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When I first saw the NVIDIA DGX H100 paired with BF16 precision, it felt like the go-to rig for scaling mixture-of-experts (MoE) models. Still, most teams are stuck worrying about price tags and the limits of their hardware.
When I first saw Moonshot’s K2 Thinking pop up on the repo, it felt like the open-source crowd finally got a serious contender. In the past weeks it’s already topping a handful of the usual benchmarks that developers and researchers keep an eye on.
A teacher’s desk sits empty in countless schools right now. The tech on the market looks sleek, yet the human side of education seems to be hitting a wall.
Apple seems to be leaning on a custom-built version of Google’s Gemini model for what it’s calling “Apple Intelligence.” After a string of hiccups that left its AI plans looking a bit shaky, the iPhone maker pulled the plug on some new Siri features...
When Google Cloud announced a wider rollout of its Agent Builder platform, I felt the AI-assistant space getting a bit crowded.
When I first saw a tool that could grab text straight from a URL, I wondered if it would matter to anyone fiddling with large language models.
Last week a ransomware crew slipped past a Fortune 500 security operations center in under a minute, and it felt like a wake-up call.
When I skimmed the latest list of the 18 most-downloaded open-source AI models from India, the first thing that jumped out was how many of them are speech-to-text tools.
Ever tried getting a TTS engine to read a whole novel? It usually trips up after a few seconds. The problem isn’t the voice itself so much as the way the model slices up the text.
When I skimmed the newest white paper on AI infrastructure, the numbers caught my eye. A group of researchers mapped not only the spike in compute cycles but also the widening environmental toll of each fresh model.
When Confluent rolled out its agent-ready streaming platform last week, the headline was clear: AI agents seem to need a constant flow of fresh data if they’re going to act on their own.
Open-source folks have been juggling flexibility versus safety for a while now when they plug big language models into their tools.
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