What to expect from Google this week

2026-05-18 · Source: MIT Technology Review · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation · Depth: Intermediate, quick

Summary

Google is entering its annual I/O developer conference in 2026 as a distant third in the foundation model race, particularly in coding capabilities, where Anthropic's Claude Code and OpenAI's Codex significantly outperform Google's offerings. This has reportedly led to some DeepMind engineers using Claude for their work. The conference is expected to feature Google's efforts to improve its coding models, possibly with an update to its Antigravity agentic coding platform, though a transformative comeback is not anticipated immediately. Google's strengths lie in AI for science and health, areas where it has previously released tools like the AI co-scientist and AlphaEvolve, and is set to make its AI-powered Health Coach publicly available. The conference will also unfold amidst the Elon Musk v. Sam Altman trial and internal controversies, including a recent employee protest against a DoD deal.

Key takeaway

For AI Engineers evaluating foundation models for coding tasks, you should recognize that Google's current offerings lag behind competitors like Anthropic's Claude Code and OpenAI's Codex. While Google may announce updates at I/O, do not expect immediate parity; consider alternative models for critical coding workflows. However, if your focus is on scientific or health AI, Google's established leadership and upcoming tools like Health Coach warrant close attention for potential advancements.

Key insights

Google faces significant challenges in AI coding but maintains a strong lead in AI for science and health applications.

Principles

• Coding capabilities define foundation model reputation.
• Scientific AI is a distinct competitive advantage.

In practice

• Explore Google's AI co-scientist for hypothesis generation.
• Investigate AlphaEvolve for mathematical problem-solving.

Topics

• Google I/O
• Foundation Models
• AI Coding
• AI for Science
• Health AI

Best for: AI Engineer, Machine Learning Engineer, Research Scientist, AI Scientist, Director of AI/ML, Tech Journalist

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Editorial summary, takeaway, and curation by AIssential. Original article published by MIT Technology Review.