Taalas, start-up based in Toronto, emerged from stealth to announce $50m over two rounds of funding for its development of AI silicon.
Taalas said it 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 enables a single chip to outperform a small GPU data center, opening the way to a 1000x improvement in the cost of AI.
The company anticipates tapeout of its first large language model chip in the third quarter of 2024 and planning to make it available to early customers in the first quarter of 2025.
"Artificial intelligence is like electrical power – an essential good that will need to be made available to all. Commoditizing AI requires a 1000x improvement in computational power and efficiency, a goal that is unattainable via the current incremental approaches. The path forward is to realize 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," said Ljubisa Bajic, Taalas' CEO.
- 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.
