Google AI
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Gmail’s New AI Inbox and Features
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Google has introduced a new AI Inbox for Gmail that offers personalized task overviews and important updates, featuring sections like "Suggested to-dos" and "Topics to catch up on." This AI-powered feature aims to streamline email management by highlighting priority emails and categorizing updates into areas such as finances and purchases. Additionally, Gmail now supports AI Overviews in search, allowing users to ask natural language questions to quickly find information within their emails, and a new "Proofread" feature to enhance writing clarity and structure. These innovations, initially available to select users, are part of Google's broader effort to integrate AI into Gmail, making email management more efficient and intuitive. This matters because it enhances productivity by simplifying email organization and improving communication efficiency through AI-driven tools.
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Join the 3rd Women in ML Symposium!
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The third annual Women in Machine Learning Symposium is set for December 7, 2023, offering a virtual platform for enthusiasts and professionals in Machine Learning (ML) and Artificial Intelligence (AI). This inclusive event provides deep dives into generative AI, privacy-preserving AI, and the ML frameworks powering models, catering to all levels of expertise. Attendees will benefit from keynote speeches and insights from industry leaders at Google, Nvidia, and Adobe, covering topics from foundational AI concepts to open-source tools and techniques. The symposium promises a comprehensive exploration of ML's latest advancements and practical applications across various industries. Why this matters: The symposium fosters diversity and inclusion in the rapidly evolving fields of AI and ML, providing valuable learning and networking opportunities for women and underrepresented groups in tech.
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Google’s FunctionGemma: AI for Edge Function Calling
Read Full Article: Google’s FunctionGemma: AI for Edge Function Calling
Google has introduced FunctionGemma, a specialized version of the Gemma 3 270M model, designed specifically for function calling and optimized for edge workloads. FunctionGemma retains the Gemma 3 architecture but focuses on translating natural language into executable API actions rather than general chat. It uses a structured conversation format with control tokens to manage tool definitions and function calls, ensuring reliable tool use in production. The model, trained on 6 trillion tokens, supports a 256K vocabulary optimized for JSON and multilingual text, enhancing token efficiency. FunctionGemma's primary deployment target is edge devices like phones and laptops, benefiting from its compact size and quantization support for low-latency, low-memory inference. Demonstrations such as Mobile Actions and Tiny Garden showcase its ability to perform complex tasks on-device without server calls, achieving up to 85% accuracy after fine-tuning. This development signifies a step forward in creating efficient, localized AI solutions that can operate independently of cloud infrastructure, crucial for privacy and real-time applications.