n a move set to shake up the AI hardware world, Chris Lattner best known for creating key developer tools at Apple and leading AI infrastructure at Google has secured $250 million for his startup Modular. Launched alongside former Google colleague Tim Davis in 2022, Modular aims to break the stranglehold that companies like NVIDIA and AMD hold over GPU software by offering a unified, high-performance layer that runs seamlessly across any chip.
Modular’s core innovation is a developer platform and new programming language built on Python that lets engineers write AI code once and deploy it on GPUs, CPUs, or custom accelerators without rewriting kernels. Drawing on Lattner’s deep experience with compiler design, the platform optimizes critical operations such as attention kernels for each hardware target, often outpacing vendor tools at launch. This flexibility not only speeds up performance tuning but also protects developers from vendor lock-in as new chips hit the market.
Investors are betting big on this vision. The latest funding round, led by the U.S. Innovative Technology Fund, values Modular at $16 billion and brings total backing to over $380 million. General Catalyst, Greylock, GV, and DFJ Growth also participated, praising Lattner’s track record and Modular’s potential to become the industry standard for AI compute. “There’s no unified software layer today,” notes one investor. “Modular could be the glue that holds AI computing together.”
Early adopters include major cloud providers and chipmakers. Amazon and NVIDIA have already partnered on pilot projects, while AMD is exploring ways to integrate Modular alongside its open-source ROCm platform. The flexibility of Modular’s layer means companies can immediately tap into new GPU features like next-generation AI instructions without waiting months for vendor-supported libraries.
Beyond raw performance, Modular puts a premium on developer productivity. Its Python-friendly language hides low-level complexity, automates kernel generation with AI assistance, and integrates with popular ML frameworks. Engineers can prototype in familiar environments and trust that their code will scale from a laptop to a fleet of data-center GPUs.
Looking ahead, Modular plans to expand support for custom AI accelerators and emerging silicon architectures, reinforcing its role as a neutral bridge between hardware innovation and software capabilities. With AI workloads demanding ever more specialized chips, the market for a portable, high-performance software layer has never been greater.
By unifying disparate hardware under one cohesive programming model, Chris Lattner’s Modular may finally deliver the “ultimate GPU software” that the industry has long sought. If successful, it could usher in a new era where developers focus on building AI breakthroughs instead of wrestling with vendor toolchains transforming how tomorrow’s intelligent applications are created and deployed.
