Why d-Matrix bets on in-memory compute to break the AI inference bottleneck

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AI inference is poised to become the single largest compute workload. For some time now, after all, AI service providers like OpenAI have claimed that they are mostly constrained by compute availability. Even as these companies build massive, power-hungry data centers to run both their training and inference workloads, the need for optimized hardware and software solutions remains.

Meanwhile, it’s not just the frontier AI labs that are concerned with the cost of running these models, but increasingly, enterprises want full control over…



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Why d-Matrix bets on in-memory compute to break the AI inference bottleneck


AI inference is poised to become the single largest compute workload. For some time now, after all, AI service providers like OpenAI have claimed that they are mostly constrained by compute availability. Even as these companies build massive, power-hungry data centers to run both their training and inference workloads, the need for optimized hardware and software solutions remains.

Meanwhile, it’s not just the frontier AI labs that are concerned with the cost of running these models, but increasingly, enterprises want full control over…



Source link

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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