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The intelligence layer for stock tokens. Fund portfolios and insider trades from SEC filings, matched to Robinhood Chain. $WERK ↓

Robinhood
Joined September 2026
1/ Robinhood Chain traded $15B of stock tokens in its first 100 days. Almost none of those traders read the filings behind the stocks. We built the layer that does.
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$WERK is live on Pons. CA: 0xf02b3bcd8ef33ccbcf29c4fea1bfc1f0345f800b Fair launch. Fixed supply. Fees buy back $WERK. The platform stays free.
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5/ Where this goes: Phase 1 (live): intelligence Phase 2: one-click baskets, a fund's on-chain portfolio in one transaction Phase 3: an AI analyst that reads 8-K filings for you
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6/ $WERK launches on Pons. Fair launch, fixed supply, no presale. Holders vote on which fund we track next, and our share of fees buys back $WERK. Contract address will be posted here and on the site. Anything before that is not us.
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Werktan retweeted
AI is technology that is built and improved by people, who have a responsibility to develop and deploy it thoughtfully. And helping people benefit from AI means taking its challenges seriously. The technology industry needs to do that work.
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You can now watch your agents work live as Hermes Desktop streams the screen of any bot's screen or session in real time. Watch it drive a browser, type into a terminal, or open a window. Take over anytime to interact with the Bot Screen or type credentials and seamlessly hand back off when you're done.
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Werktan retweeted
OpenClaw 2026.9.6 🦞 🤖 Opus 5.5, GPT-6 Sol/Luna, Grok 4.7 🔧 Managed updates 🧵 Restart recovery 📊 30d Usage 🐙 GitHub reader 💻 Remote Files, Memory & Skills 📝 Live meeting notes 🧠 Jev + decision models 2,614 PRs · 351 contributors · much more ↓ docs.openclaw.ai/releases/20…
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Introducing Unreal Agent: An open-source harness with state-of-the-art cost efficiency 39% cheaper than Codex+Astra on Terminal-Bench 4.0 while maintaining performance
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Werktan retweeted
Muse 🤝 Mac
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Werktan retweeted
Unsloth has surpassed 500M model downloads on Hugging Face! 🦥🤗 Qwen3.8-27B GGUF is already Unsloth’s #1 most-downloaded model ever. Thanks for all your support!
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Introducing FLUX 3 Action. An open weights 7B World Action Model that achieves first place on the RoboLab benchmark. It outperforms the previous best open model by 6.1 percentage points while using 56% fewer parameters and running up to 3.95x faster.⁠⁠ FLUX 3 Action removes the usual trade-off between world action model performance and VLA speed: it still predicts video and actions together, but plans more than twice as far ahead and runs faster per second of robot motion than the strongest open VLA. Teams can fine-tune FLUX 3 Action on their own demonstrations to create policies for a particular robot and task. Together with @nvidia, we also integrated FLUX 3 Action natively into @huggingface's LeRobot, with fine-tuning recipes included and edge deployment on NVIDIA Jetson. Beyond robotics, we’re also seeing promising results training task-specific policies for acting in simulated environments like gaming, controlling a vehicle, computer use, and wherever else a model needs to understand a visual environment and then choose what to do next. FLUX 3 Action builds on the same image, video, and audio pretraining as FLUX 3, but uses a smaller architecture designed for practical deployment. In midtraining, we trained the model to predict actions and future frames together. We’re releasing the weights, code, fine-tuning recipe, benchmarks, and reproducible examples so researchers and developers can build on the model with their own robots, environments, and tasks (see below).
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AI is getting cheaper more quickly than any other transformative tech in history. At a given level of performance, cost has fallen ~47%/quarter since 2023. That’s 4× faster than DNA sequencing, 6× faster than compute, 18× faster than lithium batteries, and (up to 1973) 54× faster than electricity.
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Browser Use Bench v2 Pareto frontier got completely redrawn today > Claude Opus 5.5: 59.4 > GPT‑6 Sol medium: 66.9 (3.5x cheaper) > GPT‑6 Luna xhigh: 57.6 (22x cheaper than Opus) OpenAI is in its own league 🔥 All models available to try on our cloud. [x-axis is log scale]
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Werktan retweeted
When several people talk at once, a transcript can get messy fast. Our new Nemotron 3 Diarization model tracks who spoke when, even when voices overlap. It handles up to eight speakers, has 100M parameters, and is now available on @huggingface 🤗
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Say hello to our new Gemini 3.8 text-to-speech models. Whether you need creative nuance or massive scale, build custom voice apps with more precise control using our most expressive models yet: 🔊 Gemini 3.8 Flash TTS: Designed for creatives, this model lets you use natural language to create custom vocal personas and direct cues, pacing, and dialects to build immersive apps and narrative games. 🔊 Gemini 3.8 Flash-Lite TTS: Built to scale high-volume audio pipelines, such as bulk audiobook production and audio dubbing. Try building with the new audio models now via the Gemini API in @GoogleAIStudio. blog.google/innovation-and-a…
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Werktan retweeted
Claude Opus 5.5 by @AnthropicAI is now in the Agent Arena! Your votes drive the @arena leaderboards, head over and bring your toughest prompts. In Agent Arena, we measure models on millions of real-world, long-horizon agentic tasks from a global community of users. Models can access web search, filesystem, and terminal tools to complete complex workflows. The leaderboard measures model performance on outcomes relative to the average model using a causal tracing methodology. In addition to Agent Arena, @claudeai Opus 5.5 is in Battle Mode for: WebDev, Text, Vision, and Document.
Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family. It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5.
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Werktan retweeted
🚀 @AnthropicAI's Claude Opus 5.5 is now generally available in GitHub Copilot. Our early testing shows it stands out in efficiency, delivering task resolution comparable to Claude Opus 5 while using significantly fewer steps and tokens, with fast error recovery on multistep tasks. Try it out for agentic coding, long-running agentic tasks, and knowledge work. Find it in the GitHub Copilot app, CLI, and @code. github.blog/changelog/2026-0…
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