1967 called. It solved your AI scaling problem.

DeepSeek just solved a critical AI scaling problem using an algorithm from 1967. Their new manifold-constrained Hyper-Connections (mHC) architecture cuts signal amplification from 3000x to just 1.6x—a 1873x stabilization gain. The secret sauce? The Sinkhorn-Knopp algorithm, a matrix normalization technique that predates the moon landing. Trillion-parameter dense models just became viable.

We also published a complete NotebookLM tutorial. Google’s source-grounded AI tool has gone viral for Audio Overviews—the feature that turns your documents into podcast-style conversations. Upload a research paper, get two AI hosts discussing it in 3 minutes. Stanford found 87% fewer hallucinations versus ChatGPT. It’s free.

Speaking of AI coding, Cursor published research on multi-agent scaling that’s worth your attention. They ran hundreds of concurrent AI agents on single codebases for weeks—and built a web browser from scratch (1 million lines, 1,000 files). A Windows 7 emulator took 1.2M lines. The key insight: hierarchical “planner” and “worker” roles outperformed flat agent structures.

Meanwhile, OpenAI invested in Merge Labs—Sam Altman’s brain-computer interface startup—as part of a $252 million seed round at an $850M valuation. The company uses molecules instead of electrodes and ultrasound instead of implants. OpenAI says BCIs will create “a natural, human-centered way for anyone to seamlessly interact with AI.”

And the AI coding wars keep escalating. Replit is raising $400M at a $9B valuation—tripling its September valuation. The company generated $240M in revenue in 2025 and expects to hit $1B in 2026. For context: Cursor’s Anysphere raised $2.3B at $29B late last year. Code is the new battleground.