New neural net for Language and Machine Translation! Fast and simple way of capturing very long range dependencies https://t.co/0gSoVVGrYd https://t.co/cWANbRTAMQ

Primer on Neural Networks for Natural Language Processing #AI #MachineLearning #DeepLearning #ML #DL #nlp #tech https://t.co/rStdho8pTx https://t.co/TRtvz91SpT

@DeepLeffen i am only mildly disturbed by the sheer accuracy the model has managed to pick up on these references https://t.co/OM2Xijwr6F

I dislike this so much... Unfortunately, it’s very common amount those tweets recommended by Twitter as belonging to “Machine Learning” category. How can you convey any useful information when 90% of your tweet is just spamming hashtags? https://t.co/1Obp25LJTA

Naive Bayes Classifier From Scratch in Python https://t.co/BxR2urXisa https://t.co/i6pIxS5wMe

Complete Machine Learning pipeline for NLP tasks https://t.co/Bz7Qrde59L

Complete Machine Learning pipeline for NLP tasks https://t.co/Bz7QrdwenT

🚀 Quantum Computing: The end of waiting? 🧠⚛️ Classical computers think in bits: 0 OR 1 🪙 Quantum computers use qubits: 0 AND 1 (kind of like a spinning coin) 🌀🪙 So instead of “checking one straw at a time” 🐢⏳, quantum machines can explore many possibilities in parallel—then use interference to amplify the best answers ✨📈 (Not magic, not for everything… but game-changing for specific problems.) 🌍 Why it matters (the big idea): 🧬 Drug discovery → simulate molecules faster, discover new medicines 🧱 New materials → better batteries, superconductors, catalysts 🌡️ Climate & energy → improved chemistry + materials for cleaner tech 🛰️ Optimization → logistics, routing, scheduling, supply chains 🔐 Cryptography → new security era (post-quantum world) We’re still early—today’s devices are noisy 🧊🔧—but the direction is clear: We’re not just making computers faster… we’re changing how we compute. ⚡🧠 What’s your take—breakthrough of the decade or “still too early”? 👇🔥 #QuantumComputing #Quantum #Qubits #DeepTech #FutureTech

First comprehensive framework for how AI agents actually improve through adaptation. While there is a lot of hype about building bigger models, the research reveals a different lever: systematic adaptation of agents and their tools. Researchers from many universities surveyed the rapidly expanding landscape of agentic AI adaptation. What they found: a fragmented field with no unified understanding of how agents learn to use tools, when to adapt the agent versus the tool, and which strategies work for which scenarios. These are all important for building production-ready AI agents. Adaptation in agentic AI follows four distinct paradigms that most practitioners conflate or ignore entirely. The framework organizes all adaptation strategies into two dimensions. > Agent Adaptation (A1, A2): modifying the agent's parameters, representations, or policies. > Tool Adaptation (T1, T2): optimizing external components like retrievers, planners, and memory modules while keeping the agent frozen. Let's discuss each in more detail: A1: Tool Execution Signaled Agent Adaptation. The agent learns from verifiable outcomes produced by tools it invokes. This involves code sandbox results, retrieval relevance scores, and API call outcomes. Methods like Toolformer, ToolLLM, and DeepRetrieval also fall here. The signal comes from whether the tool execution succeeded, not whether the final answer was correct. A2: Agent Output Signaled Agent Adaptation. The agent optimizes based on evaluations of its own final outputs. This includes both tool-free reasoning (DeepSeek-R1, Kimi-1.5) and tool-augmented adaptation (ReTool, Search-R1). The signal comes from answer correctness or preference scores, not intermediate tool calls. T1: Agent-Agnostic Tool Adaptation. This involves tools trained independently of any specific agent, including HuggingGPT, ViperGPT, and classic ML tools that serve as plug-and-play modules. These tools generalize well across different agents but may not be optimized for any particular one. T2: Agent-Supervised Tool Adaptation. Tools adapted using signals from a frozen agent's outputs. Includes reward-driven retriever tuning, adaptive search subagents, and memory-update modules like Reflexion and Memento. The agent stays fixed while tools learn to better support its reasoning. The trade-offs between paradigms are explicit. Cost and flexibility: A1/A2 require substantial compute for training billion-parameter models but offer maximal flexibility. T1/T2 optimize external components at a lower cost but may hit ceilings set by the frozen agent's capabilities. Generalization patterns differ significantly. T1 tools trained on broad distributions generalize well across agents and tasks. A1 methods risk overfitting to specific environments unless carefully regularized. T2 approaches enable independent tool upgrades without agent retraining, facilitating continuous improvement. The researchers identify when each paradigm fits. A1 suits scenarios with verifiable tool outputs like code execution or database queries. A2 works when only the final answer quality matters. T1 applies when tools must serve multiple agents. T2 excels when the agent is fixed, but tool performance is the bottleneck. State-of-the-art systems increasingly combine paradigms. A deep research system might use T1-style pretrained retrievers, T2-style adaptive search agents trained via frozen LLM feedback, and A1-style reasoning agents fine-tuned with execution feedback in a cascaded architecture. Four open challenges remain unsolved: - Co-adaptation: jointly optimizing agents and tools remains underexplored. - Continual adaptation: enabling lifelong learning without catastrophic forgetting. - Safe adaptation: preventing harmful behaviors during optimization. - Efficient adaptation: reducing computational costs while maintaining performance. The choice of adaptation paradigm fundamentally shapes what an agentic system can learn, how fast it improves, and whether improvements transfer across tasks. Teams building production agents need a principled framework for these decisions, not ad-hoc choices. Report: https://t.co/o2KPQLLQsZ Learn to build effective AI agents in our academy: https://t.co/g1Ijo0S5AA

