AI in Science & Research: 6 real deployments

Using AI to generate medical systematic reviews and peer review services while advertising them as '100% human-written, never AI', with fabricated PhD staff credentials

Four US national laboratories run Meta vision models on secure infrastructure to analyze scientific imagery for the Genesis Mission.

Reported: Deployed on 300 A100 GPUs, the pipeline reduced grapevine drought-resilience analysis from about one month to roughly 15 minutes.

WSU and Google built a fully automated AI pipeline for wildlife camera-trap analysis, tested across Washington, Glacier National Park and Guatemala's Maya Biosphere Reserve.

Reported: Camera-trap analysis cut from seven months to under a week; matched human ecologists in 85-90% of cases.

Used Claude (Mythos Preview and Opus 4.8) to design protein binders against research targets validated by Adaptyv Bio and Twist Bioscience; Opus 5 processed raw NMR and LC-MS data

Reported: designed protein binders against 14 of 15 targets tested, hitting 22-35% success versus the typical 10-15% industry rate; Opus 5 processed raw NMR and LC-MS data in 23 and 19 minutes with purity within 0.1% of the lab's own reading

Google DeepMind's Co-Scientist, a multi-agent Gemini system that autonomously generates, debates, and refines scientific hypotheses, is deployed to all 17 U.S. DOE National Laboratories under the White House's Genesis Mission.

Reported: Early applications include novel drug repurposing candidates

ESA's EcoPulse detects 'animal panic' from satellite imagery for wildlife conservation, offered as custom analyses priced at 12K-45K euros.

Reported: 87% accuracy detecting animal panic from satellite imagery.