The company’s customised AI chips aim to achieve cheaper and faster results than traditional AI hardware.
Toronto-based start-up Taalas has raised $169m for its specialised AI hardware models.
Total investment in the company stands at $219m, with funding from Quiet Capital and Fidelity, among others, according to Reuters.
In a blogpost from CEO Ljubisa Bajic announcing the release of its first models, the company said it wants to mitigate the “high latency and astronomical cost” of AI, and that its specialised method is faster and cheaper than traditional AI chip approaches.
The company said it took a team of 24 and a spend of $30m since its founding less than three years ago to bring to market its first product, a hard-wired Llama 3.1 8B, which is available as both a chatbot demo and an inference API service.
The company’s aim is to mitigate the need for vast and expensive data centres through the principles of specialisation, merging storage with computation, and simplification.
Taalas said its “platform for transforming any AI model into custom silicon” means that “from the moment a previously unseen model is received, it can be realised in hardware in only two months”.
It claimed its hardware output is “an order of magnitude faster, cheaper and lower power than software-based implementations”, achieved through physically customising chips depending on the bespoke needs of the AI model in question.
Taalas claimed its silicon Llama chip, for example, is nearly 10 times faster than the current state of the art, costs 20 times less to build and consumes 10 times less power.
Taalas aims to release two further models in 2026.
AI chipmaking giant Nvidia this week announced a huge deal with Meta to provide millions of chips for Meta’s AI infrastructure in exchange for billions of dollars.
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