According to Jeff Dean on X (via @JeffDean), he joined the Latent Space podcast hosted by @latentspacepod, @swyx, and @FanaHOVA, sharing a discussion with a published summary site and video links. According to Latent Space (podcast page linked by @JeffDean), the conversation covers Google DeepMind’s Gemini progress, model evaluation practices, safety alignment, and scaling strategy, highlighting practical implications for enterprises adopting multimodal AI and long-context assistants. As reported by Latent Space, Dean outlines how foundation model capabilities translate into product features across Google Search, Workspace, and Android, and discusses the economics of AI infrastructure, including TPU optimization and serving efficiency, which can lower inference costs for production workloads. According to the same source, the episode also examines open model dynamics, research-to-product transfer, and benchmarks, offering guidance to AI teams on model selection, cost-performance tradeoffs, and opportunities in tooling for retrieval, evaluation, and guardrails.

According to Grok on X, the Grok app released a ‘Funky Dance’ template that lets users test their pets’ dance moves via a new generative media workflow, available now in the app. As reported by the Grok post, the feature promotes playful, template-driven video creation, indicating continued investment in consumer-grade multimodal generation. According to the original X announcement, this opens opportunities for pet brands and creators to drive engagement through UGC challenges, while also signaling demand for lightweight inference pipelines that run quickly on mobile clients or cloud backends for short-form clips.

According to @demishassabis, who shared Fortune’s cover story interview by @agarfinks, Demis Hassabis outlines DeepMind’s roadmap across frontier models, scientific AI, and healthcare. As reported by Fortune, Google DeepMind is scaling multimodal foundation models while integrating them with Alphabet’s product stack to drive monetization in Search, Cloud, and Android. According to Fortune, DeepMind’s Isomorphic Labs is advancing AI-first drug discovery by combining protein structure prediction and generative design to shorten preclinical cycles and improve hit rates with pharma partners. As reported by Fortune, the strategy emphasizes safety research, evaluation benchmarks, and controlled deployment to enterprise customers via Google Cloud. According to Fortune, commercial opportunities highlighted include AI copilots for knowledge work, bioinformatics services for pharma R&D, and custom model hosting for regulated industries, with a focus on reliability and cost efficiency.

According to @grok on X, Grok has introduced a voice mode that delivers the same visually rich interface as Grok chat, enabling users to ask questions hands‑free when typing is not possible. As reported by the official Grok post on February 9, 2026, the feature focuses on parity between voice and text experiences, signaling a push toward multimodal conversational workflows for real‑time assistance. For businesses, this expands customer engagement channels, supports voice-driven search and support flows, and opens opportunities to integrate Grok’s voice UX into mobile apps and in‑car or field operations, according to the Grok announcement.

According to DeepLearningAI, Zhipu AI has launched GLM-Image, an open-weights image generator specifically engineered to deliver clearer and more accurate text within generated images. The model utilizes a two-stage process, separating layout design and detail rendering, which has enabled it to outperform both open-source and select proprietary competitors in text quality benchmarks. This development, as reported by DeepLearningAI, highlights significant advancements in multimodal AI and presents notable business opportunities for industries requiring high-fidelity text rendering in synthetic imagery.