Perplexity has released Photon, an in-house retrieval and ranking engine written in Rust, replacing a forked open-source engine. The company reports that production p99 latency dropped from roughly 800 ms to 65 ms. Photon now handles all production search traffic and powers a new Fast Search mode in the Perplexity Search API, priced at $1 per 1,000 requests.
Iterable has unveiled a major Fall Product Release adding native RCS messaging, Nova Conversations, an Integrations Hub, and new Nova Intelligence Agents to its AI customer engagement platform. The company says the update is designed to connect fragmented customer data across the marketing stack and create a continuous intelligence loop in which every interaction informs the next.
Google has announced the Retrieve-for-Train-Diffusion (R4T-Diffusion) model, a three-stage query fan-out framework that combines reinforcement learning, synthetic data generation, and a compact 53.9-million-parameter diffusion model. The system claims a 12-to-20× speed improvement over autoregressive approaches and is described as delivering production-ready search at scale, though whether it has been fully deployed remains unconfirmed.
Pinterest has unveiled a standardized multimodal AI infrastructure built with Nvidia's Blackwell B200 GPUs and open-source Dynamo framework, aiming to make visual search faster and more cost-efficient across its fleet of roughly 14,000 Nvidia GPUs. Company benchmarks claim precomputing visual representations reduced overall latency by 7.3 times and cut inference costs to less than 8% of closed proprietary models.