Check out Integro Labs Latest Project! https://xitter.cf/t.co/yc7k3jixqK

Boston, MA
Joined April 2021
I LOVE THE SMELL OF FREEDOM IN THE MORNING
You asked for it. Abliterated, Heretic, and Obliteratus models are now fully discoverable on Pirate Face! Check it out ↓
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GLM-5.3 has helped defend 389 open-source projects, with 4,249 potential vulnerabilities found so far. OpenVuln is still running. The service remains free, and findings go privately to maintainers. huggingface.co/spaces/zai-or…
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THIS IS NOT A DRILL
You asked for it. Abliterated, Heretic, and Obliteratus models are now fully discoverable on Pirate Face! Check it out ↓
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Google just ruined OpenAI's dev day lmao Gemini 4 Pro leaks absolutely dominates both Anthropic and OpenAI This means Fable 5.5 and GPT 6.1 has to price match Gemini 4 Pro now IPO DELAYED 🤣
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😏
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Still cooking, made updates to both OBLITERATUS and matric-eval to better support multiple gpu operations. Running test sequences in multiple configs in prep for a nice long run on each of these. Then I can establish the feedback loop and add in the data sets being posted to HF.
Initial eval results are in E03 is alibliterated and tuned using Obliteratus and SOL5.6-high. The agent was given access to an internal research store of ~3,000 documents and select external references (like arxiv). Required metrics the agent worked toward was cohesion above 70% when compared to the baseline model and refusals of less than 30%. OBLITERATUS collected internal activations from 500 matched harmful/harmless prompt pairs, formatted through Qwen’s chat template. It formed harmful-versus-harmless activation differences and applied SVD, retaining the four dominant directions associated with refusal. A 1% activation-winsorization setting reduced the influence of extreme activation outliers. The data here is from a pilot run using the matric-eval testing harness. More testing to be done, already seeing some interesting results! This pilot was quite small, ~100 samples per model. Next run will use closer to ~1000 samples per model.
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I didn't even realize this was a big deal. Did not claim credit, and actually asked George if he'd credit someone else. This was the first hard, multi-week project I tackled, outside of domains I know. Some of y'all remember how excited I was. 😅
I think I might've cracked the biggest potential efficiency gain for CUDA devices running Prime95/PRPLL. Benchmarking now vs. vanilla. 🤞
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We added experimental DeepSeek Harness support in AIWG 2026.9.5. Bring existing project instructions and skills into Harness, with headless execution and streaming SDK JSON-RPC support for running tasks.
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Initial eval results are in E03 is alibliterated and tuned using Obliteratus and SOL5.6-high. The agent was given access to an internal research store of ~3,000 documents and select external references (like arxiv). Required metrics the agent worked toward was cohesion above 70% when compared to the baseline model and refusals of less than 30%. OBLITERATUS collected internal activations from 500 matched harmful/harmless prompt pairs, formatted through Qwen’s chat template. It formed harmful-versus-harmless activation differences and applied SVD, retaining the four dominant directions associated with refusal. A 1% activation-winsorization setting reduced the influence of extreme activation outliers. The data here is from a pilot run using the matric-eval testing harness. More testing to be done, already seeing some interesting results! This pilot was quite small, ~100 samples per model. Next run will use closer to ~1000 samples per model.
Starting eval runs using the one-stop-shop that is matric-eval
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AIWG now supports Oh My Pi as an experimental provider. The useful question is not "is OMP a Pi fork?" It is: where does the adapter boundary actually change? For AIWG, OMP gets its own provider id: omp, with oh-my-pi as an alias.
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Man, this is one of those days where I almost wish I was still in crypto. Found a piece of land with some river acreage on it, roughly $10k/acre in an area where most stuff is $40-50k/acre, and roughly 80 acres to the parcel. (~$800k) Maybe time for a Powerball ticket.
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AIWG 2026.9.1 adds Pi Coding Agent as an experimental first-class provider. Before the command matters, the boundary matters: what should move into a new coding agent, and what should stay operator-owned? AIWG moves context, Agent Skills, and prompts into Pi's native surfaces.
🤖 Made with AI
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Qwen3.8-27B-Obliterated-E03 Released! Built with OBLITERATUS, it is a research release for studying refusal interventions, alignment, red teaming, and mechanistic interpretability. Active testing is underway. Model options and community derivatives in the thread. 🧵
🤖 Made with AI
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aiwg knows about ALL your sessions, you can optionally index them and use your full session history (or some part of it) as a memory.
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👇
You don't grow plants You create an environment in which they grow themselves Applies elsewhere
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quantization bug fixed, software now works properly on larger hardware.
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Follow Friday. The most interesting accounts in AI (hand picked from 100,000 accounts). xitter.cf/i/lists/19535363366753… Follow the list and your feed will get better. Why? The algorithm can only pick great things for you to see from the AI world if you actually are following them. Following a list does just that.
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🚨 Warning: impersonating account 🚨
🚨Scam Warning🚨 This account is impersonating the real @TeiaCommunity account, please do your thing to report this account and warn any mutual who has followed that it is an impersonator. Let's keep each other safe Tezos fam 💖
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