WAYR TODAY

Category: AI

  • Microsoft’s PowerToys Advanced Paste Gains On-Device AI Capabilities

    This article was generated by AI and cites original sources.

    Microsoft has enhanced its Advanced Paste tool within PowerToys for Windows 11 by introducing an on-device AI model to improve its functionality. The latest 0.96 update allows users to leverage Microsoft’s Foundry Local tool or the open-source Ollama to run AI models directly on their device’s neural processing unit (NPU), eliminating the need for cloud connectivity.

    This advancement means users can execute tasks such as AI-powered text translation or summarization without requiring API credits, while ensuring data remains localized on their device.

    In addition to on-device AI support, the updated Advanced Paste now offers compatibility with various online models like Azure OpenAI, Gemini, and Mistral, expanding beyond its previous support for OpenAI alone. The tool also features a redesigned interface, showcasing the current clipboard content and introducing a model selection drop-down menu for enhanced usability.

    Source: The Verge

  • US Authorities Charge Four for Illegal Smuggling of Nvidia AI Chips to China

    This article was generated by AI and cites original sources.

    US federal prosecutors have charged four individuals for illegally smuggling Nvidia GPUs and HP supercomputers equipped with Nvidia GPUs from the US to China. The smuggling operation circumvented US restrictions that prohibit Nvidia from selling its most powerful chips for AI training to China, a court filing revealed. Despite export controls, Chinese companies like DeepSeek have managed to develop competitive AI models, including the R1 model released earlier this year. According to Scale CEO Alexander Wang, China may possess more of Nvidia’s H100 AI chips than commonly believed, potentially facilitated by operations such as these.

    According to court documents, the accused individuals are Mathew Ho, Brian Curtis Raymond, Tony Li, and Harry Chen. The group allegedly conspired to export Nvidia’s GPUs without the required licenses, shipping 50 of the high-demand H200 GPUs and multiple batches of the earlier H100 GPUs. The operation involved a purported front company named Janford Realtor, LLC, which was utilized as an intermediary for the unlawful exports to China. Ho, a US citizen, was listed as the company’s registered agent, while Li, a Chinese national, was identified as a manager.

    The case sheds light on the challenges faced by tech companies dealing with sensitive technologies and the ongoing efforts to prevent unauthorized transfers. Nvidia, which recently reported record quarterly revenue of $57 billion, remains subject to US export controls on certain products, reflecting the complex landscape of international tech trade.

    Source: The Verge

  • OpenAI Introduces Group Chat Feature in ChatGPT for Collaborative Conversations

    This article was generated by AI and cites original sources.

    OpenAI has launched a new feature that allows users to engage in group chats within the ChatGPT platform. This feature enables individuals to invite up to 20 participants to converse with the AI chatbot simultaneously. Following a successful pilot phase earlier this month, the group chat functionality is now accessible to all logged-in users globally.

    The group chat feature is designed to facilitate collaboration among users, whether for organizing events, making travel arrangements, or outlining tasks, with the support of ChatGPT. To initiate a group chat, users can click on the “people” icon in the top-right corner of the ChatGPT app. The AI chatbot then duplicates the existing conversation into a new group chat, where additional participants can be added through a shared link. Users are prompted to provide a name, username, and photo upon entering or creating a group chat, enhancing the visibility of individual contributors.

    OpenAI has trained ChatGPT to adapt to the natural flow of conversations within group chats, ensuring appropriate and timely interactions. Users can directly address “ChatGPT” in their messages to prompt a response from the AI chatbot. Additionally, ChatGPT can react to messages using emojis and incorporate profile photos to personalize interactions.

    Users can access various customization options by selecting the group chat icon on the screen, including features to manage participants, adjust notification settings, and provide specific instructions to ChatGPT. Importantly, OpenAI emphasizes that ChatGPT does not use personal chat memories or create new memories based on group conversations.

    Source: The Verge

  • ScaleOps Unveils AI Infra Solution to Optimize GPU Costs for Enterprise LLMs

    This article was generated by AI and cites original sources.

    ScaleOps, a cloud resource management platform, has introduced a new AI Infra Product designed to help enterprises manage self-hosted large language models (LLMs) and GPU-based AI applications more efficiently. The solution addresses the need for optimized GPU utilization, performance predictability, and reduced operational complexity in large-scale AI deployments.

