we are NOT PREPARED for the end of 2026

2026-05-22 · Source: Wes Roth · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Emerging Technologies & Innovation, Capital Markets & Investment Management · Depth: Intermediate, extended

Summary

Google I/O showcased significant AI integration, embedding Gemini across Chrome, Docs, Gmail, and YouTube, including an "Omni video generator" that "watches" and understands video content beyond text. This reflects a "world model" vision championed by Demis Hassabis, contrasting with the "code-focused AI" approach of recursive self-improvement favored by others. The rapid pace of AI is evident in breakthroughs like OpenAI's model disproving an 80-year-old geometry conjecture by Paul Erdos, demonstrating AI's utility in frontier mathematical discovery. The discussion also covers upcoming IPOs for OpenAI, Anthropic, and SpaceX, with valuations "juice to the gills," and the potential for space-based AI infrastructure, contingent on reducing launch costs from \$1,600 per kilo to \$200 per kilo by 2035. The speakers also touch on Meta's shift to a more closed AI strategy.

Key takeaway

For investors evaluating the rapidly evolving AI market, recognize that while IPOs like Anthropic and SpaceX offer high-growth potential, their valuations are often inflated at launch. Your strategy should prioritize dollar-cost averaging over time to mitigate initial volatility. Consider Google stock as a diversified bet, given its foundational AI infrastructure (TPUs) and broad consumer-facing agentic ecosystem, which positions it strongly against competitors like Nvidia and OpenAI.

Key insights

AI development is rapidly advancing across diverse modalities, from integrated consumer agents to frontier scientific discovery, reshaping technology and investment.

Principles

• Intelligence is exceptionally broad and can emerge from diverse data modalities.
• Deep understanding cannot be outsourced to AI, despite its research assistance.
• The path of least resistance in AI adoption may hinder genuine comprehension.

Method

AI models are increasingly used to narrow down vast problem spaces, allowing human experts to formalize solutions.

In practice

• Integrate Gemini into daily workflows for contextual assistance.
• Utilize AI for initial research and data gathering, but verify understanding.
• Explore AI-powered tools like smart basketballs for novel data analysis.

Topics

• Google AI Ecosystem
• Large Language Models
• AI Investment Strategy
• Space-based Compute
• Mathematical AI
• AI Ethics

Best for: Research Scientist, AI Scientist, Director of AI/ML, Investor

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Editorial summary, takeaway, and curation by AIssential. Original article published by Wes Roth.