Topic 41: What's Cool About AlphaEvolve and Codex?

Such a cool week! AI tools are finally getting good enough to fit naturally into the developer workflow. Coding assistants turn into our collaborators, allowing us to save time spent on repetitive coding tasks and achieve real productivity gains. In line with Microsoft’s focus on agentic web and GitHub Copilot updates, presented at Microsoft Build, today we decided to explore other new important coding agents that deserve your attention: self-evolving Google DeepMind’s AlphaEvolve and first cloud hosted Autonomous Software Engineer (A-SWE) OpenAI’s Codex. (Coding agents and models are certainly trending this week with Google’s asynchronous coding agent Jules, Mistral’s Devstral coding model etc also announced).

Google DeepMind introduced AlphaEvolve just ahead of the Google I/O. It’s an evolutionary coding agent designed to autonomously discover novel algorithms and scientific solutions. It’s the breakthrough that we really needed to reshape how AI can optimize engineering algorithms (even the building of hardware) and solve complex problems. Meanwhile, Codex from OpenAI is a powerful AI-powered coding assistant that writes, tests, and fixes code. It works safely with your repository and acts as a virtual coworker within ChatGPT. Let’s explore what is so special about these releases, how they work and revolutionize coding and AI in general!

In today’s episode, we will cover:

• Evolution is the key: Google DeepMind’s AlphaEvolve

  • How does AlphaEvolve work?

  • Achievements of AlphaEvolve

  • Not without limitations

• OpenAI’s Codex coding assistant

  • How does Codex work

  • How good is Codex?

  • Codex CLI:

  • Current limitations

• Conclusion

• Sources and further reading

Evolution is the key: Google DeepMind’s AlphaEvolve

Let’s start with Google DeepMind, which “Alpha” developments have been revolutionizing not only AI field for a very long time. Do you remember the legendary AlphaGo, which was first AI system to defeat a world champion in the complex board game Go? Then came AlphaZero, a general-purpose game-playing AI that mastered chess, shogi, and Go without human data. It learned on its own through self-play, and it was a moment when Monte Carlo Tree Search (MCTS) shined as a powerful algorithm to decide which move to play next.

One of the most outstanding breakthroughs is AlphaFold, which solved one of biology’s biggest mysteries: how to predict a protein’s 3D shape just from its amino acid sequence. Thanks to combination of machine learning, evolutionary biology, and structural modeling, it has revolutionized our ability to understand proteins and saved years of labs work. It predicted the structures of over 200 million proteins and sped up drug discovery and medical research. After all, AlphaFold brought its creators, Demis Hassabis and John Jumper, the Nobel Prize in Chemistry.

Google DeepMind’s problem-solving tools are also notable for their achievements. AlphaGeometry excels at solving complex geometry problems, performing comparable to top human competitors in mathematical olympiads. AlphaProof, combining language models with reinforcement learning to translate natural language problems into formal proofs, achieved results on par with silver medalists in the International Mathematical Olympiad.

As we can see Google DeepMind’s developments go beyond just AI, serving for practical fields, which are crucial for our world, and building the most powerful algorithms that can learn on their own. And now its time for the new AlphaEvolve.

At its core, AlphaEvolve is an advanced AI tool that helps LLMs become even better at solving very complex problems – like improving computer systems or tackling scientific challenges. It’s a coding agent inspired by the concept of evolution, which works similar to natural selection. It tries out changes to the code, gets feedback, and keeps improving over time. This tool automates part of the scientific discovery process, which involves brainstorming ideas, trying things out, learning from failures, and refining results. This process can take years, but AlphaEvolve speeds this up by letting AI do a lot of that work.

Let’s break down what technologies stay behind AlphaEvolve.

How does AlphaEvolve work?