Treating annotation as a data understanding problem, rather than a labeling workflow challenge, can systematically drive down error rates and reduce the time and cost of producing high-quality data ...

Most AI initiatives fail not because the models are weak, but because organizations aren’t built to sustain them. A large ...

For years, AI in drug discovery has been held back by a deceptively simple problem: the data isn’t good enough. Mountains of sequencing, pooled perturbation studies, and those mixed-cell experiments ...