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Earlier quoted context omitted.
Will be capable and fast enough for 2-3 weeks until new sota drops
If it is capable today why would a new model change this?
I feel like NAND process tech could become useful at solving some of these problems. A GPU where you can update the weights a few thousand times may be sufficient.
Baking models onto silicon would've been the next logical move to get a moat.
Google is already doing this and has an experimental project on top of already having TPUs and cramming their quantized flash onto individual TPUs for inference.
Earlier quoted context omitted.
It doesn’t believe it’s running on that chip, it’s arguing with me
It's running a very small, non-reasoning model at the moment. But more generally, almost all LLMs argue on the hardware/model they are/are on.
The demo: https://chatjimmy.ai/
It also mostly passes the "schlong" test
The demo: https://chatjimmy.ai/
I feel like NAND process tech could become useful at solving some of these problems. A GPU where you can update the weights a few thousand times may be sufficient.
You need to be able to add|mul where the data (the weights) are stored.
The demo: https://chatjimmy.ai/