think a major incentive could be to sell hardware. If Apple is able to get their hands on a local LLM capable of covering a significant % of what people use ChatGPT for, the pitch they can offer is: "Free, private, offline ChatGPT so long as your laptop has X GB of RAM" Beyond that, I wouldn't underestimate the incentive of "because I can". The "secret sauce" you refer to is effectively just a DB & a while loop that feeds text to a bunch of tensors. If an indie dev decides they want to release something that dismantles the OpenAI & Anthropic moats, there really isn't all that big of a technical barrier stopping them. | |||||||||||||||||
| ▲ | bigyabai an hour ago | parent [-] | ||||||||||||||||
LLM inference decode is heavily dependent on memory speed, not just having lots of memory. You can't say "X amount of ram" because the memory bandwidth on an M1 is 68.3 GB/s versus the 614 GB/s of an M5 Max, or a 4090's 1.01 TB/s over GDDR6X. This basically creates a bottleneck at the oldest/cheapest Apple Silicon machines, which are already crippled for context prefill. | |||||||||||||||||
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