AMD deepens AI inference bet with Taalas deal as chip race heats up
Toronto-based Taalas develops specialized silicon designed to reduce computing and memory bottlenecks in AI inference, the process of running trained AI models to generate responses or predictions.

Toronto-based Taalas develops specialized silicon designed to reduce computing and memory bottlenecks in AI inference, the process of running trained AI models to generate responses or predictions.
Specialized inference chips have become a critical focus for semiconductor makers as AI shifts from training to real-time, high-volume deployment, and companies race to cut computing costs.
Larger rival Nvidia in March unveiled a new central processor and AI system built on technology from Groq, a chip startup specializing in inference.
AMD plans to integrate Taalas' technology into its accelerator roadmap and develop system-level solutions using AMD Instinct graphics processing units (GPUs).
"AMD is building a full-stack AI platform that gives customers the flexibility to deploy the right compute solutions for every AI workload," Vamsi Boppana, senior vice president of AMD's Artificial Intelligence Group, said in a statement.
Taalas' technology and engineering team strengthens AMD's AI portfolio by "delivering differentiated inference performance and efficiency," Boppana added.
Taalas, founded in 2023, had raised $169 million in February to support the development of chips optimized for AI models, bringing its total funding to around $219 million.
AMD has been bolstering its AI business through a string of acquisitions. In November, the company said it bought MK1, an AI software startup specializing in high-speed inference.
The company purchased MEXT to expand its AI portfolio in June and added FastFlowLM to its Artificial Intelligence Group in July.
(Reporting by Juby Babu in Mexico City; Editing by Sriraj Kalluvila)
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