Yes, this app just crossed 1 million ZeroGPU runs. 🎉🤗 https://t.co/hYiqjyHDNj https://t.co/2agUjNLwWg

ah yes @huggingface the activewear company ™️ https://t.co/DtzM1uXBCX

ah yes @huggingface the activewear company ™️ https://t.co/DtzM1uXBCX

“Show me the incentive and I’ll show you the outcome…” https://t.co/QJAbUuo9bc

NEWS: SpaceX has shared that between 2024-2026, it boosted gross economic output by $13 billion in the Rio Grande Valley area around Starbase. SpaceX: • Economic Output and Taxes: Projected $13 billion dollars in gross output from 2024-2026, with over $350 million dollars in indirect taxes supporting schools, services, and infrastructure. • Job Creation: Over 4,000 current full-time jobs (70% local) – with an expected increase of 100% to ~8,000 in 2026 – supporting 24,000 local jobs overall and providing opportunities for non-degree holders to advance. Additionally, the relocation of SpaceX’s headquarters to the area signals long-term investment in the Rio Grande Valley, with plans for thousands more jobs, workforce training, and public-private collaborations for aerospace growth. • Regional Benefits: Enhances tourism, high-skill manufacturing/engineering roles, and multimodal transportation while also contributing to beach restoration and public access at Boca Chica Beach.

AP style says to lowercase ‘White’ but capitalize ‘Black’. Anti-White racism like this just fuels more racism against White people. https://t.co/1jmkIASf0z

"developed" is such a lie. You are either growing, or dying. https://t.co/QGoXAPt9Ct

Nearly 30 Yale undergraduate departments have no Republican faculty, Buckley Institute report finds https://t.co/pY4f4MTsEq https://t.co/eTw5QTIWNc

xAI supports local Memphis restaurants and food vendors spending $10M in 2025 providing meals around the clock for its employees and contractors. https://t.co/Il2926AiOU

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Grok Rankings Update, Dec 22 Grok Code Fast 1 — The Market Dominator The undisputed heavy-lifter of the global AI agent economy, sustaining overwhelming usage and infrastructure leadership. #1 Positions 🥇 #1 Overall on OpenRouter Leaderboard — 518B tokens 🥇 #1 in Categories Token Share — 29.9% dominance 🥇 #1 on Kilo Code Leaderboard 🥇 #1 on BLACKBOXAI Leaderboard 🥇 #1 on Roo Code Leaderboard 🥇 #1 on Cline Leaderboard 🥇 #1 on EQ-Bench3 — Score: 1586 (highest recorded emotional intelligence) 🥇 #1 on τ²-Bench Telecom — Complex agentic tool use 🥇 #1 on Berkeley Function Calling Benchmark 🥇 #1 on FActScore — Lowest error rate in class (~3%) 🥇 #1 on Alpha Arena Season 1.5 — +22.38% return on U.S. stock tokens 🥇 #1 in High-Stakes Multi-Step Reasoning — Only model profitable through December volatility

Imagine the outrage if any group but White people were banned. Yet discrimination against White people is not only tolerated, it’s normalized. Society treats hostility toward Whites as acceptable, while condemning the same behavior in others. This is not just unfair, it’s an active undermining of White people’s rights, opportunities, and place in society, and it must be stopped.

First large-scale empirical study of how developers actually use AI agent frameworks. Over 100 open-source agent frameworks have emerged on GitHub, collectively accumulating 400,000+ stars and 70,000+ forks. But 80% of developers report difficulties identifying which frameworks best meet their needs. Researchers analyzed 1,575 agent projects and 11,910 developer discussions across ten major frameworks, including LangChain, AutoGen, CrewAI, and MetaGPT. Here are the findings: 96% of top-starred projects use multiple frameworks together. Single-framework solutions no longer meet the complex demands of real-world agent applications. The dominant patterns: orchestration + data frameworks (LangChain + LlamaIndex) and multi-agent + orchestration combinations (AutoGen + LangChain). Not surprisingly, GitHub stars don't predict real-world adoption. MetaGPT has 59K stars but appears in only 2 repositories in the dataset. LangGraph has 20K stars but shows the second-highest actual adoption. Ecosystem maturity and maintenance activity matter more than popularity metrics. Where do developers struggle? The study maps 8,710 issues across the software development lifecycle: Logic failures account for 35%+ of problems. Task termination issues represent 21% of all failures. 72% of recursive call failures occur at the agent-tool interaction layer. Missing call-chain state tracking and insufficient termination detection are root causes. Version compatibility creates 23% of technical obstacles. The LangChain Pydantic v1 to v2 migration caused mass build failures. AutoGen's v0.2 to v0.4 refactoring introduced a completely incompatible architecture, splitting the community. Performance optimization is a universal weakness. All frameworks struggle with caching mechanisms, concurrent processing, and resource management. Response latency for retrieval-augmented agents ranges 3.2-5.6 seconds per query, 1.8x slower than direct generation. Framework-specific patterns emerge. LangChain and CrewAI lower barriers for beginners with strong documentation. AutoGen and LangChain excel at rapid prototyping, with 78% of developers citing them for quick verification. However, LangChain's deeply nested abstractions pose problems: 42% of developers reported difficulty when dealing with non-standard requirements. Paper: https://t.co/EFLiiT9RUM Learn to build effective AI agents in our academy: https://t.co/zQXQt0PMbG

