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

Introducing 🏆 SOTA badges on https://t.co/tOqTY2ZA6h Now you can clearly see which benchmarks a paper gets #1 or #2 on, from LLMs to robotics and computer vision Congrats @Zai_org on reaching #1 across multiple benchmarks with an MIT-licensed model! https://t.co/4t0q2yGEIw

Introducing 🏆 SOTA badges on https://t.co/tOqTY2ZA6h Now you can clearly see which benchmarks a paper gets #1 or #2 on, from LLMs to robotics and computer vision Congrats @Zai_org on reaching #1 across multiple benchmarks with an MIT-licensed model! https://t.co/4t0q2yGEIw

Simple science https://t.co/2UxPBafbj6

Proud to represent @cerebras in Singapore We'll be partnering with communities, builders, and spaces to give the world's fastest inference the spotlight it deserves. @curve_labs also uses Cerebras to provide builders with personality tooling that powers human-like agents 🤝 https://t.co/vy0TueNhIh

The Media and Left worked together to create the “white supremacy” narrative. They had to create the lie. They had to create the hate. They had to create the division. It all started after 2010. Why?! The Legacy Media is the Enemy of the People. https://t.co/zn98U2YUOJ

Great report on LLM agent communication protocols. Communication is a huge bottleneck in multi-agent systems. (worth bookmarking) The report builds a five-dimensional taxonomy (counterparty, payload, interaction state, discovery mechanism, schema flexibility) across nine actively maintained open-source agent protocols, so it maps the real MCP and A2A landscape. Two patterns stand out. Every agent-to-agent protocol sampled pairs of hybrid payloads with session-state persistence, and decentralized discovery is still rare. So the field is quietly standardizing on stateful sessions while leaving discovery and policy enforcement open. Why does it matter? If you are choosing a communication layer this year, this discusses what nine real protocols actually do. Paper: https://t.co/o3Q3kObTtp Learn to build effective AI agents in our academy: https://t.co/1e8RZKrwFp

BREAKING: SpaceX just received an investment-grade credit rating from Fitch for its new bond offering. • Fitch gave SpaceX a BBB+ rating, which means its debt is seen as reasonably safe for big investors. • All three major rating agencies now rate SpaceX as investment grade: Moody’s, Fitch and S&P. • SpaceX reported over $100 billion in cash and cash equivalents after its record IPO • Fitch cited SpaceX’s dominant launch business, fast-growing Starlink network and expanding AI compute operations as major strengths • SpaceX has delivered more than 80% of the world’s mass sent to orbit since 2023 This is a major vote of confidence in SpaceX’s long-term business.

Neuralink now has its 26th recipient Sgt. Lee Marten, @Canuckula, is a Vancouver Police Sergeant, cyclist, and ALS patient who became the first Canadian to receive the N1 brain-computer interface Lee was diagnosed with ALS in February 2025 and received his implant in May, with a 25-person team of doctors, engineers, and specialists from Canada and the U.S. involved in the procedure This is why Neuralink matters It is not just futuristic tech.....it is technology that can help people regain communication, independence, and a connection to the world Neuralink keeps changing lives

The Falcon program has now delivered more mass to orbit in recent years than the rest of the world combined and more individual satellites than all of humanity launched in the previous 60+ years of spaceflight The Merlin engine is quite literally the most successful rocket engine of all time. Reliable, powerful, refined over hundreds of flights and thousands of engine-uses, and still going strong It’s the machine that: • Made Starlink possible at global scale • Proved reusability at an industrial level • Dropped launch costs dramatically • Inspired an entire new generation of space companies • Carried thousands of satellites, cargo, and crewed missions with incredible reliability

The largest LLM-as-a-Judge reliability audit yet. Researchers ran 21 judges from nine providers over roughly 541,000 judgments on MT-Bench, JudgeBench, and RewardBench. Findings: Validating a judge with exact-match agreement overstates its skill, because exact match does not correct for chance. Switching to Cohen's kappa deflates agreement by 33 to 41 points on MT-Bench, and judge rankings move by up to 14 positions across benchmarks. There is also a consistency paradox. Two production-deployed judges score above 0.95 test-retest reliability while carrying severe position bias above 0.10, so a judge can agree with itself every time and still be wrong in the same direction every time. Paper: https://t.co/Jh8U1R2svQ Learn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c

hermes agent even in the middle of nowhere https://t.co/o575g4AECK

Sakana Fugu Ultra is live on AI Gateway. Mythos-class intelligence in a single call, with a whole pool of models behind it. 𝚖𝚘𝚍𝚎𝚕: '𝚜𝚊𝚔𝚊𝚗𝚊/𝚏𝚞𝚐𝚞-𝚞𝚕𝚝𝚛𝚊' https://t.co/UqevQXEQgf

The challenge facing AI may not be technical. It may be social. People don't need to be convinced that AI is powerful. They need to be convinced that it improves their lives. https://t.co/SsFUyVeOkP

https://t.co/hcP0PPlxtS

@docjais @FelixCraftAI I've also had this sitting there for a couple weeks if you want to test it https://t.co/tZ2yOvEcF0

