AI content incidents jumped from 47 to 475 per month in six years. As generative tools spread across business processes, firms must tighten controls and verification since legal and reputational risk now scales with every output. Source @StatistaCharts via @antgrasso
GENERATIVE AI
-

AI Scaling Bad Targeting: Context Matters More Than Prompts
By
–
The hardest part of AI is not about writing the perfect prompt.
The hardest part is knowing who you’re actually talking to. AI won’t fix bad targeting.
It just helps you scale it faster. Automated “AI-generated outreach” fails for the same reason this text did: → No context -
Analyzing Claude’s Deep and Distinctive Personality Traits
By
–
Lisez bien. Je pense avoir cerné la personnalité profonde et très particulière de Claude.
-

Anthropic Refuses to Release Its Too Powerful Mythos AI Model
By
–
Anthropic has created an AI model so powerful that it refuses to release it. Mythos discovered thousands of critical zero-day vulnerabilities in the world's most used software within days. Amazon, Apple, Microsoft, Google are already testing it. An Anthropic engineer: "I found more bugs in two weeks than in the rest of my entire life." [Translated from EN to English]
→ View original post on X — @alex_tsico, 2026-04-12 11:39 UTC
-

Prompt that Forces LLMs to Be Clear and Direct
By
–
Muchos se quejan de que ChatGPT divaga demasiado. Un tipo en Reddit encontró el prompt definitivo que hace que ChatGPT, Claude o Gemini respondan claro, preciso y directo al grano. Abajo tienes el prompt completo
-

AI Hand Generation Progress: Sora Demonstrates Significant Improvement
By
–
Do you remember when AI couldn't do hands?
— fofr (@fofrAI) 12 avril 2026
Not perfect, and still feels off in parts, but also, wow. (Seedance 2) pic.twitter.com/ntAxtrHYLNDo you remember when AI couldn't do hands? Not perfect, and still feels off in parts, but also, wow. (Seedance 2)
-

AI Hand Movement Generation Synchronized with Music Advances
By
–
One more, where the hand movements follow the music. Not perfect, but AI has come so far so quickly. pic.twitter.com/wuyugDaeCd
— fofr (@fofrAI) 12 avril 2026One more, where the hand movements follow the music. Not perfect, but AI has come so far so quickly.
-

Claude Mythos Linked to ByteDance’s Looped LLM Research
By
–

This might be the most important observation about Claude Mythos that nobody is picking up on. Chris is connecting Mythos to ByteDance’s “Scaling Latent Reasoning via Looped Language Models” paper. The core idea: instead of thinking out loud with chain-of-thought text, a looped
-

Hassabis vs LeCun: Major AI Researchers Clash on LLM Future
By
–
The CEO of Google DeepMind just went on record saying he disagrees with one of the most respected AI researchers in the world.
— Milk Road AI (@MilkRoadAI) 12 avril 2026
Demis Hassabis, the man behind AlphaFold, AlphaGo, and Google's entire AI operation publicly pushed back against Yann LeCun's claim that large language… pic.twitter.com/qmrLXNEqXUThe CEO of Google DeepMind just went on record saying he disagrees with one of the most respected AI researchers in the world. Demis Hassabis, the man behind AlphaFold, AlphaGo, and Google's entire AI operation publicly pushed back against Yann LeCun's claim that large language models are a dead end for artificial intelligence. LeCun, who left Meta earlier this year to start his own AI lab, has been saying for years that LLMs cannot reason, cannot plan, and will never get us to human-level intelligence. Hassabis disagrees, and he said so directly. His position is that scaling laws are still working, foundation models are still getting more capable, and whatever AGI ends up looking like, LLMs will be a central part of it, not something that gets replaced. He does say there is roughly a 50/50 chance that one or two additional breakthroughs will be needed beyond scaling alone, things like better memory, long-term planning, and world models. But the core disagreement with LeCun is clear, Hassabis believes the current architecture is sound and the current path leads somewhere real. Two Nobel-recognized researchers, two founding figures of modern AI, now publicly on opposite sides of the most important technical question in the industry.
→ View original post on X — @ceobillionaire, 2026-04-12 09:02 UTC

