News from the AI & ML world
DeeperML - #gemini
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@Google DeepMind Blog
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Google is preparing to unveil significant AI advancements, with speculation pointing towards enhancements to its Gemini model. Rumors suggest a potential update to Gemini 2.0 Pro, possibly named "Nebula," which has been observed performing well on specific prompts. This new model is expected to incorporate advanced reasoning capabilities, adding a new layer of sophistication to Google's AI offerings.
Google's strategy involves integrating AI into various facets of its services, which is evident by the official rollout of its Data Science Agent to most Colab users for free. Gemini 2.0 is designed to be universally applied across Google's products. It will enhance AI Overviews in Google Search, which now serve one billion users, by making them more nuanced and complex. Additionally, live video and screen sharing are being rolled out to Gemini Live, improving the models features. Recommended read:
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@Latest from Tom's Guide
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Google has unveiled Gemini 2.5 Pro, its latest and "most intelligent" AI model to date, showcasing significant advancements in reasoning, coding proficiency, and multimodal functionalities. According to Google, these improvements come from combining a significantly enhanced base model with improved post-training techniques. The model is designed to analyze complex information, incorporate contextual nuances, and draw logical conclusions with unprecedented accuracy. Gemini 2.5 Pro is now available for Gemini Advanced users and on Google's AI Studio.
Google emphasizes the model's "thinking" capabilities, achieved through chain-of-thought reasoning, which allows it to break down complex tasks into multiple steps and reason through them before responding. This new model can handle multimodal input from text, audio, images, videos, and large datasets. Additionally, Gemini 2.5 Pro exhibits strong performance in coding tasks, surpassing Gemini 2.0 in specific benchmarks and excelling at creating visually compelling web apps and agentic code applications. The model also achieved 18.8% on Humanity’s Last Exam, demonstrating its ability to handle complex knowledge-based questions. Recommended read:
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Matthias Bastian@THE DECODER
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Google is enhancing its Gemini AI assistant with the ability to access users' Google Search history to deliver more personalized and relevant responses. This opt-in feature allows Gemini to analyze a user's search patterns and incorporate that information into its responses. The update is powered by the experimental Gemini 2.0 Flash Thinking model, which the company launched in late 2024.
This new capability, known as personalization, requires explicit user permission. Google is emphasizing transparency by allowing users to turn the feature on or off at any time, and Gemini will clearly indicate which data sources inform its personalized answers. To test the new feature Google suggests users ask about vacation spots, YouTube content ideas, or potential new hobbies. The system then draws on individual search histories to make tailored suggestions. Recommended read:
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Matthias Bastian@THE DECODER
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Google has announced significant upgrades to its Gemini app, focusing on enhanced functionality, personalization, and accessibility. A key update is the rollout of the upgraded 2.0 Flash Thinking Experimental model, now supporting file uploads and boasting a 1 million token context window for processing large-scale information. This model aims to improve reasoning and response efficiency by breaking down prompts into actionable steps. The Deep Research feature, powered by Flash Thinking, allows users to create detailed multi-page reports with real-time insights into its reasoning process and is now available globally in over 45 languages, accessible for free or with expanded access for Gemini Advanced users.
Another major addition is the experimental "Personalization" feature, integrating Gemini with Google apps like Search to deliver tailored responses based on user activity. Gemini is also strengthening its integration with Google apps such as Calendar, Notes, Tasks, and Photos, enabling users to handle complex multi-app requests in a single prompt. Google is also putting Gemini 2.0 AI into robots through the DeepMind AI team, which has developed two new models of Gemini specifically designed to work with robots. The first, Gemini Robotics, is an advanced vision-language-action (VLA) LLM that uses physical motion to respond to prompts. The second model, Gemini Robots-ER, is a VLM with advanced spatial understanding, enabling robots to navigate changing environments. Google is partnering with robotics companies to further develop humanoid robots. Google will replace its long-standing Google Assistant with Gemini on mobile devices later this year. The classic Google Assistant will no longer be accessible on most mobile devices, marking the end of an era. The shift represents Google's pivot toward generative AI, believing that Gemini's advanced AI capabilities will deliver a more powerful and versatile experience. Gemini will also come to tablets, cars, and connected devices like headphones and watches. The company also introduced Gemini Embedding, a novel embedding model initialized from the powerful Gemini Large Language Model, aiming to enhance embedding quality across diverse tasks. Recommended read:
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Chris McKay@Maginative
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Google is currently navigating the "innovator’s dilemma" by experimenting with AI-driven search solutions to disrupt its core search business before competitors do. The company is testing and developing AI versions of Google Search, including a new experimental "AI Mode" powered by Gemini 2.0. This new mode transforms the search engine into a chatbot-like interface, providing more nuanced and multi-step answers to user queries. It allows users to interact with the AI, ask follow-up questions, and even compare products directly within the search page.
