Kunle Olukotun Quotes

“Wikipedia: Kunle Olukotun”

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“And again, you want to be able to handle those large embedding tables because the larger the embedding table, the more accurate the model, the better recommendation you’re able to give.”

“And so what you want is the capability to both do large batch training very efficiently, but also to single-batch inference very efficiently. And so we can do that with the SambaNova systems.”

“for instance, huge natural language processing models for the financial sector or for developing chatbots and customer services, voice-based commerce. Also, natural language processing, finds use in cancer research also.”

“Or huge vision models that we call true resolution that allow you to do medical images without reducing the resolution to make the image more blurry, so that you can fit it into the memory requirements of conventional systems.”

“So think of SambaNova systems as this capability of doing training and inference very efficiently. And then the real full circle: Once you can do training and inference on the same platform, you can dynamically switch between them.”

“what SambaNova brings to the table is the ability one or two or a quarter rack of capability to be able to provide terabytes of memory. And so that allows you to build huge models that can serve any of the particular industrial verticals or commercial verticals that are of interest.”

“the whole goal is, of course, to provide the capabilities to be able to train very, very large, accurate models. If you look at the current landscape of computing capabilities, mostly dominated by GPUs, what you need is many, many GPUs because of the limited amount of memory that each of the GPUs can have.”