Show HN: Core – open source memory graph for LLMs – shareable, user owned https://ift.tt/mVZIBn6

Show HN: Core – open source memory graph for LLMs – shareable, user owned I keep running in the same problem of each AI app “remembers” me in its own silo. ChatGPT knows my project details, Cursor forgets them, Claude starts from zero… so I end up re-explaining myself dozens of times a day across these apps. The deeper problem 1. Not portable – context is vendor-locked; nothing travels across tools. 2. Not relational – most memory systems store only the latest fact (“sticky notes”) with no history or provenance. 3. Not yours – your AI memory is sensitive first-party data, yet you have no control over where it lives or how it’s queried. Demo video: https://youtu.be/iANZ32dnK60 Repo: https://ift.tt/K7tV82w What we built - CORE (Context Oriented Relational Engine): An open source, shareable knowledge graph (your memory vault) that lets any LLM (ChatGPT, Cursor, Claude, SOL, etc.) share and query the same persistent context. - Temporal + relational: Every fact gets a full version history (who, when, why), and nothing is wiped out when you change it—just timestamped and retired. - Local-first or hosted: Run it offline in Docker, or use our hosted instance. You choose which memories sync and which stay private. Try it - Hosted free tier (HN launch): https://core.heysol.ai - Docs: https://ift.tt/aoA8Mvx https://ift.tt/K7tV82w July 1, 2025 at 09:54PM

Show HN: Fixstars AIBooster – Accelerate AI Training and Cut GPU Costs https://ift.tt/87iNcvG

Show HN: Fixstars AIBooster – Accelerate AI Training and Cut GPU Costs Hi HN, We're excited to introduce Fixstars AIBooster, our new performance engineering tool designed to significantly accelerate AI model training while optimizing GPU utilization. AIBooster provides: Real-time monitoring of GPU, CPU, memory, and power consumption. Clear visibility into performance bottlenecks, helping developers optimize AI workloads. Proven acceleration of AI training processes—users commonly achieve up to 2-3x speed improvements. Significant cost savings by maximizing infrastructure efficiency. It's free to try, requires minimal setup, and integrates seamlessly into your existing infrastructure. We've built this tool to empower AI developers to get the most from their GPU infrastructure without complicated tuning. We'd love your feedback, questions, or suggestions! https://ift.tt/fY2nmQr July 2, 2025 at 12:15AM

Show HN: Runik – Turn fan wikis into e-reader dictionaries https://ift.tt/F92wi7Y

Show HN: Runik – Turn fan wikis into e-reader dictionaries Hey HN! As a reader of epic fantasy and sci-fi, I often find myself reaching for my phone to look up an obscure side character — or the difference between “Genebackis” and “Genebaris”. So I built runik to bring in-world definitions directly onto my e-reader and stay immersed in the story. Runik parses the contents of fan wikis into Kobo and Kindle compatible dictionaries. It uses the device’s built-in word lookup feature, so there’s no jailbreaking required and definitions can be used offline. It’s still in early development and is built with Go (Wails) + Svelte + Dictutil — feedback is appreciated! Note: Kindle support requires kindlegen, which comes bundled with the Kindle Previewer app (details in the README). https://runik.app/ https://ift.tt/xSp8JGZ https://ift.tt/xSp8JGZ July 1, 2025 at 11:25PM