AI Mode delivers a full-page AI-generated response. Users can interact with the AI, ask follow-up questions, and even compare products. This mode runs on a custom Gemini 2.0 version and is currently available to Google One AI Premium subscribers. This move comes as Google faces increasing competition from other AI chatbots like OpenAI's ChatGPT and Perplexity AI, who are rethinking the search experience. The goal is to provide immediate, conversational answers and a more comprehensive search experience, though some experts caution that the traditional link-based search may eventually disappear as a result. Recommended read:
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@Dataconomy
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Google has enhanced the iOS experience by integrating Gemini AI with new lock screen widgets and control center access. iPhone users can now interact with Gemini directly from their lock screen, gaining quick access to Gemini Live and other tools without needing to unlock their devices. This update simplifies AI interactions on Apple's mobile platform, making it more accessible and convenient for users.
The new Gemini app widget allows instant access to the AI's voice chat feature, Gemini Live, by simply adding the widget to the lock screen and tapping it. Beyond voice chats, the update introduces three additional widgets: Camera Upload, allowing users to snap photos and send them to Gemini for analysis; Reminders & Calendar, for quickly setting events or tasks; and Text Chat, enabling immediate typed conversations. These widgets aim to streamline basic AI interactions, reducing the need to unlock the device. Recommended read:
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@tomsguide.com
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Google is enhancing its AI capabilities by integrating Gemini AI into Google Calendar and introducing Gemini Embedding, its most advanced text embedding model. The integration with Google Calendar aims to provide users with a more efficient way to manage their schedules by using natural language to check events, create meetings, and find key details. Google is set to roll out a Gemini AI upgrade to Google Calendar, allowing users to use the AI assistant to create events, check schedules, or recall event details.
Gemini Embedding offers state-of-the-art performance, increased language support, and improved efficiency for AI-powered search, classification, and retrieval tasks. The new model supports over 100 languages and offers a mean score of 68.32 on the MTEB Multilingual leaderboard, outperforming competitors. Google has launched an experimental Gemini-based text embedding model, offering state-of-the-art performance, increased language support, and improved efficiency for AI-powered search, classification, and retrieval tasks. Recommended read:
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Carl Franzen@AI News | VentureBeat
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Google has recently launched a Gemini-powered Data Science Agent on its Colab Python platform, aiming to revolutionize data analysis. This AI agent automates various routine data science tasks, including importing libraries, cleaning data, running exploratory data analysis (EDA), and generating code. By handling these tedious processes, the agent allows data scientists to focus on more strategic and insightful aspects of their work, such as uncovering patterns and building predictive models.
The Data Science Agent, accessible within Google Colab, operates as an intelligent assistant that executes tasks autonomously, including error handling. Users can define their analysis objectives in plain language, and the agent generates a Colab notebook, executes it, and simplifies the machine learning process. In addition, Google is expanding the capabilities of its Gemini AI model, which will soon allow users to ask questions about content displayed on their screens. This enhancement, part of Google's Project Astra, enables real-time interaction and accessibility by identifying screen elements and responding to user queries through voice. Recommended read:
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S.Dyema Zandria@The Tech Basic
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Google is enhancing its Gemini AI with a new feature that allows users to create AI podcasts from research materials. This new capability, called Audio Overviews, converts research and study materials into engaging, podcast-style discussions featuring AI hosts. This aims to make learning and information consumption more accessible and enjoyable, particularly for educational purposes.
The Audio Overviews feature leverages Gemini's Deep Research capabilities. Users can input a topic, have Gemini generate a detailed report, and then convert that report into a conversational podcast with AI hosts. These hosts discuss the information in an approachable manner, similar to two friends exploring a topic. This tool is available to both free and paid Gemini Advanced users. Recommended read:
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Koray Kavukcuoglu@The Official Google Blog
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AI News | VentureBeat
, www.techrepublic.com
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Google has unveiled Gemini 2.5 Pro, touted as its "most intelligent model to date," enhancing AI reasoning and workflow capabilities. This multimodal model, available to Gemini Advanced users and experimentally on Google’s AI Studio, outperforms competitors like OpenAI, Anthropic, and DeepSeek on key benchmarks, particularly in coding, math, and science. Gemini 2.5 Pro boasts an impressive 1 million token context window, soon expanding to 2 million, enabling it to handle larger datasets and understand entire code repositories.
