Architecture All Access: Neuromorphic Computing Part 2

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  • Опубликовано: 1 ноя 2024

Комментарии • 29

  • @williamcaseywells604
    @williamcaseywells604 4 месяца назад +6

    Massively underrated video. Outstanding balance between accessibility to the layperson with decent technical discussion for computer engineers.

  • @dmkdata
    @dmkdata Год назад +5

    Great video. I'm very curious to see where neuromorphic hardware finds its first commercial application.

    • @ALEXGIBSONCMG
      @ALEXGIBSONCMG Год назад

      out of the corner of my eye your icon looked like the Drumsy channel icon for a second.

    • @SaiyanGokuGohan
      @SaiyanGokuGohan Год назад

      A company called Brainchip are the first and only commercial neuromorphic company and Valeo and Renesas are bringing out applications end of this year (2023) Valeo’s Scala3 Lidar and renesas and multiple applications

  • @centuriomacro9787
    @centuriomacro9787 Год назад +1

    Its fascinating that biology created such a performant power efficient computer like our brain. Youre work at Intel is very exciting and inspiring.

  • @AlexSchendel
    @AlexSchendel Год назад +4

    Very cool technology! Looking forward to seeing where Loihi and LAVA end up!
    Impressive that Loihi 2 was ready to go on Intel 4 so fast! From what I can see though, the extra density you gained versus Loihi on 14nm went towards a much smaller die size. Are there plans for something like a Loihi 3 that might scale the die size back up and tackle some larger networks?
    I also saw the stack-able Kapoho Point boards were released a couple months ago, but there wasn't really any press on that, it would be interesting to hear more about that. So there are four Loihi 2 chips per Kapoho Point board and you can stack multiple boards for 8, 16, potentially even more? I recall there were full server racks with over 700 Loihi chips in them though. Is there any plan for that sort of scale with Loihi 2?
    In any case, very cool stuff and I think the most interesting thing of all would be to see what this sort of technology enables. Loihi had some interesting graphs showing how it stacked up against more traditional accelerators and such, but I haven't seen that for Loihi 2 anywhere.

  • @ycombinator765
    @ycombinator765 19 дней назад

    this stuff is crazy exciting!

  • @genekisayan6564
    @genekisayan6564 3 месяца назад +1

    This is profoundly exciting

  • @fpgamachine
    @fpgamachine Год назад +2

    Amazing, wonderful. I would like to buy a development board with one of those chips.

  • @Nissearne12
    @Nissearne12 10 месяцев назад

    Is there any evaluation board avaleble to buy and play around with. Neuromophic chip seems to be very exciting things.

  • @aaronmatos5581
    @aaronmatos5581 Год назад +1

    Niceeeeee! I was expecting this! Thanks for the information!

  • @brian5735
    @brian5735 5 месяцев назад

    Amazing, I love it. Thanks

  • @drewgonzales6969
    @drewgonzales6969 Год назад

    great presentation.

  • @DukeAbbaddon
    @DukeAbbaddon Год назад

    Brilliant!

  • @DukeAbbaddon
    @DukeAbbaddon Год назад

    10:12 Encore! RS

  • @jdog5362
    @jdog5362 Год назад +3

    Akida 1000 more synapses

  • @Ebonysails
    @Ebonysails 4 месяца назад

    4:04 mycelium-based neuromorphic systems can overcome this issue.

  • @o1-preview
    @o1-preview Год назад

    16th!

  • @IngeniousDimensions369
    @IngeniousDimensions369 Год назад

    Cool…🥹🥹🤓🤓

  • @AlessandroAI85
    @AlessandroAI85 2 месяца назад

    Amazing, but not clear at all! I wonder how many people without a previous knowledge actually understood the content of this video!

  • @darylallen2485
    @darylallen2485 9 месяцев назад +1

    Crysis? 😂

  • @nyhammer1
    @nyhammer1 9 месяцев назад

    RUclips is getting filled with AI generated content ...

