Signal/Noise
Signal/Noise
2025-01-11
Without specific news articles to analyze, I cannot provide the strategic analysis that Signal/Noise readers expect. The format demands connecting real developments into coherent strategic narratives about power, money, and control in AI—not speculation or generic commentary about hypothetical trends.
Analysis Requires Signal
Signal/Noise exists to cut through the noise of daily AI announcements and reveal the strategic chess game underneath. This requires actual moves on the board—real company announcements, funding rounds, product launches, regulatory developments, or executive changes that reveal shifting power dynamics. Without concrete developments to analyze, any commentary would be exactly the kind of content-for-content’s-sake noise this publication was created to eliminate. The value proposition is simple: we take the headlines you’ve already seen and show you what’s really happening. No headlines means no analysis worth your time. The most honest thing we can do when there’s insufficient signal is acknowledge it rather than manufacture insights from thin air. In a world where AI can generate infinite analysis of nothing, the scarcest resource isn’t commentary—it’s the discipline to only speak when there’s something meaningful to say.
Questions
- What does it mean for analytical credibility when every platform demands daily content regardless of actual developments?
- In an attention economy, is restraint from analysis a competitive advantage or a missed opportunity?
- When AI can generate infinite commentary, what makes human strategic analysis irreplaceable?
Past Briefings
AI’s Blind Geniuses
Everyone's measuring AI adoption. Nobody's measuring AI results. If Jensen Huang and Alfred Lin can't agree on a scorecard, that tells you more about the state of AI than any benchmark can. THE NUMBER: 0.37% or 100% — the gap between the best score any AI achieved on ARC-AGI-3 (Gemini 3.1 Pro's 0.37%) and Jensen Huang's claim that we've already reached AGI. Even among the most credible voices in AI, nobody can agree on whether we're at the starting line or the finish line. That uncertainty isn't a bug. It's the operating environment. And it's exactly why the question of...
Mar 25, 2026OpenAI Killed Sora 30 Minutes After a Disney Meeting. The Kill List Is the Strategy Now.
$15M/day to run, $2.1M lifetime revenue. The pivot to Codex puts them behind Claude Code — in a market China is about to commoditize from below. THE NUMBER: $15 million / $2.1 million — the daily operating cost of Sora vs. its lifetime revenue. When a product costs 2,600x more to run per day than it has ever earned, killing it isn't a choice. It's arithmetic. The question is what that arithmetic tells you about everything else OpenAI is doing. OpenAI killed Sora this week. Not quietly — 30 minutes after a working session with Disney, whose $1 billion investment...
Mar 24, 2026I’m a Mac. I’m a PC. And Only One of Us Is Getting Enterprise Contracts
THE NUMBER: 1,000 — the number of publishable-grade hypotheses an AI model can generate in an afternoon. Terence Tao, the greatest living mathematician, says the bottleneck is no longer ideas. It's knowing which ones are true. Two engineers hacked an inflight entertainment system this week to launch a video game at 35,000 feet. The airline gave them free flights for life. The hacker community on X thought it was the coolest thing they'd seen all month. Every CISO reading this just felt their blood pressure spike. That's the divide. Not between capabilities. Between cultures. Remember those "I'm a Mac, I'm...