Baryon Oscillation Spectroscopic Survey (BOSS) map, the largest known structure in the universe

37 posts on AWS, GenAI, agents and building AI that actually holds up. Pick a topic below, or browse everything.

Build AI that matters 🌱 is now live!

Build AI that matters is a deck focused on building AI that doesn’t just work in demos - it works in the real world, under pressure, when it matters most.

This isn’t about chasing state-of-the-art or shipping fast. It’s about building AI systems you can actually trust.

Dependable AI in Airborne Systems ✈️

Integrating AI into safety-critical airborne systems presents profound challenges — this talk addresses the complexities of ensuring reliability, predictability, and compliance with stringent aviation safety standards.

poolside Offsite in Peniche 🥽

Still energized from an extraordinary exchange with poolside’s leadership team, exploring a not-so-distant future where humans and AI agents collaborate seamlessly.

AI x Innovation @ AIHub 🧠

The AI x Innovation team visited the AIHub by Unicorn Factory Lisboa for an inspiring exchange with startups pushing the boundaries of AI.

AI Red Teaming @ Critical Software 🟥

In collaboration with the AIHub by Unicorn Factory Lisboa, we’re hosting a semi-private AI red teaming exercise in our Lisbon office — bringing together enterprises and leading startups to stress-test AI systems in a controlled, ethical, and collaborative setting.

📨 DM me for more details.

Red-tinted matrix-style digital rain animation

Safety-Critical AI is now Awesome 🚀

Awesome Safety-Critical AI is a curated collection exploring AI’s role in safety-critical systems — where failure means loss of life, major property damage, or environmental harm.

This isn’t about polishing demos or chasing benchmarks. It’s about anticipating chaos and designing systems that can withstand it.

This isn’t just another awesome list. It’s a manifesto and a call to action!

🌟 Check it out and star it on GitHub!

Hacking GraphRAG with Amazon Bedrock 🌄

Run GraphRAG pipelines powered by Amazon Bedrock using LiteLLM proxy — combining knowledge graphs with retrieval-augmented generation.

📝 Read the full article on AWS Community.

Mapping embeddings: from meaning to vectors and back

My journey with RAGmap 🗺️🔍 and RAGxplorer 🦙🦺, featuring an accessible introduction to embeddings, vector databases, dimensionality reduction techniques, and advanced retrieval strategies.

📝 Read the full article on AWS Community.

📢 UPDATE: An expanded, interactive version is now available at critical-ai.dev/MappingEmbeddings.

A Tour of GenAI 🚀 - There and Back Again

My perspective on the GenAI narrative — no hype, no hubris, no hogwash.

📢 UPDATE: Now live at critical-ai.dev/GenAI!

Time in Machine Learning Engineering ⏳

This article started out as a joke and didn’t wander very far in state space. It is a witty and not-so-rigorous attempt to demonstrate the importance of time in ML projects that will annoy most mathematicians and alienate some physicists. There’s some truth in it… it’s just really hard to find. Enjoy! 😛

📝 Read the full article on Medium

WBME Workshop - Machine Learning for Medicine and Healthcare 👨‍⚕️

An exploration of machine learning and its transformative impact on healthcare — from the expert systems revolution of the 1980s to today’s AI-driven diagnosis, prognosis, and treatment of SARS‑CoV‑2. Discover how AI is reshaping medicine and what the future might hold.

📝 Full content available on GitHub

For more information about this event, visit 12th WBME - Workshop on Biomedical Engineering


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