    • @Citrusautomaton
      @Citrusautomaton 5 месяцев назад +2

      And this has to do with this video, how?

  • @techaido
    @techaido 11 месяцев назад

    Great talk and smart guy, but he doesn’t give himself enough credit, saying that evolution (which is NOTHING (it’s just a theory) is more intelligent than him.
    1:00 THE PERFECT CHIP DESIGNER Is GOD otherwise stop working on your design, because with time it’s just going to evolve into the perfect chip.

  • @DukeAbbaddon
    @DukeAbbaddon Год назад +1

    {Solve} : {{Maths Roll Error on 24Bit Audio versus 32Bit} ~= Stutter} : Windows 3D Audio, DTS & Dolby Atmos 2022-11-30 RS
    *
    {Solve} : {Maths Roll Error} : (c)RS
    {Maths Roll Error on 24Bit Audio versus 32Bit} ~= Stutter
    Additional roll, Error margin on 32Bit maths Float with 24Bit 5 point margin roundups,
    A 32Bit float rolls up on a single operation 226526554817.{24Bit float + Error roundup} .9> .49 = .5+ = roll up..
    R={5+ or 4- | 0.45+ or 0.44-} : or {0.445, |> 0.444444444445 |> 0.4 N4 +Decimal Places +5}
    Clipping operation depth of float; Is 3 operations or 2 with Stop count = 1 to 24 bit places + 1 or 2 for error rolling, up or down.
    Precision Clip
    Math OP | Clip > Cache {Math OP Use}
    Precision Counter
    Math OP + Counter(internal to FPU:CPU | Stop > Cache {Math OP Use}
    *
    Windows 3D Audio, DTS & Dolby Atmos should do to at least 32Bit 384Khz 7.1 Channels,
    There is absolutely no reason a 64Bit processor cannot do 64Bit audio,
    Mind you 32Bit Integer is around 60% of total CPU Support with 64Bit divided by 2,
    So 32Bit Audio is 100% speed conformant & there are few reasons to reduce it to 24Bit or 16Bit without processing benefaction; Such as Error management on 24Bit on 32Bit instruction:
    Both AMD & Intel X64
    Rupert S 2022-11-30
    "State-of-the-art approaches such as OpenMP and OpenCL"

    • @o1-preview
      @o1-preview Год назад

      its been 8 months, what are you views now?

    • @DukeAbbaddon
      @DukeAbbaddon Год назад

      @@o1-preview Very positive!
      Inference & FMA De-Block Styles
      For upscaling matrix: MMX+ & SiMD
      16x16 Block as used just about in HD,
      8x8 Blocks Certainly NTSC, PAL, JP_NTSC!,
      Very usable for deblocking JPG,
      16x16 & 8x8 is very good for Inferencing active on Scaling & Deblocking..
      4x4 for main Inference XBox & 8x8 for PS5..
      XBox can use (4x4)x4 for 8x8 & (4x4)x16 for 16x16; Very powerful!
      PS5 can use (8x8)x1 or x2 for 8x8 & (8x8)x4 (x8 for additional processing) for 16x16; Very powerful!
      Inference & FMA De-Block Styles List
      (4x4)x4
      (4x4)x8
      (4x4)x16 + processing
      (4x4)x32 +++ processing
      (8x8)x4
      (8x8)x8 + processing
      (8x8)x16 + processing
      (16x16)x1 + processing
      (16x16)x2 ++ processing
      (16x16)x4 +++ processing
      8:4Bit Concepts: 65535/255=8Bit 65535/16=4Bit
      16bit/4bit : 4Bit colour pallet, But we can fraction 16Bit/4bit in essence 16/4! 65535/16; Compression Shapes & Gradients.
      Polygon, Shadow, Contact
      Alpha Channel 2Bit, 4Bit
      Grayscale edge define sharpening
      Single Colour Edge detect
      Shape Fill in Alpha 10,10,10,2
      Xor, Pattern, Shading, Shader, Cull, Shape & Depth Compare after define