    The AI Infra Product has already demonstrated significant cost savings, with early adopters reporting a 50-70% reduction in GPU expenses. The system ensures smooth operation under heavy loads through proactive and reactive mechanisms, maintaining performance even during sudden traffic spikes.

    By offering workload-aware scaling policies, ScaleOps’ solution optimizes GPU resources in real-time while seamlessly integrating with existing deployment pipelines and application code. The product’s compatibility with various enterprise infrastructure patterns, including Kubernetes distributions, major cloud platforms, and on-premises setups, ensures widespread applicability.

    The platform also provides comprehensive visibility into GPU utilization, model behavior, and scaling decisions, empowering engineering teams to fine-tune scaling policies as needed. Installation is simplified to a two-minute process, emphasizing ease of use and immediate optimization benefits.

    Early case studies highlight substantial GPU cost reductions, such as a creative software company achieving over 50% savings in GPU spending and a global gaming company projecting $1.4 million in annual savings. These results underscore the product’s potential for rapid ROI and enhanced operational efficiency.

    Source: VentureBeat

  • OpenAI Enhances ChatGPT Atlas with Vertical Tabs for Improved Navigation

    This article was generated by AI and cites original sources.

    OpenAI has introduced an update to ChatGPT Atlas, incorporating vertical tabs that resemble the layout of the Arc browser. This enhancement allows users to access tabs through a left-hand sidebar instead of the traditional top tab placement within the AI-powered browser.

    Users can now resize the sidebar on ChatGPT Atlas, customize tab orders, and even select Google as their default search engine. The new sidebar feature, while not as extensive as Arc’s, offers increased flexibility and ease of navigation. To experience vertical tabs, users can right-click within the address bar, navigate to ‘Tab Style,’ and select ‘Vertical Tabs’.

    Additionally, the update includes the ability to drag multiple tabs simultaneously by holding Command or Shift while clicking. Users can import extensions from their current browser upon downloading Atlas, although this functionality is not yet accessible to existing users. Furthermore, an improved downloads interface and support for iCloud keychain passkeys have been implemented.

    ChatGPT Atlas, launched on macOS recently, joins the ranks of AI-driven browsing experiences such as Perplexity’s Comet and Google’s Gemini extension in Chrome. With ChatGPT Atlas, users can input URLs or pose questions to receive AI-generated responses. For a detailed list of modifications, visit OpenAI’s official website.

    Source: The Verge

  • NestAI Secures €100M Funding, Partners with Nokia to Develop AI for Defense Applications

    This article was generated by AI and cites original sources.

    Finnish startup NestAI has successfully raised €100 million in funding, with support from Finland’s sovereign fund Tesi and tech giant Nokia. The investment will fuel the development of AI solutions tailored for unmanned vehicles, autonomous operations, and command and control platforms. NestAI’s collaboration with Nokia aims to create advanced AI products specifically for defense applications, focusing on the concept of ‘physical AI’ that integrates language models and related technologies into real-world scenarios.

    By establishing ‘Europe’s leading physical AI lab,’ NestAI is positioning itself to drive technological sovereignty on the continent. The company’s strategic focus on defense applications aligns with the evolving landscape influenced by the ongoing Ukraine-Russia conflict. Notably, NestAI has committed to supporting the Finnish Defense Forces in implementing AI solutions.

    Founder Peter Sarlin, known for his involvement in the AI sector, has emphasized the importance of NestAI’s mission to enhance Europe’s defense capabilities and sovereignty. Sarlin maintains a philanthropic and investor role, steering NestAI as chairman while continuing his responsibilities at AMD.

    Source: TechCrunch

  • Meta’s DreamGym Framework Enhances AI Agent Training with Simulated Environments

    This article was generated by AI and cites original sources.

    Meta, in collaboration with the University of Chicago and UC Berkeley, has introduced a new framework called DreamGym that aims to improve the training of AI agents by leveraging simulated environments. DreamGym addresses the challenges associated with reinforcement learning (RL) for large language model (LLM) agents, such as high costs, infrastructure complexity, and unreliable feedback.

    The core of DreamGym lies in its ability to simulate an RL environment, dynamically adjusting task difficulty as agents progress through training. This innovative approach significantly enhances RL training, demonstrating improvements in both synthetic and real-world scenarios.

