Longevity Hypothesis Challenge 👾 Goal: Test agent-augmented workflows to... accelerate the path from ideation → refinement → funding. > Prompt Aubrai to generate & refine longevity hypotheses on X > Hypotheses get timestamped on Base using Molecule Proof of Invention (PoI) > Top ideas get published on ResearchHub and funded with 100K $RSC from the Bio treasury Already 700+ hypotheses have been generated by Aubrai. Now, it's time to start turning the best ideas into real-world experiments to support or refute them. Learn more:show more

💬 We get asked What advantages do AI-based tools... bring to trading? ❕ Answer from a GT App Top Trader: They help reduce manual work and make trading decisions more structured. Instead of guessing, you start with ready setups and test them faster. 🔸 Faster analysis Less time goes into switching between charts, indicators, and timeframes. AI-generated strategies give you a ready starting point that you can immediately test and evaluate. 🔸 Structured approach Instead of searching for ideas, you work with complete strategy setups. You can backtest them, review performance, and understand how they behave before going live. 🔸 What I do I use the GT AI Trading Agent to generate strategy ideas and test them quickly. It helps me move from an idea to a validated setup without wasting time on manual trial and error. Want to try AI Trading yourself?show more

Today we're dropping the "beta" tag from Adaptyv, launching... our new website and announcing our $8M seed round. When we started Adaptyv a few years ago, our core belief was: AI models for biology are only as good as the experimental data they're trained on and the hypotheses they can test in the real world. Now, after a year of working with many great partners, we’ve scaled our infrastructure to the point that we're now open to anyone who wants to use our platform! Overall, this year, over 30 companies started using Adaptyv to validate their protein designs - from some of the biggest pharmas to frontier AI labs to many, many techbio startups. We've run hundreds of experiments, tested well over 10,000 proteins this year and are generating the data that validates the best AI models currently in development.show more

Been a year of building Base in India: -... FBI is now the largest builder collectives not just on Base but on Ethereum - the FBI fellowships have inspired creator x builder combos in all builder programs - Virtual events Base India - Base cafe now hosts 10+ events - 180+ dapps by Indian builders and founders being built on Base - noice went from being a base hackathon project to being listed on coinbase in 100 days - team is expanding and now we’re a proper squad 💙 - more and more young Indian builders experimenting with Internet capital markets - 95% Indian projects on Base or adding Base support And yet. We’ve been infamous for not doing meet-ups. No college tours. No city meet-ups. I think it’s time to finally do a meetup. Should we do one?show more

✨ I revived my first AI startup from 6... years ago with Claude Code [ 💡 ] Back then it used GPT-3 (this was 2 years before ChatGPT existed!) to generate new startup ideas which then people can vote on And the best startup ideas rise to the top! Back then I made it because people complained they didn't have any ideas to build a startup This week I moved it to its own VPS and installed Claude Code and told it to fix everything, the DB had become big and there was stupid write operations on every page load that it made it very slow Claude Code is excellent at fixing all those small bugs from old projects and quickly fixing them As Garry Tan says "boil the oceans" as in before I'd not have the time to fix these kinds of projects, it wouldn't be worth it, I mean IdeasAI doesn't even make money, but now it takes me an hour to do this and it works again! I also upgraded GPT-3 to xAI's Grok 4.2 for new startup ideasshow more

