In Q3, the company plans to tape out its first large language model chip and, in Q1 2025, intends to 
make it available to early customers.
Taalas has raised $50 million dollars over two rounds of funding led by Pierre Lamond (pictured right) and Quiet Capital.
“Commoditising AI requires a 1000x improvement in computational power and efficiency, a goal that is unattainable via the current incremental approaches,” says Taalas co-founder and CEO Ljubisa Bajic (pictured left) 
who also founded Tenstorrent, “the path forward is to realise that we should not be simulating intelligence on general purpose computers, but casting intelligence directly into silicon. Implementing deep learning models in silicon is the straightest path to sustainable AI.”
Taalas is developing an automated flow for rapidly implementing all types of deep learning models (Transformers, SSMs, Diffusers, MoEs, etc.) in silicon. Proprietary innovations enable one of its chips to hold an entire large AI model without requiring external memory. The efficiency of hard-wired computation
“We believe the Taalas ‘direct-to-silicon’ foundry unlocks three fundamental breakthroughs: dramatically resetting the cost structure of AI today, viably enabling the next 10-100x growth in model size, and efficiently running powerful models locally on any consumer device. This is perhaps the most important mission in computing today for the future scalability of AI. And we are proud to support this remarkable n-of-1 team as they do it,” says Matt Humphrey, Partner at Quiet Capital.
Taalas was founded by Ljubisa Bajic, Drago Ignjatovic, and Lejla Bajic. Prior to co-founding Taalas, Ljubisa founded Tenstorrent in 2016. Drago and Lejla joined Tenstorrent soon after as early engineering leaders. The team has spent decades collectively working together on a long list of AI processors, GPUs, and CPUs across Tenstorrent, AMD, and NVIDIA.
“The Taalas’ founders’ track record in the industry is second to none,” says Pierre Lamond.
