Computational genomics pioneer Jimmy Lin explains what many machine learning-focused biotech companies and get wrong about hiring, data, and communication.
A GPT-3-like AI model for science would accelerate innovation and improve reproducibility. Creating it will require us to unlock scientific publications.
Hand-wringing over the latest New Thing isn't unique. In fact, it tends to follow a predictable, four-step cycle fueled by politicians, scientists, and media.
AI-created models of the brain are emerging that have applications in art, advertising, and health. Adoption of AR and BCI will further enhance model utility.
A recap of artificial intelligence and machine learning coverage in Future so far in 2022, as well as the biggest advances in AI/ML research.
Daphne Koller explains why some fail the academia-to-biotech transition and identifies what we'll need for AlphaFold-level successes across biology and biotech.
As enterprises grow their AI footprints, they must pay attention to data quality and real-world conditions to ensure what works in the lab works in production.
The decade of data is here, as shown by bellwether startups across the most exciting categories, like AI/ML, ELT and orchestration, and data observability.
As traffic explodes, programmable chips are creating ways for the biggest companies to differentiate, with major implications for the industry.