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  • 1
    Online Resource
    Online Resource
    [Place of publication not identified] : O'Reilly Media, Inc.
    Language: English
    Pages: 1 online resource (1 sound file (35 min.))
    Edition: [First edition].
    DDC: 006.3
    Keywords: Artificial intelligence ; Intelligence artificielle ; artificial intelligence ; Audiobooks ; Podcasts ; Livres audio ; Émissions baladodiffusées
    Abstract: Pete Warden, founder of Useful Sensors and co-author of TinyML, discusses use cases for artificial intelligence that we rarely think about: how can you run AI on very small systems? How can you put AI on consumer devices in ways that are actually useful and not just buzzword-compliant? AI doesn't have to rely on massive GPU farms. Pete talks about what happens when you exchange one set of requirements (extreme power, heat, and expense) for another (minimal size, cost, and heat). About the Generative AI in the Real World podcast: In 2023, ChatGPT put AI on everyone's agenda. In 2024, the challenge will be turning those agendas into reality. In Generative AI in the Real World, Ben Lorica interviews leaders who are building with AI. Learn from their experience to help put AI to work in your enterprise. Points of Interest 00:00: Introductions, including Pete's introduction to his company. 2:22: What are some of the challenges and use cases for sensor-driven AI? 4:11: Is sensor-driven AI relevant to industries other than hardware? 6:22: Now we're in the age of foundation models and large language models. Is "large" incompatible with "tiny"? Can you run language models on smaller devices? 8:00: Will there be developments in tinyML that will benefit the broader LLM community? 9:30: What's deployable today in computer vision, speech, and language? What can be done with hardware that's constrained by cost, size, and power consumption? 11:15: How will product designers work with sensor-driven AI? Will they simply select from a palette of optional modules? 12:37: Pete walks us through the development of AI-in-a-Box, from its conception to its reception. 15:31: Your devices don't have network connections. Without a network connection, how do you update models? Is it necessary? 19:00: Do you do Retrieval Augmented Generation (RAG) on your devices? 20:35: Our devices have user interfaces that combine voice and presence. A voice interface is central, but visual (and other channels) help to create an awareness of the speaker. 21:35: What are some of your specific challenges, like power consumption and latency? How do you make tradeoffs? 22:45: What is the future of large language models for sensor-driven AI? 26:50: What are some of the security concerns for sensor-driven AI and what are you doing about them? 28:22: What is Dark Compute and why is it important? 30:48: What are the biggest opportunities for pushing AI into consumer devices? We need to start with problems that users actually care about. 32:30: How can listeners connect to the broader movement around TinyML?.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
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  • 2
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Language: English
    Pages: 1 online resource (1 video file, approximately 34 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Pete Warden and Nupur Garg (Google) take you through TensorFlow Lite, TensorFlow’s lightweight cross-platform solution for mobile and embedded devices. It enables on-device machine learning inference with low latency, high performance, and a small binary size. It’s the standard solution at Google and the primary inference framework for all on-device use cases. Prerequisite knowledge Familiarity with ML What you'll learn Learn how TensorFlow Lite tools work and how to convert and optimize models for mobile and embedded devices
    Note: Online resource; Title from title screen (viewed February 28, 2020) , Mode of access: World Wide Web.
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  • 3
    Online Resource
    Online Resource
    [Place of publication not identified] : O'Reilly Media
    Language: English
    Pages: 1 online resource (1 streaming video file (40 min., 49 sec.)) , digital, sound, color.
    Keywords: Computer vision ; Image analysis ; Electronic videos ; local
    Abstract: "There have been big improvements in image analysis over the last few years thanks to the adoption of deep learning neural networks to solve vision problems, but figuring out how to get started with them isn't easy. In this webcast Pete Warden will walk through some popular open-source tools from the academic world, and show you step-by-step how to process images with them. Starting right from downloading the source and data, setting up the dependencies and environment, compiling, and then executing the libraries as part of a program, you'll be shown how to solve your own computer vision problems."--Resource description page.
    Note: Title from title screen (viewed November 17, 2014)
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  • 4
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly
    ISBN: 9781449314422
    Language: English
    Pages: 1 streaming video file (1 hr., 49 min., 17 sec.) , digital, sd., col.
    Keywords: Electronic data processing ; Distributed processing ; Wide area networks (Computer networks) ; Web services ; Electronic videos ; local
    Abstract: "MapReduce may be Google's secret weapon for dealing with enormous quantities of data, but many programmers see it as intimidating and obscure. This video master class shows you how to build simple MapReduce jobs, using concrete use cases and descriptive examples to demystify the approach. All you need to get started is basic knowledge of Python and the Unix shell."--Resource description page.
    Note: Title from title screen (viewed Oct. 24, 2011). - Publication information from end credits
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  • 5
    Online Resource
    Online Resource
    [United States?] : O'Reilly Media | Boston, Mass. :Safari Books Online,
    ISBN: 9781449306021
    Language: English
    Pages: 1 streaming video file (40 min., 51 sec.) , digital, sd., col.
    Keywords: Electronic data processing ; Electronic videos ; local
    Abstract: "Many hands make light work", as the saying goes. That's true when thousands of people can collaborate on a data set. In this session, we'll look at collective interfaces that allow many distributed users to examine and share data with one another, and how that's changing traditional desktop visualization tools." --Resource description page.
    Note: Title from title screen
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