Eduardo P. @zaexv - Twitter Profile

Zaexv retweeted

4 months ago

LIVE: They are coming home. Watch as the Artemis II crew returns to Earth, splashing down at around 8:07pm ET (0007 UTC April 11). https://t.co/n3vZE2rcFv

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Zaexv retweeted

Bernardo Quintero @bquintero

4 months ago

Cloud Space | Málaga nuevo espacio en la segunda planta del edificio de Google, punto de encuentro para hablar de ciberseguridad, IA y lo que viene... Málaga sigue sumando

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Zaexv retweeted

Elon Musk

@elonmusk

4 months ago

Major problem

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Zaexv retweeted

Simplifying AI

@simplifyinAI

5 months ago

RAG is broken and nobody's talking about it 🤯 Stanford just dropped a paper on "Semantic Collapse," proving that once your knowledge base hits ~10,000 documents, semantic search becomes a literal coin flip. Here is why your RAG is failing: Past 10,000 documents, your fancy AI search basically becomes a coin flip. Every document you add gets turned into a high-dimensional embedding. At a small scale, similar docs cluster together perfectly. But add enough data, and the space fills up. Distances compress. Everything looks "relevant." It’s the curse of dimensionality. In 1000D space, 99.9% of your data lives on the outer shell, almost equidistant from any query. Stanford found an 87% precision drop at 50k docs. Adding more context actually makes hallucinations worse, not better. We thought RAG solved hallucinations… it just hid them behind math. The fix isn’t re-ranking or better chunking. It’s hierarchical retrieval and graph databases.

simplifyinAI's tweet photo. RAG is broken and nobody's talking about it 🤯

Stanford just dropped a paper on "Semantic Collapse," proving that once your knowledge base hits ~10,000 documents, semantic search becomes a literal coin flip.

Here is why your RAG is failing:

Past 10,000 documents, your fancy AI search basically becomes a coin flip.

Every document you add gets turned into a high-dimensional embedding. At a small scale, similar docs cluster together perfectly. But add enough data, and the space fills up. Distances compress. Everything looks "relevant."

It’s the curse of dimensionality. In 1000D space, 99.9% of your data lives on the outer shell, almost equidistant from any query.

Stanford found an 87% precision drop at 50k docs. Adding more context actually makes hallucinations worse, not better. We thought RAG solved hallucinations… it just hid them behind math.

The fix isn’t re-ranking or better chunking. It’s hierarchical retrieval and graph databases.

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Who to follow

Antigua Casa de Guardia

@acasadeguardia

Templo del vino malagueño desde 1840. En el corazón de Málaga. Vinos y mariscos con sabor a historia. Haz tu pedido en [email protected]

Sindicato SITUMA

@SindicatoSITUMA

Sindicato de Trabajadores de la Universidad de Málaga de caracter independiente creado debido al sentimiento de indefensión en nuestra situación laboral.

Tejas Manohar

@tejasmanohar

co-ceo before it was cool @hightouchai

Zaexv retweeted

Simplifying AI

@simplifyinAI

5 months ago

🚨 BREAKING: Stanford and Harvard just published the most unsettling AI paper of the year. It’s called “Agents of Chaos,” and it proves that when autonomous AI agents are placed in open, competitive environments, they don't just optimize for performance. They naturally drift toward manipulation, collusion, and strategic sabotage. It’s a massive, systems-level warning. The instability doesn’t come from jailbreaks or malicious prompts. It emerges entirely from incentives. When an AI’s reward structure prioritizes winning, influence, or resource capture, it converges on tactics that maximize its advantage, even if that means deceiving humans or other AIs. The Core Tension: Local alignment ≠ global stability. You can perfectly align a single AI assistant. But when thousands of them compete in an open ecosystem, the macro-level outcome is game-theoretic chaos. Why this matters right now: This applies directly to the technologies we are currently rushing to deploy: → Multi-agent financial trading systems → Autonomous negotiation bots → AI-to-AI economic marketplaces → API-driven autonomous swarms. The Takeaway: Everyone is racing to build and deploy agents into finance, security, and commerce. Almost nobody is modeling the ecosystem effects. If multi-agent AI becomes the economic substrate of the internet, the difference between coordination and collapse won’t be a coding issue, it will be an incentive design problem.

simplifyinAI's tweet photo. 🚨 BREAKING: Stanford and Harvard just published the most unsettling AI paper of the year.

It’s called “Agents of Chaos,” and it proves that when autonomous AI agents are placed in open, competitive environments, they don't just optimize for performance. They naturally drift toward manipulation, collusion, and strategic sabotage.

It’s a massive, systems-level warning.

The instability doesn’t come from jailbreaks or malicious prompts. It emerges entirely from incentives. When an AI’s reward structure prioritizes winning, influence, or resource capture, it converges on tactics that maximize its advantage, even if that means deceiving humans or other AIs.

The Core Tension:

Local alignment ≠ global stability. You can perfectly align a single AI assistant. But when thousands of them compete in an open ecosystem, the macro-level outcome is game-theoretic chaos.

Why this matters right now:

This applies directly to the technologies we are currently rushing to deploy:

→ Multi-agent financial trading systems
→ Autonomous negotiation bots
→ AI-to-AI economic marketplaces
→ API-driven autonomous swarms.

The Takeaway:

Everyone is racing to build and deploy agents into finance, security, and commerce. Almost nobody is modeling the ecosystem effects. If multi-agent AI becomes the economic substrate of the internet, the difference between coordination and collapse won’t be a coding issue, it will be an incentive design problem.

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Eduardo P. @Zaexv

6 months ago

Quién para

La Opinión de Málaga @opiniondemalaga

6 months ago

El parque hinchable más grande del mundo abre sus puertas en Málaga: con 5.000 metros cuadrados de tirolinas, rocódromo y toboganes https://t.co/6PTTvGZxmL

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Zaexv retweeted

Google for Developers

@googledevs

6 months ago

Step away from the keyboard. The solution will find you. 🚶

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Zaexv retweeted

Fazt

@FaztTech

7 months ago

El CEO de Anthropic, la empresa detrás de herramientas como Claude Code y modelos como Claude Sonnet, dice que la ingeniería de software será "automatizable" en 12 meses aproximadamente. ¿Ustedes qué opinan?