Exploring the evolution of software and the emergence of Large Language Models (LLMs) as a new programmable paradigm.

Exploring the multifaceted concept of intelligence, both natural and artificial, and its role in addressing complex global challenges.

Exploring the potential of AI systems that can rewrite their own code to achieve continuous self-improvement and adapt to new challenges.

An analysis of the realism of AI predictions, exploring the potential economic and societal impacts.

Is the AI copilot truly an innovative tool, or does it represent a descent into mediocrity by encouraging laziness and a detachment from the underlying machine?

A critical analysis of the “AI 2027” scenario, examining its plausibility and potential impact on the AI landscape.

AI is transitioning from imitating human data to learning from its own experiences, promising superhuman capabilities by interacting directly with the environment.

The rise of AI, particularly LLMs, presents both opportunities and challenges to our ability to focus and think critically.

As AI tools become increasingly prevalent in computer science, the ability to focus and deeply understand problems may become the most crucial skill for engineers.

Reflecting on a career in programming, what are the common pitfalls and regrets that developers face?