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.
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.
Still energized from an extraordinary exchange with poolside’s leadership team, exploring a not-so-distant future where humans and AI agents collaborate seamlessly.
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.
The Liga dos Inovadores podcast just released a new episode featuring a conversation about our work at Critical Software and the unique challenges of deploying AI in Defense (OVERSEE) and Space (Karvel).
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!
Build ML pipelines with DSPy powered by Meta’s Llama 3 70B Instruct running on Amazon SageMaker — shifting from prompt engineering to programmatic LLM workflows.
Deploy a high-quality translation model at scale using Amazon SageMaker Serverless Inference — bringing machine translation to languages that need it most.
Create cloud-native, AI-powered document processing pipelines on AWS using Project Lakechain — a framework for building sophisticated document transformation workflows.
Build your own virtual software company using Amazon Bedrock ⛰️ and ChatDev 👨🏼💻 to develop custom applications through LLM-powered multi-agent collaboration.
My journey with RAGmap 🗺️🔍 and RAGxplorer 🦙🦺, featuring an accessible introduction to embeddings, vector databases, dimensionality reduction techniques, and advanced retrieval strategies.
A personal exploration of the fascinating convergence between LLMs and operating systems, with thoughts on how they might collaborate in the near future.
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! 😛
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.