Gemini 2.5 Pro excels in advanced reasoning benchmark tests, achieving a state-of-the-art score on datasets designed to capture human knowledge and reasoning. Its enhanced coding performance allows for the creation of visually compelling web apps and agentic code applications, along with code transformation and editing. Google plans to release pricing for Gemini 2.5 models soon, marking a significant step in their goal of developing more capable and context-aware AI agents. Recommended read:
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Evelyn Blake@The Tech Basic
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The Tech Basic
, gHacks Technology News
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Google has begun rolling out real-time interaction features to its AI assistant, Gemini, enabling live video and screen sharing. These enhancements, powered by Project Astra, allow users to engage more intuitively with their devices, marking a significant advancement in AI-assisted technology. These features are available to Google One AI Premium subscribers.
The new live video feature allows users to utilize their smartphone cameras to engage in real-time visual interactions with Gemini, enabling the AI to answer questions about what it observes. Gemini can analyze a user’s phone screen or camera feed in real-time and instantly answer questions. The screen-sharing feature enables the AI to analyze and provide insights on the displayed content, useful for navigating complex applications or troubleshooting issues. Google plans to expand access to more users soon. Recommended read:
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Evelyn Blake@The Tech Basic
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The Tech Basic
, gHacks Technology News
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Google has started rolling out new AI tools for Gemini, allowing the assistant to analyze your phone screen or camera feed in real time. These features are powered by Project Astra and are available to Google One AI Premium subscribers. The update transforms Gemini into a visual helper, enabling users to point their camera at an object and receive descriptions or suggestions from the AI.
These features are part of Google's Project Astra initiative, which aims to enhance AI's ability to understand and interact with the real world in real-time. Gemini can now analyze your screen in real-time through a "Share screen with Live" button and analyze your phone's camera. Early adopters have tested the screen-reading tool, and Google plans to expand access to more users soon. With Gemini's live video and screen sharing functionalities, Google is positioning itself ahead in the competitive landscape of AI assistants. Recommended read:
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mpesce@Windows Copilot News
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AI News | VentureBeat
, Windows Copilot News
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Google is advancing its AI capabilities on multiple fronts, emphasizing both security and performance. The company is integrating Google Cloud Champion Innovators into the Google Developer Experts (GDE) program, creating a unified community of over 1,400 members. This consolidation aims to enhance collaboration, streamline resources, and amplify the impact of passionate experts, providing a stronger voice for developers within Google and the broader industry.
Google is also pushing forward with its Gemini AI model, with the plan for Gemini 2.0 to be implemented across Google's products. Researchers from Google and UC Berkeley have found that a simple test-time scaling approach, based on sampling-based search, can significantly boost the reasoning abilities of large language models (LLMs). This method uses random sampling and self-verification to improve model performance, potentially outperforming more complex and specialized training methods. Recommended read:
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@Google DeepMind Blog
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Google DeepMind Blog
, The Tech Basic
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Google has launched Gemini 2.0, its most capable AI model yet, designed for the new agentic era. This model introduces advancements in multimodality, including native image and audio output, and native tool use, enabling the development of new AI agents. Gemini 2.0 is being rolled out to developers and trusted testers initially, with plans to integrate it into Google products like Gemini and Search. Starting today, the Gemini 2.0 Flash experimental model is available to all Gemini users.
New features powered by Project Astra are now accessible to Google One AI Premium subscribers, enabling live video analysis and screen sharing. This update transforms Gemini into a more interactive visual helper, capable of instantly answering questions about what it sees through the device's camera. Users can point their camera at an object, and Gemini will describe it or offer suggestions, providing a more contextual understanding of the real world. These advanced tools will enhance AI Overviews in Google Search. Recommended read:
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Nathan Labenz@The Cognitive Revolution
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Google DeepMind Blog
, Windows Copilot News
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DeepMind's Allan Dafoe, Director of Frontier Safety and Governance, is actively involved in shaping the future of AI governance. Dafoe is addressing the challenges of evaluating AI capabilities, understanding structural risks, and navigating the complexities of governing AI technologies. His work focuses on ensuring AI's responsible development and deployment, especially as AI transforms sectors like education, healthcare, and sustainability, while mitigating potential risks through necessary safety measures.
Google is also prepping its Gemini AI model to take actions within apps, potentially revolutionizing how users interact with their devices. This development, which involves a new API in Android 16 called "app functions," aims to give Gemini agent-like abilities to perform tasks inside applications. For example, users might be able to order food from a local restaurant using Gemini without directly opening the restaurant's app. This capability could make AI assistants significantly more useful. Recommended read:
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