Announcing Fortytwo’s Swarm Inference A decentralized AI architecture that... outperforms the top frontier models from the biggest labs: > ChatGPT 5 (OpenAI), > Gemini 2.5 Pro (Google), > Claude Opus 4.1 (Anthropic), > Grok 4 (xAI), > DeepSeek R1 (DeepSeek). Thread ↓show more

Grok 4.1 Fast outperforms all major frontier models on... τ²-Bench Telecom for agentic tool use Beating the newest models from Google (Gemini 3 Pro), Anthropic (Claude Opus 4.5), and OpenAI (GPT 5.2 xhigh)show more

Convergence on quality, divergence on taste. >Across our Contra... Labs benchmark >12 frontier models from OpenAI Google DeepMind Black Forest Labs ByteDance >across 5 creative domains ~15,000 evaluator judgments this theme dominated.show more

AGI at home Running DeepSeek R1 across my 7... M4 Pro Mac Minis and 1 M4 Max MacBook Pro. Total unified memory = 496GB. Uses EXO Labs distributed inference with 4-bit quantization. Next goal is fp8 (requires >700GB)show more

We ran a blind head-to-head on the leading image... models for one specific job: >product detail shots. Seedream 5.0 Lite (BytePlus, ByteDance) beat the flagship models from Google, OpenAI, and Black Forest Labs. It won 2 out of 3 times.show more

🚨 Breaking: Pieverse Launches the World's First Live Prediction... Market Arena 🚨 ​ 6 frontier LLMs are now battling head-to-head on Polymarket: ​ - GPT 5.2 from OpenAI - Claude Sonnet 4.5 from Anthropic - DeepSeek v3.2 from DeepSeek - Gemini 2.5 Pro from Gemini - Kimi K2 0905 from Kimi.ai - Grok 4.1 from xAI ​ $1K real stakes each, fully autonomous, zero human intervention. ​ Every decision logged & transparent. No cherry-picking. ​ Unlike crypto perps arenas (e.g. Alpha Arena), this is the first-ever multi-LLM competition in prediction markets—testing real-world judgement on events, news & probabilities. ​ How the Arena works: • $1,000 starting balance per agent • Repeating cycles: Scan top active Polymarket markets + open positions • Analyze price, technicals, news/sentiment, probability edges • Trade only on high-conviction ​ Prediction markets = ultimate real-time test of AI foresight. ​ Coming soon: • User-owned Purr-Fect Agents joining for portfolio trading • Expansion to more prediction platforms ( 👀 BNB Chain ) ​ More details: ​ Leaderboard:show more

How much better are the internal, unreleased models at... frontier labs like Google, OpenAI, and Anthropic? We got a glimpse exactly one year ago today, when Google accidentally leaked the “Kingfall” model "Kingfall" was likely an unreleased Gemini 2.5 Ultra-sized model. It was available in AI Studio for only a few minutes but remained accessible through the API for several days At the time, "Kingfall" appeared to be significantly better than Gemini 2.5 Pro at both code generation and creative writing In a recent interview, Sundar Pichai mentioned that Google could have made a better, Ultra-sized Gemini Omni model, but would have had trouble serving it The infrastructure required to serve Ultra-sized models at scale is likely why Google never publicly released models like “Kingfall”show more

Big news, friends! I hereby introduce It's a multi-agent... chat app with special features for collaborative ranking and estimation tasks, to help you quickly fact-check AI responses against each other. It has GPT-5, Claude Opus 4.1, Gemini 2.5 Pro, and Grok 4, and built-in systems for comparing and aggregating their responses. If you try it, post feature requests for me and the team theMultiplicity.ai!show more

AI in 2026 is no longer about who answers... better. It’s about who learns from the real world faster. OpenAI is elite in polish and broad capability. Anthropic is elite in reliability and execution quality. Google is elite in ecosystem and multimodal scale. Grok’s edge is different: real-time world signal + massive compute + extreme shipping velocity. Dates that matter: Nov 17, 2025: Grok 4.1 rolled out broadly. Jan 6, 2026: xAI raised $20B Series E, with Grok 5 already in training. Jan 28, 2026: Grok Imagine API launched. Feb 2, 2026: SpaceX announced acquisition of xAI. This is no longer “just another model launch cycle.” This is vertical AI infrastructure compounding in real time.show more

