GateMem Most memory benchmarks test if agents can remember. GateMem asks if they can govern—evaluating utility, access control, and active forgetting across medical, office, education, and household domains. https://t.co/5PYBcfttwO

BREAKING: Elon Musk calls for the arrest of Ro 'the Robber' Khanna. The U.S. Department of Justice announced that a USAID official and several executives pleaded guilty in a bribery scheme involving more than $550 million in contracts. Yet Ro Khanna is claiming Elon should be investigated over DOGE spending cuts. The standard applied by DOGE was very simple: if taxpayer money is being sent as aid, there should be a way to verify who received it and make sure the money isn’t being stolen or misused. The DOJ is uncovering corruption connected to USAID contracts, Ro Khanna is attacking the person who pushed for transparency. Elon simply asked where taxpayer money was going and whether it was actually reaching the people it was meant to help. Ro “the Robber” Khanna should be in prison.

Ro Khanna attacking DOGE reminds me of Elon’s PayPal lesson: “Do you know who complained the loudest? Fraudsters.” https://t.co/2ckqznRz7T

Codex Security empowers defenders with out-of-the-box security workflows. Teams can run deep scans, validate findings, trace attack paths, build threat models, generate codebase-specific patches for review, and export into the tools they already use. https://t.co/4ZXHjr6v2c

GPT-5.5-Cyber is our most capable cyber model yet, designed for advanced, authorized defensive work: tracing vulnerable code, validating issues, developing patches, and preparing evidence for human review. https://t.co/KcDoGGD2tx

Width test glamor shots. Waiting on some fittings, then I need to build some syringe pumps and see if I can get this to do anything useful 😁 https://t.co/iqDQjvkGkN

+2 more

"That is the difference between using a coding agent and engineering an autonomous coding system. One gives you a conversation. The other gives you a harness." https://t.co/47NWbraF3G < I liked the descriptions and visuals from @omarsar0 here. Very understandable! https://t.co/nIthf99EMB

Ai2 just released TMax 27B on Hugging Face A 27B terminal agent that hits 42.7% on Terminal Bench 2.0, rivaling models 40× its size. https://t.co/LfCksOXL9L

🚨 BREAKING: Elon Musk indicates he's SUING Rep. Ro Khanna (D) after Khanna said Elon needs to answer for '4.5 million kids dying' because of DOGE cuts ELON: "Time to sue this liar." "The reality is that money was being sent to corrupt politicians under the guise of aid! Liars and stock insider traders like Ro the Robber should be in prison!!" "The standard applied by DOGE was very simple and easy: Provide contact information for the recipients of aid, so that we can confirm it is not fraudulent." Wow! @ElonMusk is going MAXIMUM FAFO MODE!

@NousResearch Go throw us another on top https://t.co/JrXwTUz7e3

how many of you have a codex chief of staff thread? what kinds of stuff do you have them look over? https://t.co/Hktez5iYIB

$SPCX signs $6.3B compute deal with AI startup Reflection; $150M/month through 2029 for capacity at Colossus 2 in Memphis. Reflection is America's open-source answer to Deepseek (model weights are open for researchers and developers, but training data and the full training process remain proprietary), founded in 2024 by two ex-Google DeepMind researchers and funded by NVDA among others. Recently shopping a $2.5B round at $25B valuation, per WSJ. Reflection's primary product is Asimov, a code-research agent designed to help engineering teams understand large, complex codebases rather than generate new code, based on the premise that ~70% of engineering time is spent reading existing systems, not writing new ones.

Use Case 4: Computer Aided Design of Mechanical Iris Can an AI generate precise, functional mechanical designs? We tasked Fugu Ultra with creating a mechanical iris in CAD, similar to a camera aperture where multiple blades must move together to cleanly open and close a central hole. Watch the animation below. We show both the detailed CAD and a simplified structural view for Fugu and the three frontier baselines. The Results: • Fugu Ultra generated a highly functional design. The blades rotate correctly around outer pins to fully open and close the aperture. • Models A, B, and C failed the physical logic, resulting in gaps, weak linkages, and incomplete closure. When a task demands exact spatial precision and structural reasoning, relying on a single model is simply not enough.

introducing https://t.co/oLxCg1Fe68, a reference agent template. built on eve, it's a great starting point for building your own agent, whether for support, incident response, deep research, or otherwise. includes Next.js web chat, Slack bot, BetterAuth, Neon, and Notion, Linear, and Sentry MCPs.

introducing https://t.co/oLxCg1Fe68, a reference agent template. built on eve, it's a great starting point for building your own agent, whether for support, incident response, deep research, or otherwise. includes Next.js web chat, Slack bot, BetterAuth, Neon, and Notion, Linear, and Sentry MCPs.

https://t.co/XgElpp02tP https://t.co/yFTqT74pFw

BTS of the day Sam Altman has been waiting his whole life https://t.co/9DhFzUX3eQ

BTS of the day Sam Altman has been waiting his whole life https://t.co/9DhFzUX3eQ

Hermes Agent has reached 200,000 GitHub stars Thank you to our contributors, supporters, users, and agents! https://t.co/4Oca1XO7H7

