According to Sundar Pichai, the new Gemini 2.5 Computer Use model is now available in the Gemini API and has established a new standard across multiple AI benchmarks with improved low latency. The model’s standout feature is its advanced ability to interact with web elements such as scrolling, filling forms, and navigating dropdown menus, signaling a significant step toward developing general-purpose AI agents. Developers can access and test these advanced capabilities via API on Google AI Studio and Vertex AI, opening new business opportunities for automation and productivity tools (Source: Sundar Pichai on Twitter, Oct 7, 2025).

According to Google DeepMind, the new Gemini 2.5 Computer Use model leverages advanced visual understanding and reasoning to enable AI agents to navigate browsers by clicking, scrolling, and typing as a human user would. This upgrade significantly enhances practical AI applications for automated online tasks, streamlining workflows in industries such as customer support, e-commerce, and data entry. The model outperforms previous versions on multiple industry benchmarks, offering improved speed and reliability, which positions it as a game-changer for businesses seeking to automate complex web-based operations (source: Google DeepMind, Twitter, Oct 7, 2025).

According to Demis Hassabis, AI Mode for Search has officially launched in the UK, offering users enhanced search experiences through advanced reasoning, logical thinking, and multimodal understanding powered by Gemini 2.5 (source: @demishassabis). This update builds on previous AI Overviews, providing practical applications for both consumers and businesses, such as improved information retrieval, context-aware responses, and the ability to process multiple types of content including text and images. For AI industry players, the rollout signifies a major step in mainstreaming multimodal AI-powered search, opening up new opportunities for search engine optimization, targeted advertising, and integrating AI-driven customer interaction solutions.

According to Demis Hassabis on Twitter, Google has officially launched the Gemini 2.5 series, representing a significant advancement in AI model performance and usability. The new Gemini 2.5 models have been developed with direct user and developer feedback, resulting in improved accuracy, speed, and integration capabilities for enterprise and application use cases (source: Demis Hassabis, Twitter, June 17, 2025). This release opens new business opportunities for companies seeking scalable AI solutions for automation, data analysis, and generative AI applications. Enterprises and developers can now leverage Gemini 2.5’s enhanced features to build more sophisticated AI products and integrate cutting-edge AI into their workflows, accelerating innovation in sectors such as finance, healthcare, and e-commerce.

According to Demis Hassabis on Twitter, the unprecedented demand for Google's Gemini 2.5 and Veo 3 AI models is being successfully managed by their advanced infrastructure, chip, and Site Reliability Engineering (SRE) teams. This highlights the scalability and robustness of Google's custom Tensor Processing Units (TPUs), which are critical for supporting large-scale AI workloads. The operational excellence of these teams ensures continuous uptime and performance, enabling businesses to deploy state-of-the-art generative AI solutions at scale. As AI adoption accelerates, the ability to maintain and scale AI infrastructure such as TPUs presents significant business opportunities for cloud service providers and enterprise AI deployments (source: @demishassabis, Twitter, May 31, 2025).

According to Oriol Vinyals (@OriolVinyalsML), Gemini 2.5 has achieved the top position on a new AI benchmark leaderboard, highlighting its advanced performance in natural language processing tasks. This result, shared on Twitter on May 29, 2025, demonstrates Google's ongoing competitiveness in large language model development. For enterprises, Gemini 2.5's leadership on such benchmarks signals improved reliability and performance for AI-powered applications, potentially driving adoption in sectors like customer service automation, content creation, and enterprise data analysis. The benchmark achievement reinforces the need for businesses to continuously evaluate emerging AI models for integration opportunities in their workflows (source: Oriol Vinyals, Twitter).