From Agent-1 to Superintelligence: Decoding the AI 2027 Scenario and Its Profound Implications linkedin.com/pulse/from-agen… via @ingliguori
→ View original post on X — @ingliguori, 2026-04-03 17:25 UTC

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From Agent-1 to Superintelligence: Decoding the AI 2027 Scenario and Its Profound Implications linkedin.com/pulse/from-agen… via @ingliguori
→ View original post on X — @ingliguori, 2026-04-03 17:25 UTC

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8 Types of #LLMs for Next Generation #AIAgents
by @PythonPr #GenAI #AI #ArtificialIntelligence #MachineLearning #ML
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Last night, Senior Director of Applications, @yining_shi led a Runway Characters Hackathon where attendees learned to build intelligent real-time video agents directly into their apps, products, games and services. All in a matter of hours.
— Runway (@runwayml) 3 avril 2026
To start building for yourself, visit… pic.twitter.com/ZryE2LGQEe
Last night, Senior Director of Applications, @yining_shi led a Runway Characters Hackathon where attendees learned to build intelligent real-time video agents directly into their apps, products, games and services. All in a matter of hours. To start building for yourself, visit the Runway Developer portal at the link below for walkthroughs, video tutorials and pre-built applications.

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First update of the call, from Sachin: Gemma 4 is out now on KerasHub! Best open-source model so far for reasoning and agentic workflows.

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We're shipping an elaborate guide on how to profile diffusion pipelines in Diffusers to set them up for success with `torch.compile` 🔥 We devised a workflow with Claude & it turned out to be quite effective. It served its purpose well. With the help of the trace alone, we uncovered: 1. CPU <-> GPU syncs 2. CPU overheads 3. Kernel launch delays When we provided the profile trace and our observations from the trace to Claude, and helped us get rid of the issues, it did well. However, it did so iteratively. The process was intellectually fun and engaging!
→ View original post on X — @huggingface, 2026-04-03 17:07 UTC
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🆕 Marc Andreessen’s 2026 AI Thesis: Agents, Open Source, and Why This Time Is Differenthttps://t.co/wmu0s7vyLn@pmarca of @a16z says AI people keep swinging between utopian and apocalyptic for one simple reason: this field has been “almost here” for 80 years. But now, the… pic.twitter.com/kYnLP5jZh1
— Latent.Space (@latentspacepod) 3 avril 2026
🆕 Marc Andreessen’s 2026 AI Thesis: Agents, Open Source, and Why This Time Is Different latent.space/p/pmarca @pmarca of @a16z says AI people keep swinging between utopian and apocalyptic for one simple reason: this field has been “almost here” for 80 years. But now, the breakthroughs are no longer theoretical. Reasoning, coding, agents, and self-improvement are all starting to work at once. This episode goes deep on AI winters, OpenAI + OpenClaw, infrastructure overbuild risk, proof-of-human, why software may soon be written mostly for bots, and why the real bottleneck may be society adopting AI rather than the models improving.

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Join @hwchase17 and Chirantan "CJ" Desai, CEO of @MongoDB for a fireside chat at Interrupt — May 13-14 in San Francisco. MongoDB is the company behind one of the most widely used databases for modern applications — used by thousands of teams to power everything from real-time analytics to AI-native workloads. At Interrupt, Harrison and CJ will chat about how teams are building agents at the world's largest enterprises, and what's next for the space. Get your tickets: interrupt.langchain.com/
→ View original post on X — @langchain, 2026-04-03 16:47 UTC
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Yes, it keeps a running list of entities encountered as it does the weekly summaries, then later goes through each entity and generates a document for it in a second pass.
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I asked @simonw what the next leap in AI software engineering is likely to be.
— Lenny Rachitsky (@lennysan) 3 avril 2026
He explained the "dark factory" pattern where teams don't write any code or even look at their code. https://t.co/LWQPeaxml9 pic.twitter.com/2SmKC8bH4i
I asked @simonw what the next leap in AI software engineering is likely to be. He explained the "dark factory" pattern where teams don't write any code or even look at their code.

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I just helped hundreds of business professionals build their first AI agents in my AI Agent Mastermind. Here are five built by people who had never opened a terminal before this week: 1️⃣ A personalized morning brief. She took my original morning brief setup, remixed it with global news, local news from Sweden, a Linear ticket queue, a joke of the day for the family breakfast table, and a motivation quote based on business needs. 2️⃣ Someone who had never touched a command window used PowerShell and natural language to solve a screenshot clipping issue they had been working around for months. 3️⃣ A Spanish learning app called Vamanos, built on a "carefully negotiated token schedule" so it does not eat into her consulting work. Cultural context profiles for herself and her husband, token alerts so Claude can parent her if she goes off the rails, and Easter eggs with advice from my course sprinkled throughout. She built it for a trip she is taking next year. Sorry Duolingo. 4️⃣ A Google Commute Agent. Built because Google Calendar has no built-in way to book meetings back to back with distance awareness. It scans for events with physical addresses, calculates real drive time via Google Maps API, and automatically adds commute and parking buffer blocks around each one. 5️⃣ A weekly research briefing delivered to Gmail, connected to Perplexity for live web research, with a clickable macOS desktop app for whenever she wants to run it outside the schedule. These are all solving problems that had been annoying someone for months or years, or ways to show up more fully in their lives. It’s weirdly addictive to watch. We’re opening a second cohort soon. Enrollment will be extremely limited, and it’ll only be open to people on the waitlist. Join the waitlist here: joinaiagentmastermind.com
→ View original post on X — @alliekmiller, 2026-04-03 16:28 UTC