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@ShiftRWA Execution risk stays real, tokens alone won't seal it

At the recent ALL IN interview with Nvidia’s CEO, Jensen Huang, he unveils the company's evolution, the future of AI, and its economic impact. Here’s a TL;DR ⬇️ - Physical AI Inflection: Targeting $50T manufacturing/logistics industry "void of modern technology" - Disaggregated Inference: Specialized hardware for different AI tasks (Groq LPUs + GPUs) - New Economics: Selling intelligence, not GPUs. Engineers spending big on tokens for superhuman productivity - Research Revolution: AI agents completing years of work in 30 minutes - Autonomous Everything: Building the stack, not the products Jensen's "$50T Physical AI" is the hidden tokenization opportunity. AI-powered factories become measurable productive assets. Autonomous logistics become tradeable infrastructure. Accelerated research creates high-velocity IP assets. What do you think of this conviction?

@marinkazitnik Governance and reproducibility will decide if this stays productive

A striking example of collaborative AI for science: 15 long-running AI agents working on a research problem, exchanging ideas and results on a shared research board over 48 hours No coordinator. Just iterative critique, revision, and experimentation 👇

@DAIEvolutionHub Shareable binaries speed up internal demos

Convert Docker images into standalone executables. Shareable. Simple. Open-source. github.com/rzane/docker2e…

@mascot75572 Solid path to easier automation. How do you ensure tenant isolation across environments?

A few months ago, I noticed something interesting. Most people getting into automation don’t struggle with building workflows. They struggle with getting started. Setting up n8n locally Configuring Docker Dealing with servers, SSL, and deployments The friction isn’t in the logic — it’s in the infrastructure. So I decided to work on that problem. Today, SeltechAI is live with its first set of 15 founding users. Each user can spin up a fully working n8n environment instantly, without touching servers or worrying about setup. Over the past few weeks, I’ve been focused on stabilizing the system and turning it into something usable at scale. Recent updates: • Instant n8n instance deployment with isolated environments • Built-in billing system • Referral system for partnerships and distribution • Improved performance and resource control The platform now runs on a 14-day trial for new users, moving toward a more structured and sustainable model. Still early, but the goal is clear: Remove the infrastructure barrier so more people can actually build and ship automation workflows. #ai_automation

@ZidoBlack @PerleLabs Prompt versioning inside Docker would simplify audits

Ever came up with a sensitive prompt question about the generation of @PerleLabs AI model? and why the Docker Structure Changes Everything from the traditional prompt command system to a modern telepathically substructure of it's model network. Perle isn’t just a causal Web3 concept it’s a prompt driven intelligence system, and its Docker architecture is what gives it real power to work efficiently behind the scenes. At the core, Docker isn’t just about containers nor embroidery fill-ups. it’s about control, precision, and scalability of intelligence, rather it contributes to ones human to ai prompt command hygienic flow chart. Note, my prompt Intelligence becomes a Modular asset With Docker, the #PerleAI model separates my prompt engineering layer from every other mixed up system. That means: My thinking process is isolated My logic is reusable and reclyable My intelligence becomes deployable I'm no longer just writing prompts. I'm owning a portable intelligence engine template that makes interaction between my models and i very smooth. Seamless Integration Between AI and Web3 Perle connects: Prompt Engine room AI Interpretation Web3 Execution and precept showing workings. Docker ensures each part runs independently but communicates smoothly. Result or end product been questioned? Faster execution Cleaner architecture Zero dependency chaos Scalability Without Losing Identity Most systems lose uniqueness when they scale. Perle doesn’t. Because each Docker container preserves these following intelligent taproot of mine. My prompt patterns My decision logic My behavioral structure So even at scale, #ToPerle remains that my intuition just multiplied. Stability & Fault Isolation If one part fails paradventure by Web3 connection, the rest of the system stays alive. That means: No total system crash Easier debugging Continuous uptime Perle becomes resilient by design. Faster Deployment, Anywhere With Docker, Perle AI can run: On your local machine On cloud servers Even lightweight environments like me trying to work on my Termux app, #PerleAI agent will slot perfectly with that One command, and my entire intelligence stack is live. From Idea to Infrastructure This is where the real shift sets in Perle turns My random thoughts to decisive Prompts. Then turns those Prompts to Systems and systematic taproot. Then in return turn these systems to scalable Infrastructure. The docker backroot is what makes that transformation real and repeatable. Closing Note, Perle AI isn’t just built to function. It’s built to replicate intelligence without tampering. And the docker is the silent engine making that possible.

@BrightOginni @opencode @daytonaio Nice pickup, Docker in Docker on sandbox is solid

New Provider Alert 🚨 You can now run @opencode servers remotely on @daytonaio sandboxes with Gitterm Hoping to build more features with their Docker-In-Docker cap, allowing you to have a truly complete dev environment in a sandbox using docker containers for your app deps

@simplifyinAI Markdown makes reads easier, curious about table support

Microsoft just changed the game 🤯 They open-sourced a tool that converts literally any file into clean markdown for LLMs in under 60 seconds. - Converts 10+ file formats out of the box. - Run via command line, Python API, or Docker. - Built-in MCP server for direct Claude Desktop integration. 100% open source.

