Deepseek research touts memory breakthrough, decoupling compute power and RAM pools to bypass GPU & HBM constraints — Engram conditional memory module commits static knowledge to system RAM

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DeepSeek has released a new technical paper, which details a new method for how new AI models might rely on a queryable database of information committed to system memory. Named “Engram”, the conditional memory-based technique achieves demonstrably higher performance in long-context queries by committing sequences of data to static memory. This eases the reliance on reasoning for AI models, allowing the GPUs to only handle more complex tasks,…



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Deepseek research touts memory breakthrough, decoupling compute power and RAM pools to bypass GPU & HBM constraints — Engram conditional memory module commits static knowledge to system RAM


Tom’s Hardware Premium Roadmaps

a snippet from the HBM roadmap article

(Image credit: Future)

DeepSeek has released a new technical paper, which details a new method for how new AI models might rely on a queryable database of information committed to system memory. Named “Engram”, the conditional memory-based technique achieves demonstrably higher performance in long-context queries by committing sequences of data to static memory. This eases the reliance on reasoning for AI models, allowing the GPUs to only handle more complex tasks,…



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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