📈 Data to start your week

The coming supply shock; extreme heat; baby bust & growth boom++

Hi all,

Here’s our short Monday roundup of data signals across AI, energy and markets:

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1. A GPU wave is ahead of us. More than 95% of the Grace-Blackwell GPUs have not yet been deployed, even though the chip has been shipping since December 2024.¹ (h/t Air Street Press)

   

2. Freelance hunting. Fable 5 now completes 16% of real freelance projects at a quality just as good as that of human professionals, according to the Remote Labor Index. This is about double the previous best².

   

3. David vs Goliath. A 35-billion-parameter model, trained differently³, now matches 1-trillion-parameter models on some long-horizon benchmarks.

4. Chinese pharma boost. Chinese biotech companies’ licensing deals are up 87% in the first five months of the year compared to the same period last year.

5. Wet-lab assistance. In a near-autonomous loop, GPT-5.4 helped Molecule.one’s lab run 10,080 reactions and increased the average yield in the Chan-Lam process⁴ by around 50%.

6. Holding swap. Central banks worldwide now hold more gold than US Treasuries – this is the first time since 1996.

   

7. Wealth concentration. Nearly half of all income earned in the US belongs to the top 10% of earners, the highest since WWII.

8. Fewer babies, richer adults? Across countries, a one-percentage-point lower birth rate in 1950 was associated with almost 27% higher GDP per working-age adult over 1970-2020, with no change to aggregate GDP.

9. Extreme heat. French utility EDF took almost 10% of its nuclear fleet offline (some 6.2 gigawatts) as river temperatures breached the threshold for cooling.

Thanks for reading!

1. Deployed describes chips that have been installed and are in active use. The state of announced chips, whether delivered or not, is not broken out.

2. The Remote Labor Index aims to measure how well AI agents can complete real freelance projects, spanning video, audio, 3D/CAD design, data analysis, and more, with human evaluators as judges of performance.

3. Using a new horizon-scaling method for AI agents. Horizon scaling refers to supervising agents on long‑context, multi‑step trajectories and training the entire decision process, not only the end answers.

4. This process is important in forming carbon-nitrogen bonds needed in many medicines.