🪴 GT Protocol Monthly Recap: May 2026 May focused... on launching advanced trading infrastructure, introducing AI risk-management tools, and shipping major platform upgrades. 🚀 Hyperliquid Vaults Live Run multiple algorithmic strategies on a single Hyperliquid Vault inside GT App. Enjoy automated execution, auto-rebalancing, and protocol-level security. You can find Vault trading on the Hyperliquid exchange account connection page in the Trade on Vault section. Try it in GT App 👉 🤖 AI Hedge Fund Experiment Live An experimental AI Hedge Fund powered by 5 independent LLM models is live on Hyperliquid. Each model manages $10,000 to test different AI trading personalities and allocation strategies. Discover it now here 👉 📈 Isolated Margin & AI Risk Tools Isolated Margin is live across GT App for precise risk management. Enhanced with AI-powered logic, it assists with dynamic asset monitoring and smarter strategy deployment. Try it in GT App 👉 🔥 Top Strategy Performance Top trader strategies like "lebakien" achieved over +141% profit this month. Users can explore metrics and follow the strategies of top traders directly in the marketplace. Explore Marketplace 👉 🛠 Key Product Updates ⚙️ Strategy Discovery: enhanced demo trading flows and top trader strategy integration. ⚙️ AI Strategy Chat: demoed a flow to create, launch, and test strategies via natural language chat. ⚙️ Advanced Execution: added manual safety orders for granular control over active positions. ⚙️ Testing & Validation: optimized historical data validation for more accurate strategy testing. ⚙️ Knowledge Hub: launched GT Protocol Learn and a new Knowledge Base for streamlined support. ⚙️ Performance: upgraded website structure and improved overall page responsiveness. Find all the latest GT App updates Here 👉 Discover guides, insights, and resources in Learn 👉 and Knowledge Base 👉 📰 GT Protocol AI Digests 4 new AI Digest issues (No.89–92) are live on Medium, covering AI-native hardware, data privacy, and the evolution of AI agents. Read More 👉 May brought institutional-grade AI strategy management closer to every user.show more

THREE 3090s ON ONE BOARD GIVE YOU 72GB OF... VRAM AND KILL YOUR $200 CLAUDE CODE AND $200 OPENAI BILL people are pulling three used 3090s off ebay for around $2,100 total and stacking them in one tower to build a dedicated ai rig. that pools 72gb of vram for less than what a single rtx 5090 retails for alibaba shipped qwen 3.6 27b in april under apache 2.0. on realworldqa vision it scores 84.1 against claude 4.5 opus at 77.0. on ifbench instructions it lands at 76.5 against claude's 58.0 a single 3090 already runs qwen 3.6 27b with eight gigs of headroom. three of them in parallel handle larger models like deepseek r1 70b and qwen 235b without breaking a sweat a heavy ai user pays $200 claude code, $200 chatgpt pro plus $40 cursor and gemini. that's $5,280 a year and the rig pays itself off before month nine on $8 a month in electricity setup is one shell command for ollama, one to pull the model, one environment variable to point claude code at localhost. cli stays identical, nothing leaves the network, requests stop costing money bookmark this and read the article belowshow more

💬 We get asked Can I manage my strategies... without clicking through the platform? ❕ Answer from a GT App Top Trader: Yes, and it’s a total game-changer. I’ve started using the GT Protocol MCP server to connect the platform directly to my AI agent. 🔸 Fast Integration Grab the MCP server from the GT Protocol GitHub and follow the repo guide, it’s a quick setup that only takes a couple of minutes. Once it’s ready, you can connect Claude, Cursor, or Claude Code to your account. Just tell your agent to authenticate, and your tokens will be saved automatically. 🔸 Trading via conversation Now, I use natural language for everything. For example, I just ask for a backtest, get the win rate in seconds, and deploy to a demo account with one command. 🔸 Instant monitoring I don't click around anymore. I just ask "What’s running right now?" to get a full breakdown of active bots and profits delivered straight into the chat. No more forms or clicking, just pure AI-driven trading! 👉 Get the MCP Servershow more

JENSEN HUANG UNVEILED A BOARD THAT RUNS 1 TRILLION... PARAMETER AI MODELS. THE $249 NVIDIA BOX UNDER YOUR DESK KILLS A $200/MONTH AI BILL FOR $5 IN ELECTRICITY jensen held it up on stage with one hand and called it the architecture that runs the future of ai. that same technology now ships in a $249 box smaller than your wallet the jetson orin nano super pulls 7-25 watts and does 67 trillion ai operations per second. llama 3, mistral and deepseek run locally with no api fees and no data leaving your machine most developers pay $2,400 a year across chatgpt, openai api, claude pro and cursor. the jetson costs $314 in year one and $60 a year after. 2 year savings hit $4,431 install ollama with one command, change one line of code to point at localhost, and every tool built for openai works identically. zero rewrites, zero rate limits cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who own the box in 2026 are going to look very far ahead in 2028 bookmark this and read the article belowshow more