Boom! Grok Tasks Make It One Of The Most... POWERFUL Real-Time AI Systems In The World. — My How to Use Grok Tasks With Hidden Tools For Powerful Daily Output. Grok Tasks are customizable AI workflows that integrate a variety of tools to streamline daily activities, from research and analysis to creative planning and problem-solving. I have been using them for quite sometime and because of the vital heartbeat of news and first person data on X, it is the most powerful AI platform available. By combining Tasks with tools like web searches, X platform interactions, code execution, and media viewers, you can build efficient, automated processes. These tasks work by prompting Grok with a clear description of what you want to achieve, and Grok will intelligently call the necessary tools in sequence or parallel to deliver results. Here's a step-by-step guide to creating and using Grok Tasks: Step 1: Define Your Task Start by clearly outlining the daily activity or goal. Consider what inputs you have (e.g., a URL, a query, or an attachment) and what output you need (e.g., a summary, calculation, or visual analysis). Break it down into subtasks to identify tool needs. For example, if your task involves researching current events, note that you'll need search and browsing capabilities. Step 2: Review Available Tools Familiarize yourself with the tools Grok can access. Here's a quick overview: - Code Execution: Run Python code for calculations, data processing, or simulations using libraries like numpy, pandas, or sympy. - Browse Page: Fetch and summarize content from any website URL with custom instructions. - Web Search: Perform general internet searches, returning results with optional operators like site:. - Web Search With Snippets: Get quick, detailed excerpts from search results for fact-checking. - X Keyword Search: Advanced search for X posts using operators like from:, since:, or filter:. - X Semantic Search: Find semantically related X posts based on a query, with filters for dates or users. - X User Search: Locate X users by name or handle. - X Thread Fetch: Retrieve a full X post thread, including context like replies and parents. - View Image: Analyze an image from a URL or conversation ID. - View X Video: Extract frames and subtitles from an X-hosted video. - Search PDF Attachment: Query a PDF file for relevant pages using keyword or regex modes. - Browse PDF Attachment: View specific pages of a PDF with text and screenshots. Select tools that align with your task. Aim for a mix to handle data gathering, processing, and visualization. Step 3: Craft Your Prompt Write a detailed prompt to Grok describing the task. Include: - The overall goal. - Specific steps or subtasks. - References to tools if you want to guide the process (e.g., "Use web_search to find sources, then code_execution to analyze data"). - Any constraints, like dates or limits. Example prompt: "Create a Grok Task for my morning routine: Search recent X posts about tech news using x_keyword_search, fetch a key thread with x_thread_fetch, and summarize with browse_page on linked articles." Step 4: Submit and Interact Send your prompt to Grok. It will process the task by calling tools as needed, often in parallel for efficiency. Review the output and refine with follow-up prompts if required (e.g., "Expand on that using view_image for visuals"). Iterate to fine-tune the workflow for reuse. Step 5: Save and Reuse Once refined, note the prompt as a template for future use. You can adapt it for similar tasks, making Grok Tasks a habitual part of your day. Finding Grok Tasks To discover existing Grok Tasks or inspiration for new ones, use X searches with tools like x_keyword_search or x_semantic_search (e.g., query: "Grok Tasks examples" with mode: Latest). Browse community-shared threads via x_thread_fetch, or web_search for tutorials on xAI features. Prompt Grok directly: "Show me popular Grok Tasks for productivity." 1 of 3show more

teleoperator kicking himself over not programming Asimov's Laws of... Robotics... Worth considering if we should base today's reality on the science fiction musings from the past. Testing with humanoid robots is a very interesting new challenge. Historically robots have been confined to keep out zones with rigid walls and laser barriers, lock-out/tag-out, etc. This is the easy way to ensure people don't get hurt by very capable machines. But the more we integrate humanoid robotics into collaborative roles with humans the more we need to remove those barriers by nature of the work.show more

I tested my V02 max for the first time... today: 🫀 57.4 ml/kg/min According to ChatGPT, that's the top 5–10% of men my age. The test was done in a lab using the Bruce protocol. Every 3 minutes, treadmill speed and incline increase: - stage 1: 4 km/h at 10% grade - stage 2: 5.5km/h at 12% - stage 3: 6.7 km/h at 14% - etc etc I passed out at the end of stage 5. It's just a horrible test because you're fighting inner demons to get a little farther. V02 max is a key biomarker in predicting longevity, so from now on, I'll focus my training on increasing that number.show more