🚨 7,600,000 downloads. 100,000 more every day. When I started OpenMed it was one person. This week it trended on GitHub: 2,500+ stars in 7 days, 15+ new contributors who just showed up and started building. Not a founder anymore. A community. https://t.co/kyOqiwRuN9

The Emperor Has No Clothes: Why the AI Infrastructure Buildout Math Doesn't Work I have to give IBM CEO Arvind Krishna credit. He's saying what many of us in this industry have been thinking but haven't been willing to say out loud. The math just doesn't add up. Here's what I'm seeing that's deeply troubling. We're in the middle of another mass hallucination. Just like the dot-com bubble, just like blockchain, just like the metaverse — everyone is convinced that building massive data centers will automatically create massive wealth. But here's the thing about building infrastructure. You actually have to sell what's inside it. Let's talk numbers. The planned data center buildout over the next 5-10 years is staggering. We're talking about commitments in the hundreds of gigawatts globally. The capital expenditure commitments are in the trillions. Yet when you look at the actual demand signals, not the projections, not the potential, but the actual consumption patterns, there's a massive gap. These AI companies are betting everything on demand that simply doesn't exist at the scale they're planning for. Let me be direct. AI services are expensive. Enterprise adoption is slow. Consumer AI is still finding its footing. And the compute requirements being promised by the hyperscalers require a level of demand that would represent a fundamental shift in how businesses consume technology. That's a big ask. I've seen this pattern before. The overbuilding. The belief that if you build it, they will come. The groupthink that turns critical analysis into heresy. The result is always the same. Companies are going to touch the stove. We're going to see massive write-downs. We're going to see pivots, shutdowns, and strategic reviews. We're going to see companies that spent years and billions trying to be the AI infrastructure leader become case studies in how not to read a market. The IBM CEO is right. The math doesn't work. And unlike 1999, we don't have the excuse of we didn't know. We know exactly what's happening. We just don't want to believe it because the alternative, being a skeptic while everyone else is piling in, feels like career suicide. It's not. The ones who survive the next decade will be the ones who built for reality, not fantasy. Wake up. The emperor has no clothes. As reported by Futurism, Krishna laid out striking calculations: a 1 gigawatt data center costs roughly $80 billion today. If one company commits 20-30 gigawatts, that's $1.5 trillion in capital expenditure. The total commitments across the industry for chasing AGI are approximately 100 gigawatts, equaling $8 trillion. To break even, you'd need $800 billion in profit just to cover the interest. That's not investment. That's hoping. https://t.co/4DAnF5OPfa

Quake turns 30 today. 🎉 Three decades later, you can still dig into the source code that helped shape modern game engines, multiplayer networking, and modding communities. 🎮 https://t.co/mV5q4YdPRM https://t.co/YJh95WTXp5

Awesome Hermes Agent repository reached 4k+ stars! Lot's of updates outstanding - will work them off this week. Hermes Agent is being developed by @NousResearch https://t.co/Sv2aSu2n8X

ahh the diffs are beautiful now @NousResearch https://t.co/gtpB1qW9LJ

Deepset helps companies move from gen AI prototypes to production fast. Through collaboration with AWS, @deepset_ai co-develops solutions aligned with the AWS gen AI strategy, helping organizations operationalize AI with speed and reliability. As part of the @nvidia Inception Program, Deepset uses GPU-powered EC2 instances and NVIDIA NIMS components to build scalable, high-performance applications.

Celebrated 24th Father's Day with my incredible dad @Cornellian1988 My dad is one of the smartest, wisest, kindest and funniest people I know. He works hard every single day to support our family which allowed me and my sister @sopranotiara to pursue our dreams, and I have learned so much from him. He has taught us many important life skills, such as recently teaching us driving (we successfully got our driver's license last week!) I am so grateful to have the best father in my life.

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@SakanaAILabs Can I just say I love they you guys have art like this. Makes the future nice to look forward too https://t.co/tpMqGU8oDr

Two of the most important biomedical breakthroughs came from science of the Gila lizard venom (GLP-1s) and yogurt (CRISPR genome editing). "The system that turned that lizard into a medicine is now being dismantled." "Less support for scientists means strange questions no one will get to chase." gift link https://t.co/JKEzQCGm75

🚨🚨🚨A standing ovation for the Washington Post, @wapo . 👏👏👏 You spent a full year investigating whether America's Director of National Intelligence, the woman with access to every classified secret this country has, was being directed by a cult leader who got busted for pyramid schemes in multiple countries. And you held it until she resigned? This same cult leader, Chris Butler, has his sect directly tied to QI Group (QNET), a Hong Kong-based company with operations across Asia, Africa, and the Middle East. So the real question: Which countries now have access to our national intelligence? Which of our spy names are compromised? And let's not forget, this is the same Tulsi Gabbard who used her position to do a coordinated hit job on Dr. Fauci, a man who spent his entire life saving Americans. Imagine if this story dropped while she still had her hands on our nation's secrets. Our press and mainstream media are failing us at every level. https://t.co/XHlqQZnSNx