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It's the company's first public proof point after a year and a half spent building AI infrastructure largely out of public view.

The hacker used an employee's credentials to access source code, which revealed how Suno scraped decades of audio.

OpenAI has built an LLM super-hacker called GPT-Red that it uses as a sparring partner to help its other models boost their defenses against cyberattacks. Last week the company released the latest version of its flagship LLM, GPT-5.6. OpenAI says that training it against GPT-Red made the model its most robust release yet. GPT-Red automates…

arXiv:2607.09678v1 Announce Type: new Abstract: When LLM agents hand off information to one another, does the message format matter? Two literatures disagree: format-optimization work reports that structured messages cut cost without hurting accuracy, while format-restriction work finds that imposing structure degrades generation -- and neither measures what happens when a message traverses multiple hops, where copy fidelity, not one-shot generation, dominates. We introduce a controlled relay testbed: briefs of twelve programmatically generated atomic facts are re-encoded hop-by-hop in five formats (free NL, precision-instructed NL, JSON, triples, key-value) over six hops, scored by a fixed strong grader against programmatic ground truth, across two relay-capability tiers, a cognitive-load condition, and a paired-fork error injection. We find that message-format effects are tier-dependent. (i) Under faithful-relay instructions a strong relay is nearly lossless -- the documented "telephone-game" collapse does not occur -- and adding per-hop cognitive load leaves format-level fidelity unchanged (within +/-1.8 points) while raising generation cost by 24-53%. (ii) Under a weak (1.5B) r

arXiv:2607.09689v1 Announce Type: new Abstract: To leading order under local asymptotic normality (LAN), the confidence density a worker emits over a chunk of size $n$ is a Gibbs--Boltzmann measure $\exp\{-\beta E(\theta)\}$ whose inverse temperature is the sample size, $\beta=n$. Three consequences are exact in the Gaussian/linear case and first-order otherwise: disjoint chunks carry independent Boltzmann factors, so the MapReduce \emph{reduce}, read literally, is a partition function $Z=\int\prod_k h_k\,d\theta$ whose mode is precision-weighted (inverse-variance) pooling; frequentist consistency is the zero-temperature limit $T=1/n\to0$

Phone call data breaks out AI referrals for the first time. Calls from ChatGPT become leads more often than any other channel, but convert average. The post ChatGPT Calls Turn Into Leads More Often: Invoca Report appeared first on Search Engine Journal .

GA4's AI Assistant channel fragments traffic from a single source into three separate channels, making your AI referral numbers quietly wrong. The post GA4’s AI Assistant Channel Undercounts Your AI Traffic: How To Build One That Doesn’t appeared first on Search Engine Journal .

Google is adding AI image generation to AI Overviews and rolling out a redesigned Google Images homepage. Both start rolling out over the coming weeks. The post Google Revamps Image Search, Adds Generation To AI Overviews appeared first on Search Engine Journal .

Confidence score determines how to utilise outputs.