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Joined 2 years ago
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Cake day: June 22nd, 2023

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  • We never have been 100% renewable in the UK. It’s more that we go into surplus and shutting generators down is more expensive than the price going negative. Hence we won’t get huge negative prices. Connectors to other countries can only export so much.

    It also only happens when:

    • long term weather forecast underestimated weather based generation.
    • demand is low. (E.g. weekend and public holidays)

    The population of Germany is only 25% bigger than the UK, so I think the two are comparable. A larger manufacturing base will make the demand-side curve more predictable though. Still, we’re largely talking about the effect of supply unpredictability.







  • wewbull@feddit.uktoTechnology@lemmy.worldLegalEagle Suing PayPal's Honey
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    5 days ago

    My problem here, and I don’t mean to victim blame but I don’t understand why anybody thought Honey had a business model that was trustworthy. Most people would see through the slimy guy in your example, so why would they install a slimy guy in their browser? Why would people take sponsorship from a slimy guy? Why would they read our copy that tells kids to “install it on every computer in the house”?

    Nobody asked themselves “How does Honey make money out of this?” because at the very least they were going to be data scraping! That much was obvious.











  • Matrix math is just stupid for whatever you pipe through it. It does the input, and gives an output.

    Indeed.

    That is exactly what all these “NPU” co processing cores are about from AMD, Intel, and to a further subset Amazon and Google on whatever they’re calling their chips now. They are all about an input and output for math operations as fast as possible.

    Yes, they are all matrix math accelerators, and none of which have any FPGA aspects.


  • wewbull@feddit.uktoTechnology@lemmy.worldDoes current AI represent a dead end?
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    13 days ago

    I know exactly what they are. I design CPUs for a living, use FPGAs to emulate them, and have worked on GPUs and many other ASICs in the past.

    FPGAs can accelerate certain functions, yes, but neural net evaluation is basically massive matrix multiplies. That’s something that GPUs are already highly optimised for. Hence, why I asked what circuit you’d put on the FPGA. Unless you can accelerate the algorithmic evaluation by several orders of magnitude the inefficiency of FPGAs Vs ASICs will cripple you.


  • I don’t really see how FPGA has a role to play here. What circuit are you going to put on it. If it’s tensor multipliers, even at low precision, a GPU will be an order of magnitude faster just on clock speed, and another in terms of density.

    What we’ve got right now has almost nothing to do with python, and everything to do with the compute density of GPUs crossing a threshold. FPGAs are lower density and slower.