Explores the human role in the AI age, arguing we must value critical thinking, agency, and creativity over competing with AI on raw intelligence.
An introduction to reasoning in Large Language Models, covering key concepts like chain-of-thought and methods to improve LLM reasoning abilities.
Explores the rise of 'vibecoding'—AI-assisted no-code/low-code development—and its surprising viability for both technical and non-technical users.
Explores ethical boundaries and risks of AI, advising where human judgment should prevail over automation.
Argues that AI can improve beyond current transformer models by examining biological examples of superior sample efficiency and planning.
Introducing Physica, a Physics World Model AI that enforces physical laws to prevent errors in AI-generated simulations, moving beyond token fluency.
A computer science academic reflects on academia's role in shaping societal narratives, especially around AI, through open technology and sober assessment.
Explores AI's potential as a universal problem-solving tool, framing any challenge as a transition from a current state to a desired state.
Argues that current AI models are already capable of achieving Functional AGI through better orchestration of existing systems, not new model breakthroughs.
An analysis of the ethical debate around LLMs, contrasting their use in creative fields with their potential for scientific advancement.
Distinguishes between Functional AGI (replacing knowledge workers) and Technical AGI (true generalization), arguing Functional AGI's societal impact matters most.
A technical guide exploring IBM's Granite 3.1 AI models, covering their reasoning and vision capabilities with a demo and local setup instructions.
A guide outlining the top 10 personal and business risks associated with AI adoption, including failure to adopt and security concerns.
A tutorial on installing and running the Mistral AI large language model locally on a Linux system using the Ollama platform.
A guide to the best newsletters, blogs, and resources for staying updated on the fast-moving field of Artificial Intelligence in 2025.
Apple plans to transform Siri into a powerful AI by integrating it deeply with the Apple ecosystem, including personal context and cross-app features.
Argues for a balanced approach to AI, using it for discovery but doing important learning and thinking tasks manually to preserve meaning and growth.
Explores AI agents, their capabilities, and frameworks for development, focusing on tools, planning, and evaluation.
An overview of Microsoft Azure's suite of AI services, including prebuilt APIs, machine learning, and cognitive tools for building intelligent applications.
Argues that the 'age of data' for AI is not ending but evolving into an era of 'superhuman data' with higher quality and knowledge density.
