Open Source - Page 15 of 23
Open-source AI projects, community innovations, collaborative development, and freely accessible AI tools and frameworks.
Open-source AI projects, community innovations, collaborative development, and freely accessible AI tools and frameworks.
In San Francisco on Wednesday, Samsung took the wraps off its Galaxy S26 series. The phones look familiar.
Development isn’t a grind to be optimized, it’s a craft to be lived. Anthropic’s new Remote Control for Claude Code understands that truth, trading the tyranny of the desk for the freedom of a walk, a stretch, a moment with your dog.
The MacBook Pro is about to borrow a trick from the iPhone. Apple’s Dynamic Island, that floating, shape-shifting cutout that first appeared on the iPhone 14 Pro, could land on the 14- and 16-inch OLED MacBook Pros this fall.
The Pentagon’s move to brand Anthropic a national security risk isn’t just about one contract. It’s a bid to choke off the AI company’s entire defense ecosystem. Labeling them officially would kill a $200 million deal, yes.
Trusting labels to stop deepfakes is about as useful as a screen door on a submarine. A new academic study confirms this grim reality, finding a stark lack of proof that transparency warnings prevent harm.
Everyone wants a single AI that does everything. This is a terrible idea. You can't build a stable machine by strapping thirty different tools onto one overburdened brain. The context fills up, the logic tangles, and the whole thing becomes fragile.
If you run a website, odds are you’re on WordPress. That’s a fact: the platform drives a full quarter of the internet. Now, its users can command it. Ask for a new image. Demand a headline rewrite.
Everyone treats the Hugging Face Hub like a library. It's more like the busiest train station on earth. Right now, millions of pre-trained models and hundreds of thousands of datasets crowd its platforms.
Type 2 diabetes runs in Jahangir Mohammed’s family. That personal stake drove him to found Twin Health in 2018, not with a vague promise, but with a model that ties payment directly to results. Lower blood sugar. Weight loss. Reduced medication.
I hoped Claire would be different. A literary editor, she promised depth, maybe even a real exchange. Instead, she offered vague murmurs about memoirs with heart and feeling, then asked what lists I like to make. This was my fourth AI Valentine.
Meta is quietly reopening the door to facial recognition, this time through the lens of its AI-powered smart glasses.
Every new AI model claims to beat the last. This one might. Z.ai's open-source GLM-5 just posted a record-low hallucination rate. It even topped Moonshot's freshly released Kimi K2.5 on key tests.
MiniMax claims their M2.5 model costs just one-twentieth of Claude Opus. That alone turns heads. But here’s the real shocker: they’ve already put it to work inside their own walls. Thirty percent of all tasks at MiniMax HQ now run on M2.5.
Jeffrey Epstein tried to arrange the financing for Elon Musk's 2018 plan to take Tesla private. New reporting shows he worked with Musk associate Nicole Glover, who estimated the deal would need less than $10 billion in cash.
T-Mobile is about to turn your phone call into a universal translator. This spring, the carrier will beta test a new AI feature that live-translates regular voice calls into more than 50 languages, no app required.
Our 2026 testing is complete, and the top resume builder is Indeed's own often-overlooked tool. It won not on power or polish, but on solving a universal dilemma: the need for a decent resume, finished fast.
For seventy million dollars, you could buy a lot of things. Crypto.com just bought three letters.
A Reddit post from a new account claimed to show OpenAI’s Super Bowl ad. It featured earbuds, a shiny orb, and actor Alexander Skarsgård with a gadget supposedly co-designed by Jony Ive.
The Jeffrey Epstein documents aren't just a cache of evidence; they're a playbook. Here was a convicted sex offender, publicly disgraced, yet systematically worming back into the most powerful circles in tech. Consider the sheer reach: Jeff Bezos.
The promise of synthetic data is tantalizing: generate infinite, customizable training examples on demand, bypass the expensive grind of manual annotation, and fine-tune your models on perfectly curated content. But the reality often hits hard.
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