Recently, AI startup DeepSeek dropped a new research paper unveiling Engram, a game-changing AI architecture that radically cuts video memory needs while speeding up knowledge retrieval 🤯.
Instead of storing all data in expensive GPU memory, Engram’s “conditional memory” splits the AI’s logic from its knowledge. Think of it like keeping your brain (logic) in your laptop’s RAM and your memory (knowledge) on a super-fast external SSD 💾.
Traditional methods like retrieval-augmented generation (RAG) can feel sluggish—imagine searching a huge digital library one shelf at a time. Engram, on the other hand, locates answers almost instantly, like teleporting the right page straight to you.
DeepSeek has open-sourced the Engram code, so anyone can test out this memory-efficient magic. For AI developers and enthusiasts across South and Southeast Asia, this means cheaper, faster models that remember what you chatted fifty prompts ago without breaking a sweat.
As AI becomes part of daily apps—from chatbots to recommendation engines—Engram could help startups and developers deliver smoother, more affordable experiences. The future of AI just got a major upgrade 🚀.
Reference(s):
DeepSeek unveils new AI architecture to slash memory requirements
cgtn.com