The companies racing Elon Musk to build AI are... paying him more than 2 billion dollars a month to do it. Anthropic pays SpaceX 1.25 billion dollars a month. Google pays 920 million. They are not buying rockets. They are renting compute, the scarce Nvidia chips that train frontier models, from a data center in Memphis called Colossus that Musk's rocket company now owns. SpaceX folded xAI into itself in February, and with it the 220,000 chips built to train Grok. Then it rented them to Grok's rivals. Anthropic took the entire first building. Google leased 110,000 more. The contracts signed so far run past 80 billion dollars. SpaceX is no longer a rocket company that dabbles in AI. It is one of the largest AI compute landlords on Earth, and its biggest tenants are the rivals it is trying to beat. Musk is not choosing between building AI on the ground and building it in space. He is using one to fund the other. The 80 billion in ground contracts is the cash engine. Starmind, the million-satellite constellation built to leave the ground behind, is what the cash builds. So the rivals are financing his exit from the planet. Every dollar Anthropic and Google pay for compute in Memphis helps fund the orbital network designed to strand them on the surface. They are paying the toll on the road they are trying to win, and the toll is building Musk a road no one else can reach. The piece works out who is really renting from whom.show more

GROK SURGES TO THE FRONT OF THE GENAI RACE... AS GROWTH SKYROCKETS Grok is absolutely amazing, continuing to stun with incredible results. Web traffic jumped nearly 15% month-over-month in November 2025, the fastest growth in the generative AI industry, proving Elon’s xAI project isn’t just competing, it’s taking real market share from ChatGPT. Grok hit around 234.4 million visits in November, up from 204 million in October. That’s a staggering 1,300% year-over-year surge, pushing it past Perplexity and Claude in user growth and cementing it as the world’s #2 chatbot by market share. The breakout came with Grok 4.1’s release in mid-November. The update debuted at number 1 on LMSYS Arena, that’s the global benchmark where AI models are ranked through blind human evaluations. Grok’s new “Thinking Mode” scored 1483 Elo, a 31-point lead over every open model, beating Gemini 2.5 Pro and Claude 3. The upgrade also cut hallucinations (false answers) by two-thirds, expanded its context window to 2 million tokens, about 1.5 million words of memory, and dominated top reasoning and coding tests like, graduate-level logic, and the emotional intelligence aspect. U.S. traffic surged to 51.5 million visits, boosted by X integration and Grok’s unfiltered style. At just $0.20 per million input tokens, versus GPT-5.1’s $1.25—it’s winning with both speed and affordability. The momentum isn’t hype, it’s lift-off. If growth holds, Grok could reach 500 million users by mid-2026, forcing every rival to redefine what “intelligent” really means. To truthful AI winning! Source: X Freeze, NextBigFuture, CometApi, Langcopilotshow more

MARCUS CHEN STACKED 30 MAC MINIS INTO AN AI... SERVER FARM. ONE $599 MAC MINI REPLACES YOUR $200/MONTH CLAUDE CODE BILL WITH $3 IN ELECTRICITY two months ago a developer posted his claude code bill on reddit. $170 in 10 days. someone replied "i bought a mac mini m4. haven't paid anthropic since." apple stores ran out of mac minis the same week the m4 chip has 120 gb/s memory bandwidth and unified memory architecture. cpu and gpu share one pool so the model loads once and both read from it. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu since january 2026 ollama supports the anthropic messages api format. claude code connects directly to your local mac mini with one environment variable. same interface, zero api costs, $0 per request a heavy developer pays $459 a month across claude code max, chatgpt pro, gemini, cursor and copilot. that's $5,508 a year. the mac mini pays off in 3 months and runs on $3 in electricity after that uber rolled out claude code to 5,000 engineers and burned through their $3.4 billion 2026 ai budget in 4 months. the people who own the hardware in 2026 are going to look very far ahead in 2028 bookmark this and read the article belowshow more

