ilya
2.1K posts
ilya
@iryaboy24
git commit -m “watching football”
Boston Katılım Temmuz 2012
3K Takip Edilen320 Takipçiler
I got inspired by Karpathy’s LLM Wiki, implemented it in my OpenClaw and then extended it with my own skills and a full Postgres pgvector implementation.
Want to be one of the first to try GBrain?
This is my personal opinionated version of Karpathy’s LLM Wiki on OpenClaw
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@kimmonismus Gemm4 26B is absolutely amazing and run on a 5070ti 16GB. Can not wait to try 31B on a 3090 with a larger context and kv
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Having a model like Gemma 4, which is perfectly adequate for everyday use in many cases, runs locally, is free, and secure, still feels unreal.
We have a very good AI that costs nothing, uses hardly any power, and is always there. I think that's simply fantastic.
The only problem is: 99% of people have never even heard of it.
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@NousResearch @Magnificode @openclaw Please check out the repo where I merge the 2 because I had the same question! github.com/ryaboy25/shiba…
Benchmark results have come out pretty good. And retrieval speed is as fast with no wasted tokens.
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This might be dumb, but why don't tools like @openclaw or Hermes (@NousResearch) use graph databases or knowledge graphs or whatever for persistent memory over markdown files?
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@bcherny @trq212 @ClaudeCode @AnthropicAI @NousResearch @Teknium Benchmarks:
• 50.2% LongMemEval (beats Mem0, entirely local)
• 90.7% HaluMem false memory resistance
• 34ms avg retrieval
All self-hosted. No OpenAI. No cloud.
Star it, try it, break it 🐾
github.com/ryaboy25/shiba…
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@bcherny @trq212 @ClaudeCode @AnthropicAI Hermes users, Shiba ships as a native memory provider plugin. 🔌
shiba_recall, shiba_remember, shiba_forget tools available to the LLM out of the box. Auto memory on every turn. Session summaries. Prefetch before each response.
@NousResearch @teknium
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I just open sourced my first project!
Shiba Memory, persistent, self-improving memory for AI agents.
34ms hybrid retrieval. ACT-R scoring. Native Claude Code + Hermes support. Fully local, no cloud deps.
🔗 github.com/ryaboy25/shiba…
Thread 🧵
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anyone with an RTX 3090 should be paying attention. this machine is not just a gaming setup in 2026. it can host an intelligence that one-shotted an entire game on a single card that 2x H200 at full precision could not.
get your hands dirty. compile llama.cpp with CUDA. run qwen 3.5 27B dense Q4_K_M. undisputed on 24GB. the best model for that card and it's not even close.
i haven't tested gemma 4 yet but it's on the queue. the 3090 era is far from over.
Spesh@Speshal_f
@sudoingX gave me confidence that small players can play too
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More powerful hermes specialized models coming soon 👀👀
kaios@kaiostephens
first two model releases. both on front-page of huggingface. Thank you all. Carnice-27b soon.
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Anyone who has experience with the various memory systems want to give some suggestions?
Joel - coffee/acc@JoelDeTeves
POLL: What’s the best memory system for Hermes Agent and why do you prefer it? Note: X polls only support 4 options so please answer in the comments and RT for a bigger sample size! 1. Honcho 2. OpenViking 3. Mem0 4. Holographic 5. RetainDB 6. ByteRover 7. Other / custom
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Deeper dive into some of the updates in v0.7
Memory:
We have begun transitioning each of the systems in Hermes Agent to work through defined interfaces so that the core code is more maintainable, and more providers for everything can be supported.
We started with memory:
Now there is a plugin type that is for memory providers, pulled Honcho out of the core codebase, made it a plugin, and added 6 more systems that were waiting as PRs as new options.
Now you can access your favorite much easier, and if your favorite isn't built in, it is easy to create a new plugin that does!
Nous Research@NousResearch
Hermes Agent v0.7.0 is out now. Our headline update: Memory is now an extensible plugin system. Swap in any backend, or build your own. Built-in memory works out of the box; six third-party providers are ready to go. Pick one with 'hermes memory setup'. Full changelog below ↓
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There should be stricter regulatory laws against the predatory practice of cash out offer amounts by retail sportsbooks being well beneath market values.
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Let be honest do you care about a “fair” price? You work at a Sportsbook where you goal everyday is to take money from people lol…
Jeffrey Benson@JeffreyBenson12
@potatokmish @spshoot What do you think is a fair cashout price for the sportsbook to offer on this ticket?
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@cryptdean @sagar_builds @akshay_pachaar I am working on a use case for football. This use case has a lot of noise and K clustering with YOLO11, SAHI and BoT - sort. Camera angle not being consistent is a large variable
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Real-time object detection will never be the same.
Traditional YOLO needs NMS to remove duplicate boxes; it's slow and inconsistent.
YOLO26 skips it entirely: single-pass predictions, faster inference and up to 300 detections per image.
Download model: platform.ultralytics.com/ultralytics/yo…
Akshay 🚀@akshay_pachaar
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@zeeg We move fast but test carefully. How do I repro what you’re seeing — can you screenshot or /bug and DM the feedback id?
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I really like Claude Code, but folks have gotta get your shit together with reliability. It seems like every day there's a new bug. Slow down, flex less on the number of AI generated commits you land..
Todays: it keeps trying to read from the parent directory...
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What a team!!! Doesn’t get better than this.
Nick Baumgardner@nickbaumgardner
30 years ago this week (1995): Bob Hope's final College Football All-American Football Team
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@WillStoneCFB This is very cool. Would love to chat about tech stack and if you need help building!
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College fantasy football is the most underserved niche in fantasy sports.
The big sites won’t offer it (or even offer Devy!) and no new players are entering the market.
So I’m building BlueChip: the Future of College Fantasy Football.
playbluechip.com
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ilya retweetledi
Final: Weymouth 28-19
Wildcats beat Walpole for first time since 2018.
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