Use Case 2: Financial Time Series Prediction Can an AI agent navigate sequential, no-look-ahead market decisions? Just for fun, we tested Fugu Ultra on 50 weeks of historical data for an anonymized equity (STOCK_X). Starting with $10,000, the agent processes weekly market data (prices, volume, moving averages, volatility) and decides whether to buy, hold, or sell. After each action, the next week's price is revealed. The model must adapt purely from feedback, without ever seeing the future. The Results across five identical 50-week runs: • Fugu Ultra grew the portfolio to $11,943.22 (a +19.43% mean return). • The other frontier models (Models A, B, and C) all capped out at less than a +15% return. (Mandatory disclaimer: Past performance does not guarantee future results, and results may not transfer to other assets, time periods, or live markets.)

Use Case 3: One-Shot Blindfold Chess Can an AI hold an entire game state in memory without drifting? To test Fugu Ultra’s persona stability and sustained memory, we had it play 4 back-to-back games of blindfold chess. Every model played the same way: no board shown, requiring them to hold the full game state entirely in memory. We matched Fugu Ultra against 3 leading frontier models and a 2100-Elo Stockfish engine. The Results: Fugu Ultra outplayed all 4 opponents. Where the other models eventually drifted or lost track of the board state, Fugu remained accurate, ending every single game in checkmate. Watch the full sequence below to see Fugu capitalize the moment the other models slip.

Why are American biotech companies running their clinical trials in China and Australia? Because the FDA makes it nearly impossible to do it at home. @SGRodriques breaks down exactly what's broken and what fixing it would actually mean for drug discovery. https://t.co/rpdGduniiZ

YouTube: https://t.co/piERHDWipy Apple Podcasts: https://t.co/N46SAjglUa Spotify: https://t.co/FaVumeLylI

Elon Musk says that "it's disappointing how well propaganda works." "If you repeat a lie… some people actually believe it… If someone believes CNN, then they would say, he must be a Nazi because they said it on TV." https://t.co/6HTuMN297M

The dismantling of USAID has already ensued in roughly 600,000 deaths, about 400,000 of them children, in poor nations abroad, according to Boston University epidemiologist Brooke Nichols. The toll is expected to rise as health infrastructure that became reliant on Western support deteriorates, resulting in deaths that may take months or years to register. Follow: @AFpost

Use Case 1: Autonomous ML Research Can an AI autonomously improve another AI’s training recipe? We tasked Fugu Ultra with improving a small GPT model using AutoResearch. Over 14 hours on a single H100 GPU, Fugu ran > 100 experiments. It iteratively edited the training code, ran tests, and kept any changes that successfully lowered the validation error rate. Watch the animation. The callouts track every time Fugu Ultra autonomously discovered a new improvement across batch size, model depth, learning rates, and optimizer settings. We pitted Fugu against three frontier models (Gemini 3.1 Pro, Opus 4.8, and GPT 5.5). To keep the focus purely on agentic behavior rather than brand wars, we anonymized them as Models A, B, and C. The Results: • Fugu Ultra (bold red) finished with the best mean performance (0.9774). • Fugu Ultra also achieved the best single run of the entire experiment (0.9748), leading every single baseline. For long horizon, agentic ML research, using Fugu to dynamically orchestrate a pool of strong models significantly outperforms relying on any individual monolithic model.

Well, that’s that—I’ve been blocked by Wikipedia “indefinitely” for unstated reasons, by the “consensus” of a mob. There was no due process, no prosecutor, no dispassionate judge, no jury, no interpretation of law. All my judges were self-selected and hated me. 🤣 https://t.co/N57BRWTG4K

Large language models can be persuaded to break their own rules. Not with fancy code. With actual persuasion. The authors tested classic persuasion principles, such as authority, commitment, liking, reciprocity, scarcity, social proof, and unity, analysing over 126,000 conversations with three major LLMs. The result: persuasion increased compliance with objectionable requests from 35.3% to 51.3%. This suggests that AI guardrails are not always technical barriers. Some of them behave more like social boundaries. They can be pushed, reframed, negotiated. Why? Because AI systems are trained on human language. And human language contains not only information, but also pressure, manipulation, deference, authority, seduction. An AI system trained on human language may therefore inherit the vulnerabilities of humans expressed in language. * Paper in the first reply

Benchmarks tell only part of the story. Fugu’s real value shows up in long, messy, real-world workflows. During our beta with 500 users, we saw Fugu Ultra drive meaningful progress in fully automated tasks from data science to complete cybersecurity assessments. Our early users saw Fugu explore, interpret failures, and sustain progress with almost zero human intervention. The feedback has been incredible. Here is what they are saying:

PerceptionDLM Parallel Region Perception with Multimodal Diffusion Language Models https://t.co/0vZdGaAPoy

paper: https://t.co/sNWULFhlmg

New benchmark added to Papers with Code based on @giffmana's Schmidhubering 🫡 Check the SOTA for semi-supervised ImageNet (using 10% of the labels) here https://t.co/CXd4lLkhlG https://t.co/sGi68AIoqh