The Answer Engine AI News · Sydney

OpenAI is building out the pieces of an alternative to the traditional app store model, turning ChatGPT into a place where software can be discovered and used by people and AI agents alike.

The new round is anticipated to be the company's last before its delayed 2027 public debut.

When customers talk about AI costs, the conversation usually starts with token prices and ends with access to the latest, most capable model in the cloud. Do they always need that level of capability? Not necessarily. But that is often where the conversation goes. As AI moves from experimentation to production, model choice is only…

arXiv:2609.31763v1 Announce Type: new Abstract: Long-context clinical AI systems can miss relevant patient history when prior admissions fall outside the active reasoning context. In ICU monitoring, this can cause early vital-sign drift to appear nonspecific even when it resembles a prior deterioration pattern. SMARtCARE addresses this gap through a four-state clinical decision-support architecture: Stable, Meta-cognitive, Assisted, and Regulated (Revoked). Rather than automatically retrieving prior records, SMARtCARE uses a lossy six-channel fingerprint of the patient's prior trajectory. When current drift matches that fingerprint and the prior record is absent from context, the system raises a Meta-cognitive escalation for clinician review; full retrieval occurs only through clinician action in the Assisted state. A patient-identity guard is designed to enforce correct attribution across data loading, logging, and audit layers. Evaluation combines a synthetic Monte Carlo study that validates the state-transition logic and estimator stability, not clinical performance, with real-data runs on both the MIMIC-III and MIMIC-IV Clinical Database Demos. On MIMIC-III, one prior-pattern r

arXiv:2609.31784v1 Announce Type: new Abstract: Open-weight models are often released, fine-tuned, aligned, merged, and re-released, making provenance audits ask not only whether checkpoints are related, but also which checkpoint came first. Many existing model-provenance methods are designed for a base-known audit setting: given a victim or source model, they test whether a suspect model is related to it. Although these audits are framed as source-to-suspect tests, their underlying evidence is often symmetric, relying on representation similarity, weight similarity, behavioral fingerprints, or correlation statistics. Symmetric pairwise comparisons can detect relatedness, but they cannot by themselves orient relationship between checkpoints A and B. We therefore introduce a local geometric comparison: instead of comparing two checkpoints directly, we add a third same-family checkpoint as a witness and compare the geometry around each candidate endpoint. Direction is inferred by asking which candidate behaves more like a branching parent. Motivated by this idea, and by the empirically observed asymmetry between parent-anchored and child-anchored witness-overlap distributions, we pro

A report using Similarweb panel data breaks down ChatGPT ad click-through rates by market and tracks how often the top ChatGPT advertisers changed. The post ChatGPT Ad CTR Topped 1% In 4 Markets, Not In The U.S.: Report appeared first on Search Engine Journal .

Better AI marketing starts with testing assumptions, aligning brand messaging, and building evidence into PR pitches before publishing. The post AI Won’t Kill Us All, But It’s Rewriting How Marketers Have To Work appeared first on Search Engine Journal .

Google and Uberall explain how to improve local AI-search readiness through accurate Business Profiles, relevant content, review responses, and location-level measurement. The post Google On What’s Next In AI Search + 5 Local Marketing Strategy Fixes appeared first on Search Engine Journal .

Will focus particularly on emerging use cases.

May explain government's alarm surrounding the incident.