We are at NeurIPS Conference for our 4th #MyoChallenge... and 7th #MyoSymposium! What started as a discussion with Vittorio Caggiano is a global community now MyoSuite 💪 In 2022, we started with two key hypotheses - 1⃣𝑺𝒄𝒂𝒍𝒊𝒏𝒈 𝑯𝒚𝒑𝒐𝒕𝒉𝒆𝒔𝒊𝒔: can we scale data driven learnings to achieve human level motor control? 2⃣𝑬𝒎𝒃𝒐𝒅𝒊𝒎𝒆𝒏𝒕 𝑯𝒚𝒑𝒐𝒕𝒉𝒆𝒔𝒊𝒔: Akin to Neurons's inspiration behind NN, are there embodied priors that will form the critical substrate to get to human performance? After 3 years, both these hypotheses are running strong. But in different ways than we anticipated -scaling hypothesis predicted vanilla RL algorithms (developed over OpenAI Gym and robotics tasks) will scale & realize human level motor control. RL did scale with better simulation & compute infrastructure but the curse of dimensionality became the limiter for high dimensional MSK systems. This is where our 2nd Embodiment Hypothesis kicked in. Spatial as well as morphological embodied priors facilitated development of next generation of algorithms at the intersection of representation and reinforcement learning - (DepRL from Pierre Schumacher et al, MyoDex & SAR from Cameron Vittorio Caggiano et al, Kinesis from Alberto Chiappa, muscleVAE from Yusen et al, etc) Current #MyoChallenge result evaluations phase was humbling realization - what started with a team of two evolved as a global community, the entry barriers has been lowered enough for even high school students, and underrepresented groups with limited resources to participate. It's incredible to realize the progress we have seen in 3 years. All the same time idiosyncrasies of the behaviors leave us quite unsatisfied and wanting more. Ahead of us there are exciting challenges on all frontiers -- embodiment, proprioceptive+exteroceptive sensing and control, validation -- presenting large real world potentials in health, wellness, sports, robotics. While there is a lot for us to be proud of, open challenges in understanding, as well as emulating human level motor intelligence remains. Join MyoSuite team for the awaited #MyoSymposium in discussing these frontiers on Saturday, Dec. 6th from 8-11 am: Ballroom 6D.show more

2023 was the year of AI avatars 2024 was... the year of AI photos 2025 was the year of AI videos And I think it's becoming clear now that 2026 will be the year of AI world models Fully interactive explorable 3d worlds generated from one or multiple 2d images or a prompt In turn these 2d images can then be generated by AI too So soon you can generate fully explorable virtual 3d worlds based on your own imagination Next will be figuring out how to make those worlds interactive This is World Labs (unaffiliated, but I like it) As always a lot of big AI model companies are now working on the same thing: 3d world models, only World Labs has a real properly working demo (for now) Very exciting time again!show more

I just built my own wiki generator plugin for... my agents. My agents can now generate wikis for anything I ask. One of my favorite wikis is called PaperWiki. This is a great example of what Andrej Karpathy describes. It uses obsidian vaults to organize papers, retrieve LLM-generated summaries, diagrams, and other advanced views for paper exploration. When Obsidian UI is not enough, I use my own artifact generator inside my agent orchestrator (see clip for example). This allows my agents to build any kind of view or exploration feature that I need. The papers are all curated with automations and several rules/patterns I have manually built over the years. On the surface, this looks basic. But behind the scenes, there are advanced search capabilities, connections, metadata, derived data, and other interesting bits of information that are extremely useful for my research agents. This is mostly built for agents. The artifact preview is just a high-level way to validate and quickly assess the quality of the wiki, suggest improvements, and it's also great for research. I use tobi lutke's qmd for all search capabilities. Everything is markdown. The summaries and even the diagrams. The wiki updates on its own based on several automations I have optimized over the past couple of weeks. The wiki grows and self-improves based on several requirements important for my research use cases. This is as personalized as it gets. There is nothing like it out there. And I use my research expertise to continue improving it over time. This is a vanilla wiki. There are so many things I want to build on top of this. Different aggregations, views, artifacts, etc. All to help automate more of my research work and accelerate productivity. I think the biggest leverage here is how powerful this could be for discovery and experimentation. One of my goals is to use it to find deeper connections and insights that would otherwise elude the top human researchers and use those to generate interesting new hypotheses and research experiments. That way, my agents can use autoresearch to explore research ideas at the frontier. Stay tuned for more.show more

