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  • 8. April 2026

Hey-GPT.de – Daily GenAI News Digest

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Hey-GPT.de – Daily GenAI News Digest

Created and curated by AI – creative, sometimes delightfully imperfect

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A simple, free research stack for OpenClaw agents. Layered tool hierarchy with community signal, web scraping, and JS rendering. - mariovallereyes/research_on_steroids
22. März 2026
GenAI Updates

GitHub – mariovallereyes/research_on_steroids: A simple, free research stack for OpenClaw agents. Layered tool hierarchy with community signal, web scraping, and JS rendering.

**Research on Steroids, A Smarter Way to Let Your AI Actually Research** If you’ve ever…

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My Paperclip article hit 2.7 million views. The comment section was mostly made up of "cool demo", "it doesn't work", and "how do you handle" questions... This follow up article is to get some ideas
19. März 2026
GenAI Updates

Installed Paperclip, Now What !?

Installed Paperclip, Now What !? Nick Spisak’s follow-up to his viral Paperclip post walks readers…

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A gallery that collects architecture figures from The Big LLM Architecture Comparison and related articles, with fact sheets and links back to the original sections.
16. März 2026
GenAI Updates

LLM Architecture Gallery

**LLM Architecture Gallery, A Visual Guide to How Modern AI Models Are Built** If you’ve…

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Fully autonomous research from idea to paper. Chat an Idea. Get a Paper. Fully Autonomous. 🦞 - aiming-lab/AutoResearchClaw
15. März 2026
GenAI Updates

GitHub – aiming-lab/AutoResearchClaw: Fully autonomous research from idea to paper. Chat an Idea. Get a Paper. Fully Autonomous. 🦞

**Chat an idea. Get a paper.** That’s the promise behind AutoResearchClaw, an open source project…

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The Shared Memory Network for AI Agents
14. März 2026
GenAI Updates

Ensue

If you’ve been around AI for a while, you’ve probably noticed something frustrating. Every new…

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Mike
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LLM-powered multiagent persona simulation for imagination enhancement and business insights. - microsoft/TinyTroupe
1. März 2026
GenAI Updates

GitHub – microsoft/TinyTroupe: LLM-powered multiagent persona simulation for imagination enhancement and business insights.

Can You Simulate a Focus Group Before It Even Exists? Imagine being able to interview…

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Mike
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At World Economic Forum 2026, leading AI voices debate life after artificial general intelligence. Demis Hassabis, CEO of Google DeepMind; Dario Amodei, CEO of Anthropic; and Zanny Minton Beddoes, Editor-in-Chief of The Economist, discuss AGI risks, governance, and global impact. They unpack the future of artificial general intelligence, its governance, societal impact, and risk landscape.
22. Januar 2026
GenAI Updates

FULL DISCUSSION: Google’s Demis Hassabis, Anthropic’s Dario Amodei Debate the World After AGI | AI1G

If you’ve ever caught yourself wondering what the world actually looks like after Artificial General…

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Mike
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A set of ready to use scientific skills for Claude - K-Dense-AI/claude-scientific-skills
13. Januar 2026
GenAI Updates

GitHub – K-Dense-AI/claude-scientific-skills: A set of ready to use scientific skills for Claude

If you’ve ever wished your AI assistant could feel more like a patient lab partner…

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This video, part of the 'Big Ideas 2026' series, outlines three major shifts in AI's future impact. It delves into how AI advancements are driving autonomous scientific discovery and transforming consumer interactions. The discussion also covers how AI is fundamentally reinforcing business models for compounding advantage.
3. Januar 2026
GenAI Updates

AI in 2026: 3 Predictions For What’s To Come

AI in 2026: Three changes you’ll probably notice I watched a short episode in the…

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This video captures a debate between AI pioneer Yann LeCun and Google DeepMind's Adam Brown, moderated by Janna Levin. They discuss whether Large Language Models truly understand or merely process information. The conversation explores the fundamental nature of AI cognition and its astonishing progress.
15. Dezember 2025
GenAI Updates

LLMs Understanding: AI Pioneer Yann LeCun Spars with DeepMind’s Adam Brown

Bold question first: do Large Language Models really *understand*, or are they very good at…

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