DeepLearning

When Jensen Huang took the stage at the J.P. Morgan Healthcare Conference this week, I expected a typical tech‑heavy keynote about GPUs and cloud. Instead, he and Eli Lilly’s chair‑and‑CEO Dave Ricks spent a cozy fireside chat sketching a “blueprint for what’s possible” in drug discovery. Their announcement? A $1 billion, five‑year AI co‑innovation lab in the San Francisco Bay Area that promises to marry the raw compute muscle of NVIDIA’s DGX SuperPODs with Lilly’s century‑old drug‑making know‑how. ...

Happy New Year, everyone! If you thought 2025 was wild for artificial intelligence, the first week of 2026 just looked at the calendar and said, “Hold my beer.” We are only seven days into the year, and we’ve already seen enough major announcements to fill a whole quarter. CES 2026 in Las Vegas has been an absolute whirlwind, and combined with some massive regulatory shifts and research breakthroughs, it’s clear that this year isn’t going to be about incremental updates. We’re talking fundamental shifts in how AI is built, deployed, and governed. ...

Have you ever wondered how a neural network learns to understand complex things like language or images? A big part of the answer lies in a component that acts like a tiny decision-maker inside the network. This component is the activation function, and it is a critical element that significantly impacts the performance of deep neural networks. Understanding these functions is key to grasping how a network goes from seeing random data to recognizing sophisticated patterns. So, let’s explore what they are, why they are so essential, and how they have evolved. ...