AI

When Anthropic first let us play with Claude Code, most of us imagined a “pair‑programmer” that could finish a function or debug a stack trace. That’s exactly what happened—developers fed it snippets, watched it autocomplete, and generally gave it a lot of love. But a few weeks later the same folks started asking Claude to rename their photo files, summarize meeting notes, and even draft a budget spreadsheet. In short, they were treating Claude like a very clever intern who could rummage through their desktop and hand back tidy results. ...

ChatGPT Go Is Finally Everywhere – What It Means for Everyday Users (and the Rest of Us) When OpenAI announced ChatGPT Go back in August 2025, the headline felt almost like a promise whispered in a crowded market: “AI for the masses, at a price that won’t make your wallet cry.” The rollout began in India—a smart move, given the country’s huge, price‑sensitive user base—and within a few months the plan had leapt onto 170 more country lists, becoming OpenAI’s fastest‑growing subscription tier. ...

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. ...

If you’ve ever tried to “read the mind” of a GPT‑4‑powered assistant, you know the feeling: you stare at a few lines of orchestration code and wonder why the thing just suggested buying a pineapple pizza for a corporate finance report. The answer isn’t in the handle_submit() you wrote; it’s in a sequence of invisible decisions that only a trace can reveal. That’s the premise of a recent TL;DR note I skimmed on a commuter train, and it got me thinking about how the whole discipline of software engineering is quietly being rewired. In the old world, the codebase was the bible. In the new world of AI agents, the trace—the step‑by‑step log of what the model actually did—has taken that role. ...

Picture this: You’re a doctor at the end of a grueling 12-hour shift. Your eyes are tired, your coffee has gone cold for the third time, and there’s still a stack of blood smears waiting to be analyzed. Each one contains thousands of tiny cells, and somewhere in that microscopic haystack might be the needle that indicates leukemia. Now imagine having an assistant that never gets tired, never loses focus, and — here’s the kicker — actually knows when it’s unsure about something. ...

If you blinked this week, you probably missed about seventeen major announcements in the tech world. Seriously, January 12-13, 2026, felt like someone accidentally hit the fast-forward button on the entire industry. We’ve got tech giants holding hands, robots learning new tricks, hackers getting hacked (oh, the irony), and enough security vulnerabilities to keep your IT department up at night. Grab your coffee — or maybe something stronger — because we’re diving deep into everything that happened. And trust me, there’s a lot to unpack. ...

Nous Research’s NousCoder-14B is an open-source coding model landing right in the Claude Code moment Nous Research, backed by crypto‑venture firm Paradigm, unveiled the open‑source coding model NousCoder‑14B, which was trained in just four days on 48 Nvidia B200 GPUs and reaches a 67.87 % accuracy on the LiveCodeBench v6 benchmark—about 7 percentage points higher than its base model, Alibaba’s Qwen3‑14B. The release includes not only the model weights but also the full Atropos reinforcement‑learning environment, benchmark suite and training harness, allowing anyone with sufficient compute to reproduce or extend the work. Training leverages “verifiable rewards” (binary pass/fail on executed code), dynamic‑sampling policies, and progressive context‑window expansion up to roughly 80 k tokens, while pipelining inference and verification to maximize GPU utilization. Researchers note that the 24 000 competitive‑programming problems used for training exhaust most high‑quality public data in the domain, prompting calls for synthetic problem generation and self‑play to overcome future data scarcity. With $65 million in funding, Nous Research positions its open‑source approach as a direct competitor to proprietary tools like Anthropic’s Claude Code, emphasizing transparency, reproducibility, and the next‑generation research directions of multi‑turn RL and autonomous problem creation. ...

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. ...

Lisa Su doesn’t do small announcements. When AMD’s CEO took the stage for the CES 2026 opening keynote, she came with a simple message that carried enormous weight: AI should be everywhere, for everyone. What followed was a comprehensive look at how AMD plans to make that happen, from warehouse-sized data centers all the way down to the laptop on your desk. But this wasn’t just AMD talking to itself. The company brought some serious partners along for the ride. OpenAI, Luma AI, Liquid AI, World Labs, Blue Origin, Generative Bionics, AstraZeneca, Absci, and Illumina all made appearances, each explaining how AMD hardware is powering their AI work. When you see that kind of lineup, you know something significant is happening. ...

Here’s something that should make you uncomfortable: we’re building machines that might be conscious, and we have no way to check. Not “no way right now.” Not “no way until better neuroscience tools arrive.” Dr. Tom McClelland, a philosopher at the University of Cambridge, argues in a recent analysis that we may never have a reliable method to detect consciousness in AI—and honestly, I’m not sure which possibility is more unsettling. ...

Here’s something I didn’t expect to be impressed by at CES 2026: a projector that works on curtains. Not well on curtains—that would be unrealistic—but at all. Samsung’s new Freestyle+ doesn’t care if you point it at a corner, a textured wall, or that off-white ceiling you’ve been meaning to repaint. It just figures it out. The company unveiled the portable projector ahead of this year’s Las Vegas tech showcase, and while “AI-powered” has become the tech industry’s favorite phrase to slap on anything with a processor, this one actually uses it for something useful: making projection less finicky. ...

Google’s December Drop: AI is Finally Getting Boring (In a Good Way) Every December follows the same script. We’re all trying to clear our desks for the holidays, our brains are essentially fried, and tech companies usually choose this moment to either bury a project or scream for attention one last time before the year ends. Google’s latest round of AI updates feels different. There are no “mind-blowing” sci-fi demos here. Instead, we’re seeing a shift toward utility—tools that actually address the minor, daily annoyances of being a person on the internet in 2025. It feels like AI is finally moving out of its “look what I can do” phase and into its “let me help you with that” phase. ...