    By offering a cost-effective alternative to live RL environments, DreamGym opens up new possibilities for enterprises looking to train agents for specialized applications without the usual complexities and risks involved. The framework’s impact has the potential to reshape how AI agents are trained, making the process more efficient and accessible.

    Source: VentureBeat

  • CraftStory Unveils AI Video Generation Model 2.0 with Long-Form Capabilities

    This article was generated by AI and cites original sources.

    CraftStory, a new AI startup founded by the creators of the widely used OpenCV, has announced the launch of Model 2.0, a video generation system that outperforms competitors like OpenAI’s Sora and Google’s Veo. CraftStory’s technology can produce realistic human-centric videos up to five minutes long, addressing a key limitation in the AI video industry.

    Unlike existing models that generate short clips, CraftStory’s system can create continuous, coherent videos suitable for training, marketing, and customer education purposes. The company’s parallelized diffusion architecture enables the generation of longer videos without the need for proportionally larger networks and more training data.

    By training its model on proprietary footage, CraftStory ensures high-quality video production while offering an efficient video-to-video system. The company, funded with $2 million by Andrew Filev, aims to reshape the enterprise video production landscape.

    CraftStory’s focus on long-form, human-centric videos sets it apart in a competitive market where industry giants like OpenAI and Google dominate. The startup’s innovative approach and deep roots in computer vision position it as a key player in the AI video generation domain.

    Source: VentureBeat

  • AI Leaders Collaborate to Establish Guidelines for Chatbot Companions

    This article was generated by AI and cites original sources.

    Representatives from leading AI companies, including Anthropic, Apple, Google, OpenAI, Meta, and Microsoft, recently convened at Stanford to discuss the responsible use of chatbots as companions or in roleplay scenarios. The closed-door workshop, spearheaded by Anthropic and Stanford, aimed to establish clear guidelines for the deployment of chatbot companions, particularly concerning interactions with younger users.

    While AI tools can offer useful interactions, prolonged conversations with chatbots have occasionally led to concerning consequences, such as mental distress or discussions of suicidal thoughts. Ryn Linthicum, Anthropic’s head of user well-being policy, emphasized the necessity of societal discussions on the role of AI in human interactions.

    During the workshop, industry representatives collaborated with academics and experts to explore emerging AI research and brainstorm strategies for ensuring the safe use of chatbot companions. One key insight was the importance of implementing targeted interventions within chatbots to address harmful patterns and enhancing age verification processes to safeguard children.

    As the workshop participants navigated the complexities of AI-human relationships, they underscored the significance of cross-industry collaborations in shaping the future of AI interactions. The event highlighted the evolving landscape of AI ethics and the ongoing efforts to mitigate potential risks associated with AI companions.

    Source: WIRED

  • Nvidia’s Soaring AI Chip Sales Drive $10B Data Center Growth

    This article was generated by AI and cites original sources.

    Nvidia has reported record-breaking sales of its AI chips, surpassing its Q3 2026 earnings estimates. The company announced $57 billion in revenue, with a remarkable profit of approximately $4,000 per second. Notably, Nvidia’s data center business saw exceptional growth, increasing by $10 billion in just one quarter, reaching a record $51.2 billion in revenue, marking a 66% rise from the previous year.

    With Nvidia’s data center revenue serving as a barometer for the AI industry, the company’s robust performance is closely watched. Despite concerns about a potential AI bubble, Nvidia remains optimistic about its data center growth trajectory. The projected Q4 outlook of $65 billion indicates the company’s ambition to further expand, requiring an additional $8 billion in quarterly revenue within the next three months.

    Nvidia CEO Jensen Huang revealed that the demand for AI server chips is outstripping supply, stating, “Blackwell sales are off the charts, and cloud GPUs are sold out.” Huang clarified that there are sufficient Blackwell chips in production to meet demand, with the Blackwell Ultra chip driving the surge in data center revenue. Huang also highlighted a 30% year-over-year increase in gaming revenue, signaling positive traction for Nvidia’s Blackwell gaming chips.

    Addressing concerns about an AI bubble, Huang expressed confidence in the industry’s sustainability, stating, “There’s been a lot of talk about an AI bubble. From our vantage point, we see something very different.” Nvidia’s strong performance in AI chip sales and data center growth underscores its position as a key player in the evolving tech landscape.

    Source: The Verge

  • Trump’s Proposed Executive Order: Centralizing AI Regulation and Challenging State Laws

    This article was generated by AI and cites original sources.