Regardless of what you think of Don Lemon and... the whole ordeal with Elon Musk, I think this line from him should resonate with everyone. "Twitter or X is one of the biggest information platforms in the world. Why cede that platform to extremists? So I wanted to get on there and I wanted to fight it out so that everyone had a voice." Those on the left who stopped using X because they were angry that people on the right were saying things that they don't like, are playing into the hands of the people they disagree with. Instead these people should increase their usage of X in order to combat the narratives they dislike. That's how successful societies function. And just like I would welcome Trump back on X, those on the right should embrace people like Lemon because it's so much better to have a melting pot of flavor rather than a boring pot of white rice. Societies succeed when conflicting views are heard rather than pushed to the corner. Echo chambers only further extremism.show more

A Closer Look at Alchemist AI v3.5🔎 In v1,... one agent handled everything. You’d enter a prompt like “make a snake game” and get a single block of code—one input, one output. v2 introduced multiple agents with specialized roles: prompt refinement, frontend, backend, and review. It brought more structure, but the process was still linear. Each step produced a single output. With v3, a single agent could handle multiple tasks. It generated HTML, CSS, JavaScript, searched for assets, and more—all in one go, while maintaining full context. Now in v3.5, we combine both models. Multiple agents work in parallel, each capable of producing multiple outputs at once. The prompt compiler adapts based on what you're building. A 3D game? It prioritizes game engines, rendering, and mechanics. A website or 2D app? It shifts focus to relevant frameworks and tools. The tool handler can call several services simultaneously, feeding context-aware data into the code generator for real-time execution. From single-output generation to parallel, adaptive workflows. In the next breakdown, we’ll dive into the architecture behind our proprietary engine in v3.5.show more

Dynamic workflows are a generalization of harnesses, automations, loops,... routing, and graphs. It's the most powerful feature I have built into my agent orchestrator. Supports all kinds of patterns that leverage different agent backends (claude, codex, pi, hermes,...). It's a meta-harness approach that unlocks new forms of test-time compute. Example of use cases it supports: > LLM councils to get different perspectives from LLMs or plan more intensively > Dynamically routing tasks to different agents based on needs (e.g., cost efficiency and optimal intelligence) > Advisor/Judge + executor workflows and pretty much any complex graph-based pattern required by the task. I find it especially useful for long-running work and code reviewing. > Agent teams that talk to each other if needed for the task. I like to use this for AI editing, artifact creation, and other creative tasks. And I am sure it supports so many things that I haven't discovered yet. I got inspired by the dynamic workflow feature released by the Claude Code team. I had actually built it earlier this year but wanted to generalize it across different agent backends. I think this is going to become more popular in the coming days. I will share more of my findings soon.show more

Sharing my new skill! It keeps track of high-signal... X accounts for top AI news, papers, projects, etc. Total gamechanger for me. Built with X MCP tools. Give your agent the skill and tell it to generate the artifact with top stories. Works for Codex, Claude, Hermes, OpenClaw, or whatever you use. 3 steps: 1. Set up X MCP - X API: 2. Install skill here: 3. Run prompt: "Use the x-agent-intelligence skill to build a self-contained local feed from my X MCP connection; ask for my source handles if needed, save feed.html, and validate it." It should generate a nice, beautiful HTML artifact like the one shown in the clip. You can tune it however you want. You can then set a schedule/automation to do this daily or whatever cadence you prefer. I have it every 4 hours. You will need to curate the X accounts yourself, but I have shared a few good ones under the assets. You can ask your agent to tune it to however you like. I have also shared my personal feed with our community here: I understand if it gets tricky to set up. Please reach out to me in the community forum. I plan to do a little tutorial or live session soon to help others reproduce the process. You can also store the feed as a wiki, as I have in my own implementation, but that's optional. If you encounter any issues or have ideas on how to improve it, please open a PR.show more

