INSUBCONTINENT EXCLUSIVE:
Neural Magic, a startup founded by a couple of MIT professors, who figured out a way to run machine learning models on commodity CPUs,
announced a $15 million seed investment today.Comcast Ventures led the round, with participation from NEA, Andreessen Horowitz, Pillar VC
The company had previously received a $5 million pre-seed, making the total raised so far $20 million.The company also announced early
access to its first product, an inference engine that data scientists can run on computers running CPUs, rather than specialized chips like
That means that it could greatly reduce the cost associated with machine learning projects by allowing data scientists to use commodity
hardware.The idea for this solution came from work by MIT professor Nir Shavit and his research partner and co-founder Alex Mateev
As he tells it, they were working on neurobiology data in their lab and found a way to use the commodity hardware he had in place
He says his company not only allows you to use this commodity hardware, it also works with more modern development approaches, like
explained.He says this also eliminates the memory limitations of these other approaches because CPUs have access to much greater amounts of
the cost savings of running on a CPU, but more importantly, it eliminates all of these huge commercialization problems and essentially this
big limitation of the whole field of machine learning of having to work on small models and small data sets because the accelerators are
opportunity with an approach that lets people use commodity hardware