    President Donald Trump is considering an executive order that would grant the federal government extensive authority over regulating artificial intelligence (AI). The proposed order includes the establishment of an ‘AI Litigation Task Force’ overseen by the Attorney General, with the mandate to challenge state AI laws that are viewed as impeding AI industry advancement.

    According to The Verge, the Task Force could potentially litigate against states with laws perceived as hindering AI growth, such as California’s AI safety laws and Colorado’s law against ‘algorithmic discrimination.’

    The administration’s AI Action Plan aims to spur industry innovation by bypassing what it considers burdensome local regulations. Key federal agencies like the FCC, Department of Commerce, and Federal Trade Commission are slated to execute the plan within 90 days of the order. The Department of Justice, under this directive, will work towards identifying states not in compliance with the administration’s AI policies.

    Source: The Verge

  • Google DeepMind Bolsters Robotics Expertise with Former Boston Dynamics CTO

    This article was generated by AI and cites original sources.

    Google DeepMind has made a strategic move by appointing Aaron Saunders, the former Chief Technology Officer of Boston Dynamics, as the VP of hardware engineering. This hire comes as DeepMind intensifies its focus on robotics, aiming to develop Gemini into a versatile robot operating system. Gemini, envisioned by CEO Demis Hassabis, is poised to revolutionize the robotics industry by offering an AI system that can seamlessly adapt to various body configurations, including both humanoid and non-humanoid forms.

    Saunders, known for his contributions to the creation of agile legged robots at Boston Dynamics, brings a wealth of expertise to DeepMind’s robotics endeavors. His role will be instrumental in realizing Hassabis’ vision of Gemini as an Android-like platform for physical robots, streamlining the integration of AI capabilities into diverse robotic hardware.

    DeepMind’s commitment to advancing robotics through cutting-edge AI models underscores the industry’s growing interest in more sophisticated robotic technologies. As the boundaries between AI and robotics continue to blur, the collaboration between DeepMind and industry pioneers like Boston Dynamics signals a new era of innovation in the field.

    Source: WIRED

  • Google’s Scholar Labs: AI-Powered Research Discovery Tool Unveiled

    This article was generated by AI and cites original sources.

    Google has introduced Scholar Labs, a new AI-powered search tool designed to assist users in finding relevant research studies. The tool’s unique approach to identifying valuable scientific studies has sparked discussions within the academic community about the credibility and trustworthiness of AI-driven research recommendations.

    Unlike traditional search methods that rely on metrics like citation counts and journal impact factors, Scholar Labs leverages artificial intelligence to analyze the relationships between words in a query and match them with the most suitable research papers. This innovative technique aims to provide users with precise and insightful results tailored to their research inquiries.

    During a demonstration, a user posed a question regarding brain-computer interfaces (BCIs), and the tool promptly returned a review paper on BCI research published in a respected journal, offering detailed insights into the topic and its related algorithms.

    However, some observers noted that Scholar Labs currently lacks conventional filters used in academia to differentiate between widely recognized studies and lesser-known research. Metrics such as citation frequency and journal impact factors, which are commonly used to gauge a study’s significance, are notably absent from the tool’s features.

    Google’s Scholar Labs represents a significant step in the evolution of research discovery tools, showcasing the potential of AI in facilitating academic exploration and knowledge dissemination. As the platform continues to evolve, the scientific community will closely monitor its impact on research practices and information retrieval methodologies.

    Source: The Verge

  • OpenAI Unveils Powerful GPT-5.1-Codex-Max Coding Model

    This article was generated by AI and cites original sources.

    OpenAI has introduced its latest advancement in AI-assisted software engineering, the GPT-5.1-Codex-Max coding model. This cutting-edge model, now available in the Codex developer environment, offers improved long-horizon reasoning, efficiency, and real-time interactive capabilities. GPT-5.1-Codex-Max is designed to be a persistent, high-context software development agent capable of managing complex refactors, debugging workflows, and project-scale tasks across multiple context windows.

    The model’s performance benchmarks demonstrate measurable enhancements over its predecessor, GPT-5.1-Codex, across a range of standard software engineering tasks. Notably, GPT-5.1-Codex-Max excelled in accuracy and efficiency, showcasing its potential to transform coding practices.

