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A major Italian bank has fallen victim to what's being described as a sophisticated AI-driven fraud scheme, with criminals using artificial intelligence to deceive staff and siphon off millions. It's a sharp reminder that as AI tools become more convincing, financial institutions face threats that traditional security training simply wasn't built to handle.
On a different note, a developer has quietly released a simple GPU job scheduler, born out of personal frustration during model training experiments. When out-of-memory crashes kept derailing multiple simultaneous runs on a single GPU, they built their own queuing solution — and then opened it up for others facing the same bottleneck. It's exactly the kind of practical, unglamorous tooling that keeps the broader AI research ecosystem moving.
And stepping back from the day-to-day, writer Noah Smith is asking where the so-called intelligence explosion actually is. Drawing on the work of futurist Ramez Naam, the piece questions whether the dramatic recursive self-improvement scenario so many in the AI world have anticipated is arriving on schedule — or whether the curve is bending in ways we didn't quite predict.
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