Trojan misuses Microsoft Phone Link app to steal your passwords
getty Follow ZDNET: Add us as a favorite source On Google. ZDNET Highlights Researchers have discovered a Trojan, Cloudz, that uses a plugin to intercept and steal sensitive information through …
The first week of the Musk vs. Altman trial: What it was like in the room
And then the lawyers kept talking about the destructive risks of AI and whether Elon Musk or OpenAI were better positioned to handle AI safety. And the judge was kind …
Sakana AI introduces KAME: a tandem speech-to-speech architecture that injects LLM knowledge in real time
The fundamental tension in conversational AI has always been a binary choice: respond fast or respond smart. Real-time speech-to-speech (S2S) models – the kind that power natural-feeling voice assistants – …
Peter Thiel backs $1 billion ocean data center start-up powered by waves
Peter Thiel is leading a $140 million investment in a US start-up that plans to use wave energy to fuel vast fleets of floating data centres, as Silicon Valley’s quest …
Frontier AI models are providing specific, actionable instructions to carry out a bioterror attack
Sign up today to see the future Cutting-edge innovations in science and technology cannot be forgotten There’s a pretty big list of things an AI assistant should refuse to help …
The federal data paradox: rich in data, poor in access
Industry results: Federal agencies have invested billions in data infrastructure. Much of that investment is still locked behind systems that front-line decision makers can’t interrogate without technical intermediaries. By casey …
A coding implementation to explore and analyze the TaskTrove dataset with streaming parsing visualization and validator detection
filename_counter: Counter = Counter() all_json_keys: Counter = Counter() samples_for_show: List = () for i, row in enumerate(tqdm(ds_test, desc=”inspecting structure”, total=200)): if i >= 200: break p = parse_task(row(“task_binary”)) if p(“format”) …
A developer’s guide to systematic prompting: mastering negative constraints, structured JSON output, and multi-hypothesis verbal sampling.
Most developers treat prompting as an afterthought – write something appropriate, observe the output and iterate if necessary. This approach works until reliability becomes critical. As LLMs advance into production …