+1 more

This weekend, we’re shipping 3,000 Reachy Minis all over the world! To my knowledge, it’s one of the largest shipments of AI robots of the year (or ever?) just in time for Christmas! If you’re in this batch, expect to receive an email in the coming days. Keep in mind that this first version is designed for AI builders, so it’s very bare-bones. At the moment, it has very little software on it, and, like most early hardware, will likely have a fair number of bugs and quirks. Right now, it’s much more of an open-source, DIY robotics platform than a polished consumer robot. The beautiful thing is that we’ve already seen community members managing to hack cool apps and help to improve Reachy Mini a lot! If you’re not in this batch or haven’t bought a Reachy Mini yet, you can expect delivery by the end of January, or roughly 90 days after your purchase (we’re actively working to shorten that timeline). In the meantime, you can start building for current or future Reachy owners using the simulator in the GitHub repo, as all of the software is open-source. Congrats to the @pollenrobotics @huggingface @seeedstudio teams that worked extremely hard to get to this milestone, just 5 months after the beginning of the project! I'm terribly excited to see what you’ll all build with this! Let’s go open and collaborative AI robotics!

Yesterday, we launched PAX SILICA, a partnership built for the AI age. This is the first time countries are organizing around compute, silicon, minerals and manufacturing as shared strategic assets. President Trump, Secretary Rubio and @davidsacks47 understood earlier than anyone that AI is the new backbone of economic power. This declaration operationalizes that insight. Building off of President Trump’s landmark AI Action Plan, this is American AI diplomacy at its best: building flexible coalitions, shaping markets, and putting AMERICA FIRST! 🇺🇸

+2 more

I love Substack. Always have. Their team is great. But a silent change could force me off the platform if it stays. They broke email. My paid subscribers cannot read today's paid newsletter on mobile without downloading the Substack app. @SubstackInc: roll this back. Now. https://t.co/cY4z3MMctV

Free Hotwire Native starter kit, anyone? 📂 Simplified, modern project organization 🏷️ Three tabs configured in a single place 🛜 Dynamic endpoint resolution (dev vs. prod) 🔀 Forms presented modally (via path configuration) 🌁 Bridge Components installed (& examples) 💎 More! https://t.co/BQT4j5m042

It is hard to separate AI economic impact out from other factors, but this is a clever attempt to get at the effect of AI on entrepreneurship by looking at which areas of China were more likely to adopt AI early. They estimate that ChatGPT led to a 6% increase in new startups. https://t.co/Aunf0cczUW