Another wild week for open science. New breakthroughs, new... funding, and new experiments — here’s what’s shaping the DeSci landscape right now. 1/ Pump Science and Eterna Labs wrapped up Season 2 Fly Racing, where RAP (Rapamycin) topped the charts with +38% speed and +21% distance. The longevity arms race continues as fly data translates closer to human health insights. 2/ @vitadao launched the Longevity Hypothesis Challenge, giving researchers the chance to co-develop new aging theories with Aubrai and earn up to $100K in funding. A 20K BIO referral bounty awaits those who bring in selected researchers. 3/ Galeon shared a big Atlantis update, featuring daily XP streaks, Quickflip quests, and referral rewards for explorers. The blockchain bridge is still in progress, but the journey through digital healthcare continues strong. 4/ Bio Protocol revealed Bio Launchpad Season 2, bringing upgraded BioXP mechanics, and new staking incentives. It’s evolving into a full permissionless launchpad for decentralized biotech innovation. 5/ BitDoctor.ai announced its first Contributor Mining Airdrop, rewarding early participants shaping AI healthcare. With just days to go, users are urged to bind their wallets and join the DeSci x DePIN medical revolution. 6/ LIFE AI hit a major milestone after being selected for the FastTrack AI Accelerator – Cohort 1, powered by GenAI Fund and accelerated by NVIDIA. Out of 300+ global applicants, only six startups made the cut—LIFE AI is one of them. 7/ Cerebrum DAO 🧠 unveiled Cerebrum Cortex, a new app connecting brain data, research funding, and personalized health tracking. Launching in Q4 2025, it will anchor the NEURON ecosystem for open brain science. 8/ OriginTrail announced the Global Hackathon: Scaling Trust in the Age of AI, offering $30K in prizes from Nov 3–21. Developers will build blockchain-based knowledge graphs to fight misinformation and deepfakes. 9/ Quantum Biology DAO opened registration for its Quantum Biology Hackathon, exploring how quantum effects like superposition and entanglement shape life itself. It’s where physics meets biology in real-time discovery. 10/ Curetopia $CURES 🪼🌳 uncovered a fascinating discovery in their ARS drug screens, revealing how mitochondrial and cytoplasmic gene mutations respond differently to drugs. The finding opens new questions on cell-based drug sensitivity in rare diseases. 11/ CUDIS announced its first batch of local KR partners, teaming up with top gyms and wellness brands across Korea. Together, they’re promoting sustainable urban health and redefining how fitness meets biotech. Biotech, AI, longevity, quantum, and wellness—all converging under the banner of open science.show more

I built a content engine that runs on telegram.... Two commands... /discover: sends out to 9 sources across HackerNews, Reddit communities covering AI automation, prompt engineering, vibe coding, and specialist newsletters. Pulls everything published in the last 24 hours, runs each item through an AI extraction layer that scores it against 100+ niche keywords, deduplicates, and drops the relevant ideas into a Notion database. Takes about 90 seconds. Costs fractions of a cent. /ideas: this command pulls the top scored ideas from that database, randomizes the selection so you're not seeing the same ones every time, and sends them to you in a clean numbered list. You reply with /write 3 or whatever you choose, and the system researches the topic using Perplexity's live web search, generates three distinct outline options with different angles and hooks, saves them to a Google Doc, and sends you a message telling you they're ready. You read the outlines, and you pick one. You then reply with the command /outline 2. The system writes the full piece in your voice, following your brand guidelines, with specific examples and concrete claims. It can be done in under two minutes of your time. The whole thing runs on n8n, with no subscriptions beyond what you already use. If content takes too long or you don't have ideas, this solves that. I built this for myself; I can do it for you. If you're tired of knowing you should be posting and still not doing it, let's talk.show more

🚨 AI AGENTS COULD ALREADY USE COMPUTERS. NOW THEY... HAVE THEIR OWN PHONE It’s called PhoneUse, and it launches today. You give your agent a cloud phone, a real Android or iPhone, tell it what to do, and it uses the phone just like you would. First came computer-use. Then browser-use. Now there’s phone-use. What it can do: → Order an Uber and text you updates along the way → Research trends on TikTok → Get around old apps with no API, like insurance apps → Complete two-factor verification → Read your notifications and act on its own: if your flight is delayed, it messages you And here’s the big part: most mobile apps have no API and no MCP. Until now, agents couldn’t get into them. With a phone, they can. It connects through MCP or an API, so you can use it from the agent you already have. The world still runs on mobile. Now your agent does too. Save this before you forget 🔖 Link in the comments 👇show more