From #OCPSummit25 in San Jose: a great Data Insights chat with Jeniece Wnorowski and Roger Cummings, CEO of PEAK:AIO. We cover capturing intelligence close to the data, closed-loop training, and how a workload-aware file system with deeper memory tiers simplifies AI at scale. Bonus: how partnerships help teams get results faster with fewer moving parts. If you care about AI performance without runaway complexity, this one’s for you. #PEAK:AIO #Solidigm Open Compute Project Foundation

This week in AI News...the "MegaBlob" became a thing people talk about, particularly in the investor crowd, but millions more learned about the 'circular investments' of BigTech AI and are starting to wonder what the heck is going on here. The Tech Titans are doubling down on big data centers and scaling their way to SuperIntelligence, but the evidence for post-training and 'test-time compute' as pathways forward to AGI is pretty scant. We'll have a lot to say about this later but TGIF!

ATLAS delivers up to 400% faster inference by learning in real-time. 🚀 From today's coverage on VentureBeat: "The shift from static to adaptive optimization represents a fundamental rethinking of how inference platforms should work." We couldn't agree more! "The software and algorithmic improvement is able to close the gap with really specialized hardware," says Tri Dao, Founder and Chief Scientist at Together AI. "We were seeing 500 tokens per second on these huge models that are even faster than some of the customized chips." Read more (link in comments 👇)

🚀 Meet TINKER - The Training API that frees you from infrastructure headaches. It simplifies large-scale model training so you can focus on building intelligence, not managing compute. Part of the Expedemy Research Series, where we break down the world’s most advanced AI tools and infrastructures - one system at a time. #Expedemy #AITools #MachineLearning #ResearchSeries #InfrastructureAI #TinkerAPI

Currently Focused on mastering Langchain, RAG architectures, and the intricacies of AI Agents. Here's a glimpse of what's on my study agenda: • Langchain: From basic components to complex chains and memory management. • RAG: Exploring document loading, text splitting, embeddings, vector stores, and building practical applications. • Agents: Understanding tools, toolkits, and the art of constructing intelligent AI agents. Always keen to learn and share knowledge. #ArtificialIntelligence #Langchain #RAG #AIAgents #TechLearning #Developer

🚀 Announcing: CerebraGrid — The Distributed Intelligence Mesh 🧠🌐 I’m excited to announce the creation of CerebraGrid, a new code project now available for licensing, designed to redefine how intelligent systems collaborate and scale. 🧩 What It Is CerebraGrid is a networked intelligence fabric that enables multiple autonomous nodes — agents, models, or modules — to share inference, memory, and decision capabilities across a distributed mesh. It supports collaborative reasoning, fault-tolerant AI networking, and privacy-preserving computation in a peer-to-peer architecture. Each node can offload sub-tasks, query remote memory shards, and contribute to global models, creating a dynamic system that mimics distributed cognition. 🔍 Key Modules / Innovations - Peer Mesh Protocol: Secure messaging and negotiation between nodes - Shard Memory Router: Intelligent routing of memory queries to the correct shards - Collaborative Inference Engine: Split reasoning and aggregate outputs from distributed models - Consensus Policy Module: Nodes can vote or agree on shared decisions or state updates - Fault Recovery & Redundancy System: Automatically detect failed nodes and reassign tasks - Privacy-Preserving Inference: Includes MPC / Homomorphic encryption stubs for secure shared models - Network Visualization UI: Real-time visualization of the node graph, system loads, and collective cognition ⚙️ Available Now CerebraGrid is now open for licensing, integration, or collaboration through: 🔗 Gumroad: https://lnkd.in/eMkst4pZ ☕ Ko-fi: https://lnkd.in/eWJjQ4YG 🎮 Itch.io: https://lnkd.in/e9yHDbEn You can find all of my projects, AI tools, and digital ventures here: 🌐 https://lnkd.in/eaD52U3P #ArtificialIntelligence #DistributedSystems #CognitiveComputing #AIResearch #CerebraGrid #PeerToPeer #DecentralizedAI #Innovation #TechLaunch

Looking forward to speaking at #OpenSlava2025 this week to share insights on how AI is moving from code assistants to the physical world. In my talk, I’ll explore why even GPT 10 won’t solve industrial problems alone, and how key trends such as virtualization and digital twins, physical AI, and orchestration with reasoning are shaping the next generation of systems. We’ll look at how Agentic AI can move beyond the software development lifecycle – learning to understand, interact with, and ultimately compile the physical world. Thanks to the organizers and partners for bringing together such an inspiring mix of technology and industry leaders. Kathrin Schwan Tobias Regenfuss Thomas Reisenweber Nick Rosa Dr. Matthias Ziegler

The internet was built for humans. The next version is built for agents. Context Protocol → the trust layer of the AI internet. → AI-native interfaces (Brains) → Verifiable domains (.bio, .startup, .madrid) → Data tools agents can act on

CNA is dedicated to helping the public sector leverage the benefits of AI and machine learning safely, responsibly, and efficiently. One way we accomplish this is with the Performance, Architecture, Criticality, and Evolvability (PACE) concept. Each PACE category captures a component of AI risk, to help public leaders develop a holistic understanding of what risks their agency might face. https://lnkd.in/eZ7JvPdH

⭐ Build AI Agents with LangGraph Learn to build a startup intelligence agent in this video guide, showcasing LangGraph's stateful workflows with planning capabilities and SingleStore integration for vector storage. Watch the tutorial: https://lnkd.in/ea4AyHwS