I have returned from the sea! https://t.co/Trmt54o3l6

NVIDIA just released a highly efficient gpt-oss-120b Eagle3 model on Hugging Face. This quantized MoE model uses speculative decoding for top-tier throughput. https://t.co/4IjOhHfJ2z

Just updated the Big LLM Architecture Comparison article... ...it grew quite a bit since the initial version in July 2025, more than doubled! https://t.co/oEt8XzNxik https://t.co/RZuwp6ZUaF

You may notice a new face on the stage today @HCS Sentinels❌ SSG Who? 🛰 T1? Do they even play Halo? Welcome @Kuhlect_ to Native White ⚪🫡 https://t.co/6Y7VI5aD2s

Black foreigners and White Settlers. Everyone is united except for Black South Africans! https://t.co/vezuJvQGnX

Sakana AIの技術を実社会へ。Applied Teamを急拡大中です。現在、Applied Research Engineer を積極採用しています。来年の新たな挑戦に向け、ぜひ年内にご応募ください！🚀 https://t.co/FuEoI2xrzS

Spiros Margaris: “With artificial intelligence, corporate trust is built slowly and rests on honesty.” https://t.co/R0zUBlMXtb https://t.co/4wJAII3iXE

⚡ How AI Is Reshaping Energy Technology: 7 Signals Every Leader Should Be Watching Over the past few weeks, especially at Schneider Electric’s Innovation Summit in Las Vegas, it became clear just how quickly AI is changing the rules of energy, infrastructure, and resilience. This isn’t about distant forecasts. It’s about real signals already shaping how electricity is generated, managed, and consumed at scale, from data centers and grids to industry and the public sector. In this newsletter, I break down 7 emerging signals every leader should be paying attention to as AI demand accelerates and energy systems evolve in parallel. Because the U.S. grid wasn’t designed for AI-era intensity, and the decisions made now will define the next decade of competitiveness and resilience. ✅📖 Read the full article here: https://t.co/zVovag47L0 #ad @SchneiderElec @SchneiderNA #schneiderelectric #SchneiderElectricInnovationSummit #AI #ISNA2025 #InnovationSummitLasVegas #AI #EnergyTechLeaders

RAG is dead 😉 https://t.co/ocKpEC7ABR

RAG is dead 😉 https://t.co/ocKpEC7ABR

i'm thrilled to announce DOGSPINNER: FESTIVE EDITION available now at pigenpalace dot com until christmas https://t.co/ZISTveym0U

Digital natives were born and raised experiencing the pervasive presence of digital in every part of their social life. Therefore, they expect certain concepts to remain the same even in the workplace. RT @antgrasso #workplace #CHRO #CEO https://t.co/Hyjw9bkonT

N@resh IT - All Paid Courses Free Giveaway😍 All Courses [2Tb+ Files] :- 👉 Real-time Projects; 👉 Angular; REACT JS; 👉 Spring boot microservices; 👉 Advanced Java; Core Java; Ul Full Stack; Original Price - 2 Lakhs➕ TO Get It:- 👉 Comment "All" 👉 Like & Retweet this Post. You Must Follow Me @codewithimanshu so that, I can DM you X. [Only for the First 499 People]

People want a strong leader that knows what they want. They want a leader that fights for their country and protects their people. Europe is lost to mass migration and open borders. They have harsher penalties for speech than violent crime. https://t.co/NPe0pS710V

The new Grok Imagine update is insane. Update now. Grok Imagine Prompt: monochromatic black and white image in a cyberpunk anime art style, blending futuristic and mechanical character elements, with an intricately detailed character design inspired by Shiguroi Suijima, featuring a female cyborg character with a serious expression, her face partially covered by a sleek, reflective visor, shown as a close-up portrait focusing on her upper body and face, bathed in dramatic high-contrast lighting with deep shadows enhancing her mechanical details

https://t.co/c2saksOQlL

The left could stop the rise of the far right by just being normal on migration, but they refuse to do it. https://t.co/jsxTm9RGSv