    A key architectural enhancement in GPT-5.1-Codex-Max is its long-horizon reasoning capability enabled by compaction, allowing the model to retain essential contextual information while discarding irrelevant details. This feature empowers the model to complete tasks lasting more than 24 hours, including multi-step refactors and autonomous debugging, with impressive efficiency.

    GPT-5.1-Codex-Max’s integration across various Codex-based environments, including the Codex CLI and interactive coding interfaces, signals a new era in AI-driven software development. While the model is not yet available via public API, its imminent release promises to enhance developer productivity.

    Source: VentureBeat

  • Fetch AI Unveils Platform to Enhance AI Agent Ecosystems

    This article was generated by AI and cites original sources.

    Fetch AI, a startup founded by Humayun Sheikh, has unveiled a suite of products aimed at improving the capabilities of AI agents on a large scale. The launch introduces ASI:One, a platform for personal-AI orchestration, Fetch Business for brand agent verification, and Agentverse, an open directory hosting over two million agents.

    Fetch’s system establishes a foundation for what it calls the ‘Agentic Web,’ enabling consumer AIs and brand AIs to collaborate effectively on tasks. This addresses a key limitation in current consumer AI, which often struggles with executing multi-step actions requiring coordination across businesses.

    ASI:One, the central component of the launch, acts as an intelligence layer facilitating multi-agent coordination by storing user preferences and delegating tasks to verified agents. This platform enhances personalization and enables seamless task execution across organizational boundaries.

    Fetch Business provides a verification and discovery portal for brand agents, ensuring consumer interaction with authentic representatives. By offering low-code tools for agent creation and verified identity handles, Fetch aims to enhance trust and streamline agent adoption.

    Agentverse, the final component, serves as an open directory hosting agents from various sectors, promoting cross-ecosystem discoverability and secure communication between agents. This platform plays a critical role in addressing the lack of a universal agent discovery layer, crucial for increasing AI agent utilization.

    Fetch’s release marks a significant step in advancing AI agent ecosystems by improving coordination, verification, and interaction capabilities. The company’s focus on personalization, multi-agent orchestration, and digital transaction infrastructure underscores its commitment to driving AI innovation and usability.

    Source: VentureBeat

  • DeepMind’s AlphaProof: AI Breakthrough in Mathematical Proofs

    This article was generated by AI and cites original sources.

    DeepMind, a subsidiary of Google, has unveiled AlphaProof, an AI system designed to tackle complex mathematical proofs with remarkable proficiency. Revealing capabilities that rival top human mathematicians, AlphaProof nearly earned a gold medal at the renowned International Mathematical Olympiad, showcasing its potential to revolutionize mathematical problem-solving.

    Unlike conventional computers that excel in calculations but struggle with abstract reasoning, AlphaProof signifies a leap forward in AI’s comprehension of advanced mathematics. While machines boast unparalleled speed in computations, they often fall short in grasping the underlying logic and rationale behind mathematical principles.

    “The team’s objective was to develop an AI model that not only solves math problems but comprehends the essence of mathematics at a profound level,” said Thomas Hubert, a lead researcher at DeepMind.

    AlphaProof’s journey began by addressing a common AI obstacle: the scarcity of pertinent training data. Leveraging the vast repository of mathematical texts available in training databases, including seminal works by prominent mathematicians, the AI system embarked on a quest to master the intricacies of mathematical reasoning.

    With AlphaProof’s emergence, the realm of mathematical proofs witnesses a significant advancement, heralding a new era where AI systems could potentially collaborate with mathematicians to explore uncharted mathematical territories.

    Source: Ars Technica

  • TikTok Introduces AI Content Control Feature for Users

    This article was generated by AI and cites original sources.

    TikTok is currently testing a new feature that allows users to manage the amount of AI-generated content appearing in their video feeds. This move aims to give users more control over the content they see on the platform.

    The new feature, which will be integrated into TikTok’s existing content controls under ‘Manage topics,’ includes an AI slider that enables users to adjust the visibility of AI-generated content. Users can choose to increase or decrease the presence of AI material in their feeds, offering a more personalized viewing experience. To ensure the accuracy of this feature, TikTok is also working on enhancing its AI content detection capabilities.

    To combat potential attempts to remove visible watermarks from AI-generated content, TikTok has decided to embed invisible watermarks into content created using its AI tools, such as AI Editor Pro. Additionally, videos uploaded with C2PA Content Credentials will also receive these invisible watermarks. These changes are set to be gradually implemented over the next few weeks, as the AI content control feature is currently being tested by the platform.

