MACHINE-LEARNING

DALL-E and CLIP changed what's possible with AI. Here's why combining vision and language is about to transform enterprise applications.

BERT and GPT demonstrated transfer learning's power. Building AI models no longer requires billions in compute. Here's what fundamentally changed in 2019.

Most enterprise AI initiatives die quietly. I've watched dozens fail. Here's what truly separates the winners from the graveyard of abandoned ML projects.

Google's AutoML launched this year. Suddenly ML is accessible to non-experts. Is this genuine democratization, or just marketing genius? Here's my honest take.

ELMo launched in February. The NLP revolution is accelerating. Here's how language models will transform how enterprises find and process information.

AlphaGo Zero taught itself from scratch. No human data. Self-supervised learning just became the frontier. That changes everything for enterprise AI.

Google I/O 2017 showed TPUs, TensorFlow Lite, and models you can run on a phone. Machine learning isn't exclusive anymore.

TensorFlow 1.0 just launched. Meanwhile, most enterprises are still treating ML as a research curiosity. Here's the gap I see widening.