AI Spectrum

著者： Siemens Digital Industry Software
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  • AI Spectrum podcasts cover a wide range of artificial intelligence and machine learning topics. Listen to experts within Siemens and their customers talk about the impact of AI, success stories, and the future of AI. Gain insight into real world applications so that you can potentially apply AI within your world.
    Siemens Digital Industry Software
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AI Spectrum podcasts cover a wide range of artificial intelligence and machine learning topics. Listen to experts within Siemens and their customers talk about the impact of AI, success stories, and the future of AI. Gain insight into real world applications so that you can potentially apply AI within your world.
Siemens Digital Industry Software
科学
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エピソード
  • Exploring AI and ML and Understanding Networks

    Exploring AI and ML and Understanding Networks
    2021/02/04
    Everywhere we look today, people are talking about artificial intelligence and machine learning, and you probably hear a lot of buzzwords around this topic. You might be curious on the resources needed to train a machine or what exactly the process entails. Well, simply put, think of it like this: the specialists in the AI & ML industry aim at mimicking the amazing human brain. That’s not really an easy task, but huge advancements have been made in the past decade. In today’s episode, Mike Fingeroff – Senior Member of Consulting Staff at Calypto Design Systems - and his guest, Ellie Burns – Director of Marketing at Siemens EDA - share the basics of artificial intelligence and machine learning and help us understand how neural networks work. Tune in, to learn more! In this episode, you will learn: Then and now – the changes through AI & ML history. (01:07) The catalyst for the boom of the AI industry. (05:32) What a deep neural network is & how it works. (06:34) The different types of neural networks. (08:35) Connect with Mike Fingeroff: LinkedIn Connect with Ellie Burns: LinkedIn Resources: Catapult High-Level Synthesis Siemens EDA AI in industry Read the transcript here:
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    10 分
  • Understanding Training vs Inferencing and AI in Industry

    Understanding Training vs Inferencing and AI in Industry
    2021/03/04
    In the world of AI, a key concept is how to train a neural network to perform a particular task efficiently and accurately, then a hardware solution is created that uses the results from that training - and this is called inferencing. The difference between these two concepts - training and inferencing - often creates confusion among people, and that's why, in today's episode, we are diving deep into explaining these two terms and how exactly they differ.  We are also painting a clear picture of the industries that use artificial intelligence and machine learning and what they're working on, so tune in, and find out more!    In this episode, you will learn: The difference between training versus inferencing a neural network. (00:46) Examples of frameworks that help with the training process of a neural network. (01:24) The stage AI & ML is at, currently, in terms of safety-critical applications. (04:42) The industries that are currently using AI & ML, and the types of applications they’re focusing on. (06:52) Connect with Mike Fingeroff: LinkedIn Connect with Ellie Burns: LinkedIn Resources: Catapult High-Level Synthesis Siemens EDA
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    11 分
  • Identifying Hardware Design Challenges and AI at the Edge

    Identifying Hardware Design Challenges and AI at the Edge
    2021/04/01
    The field of artificial intelligence and machine learning - just like any other industry where innovation happens - faces lots of challenges, and specialists are relentlessly looking for ways to overcome them. In this episode, Mike and Ellie tackle some of these challenges and discuss the different compute platforms, their limitations, and the surge of new platform development, as well as the many challenges that hardware designers face as they try to move AI to IoT edge devices. Tune in, and learn some of the challenges of implementing the latest cutting-edge neural network algorithms on today's compute platforms.   In this episode, you will learn: The amount of energy neural networks use. (00:54) Why analog starts to be in the spotlight again. (04:30) How applications moving to the Edge impacts training and inferencing. (05:39) Data movement requires most of the energy consumption. (07:50) Connect with Mike Fingeroff: LinkedIn Connect with Ellie Burns: LinkedIn Resources: Catapult High-Level Synthesis Siemens EDA
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    10 分

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