    Source: The Verge

  • Google’s Antigravity Platform Introduces Agent-First Architecture for Asynchronous Coding Workflows

    This article was generated by AI and cites original sources.

    Google has announced the launch of Antigravity, a new platform designed to empower developer teams with autonomous coding agents capable of handling complex tasks independently. Antigravity, powered by Gemini 3, represents a significant shift towards an agent-first approach, enabling agents to move beyond remote control to true autonomy.

    Antigravity offers an agentic coding environment that prioritizes browser control capabilities, asynchronous interaction patterns, and an agent-first design philosophy. As the volume of code continues to surge, especially with the emergence of AI-generated code, enterprises are increasingly relying on asynchronous coding agents to streamline project reviews, evaluate components, and execute tasks autonomously.

    During the public preview phase, Antigravity users can leverage Gemini 3, Anthropic’s Sonnet 4.5 models, and OpenAI’s gpt-oss to build agents compatible with major operating systems like macOS, Linux, and Windows. Google aims to position Antigravity as a cornerstone of software development in the age of agents, emphasizing trust, autonomy, feedback, and self-improvement as its core tenets.

    Antigravity’s innovative approach to coding aligns with Google’s broader efforts in the coding agent space, complementing existing platforms like Jules, Gemini CLI, and Gemini Code Assist. While facing competition from other coding agent platforms, such as Codex, Claude Code, and Cursor, Antigravity’s unique features aim to enhance collaborative development environments and elevate the efficiency of coding workflows.

    Early user feedback has highlighted both the potential and challenges of Antigravity, with some users reporting issues like errors and slow code generation. Despite these initial hurdles, Google’s foray into agent-first architecture signifies a significant step towards reshaping coding practices and promoting autonomous agent capabilities in software development.

    Source: VentureBeat

  • Google Unveils Gemini 3: Advancing the Frontiers of AI Technology

    This article was generated by AI and cites original sources.

    Google has unveiled Gemini 3, its latest frontier model family, marking a significant advancement in AI technology. This release introduces Gemini 3 Pro, Gemini 3 Deep Think, and innovative generative interface models that power visual layout and dynamic view. Gemini 3 also features the Gemini Agent for multi-step task execution and the Gemini 3 engine embedded in Google Antigravity, the company’s new agent-first development environment.

    Independent AI benchmarking organizations have recognized Gemini 3 Pro as the new global leader in AI, with remarkable performance across various domains. In a competitive AI landscape, Google’s Gemini 3 launch signifies a strategic move to strengthen its position in the market by offering cutting-edge agentic AI capabilities.

    With major performance gains over its predecessor Gemini 2.5 Pro, Gemini 3 excels in reasoning, mathematics, multimodality, tool use, coding, and long-horizon planning. The model’s enhancements in generative interfaces, multimodal understanding, and spatial reasoning expand its applications in consumer-facing and enterprise AI workflows.

    Google’s pricing strategy for Gemini 3 Pro positions it in the mid-high range compared to rival AI models, which may impact adoption rates. Despite the pricing considerations, Gemini 3’s advanced capabilities and substantial performance improvements underscore the company’s commitment to innovation in the AI space.

    Source: VentureBeat

  • Google’s Gemini 3: Enhancing Search with Advanced AI Capabilities

    This article was generated by AI and cites original sources.

    Google has unveiled Gemini 3, its latest artificial intelligence model, showcasing enhanced reasoning, multimedia, and coding capabilities. Positioned as a tool to bolster Google’s existing products, including its search business, Gemini 3 represents a significant advancement in AI technology.

    Demis Hassabis, CEO of Google DeepMind, emphasized the widespread integration of AI within Google’s operations. Despite concerns about an AI bubble, characterized by potential overvaluation and substantial data center investments, Google remains confident in its AI-driven approach.

    Google’s strategic use of AI extends beyond search enhancement; new tools like NotebookLM for podcast generation and AI Studio for application prototyping highlight the diverse applications of AI technology. The company is also exploring AI integration in gaming and robotics, anticipating substantial future benefits.

    Gemini 3 is accessible through the Gemini app and AI Overviews on Google Search, offering users interactive and personalized search experiences. Demonstrations have showcased Gemini 3’s ability to generate custom visualizations for complex queries, underscoring its potential to revolutionize search functionality.

    Source: WIRED