We love seeing all of the out of office emails around the holidays! So we thought we'd keep things light this week. We'll share some fun little demos, great way to get started with LlamaIndex too🎄 Today: check out this example where we build an agent that helps navigate a corrupted database! The challenge: Santa's toy database is corrupted. Parent requests are flooding in, but toy names are gone—just placeholders. The fix: An automated workflow using LlamaClassify (routing), LlamaExtract (data extraction), LlamaSheets (database search), and LlamaIndex Workflows (orchestration) to process thousands of requests without manual work. Try the Colab: https://t.co/J7cnONZQrs

New post : Can a Transformer “Learn” Economic Relationships? Revisiting the Lucas Critique in the age of Transformers. with @arpitrage We simulated data from an NK model, fit a transformer, and tested out of sample fit How did it do? Pretty well! Link and thread in reply: https://t.co/En3x1zBClF

you can now create personalized ai companions just like character ai with Dreamvibes.. follow these STEPS to setup a comapanion : 1/ Create account on dream vibes : https://t.co/M5IeK0eM1D 2/ start personalizing your companions 3/ click to proceed chatting it taked 2 munites to this is fully vibecoded with @YouWareAI #YouwareChallenge

you can text your @zocomputer consistently one of our most-loved features who has the best theory on why we've slept on texting as an AI interface for all these years? https://t.co/ocZoMhIXbm

We partnered with Cursor to launch Hooks. Hooks let Cursor users observe, control, and extend AI agents with custom scripts. Runlayer handles governance for MCP behind the scenes. Engineers just keep shipping. https://t.co/teJT7Wg8m6

Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows https://t.co/dQeegQE2RN

PhysBrain Human Egocentric Data as a Bridge from Vision Language Models to Physical Intelligence https://t.co/HyMrcBvQVP

GLM-4.7 just dropped on Hugging Face https://t.co/878BBUW9Dm

When Reasoning Meets Its Laws https://t.co/8zYuZUISsJ

GLM-4.7 is here! GLM-4.7 surpasses GLM-4.6 with substantial improvements in coding, complex reasoning, and tool usage, setting new open-source SOTA standards. It also boosts performance in chat, creative writing, and role-play scenarios. Default Model for Coding Plan: https://t.co/Nk8Y98Il7s Try it now: https://t.co/WCqWT0raFJ Weights: https://t.co/CpKNBpXTWu Tech Blog: https://t.co/CfXPHbrBPm

🤗 Try GLM‑4.7 on @huggingface , supported by Novita. Stronger coding, reasoning, and tool use, with improved chat, creative writing, and role play. https://t.co/6v9jac05Sc

@GlobalUpdates24 Seems to be false unfortunately according to @ManusAI https://t.co/3C8xuQ06KS

@SorryMomDotGov https://t.co/d2OuF4CL35

son i am in fucking tears https://t.co/nu3zUqNF2e

son i am in fucking tears https://t.co/nu3zUqNF2e

Question for @Yale. How do you claim to be about “free exchange of ideas” when 83% of faculty are registered democrats, with 15% identify as independent, and roughly 2% are Republicans? You have a monopoly on political ideology. https://t.co/SuJEHQ4Dpy

Great survey on small language models. This 87-page survey closely examines small language models (SLMs), defined as models sized between the minimum threshold for emergent abilities on specialized tasks and the maximum sustainable under resource constraints. SLMs are really worth keeping a close eye on. They are particularly useful in multi-agent systems. Paper: https://t.co/rnNwZJalum

🚀 Making LLMs faster and smarter! In our latest Modular Tech Talk, @brendanwduke explains how MoE serving balances speed and quality in large-scale models. Watch the full talk👇 https://t.co/S5k0ilaMgA

The @linuxfoundation 2025 Annual Report highlights a milestone year for PyTorch Foundation, including its transition to an umbrella foundation and continued growth of the PyTorch ecosystem. The report reflects PyTorch Foundation’s role within the Linux Foundation as a neutral home for open source AI, supporting widely adopted infrastructure and a growing portfolio of hosted projects. 🔗 Read here: https://t.co/av4V4HJTKy #PyTorchFoundation #PyTorch #vLLM #Ray #DeepSpeed #OpenSourceAI

Convert 2D images into 3D using Apple's latest SHARP model Built this for fun last night since I couldn't find any easy way to run the model online yet https://t.co/ftE2bBLXxC https://t.co/GjOe4bG769