klotz: google*

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  1. Google's Gemini Pro model in NotebookLM can now create study guides, FAQs, quizzes, and even spoken dialogue discussions. This new feature allows students to learn in an interactive and personalized way by connecting physics and basketball through AI-generated examples.
  2. Lambda Stack is an all-in-one package that provides a one line installation and managed upgrade path for deep learning and AI software, ensuring that you always have the most up-to-date versions of PyTorch, TensorFlow, CUDA, CuDNN, and NVIDIA Drivers.
  3. Google demonstrated new updates for Gmail using its AI model, Gemini, which can summarize long email threads, answer questions, and suggest customized email responses.
    2024-05-15 Tags: , , , by klotz
  4. Stay informed about the latest artificial intelligence (AI) terminology with this comprehensive glossary. From algorithm and AI ethics to generative AI and overfitting, learn the essential AI terms that will help you sound smart over drinks or impress in a job interview.
  5. Google is introducing updates to the Gemini family of models, including a new lighter-weight model called 1.5 Flash, improvements to 1.5 Pro, and a look at the future of AI assistants with Project Astra.
    2024-05-15 Tags: , , by klotz
  6. • This is an MCU-based vision AI module powered by Arm Cortex-M55 and Ethos-U55, supporting TensorFlow and PyTorch frameworks.
    • It has a standard CSI interface, onboard digital microphone, and SD card slot.
    • Compatible with XIAO series, Arduino, Raspberry Pi, and ESP dev board.
    • Supports off-the-shelf and custom AI models from SenseCraft AI, including Mobilenet V1, V2, Efficientnet-lite, Yolo v5 & v8.
    • Can be used for industrial automation, smart cities, transportation, smart agriculture, and mobile IoT devices.
  7. Benchmarking long-form factuality in large language models. Original code for our paper "Long-form factuality in large language models".
    2024-03-31 Tags: , , , by klotz
  8. 2024-02-21 Tags: , , , , by klotz
  9. Key concept: Setting mental models can help users understand how to interact with products that adapt over time. This chapter covers:
    Identifying existing mental models
    Onboarding in stages
    Planning for co-learning
    Accounting for user expectations of human-like interaction
    Key concept: To build effective mental models of AI-powered products, consider what you want people to know about your product before their first use, how to explain its features, and when it will need feedback from them to improve.

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