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This is a submission for the Hermes Agent Challenge: Write About Hermes Agent What if the biggest limitation in AI today isn't reasoning, model size, or context windows? What if it's memory? Every morning, millions of people open ChatGPT, Claude, Gemini, or another AI assistant and start a conversat
Tensormesh Inc. has hit upon a way to make artificial intelligence inference more efficient by eliminating the need for redundant computations, and its technology is so convincing that several of AI infrastructure giants are backing it with $20 million in funding. Today’s round saw the participation
Memory chipmakers Micron Technology Inc. and SK Hynix Inc. each saw their market values surge above $1 trillion for the first time today, driven by insatiable demand for their products from artificial intelligence firms. Micron’s stock jumped more than 19% today, as investors piled into the stock fo
This is not proof. It is early, messy evidence from my own workflow: three failures, one small comparison, and one schema bug I missed. I'd spent a week arguing, in public, that AI memory should be built on discipline before infrastructure: preserve corrections, preserve unresolved questions, decide
Mem0 and Zep are solid memory retrievers. But neither solves governance. Here's the technical breakdown of what that gap means if you're building AI agents in regulated environments. The AI memory market has consolidated. Mem0 and Zep are the two best-known players. Well-funded, well-documented, wid
AI agents forget everything. What is Engram? Pinecone — proprietary, expensive at scale, you're locked in The deeper issue isn't pricing. It's trust. You're trusting a company to: Keep your data available For personal projects, fine. For infrastructure that AI agents depend on long-term? That's a re
A top Micron executive warns the global semiconductor memory shortage, fueled by the AI boom, is severe and could extend beyond 2028. Indian firms risk being unprepared due to price sensitivity and a reluctance to commit to long-term procurement contracts, despite the nation's push for sovereign AI
If you are building agents in 2026, you have already hit the wall. Bigger models do not fix forgetfulness. Context windows can grow forever, and the agent still cannot remember what a user told it last Tuesday, that the customer's address changed three months ago, or that a recommendation it made la
Originally published on mihaibuilds.com. Cross-posting here because dev.to is where I find a lot of this kind of work myself. For the past year I kept hitting the same wall. I'd have a real conversation with Claude — work through a database design, debug something gnarly, agree on a convention I wan
Samsung’s stock has more than quadrupled in a year. The KOSPI broke 7,000 for the first time. Two Korean chipmakers now account for 42% of the index. The supercycle that built this rally is, by Samsung’s own forecast, not yet at its peak. There is a particular type of market moment that does not hap
A $725bn hyperscaler capex ramp and a 20% HBM price rise have made the South Korean chipmaker the second-most valuable company on the KOSPI. The harder question is when supply catches demand. There is a small joke in semiconductor circles about which part of an AI server is most expensive. The graph
Why storing and retrieving data isn’t enough to build reliable AI memory systems The post Stop Treating AI Memory Like a Search Problem appeared first on Towards Data Science.
The Fifth Element and Resident Evil star reveals an AI project inspired by the ancient “memory palace” method.
Google’s TurboQuant has the internet joking about Pied Piper from HBO's "Silicon Valley." The compression algorithm promises to shrink AI’s “working memory” by up to 6x, but it’s still just a lab experiment for now.
