The labs and the buzzwords behind AI's big bets

• Here's a rundown of the AI power players and the shared language shaping the conversation.

The heavyweights: Who's building what

State of play: Several AI labs dominate the U.S. business and investor conversation. Here are the key firms, in alphabetical order:

• Anthropic: The maker of Claude. The CEO, Dario Amodei, has taken a safety-focused, business-first approach, launching tools like Claude Code and Cowork to attract business contracts.
• Google DeepMind: The maker of Gemini. CEO Demis Hassabis is a Nobel Prize-winning scientist, focused on fueling research with AI. Google already has a strong business customer base, which could translate into future revenue for Gemini.
• Meta: The maker of Llama. CEO Mark Zuckerberg has positioned Meta as a major competitor to OpenAI and Google. The company releases so-called open models while weaving AI into Facebook, Instagram and WhatsApp.
• OpenAI: The maker of ChatGPT. CEO Sam Altman is focused on dominating the AI race. Altman's business model currently includes enterprise subscriptions and offerings like Codex, its coding tool. OpenAI is also beta testing ads as a potential future revenue stream.

The buzzwords: What insiders are saying

This is the shorthand used by executives and investors to describe how fast AI is getting more capable — and more independent.

• Vibe coding: Using AI to generate code from high-level prompts (aka, vibes). With vibe coding, a chatbot can build an app or website mostly by itself, but a human must still debug and refine it.
• Agent swarms: A "swarm" is a group of specialized AI agents working together to solve a complex problem. Using agentic AI, AI-powered systems can act autonomously to accomplish a task without consistent direction from a user.
• Recursive learning: When AI teaches itself, using its own outputs to inform its next version, potentially creating a feedback loop of rapid improvement without needing human-generated data. While recent models from major AI labs have helped train themselves, they are mostly still trained using human-created data.
• Human in the loop: This means what it sounds like: Keeping a person involved to review, approve or intervene, especially when AI systems act autonomously.
• Model Context Protocol (MCP): An open-source framework founded by Anthropic that lets a model securely connect and interact with other apps or data systems. This allows an AI model to talk to Excel or PowerPoint, executing tasks autonomously.

• METR curve: Derived from the nonprofit METR (Model Evaluation and Threat Research), this tracks how long it takes AI to autonomously complete tasks without human intervention. That baseline has been increasing exponentially, doubling in about 7 months on average, according to their research. Industry insiders rely on this as a means of sussing out AI's progress.
• HALO: For markets nerds, it's an acronym for "heavy assets low obsolescence." The term is used to refer to the HALO effect around stocks or assets that are tangible (aka, not replaceable by AI). After years of a tech-driven rally, real-world stuff is cool again for investors. Gold is a recent example, up over 23% year-to-date.

The "North Stars": Where AI is heading

• AGI (artificial general intelligence): This is the point where an AI can perform any intellectual task a human can do. AI CEOs ranging from OpenAI's Altman to Google DeepMind's Hassabis increasingly hint that we are within a few years of this milestone.
• The singularity: A hypothetical point in the future where technological growth accelerates beyond human control and becomes irreversible.

The bottom line: The language of AI is still being written, but understanding it is one thing you can actually control.