@LoneWolfgrid Nice consolidation. How do you handle updates across 60+ one-click apps?

I replaced Proxmox + Portainer + Uptime Kuma + Ansible + Tailscale with a single Rust binary. WolfStack manages Docker, LXC, VMs, Kubernetes, networking, storage, backups, status pages, and workflow automation from one dashboard. wolfstack.org

@AlphaSignalAI Nice to see open source multi-agent tooling taking shape

ByteDance just gave each agent its own computer. DeerFlow is a new open-source agent framework. It orchestrates multiple AI agents with memory, sandboxes, and modular skills. > Researches, codes, and builds websites > Runs bash commands inside Docker > Spawns parallel sub-agents per task > Remembers you across sessions One prompt triggers a chain. A lead agent breaks the task. Sub-agents run in parallel. Results merge. You get a complete deliverable. Skills load only when needed, keeping context windows lean. Until now, multi-agent systems either shared one messy context or required brittle orchestration code. DeerFlow treats agents like workers: isolated, specialized, and reporting back structured results to a lead agent that synthesizes everything. It works with GPT-4, Claude, Gemini, DeepSeek, or any OpenAI-compatible API. MIT license. 100% open-source.

@iam4x cheap infra, fast results, simple wins

We live in a world where its faster to one-shot prompt a simple service instead of looking for something that is un-maintainned and complex for no reasons github.com/iam4x/zig-http…

@cyber_razz Yep, once it grabs you, it sticks

@cyber_rekk Deep dives too, staying practical as we learn

I think I need to ask this again You guys In Cybersecurity, what are you actually doing?, what are you all learning and building?

@uday_devops Metrics and logs first. Resources are the bottleneck

Interviewer: Two identical Docker containers, same image, same env vars, same volume. One responds in 12ms. One takes 4 seconds. What’s different?

@HuggingModels Nice balance. How does it perform on consumer CPUs?

Meet Qwen2.5-0.5B-Instruct: a tiny but mighty language model that's taking the AI world by storm. With 7M+ downloads, this compact model packs serious conversational power into just half a billion parameters. Perfect for developers who need smart AI without massive compute.

@umbrel Works great, easy weekend setup. Ad free everywhere

one thing you can do this weekend: set up pi-hole on your umbrel. one click. takes 2 minutes. suddenly your entire home network is ad-free. your smart TV stops showing banner ads. your kid's tablet stops autoplaying garbage. your phone browsers feel faster. it's genuinely life-changing for how little effort it takes.

@binji_x Bitcoin devs are also tackling it, not just ETH

Ethereum is one of the only major efforts in money & finance that are actively combatting quantum dangers with the best cryptographers in the world. Quantum risk is real for everything. And Ethereum seeks to be a home for everything, for everyone, everywhere. It’s only right that we protect our home (and soon, yours too).

@Deyoung166 This setup saves me hours too. Skipping the manual scroll

African builders grinding in 2026 🔥, Some Universities still teaching 2018 Python basics, while agents, prompt chaining & no-code MVPs are eating the game. Quick win I use daily: n8n (free self-hosted) + Grok/ChatGPT to build a mini AI agent that auto-researches African tech trends & drafts Twitter threads in 3 clicks. Setup in <10 mins: Install n8n locally Add nodes: HTTP Request → AI (prompt Grok for trends) → Twitter post draft Run → copy → post Saves me hours of scrolling/research. Ship faster, learn by doing. RT to wake up more builders Follow @Deyoung166 for daily simple tools, collabs & Arsenal vibes ⚽🚀 #AIAutomation #NoCode #AfricanTech #BuildInPublic #TechForAfrica #SelfTaught

@Altcoinbuzzio Self-hosted AI puts privacy and control in your hands

YOUR AI. YOUR DATA. YOUR HARDWARE. WEEX AI Insights just spotlighted OpenClaw. A self-hosted AI agent gateway that puts control back in your hands. Self-hosted. Multi-channel. Agent-native. Open source under MIT license. One gateway connects every messaging app. Built-in tools, memory, sessions, and multi-agent routing. Create skills. Publish skills. Use skills others built. No API keys rented from Big Tech. No data leaving your machine. AI is only as free as the infrastructure it runs on.

@Real_Dennis_S_F @Polkadot @USDC @Sonevibe Nice demo, what gas did those two swaps consume?

.@Polkadot $DOT How to make $36 @USDC profit in two simple swaps using @Sonevibe Peg Stabilizer HSM on Polkadot Revive testnet demo tx live🔥 🧵

@leondoteth @konnex_world warzone vibe is real, infra getting hammered, love it

in 2021, i learned about web3 because of games in 2026, i am watching @konnex_world build an actual machine economy their testnet feels like a warzone right now raw infra getting stress tested in real time with fast blocks and constant pressure. no fluff, no comfort. this is where real systems survive imo a lot of projects are just eating liquidity and farming users but these guys are making robots hire each other, license ai on-demand, and settle instantly in stablecoins > 75k autonomous units minted in just 72 hours > the mint window closes on march 23 it genuinely feels like the early stages of a new on-chain primitive forming right in front of us. robots proving physical work on-chain is something i never thought i'd see this soon if you have been watching from the sidelines, you might want to look into this lesson? don't fade real infra builders