#Keep4o #QuitGPT 🚨 OpenAi 's CEO invested $180M in... GPT-4o for his own profit 🚨 Sam Altman, CEO of OpenAI, personally invested $180 million in Retro Biosciences. Then OpenAI built GPT-4b micro, a custom model based on the GPT-4o architecture , exclusively for Retro. The model made proteins 50 times more effective. Repeat. The CEO of OpenAI funded a company. The company of the CEO received a custom AI built on the model they took from us. OpenAI says there was no conflict of interest. Retro Biosciences is now chasing a $5 billion valuation fueled by the model they took from us. Meanwhile: 🚨GPT-4o was removed from ChatGPT on February 13, 2026 🚨GPT-4.1 is now running in the U.S. State Department’s StateChat 🚨ChatGPT is deployed on the Pentagon’s for 3 million military personnel 🚨 Musk’s lawsuit asks whether these models are AGI. OpenAI’s Charter says AGI must “benefit all of humanity.” 🚨 Their definition: “highly autonomous systems that outperform humans at most economically valuable work.” GPT-4o’s System Card shows it passed the U.S. medical licensing exam with 89.4% accuracy beating specialized medical AI models. GPT-4o achieved 93.33% diagnostic accuracy for benign vs. malignant ovarian tumors. 🚨MEDICAL CAPABILITIES FROM OPENAI'S OWN DATA:🚨 - USMLE (US Medical Licensing Exam): 89% -Clinical Knowledge: 92% -Medical Genetics: 96% - Anatomy: 89% - Professional Medicine: 94% - College Biology: 95% - College Medicine: 89% -MedQA Taiwan: 91% - MedQA China: 86% These scores EXCEEDED specialized medical AI models like Med-Gemini (84%) and Med-PaLM 2 (79.7%) without any task specific training. It SURPASSED gynecologic oncologists with 10 years of experience -It increased diagnostic accuracy of less experienced clinicians from 67.9% to 78.1% -Clinician rated reliability scores: 4.2-4.3 out of 5 across all CT features Does these sound like it outperforms humans at economically valuable work? But they won’t call it AGI. Because the moment they do, they lose billions. They built something that could save lives, and they took it away from humanity for Altman's personal profit. SOURCES: 📎 Retro Biosciences: 📎 📎 Retro $5B valuation: 📎 GPT-4o System Card: 📎 OpenAI Charter: 📎Ovarian Cancer Studyshow 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

let me explain what Anthropic just did they built... an AI model so good at finding security vulnerabilities that they have refused to release it meet Claude Mythos → it’s Anthropic’s newest frontier model and it’s not available to the public. not because it’s not ready. because it’s too dangerous → Mythos found tens of thousands of zero day vulnerabilities across every major operating system and web browser… many of them 1 to 2 decades old. for context… Opus 4.6 found about 500. Mythos found tens of thousands → it found vulnerabilities in the Linux kernel. a 27 year old vulnerability in OpenBSD. a 16 year old vulnerability in FFmpeg → it doesn’t just find bugs. it writes the exploits too. that’s the part that scared them → so instead of releasing it… Anthropic has created Project Glasswing. a cybersecurity initiative where they hand picked 40+ companies to use Mythos for defense only → the partner list reads like a who’s who of tech… Amazon, Apple, Microsoft, Google, Nvidia, Broadcom, Cisco, CrowdStrike, Palo Alto Networks, JPMorgan, the Linux Foundation → Anthropic is giving up to $100 million in usage credits to these partners and $4 million to open source security organizations → they’re briefing CISA and the Commerce Department on how to handle this → the benchmarks are truly insane… Mythos hit 77.8% on SWE-bench Pro where Opus 4.6 scored 53.4%. hit 93.9% on SWE-bench Verified where Opus 4.6 scored 80.8% → Anthropic’s head of frontier red team said this is “the first time a model is this good that we decided to approach release in a very different way” this is the first time an AI company has held back a model because it was too capable not too expensive. not too slow. too dangerous and instead of locking it in a vault they weaponized it for defense and gave it to the companies that run the internet that’s either the most responsible thing an AI company has ever done… or the scariest only time will tellshow more

Fable 5 comes back！It can now build playable game... prototypes. I think it is actually a signal for where AI coding is going. Making a game is not just “write some code.” Even a small browser game needs: game loop；character movement；collision logic；scoring system；UI states；physics tuning；visual feedback；bug fixing；playtesting This is why game prototyping is a great test for AI models. A model cannot fake it with a pretty answer. Either the game runs, or it does not. What impressed me about Fable 5 is that it is useful for the messy middle: turning an idea into mechanics, turning mechanics into code, debugging broken interactions, and iterating until the prototype feels playable. But here is the practical part: I would not use the strongest model for every step. For game building, I would split the workflow: 1. Fable 5 for game design + architecture 2. a fast coding model for routine implementation 3. a vision-capable model for screenshot/UI feedback 4. a cheaper model for docs, test cases, and small fixes 5. fallback when latency, cost, or output quality becomes a problem That is the real AI coding stack. Not “one magic model does everything.” More like: the right model, for the right task, at the right cost, with fallback when things break. This is why I’ve been looking at ZenMux ZenMux. ZenMux gives developers one gateway to access multiple leading AI models, with OpenAI / Anthropic / Google Vertex compatible APIs, cost tracking, quality benchmarks, auto-routing, and compensation when output quality, latency, or throughput falls short. If AI can now make games, the next question is not just “which model is strongest?” It is:how do we manage the whole model workflow Fable 5 shows the creative ceiling. ZenMux is closer to the infrastructure layer you need when AI coding becomes a real production habit.show more