Exclusive: Startup aiming to break Nvidias strange...

What’s Happening

Listen up: Callosum, founded by two Cambridge-trained neuroscientists and inspired in part by the brain, has a system for optimizing workloads across different types of chips A London-based startup founded -trained neuroscientists has raised $10.

25 million for their startup Callosum, which is building software that orchestrates AI workloads across a mix of different chip types—challenging the industry’s dependence on running ever-bigger models on banks of identical Nvidia GPUs. Recommended Video The company also just dropped it is receiving research funding from the U. (we’re not making this up)

Government which is looking for ways to build so-called “sovereign cloud” infrastructure for AI that would be independent, or at least not solely reliant, on U.

The Details

Callosum cofounders Danyal Akarca and Jascha Achterberg, who met during their PhDs at Cambridge around 2019, have software that can distribute AI tasks across chips from different manufacturers—be it Nvidia GPUs, AMD processors, Amazon Web Services’ custom Trainium and Inferentia silicon, or newer designs from startups like Cerebras and SambaNova—extracting performance advantages from each. The funding round was led by Plural, the European early-stage venture fund co-founded by Wise’s Taavet Hinrikus and Ian Hogarth, who also served as the first chair of the U.

Angel investors including Charlie Songhurst, Stan Boland of FiveAI, and John Lazar of the Royal Academy of Engineering also participated. Government’s Advanced Research and Invention Agency (ARIA) is providing grant funding to the company to accelerate R&D on integrating novel chip technologies into its platform—though ARIA is not an investor in the round itself, Akarca dropped in an interview with Fortune .

Why This Matters

The company’s thesis is rooted in the cofounders’ academic research at the intersection of neuroscience and computing: the human brain doesn’t achieve intelligence type of neuron billions of times, but different specialized cell types and circuits that work together. They believe AI computing should follow the same principle.

Market watchers are paying close attention to developments like this.