AI agents can reason. AI agents can use tools. Now they need a place to remember.
Introducing AIStor Memory, giving enterprise AI agents a durable place to store their memory, files, and secrets in a single integrated system. 🧵 bit.ly/4fDtm31
Amazon’s acquisition of DuckLabs reinforces where the lakehouse is headed: query data where it lives.
That’s the architecture MinIO is built for—a high-performance data foundation for open analytics engines and table formats like DuckDB and Iceberg.
Prompt caching works until reusable KV state is trapped on one GPU. At production scale, that state needs to move across workers and nodes.
This is the architecture behind shared context memory.
Keep reading: bit.ly/4i5kYeZ
What does the data architecture for production AI agents actually look like?
Join MinIO and @lakeFS to dive into agent memory, data isolation, reproducibility, and governance + how to build those capabilities into the infrastructure layer without slowing development down.
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Every GPU dollar should produce useful work.
When GPUs repeatedly process context they’ve already seen, you’re paying for duplicate compute.
Prompt caching changes the economics: reuse context, reduce recompute, and get more from every GPU dollar. bit.ly/47Br1Sz