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That shift won't happen until research slows down. Nobody wants to invest significant amounts of money in hardware that will be obsolete in a year.
by BobbyJo 3y ago
That shift won't happen until research slows down. Nobody wants to invest significant amounts of money in hardware that will be obsolete in a year.
- voxadam 3y ago> Nobody wants to invest significant amounts of money in hardware that will be obsolete in a year. When talking about the current ML industry it's more like nobody wants to invest significant amounts of money in hardware that will be obsolete before it's even taped out.
- kramerger 3y agoCounterpoint: whoever is the first to make advanced ML affordable, maybe even mobile has a good chance of dominating multiple markets in near future.
- fxtentacle 3y agoThere's open source to export fully trained AI models for efficient execution on arbitrary CPUs. Most likely, you won't be able to build up any moat in AI inference.
- mechagodzilla 3y agoWhat would be obsolete? The underlying operations are almost always just lots of matrix multiplies on lots of memory. Releasing a new set of weights doesn’t somehow change the math being done.
- AstralStorm 3y agoThe amount of memory available is the obsolescence.
- BobbyJo 3y agoTo the extent that AI architectures are just matrix multiplications, there is already an asic: GPUs. If you want more efficiency gain than general matrix multiplication hardware, you need to start getting specific about the NN architectures the hardware will support.