Modular secures $100M to build tools to optimize and create AI models
Summary
Compatible with existing cloud environments, machine learning frameworks like Googles TensorFlow and Metas PyTorch and even other AI accelerator engines, Modulars engine, currently in closed preview, lets developers import trained models and run them up to 7.5 times faster versus on their native frameworks, Lattner claims.Modulars other flagship product, Mojo, is a programming language that aims to combine the usability of Python with features like caching, adaptive compilation techniques and metaprogramming. Another in that category is OctoML, which automatically optimizes, benchmarks and packages models for an array of different hardware.In any case, to Lattners point, AI demand is fast approaching the limits of sustainability making any tech to cut down on its compute requirements hugely desirable. Microsoft is facing a shortage of the server hardware needed to run AI so severe that it might lead to service disruptions, the company warned in an earnings report. According to one survey, as of 2020, 87% of data scientists used Python on a regular basis.But Lattner argues that Mojos benefits will drive its growth.One thing that is commonly misunderstood about AI applications is that they are not just a high-performance accelerator problem, he said. These auxiliary tasks are usually done in Python and C++, and only Modulars approach with Mojo can bring all these components together to work in a single unified technology base without sacrificing performance and scalability.He might be right.