ÜBER DIESE EPISODE
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:
Connect with Ellie Burns:
Resources:
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VERGANGENE FOLGEN SUCHEN
Vorhandene Folgen von AI Spectrum durchsuchen.
WEITERE EPISODEN IN DIESEM PODCAST
Simulation has been a cornerstone of the design process for
many years but despite how advanced modern simulation tools have become, there are
always ways to continue advancing. Artificial intelligence and machine learning
represent one such path to improvement, working in tandem with existing
simu…
Merging AI with operational technology (OT) is no simple
task, between concerns about robustness and reliability as well as data
privacy, there are many challenges to overcome. With that said, the potential
benefits make the endeavor worth the effort. Rather than bringing AI into every
aspect of ma…
Over time what was once thought impossible slowly becomes
possible. For all its flaws, the artificial intelligence of today would be more
at home on the holodeck than the board room even 20 years ago, yet today AI is
reshaping how people do their jobs in every sector. For every great leap in techn…
Generative AI is proving to be a powerful force multiplier
across many industries, allowing a single user to do more in less time and even
highly complex tasks, like product design, are reaping generative AI-driven
benefits. However, as powerful as these AI tools are, they must be carefully
applied…
Artificial intelligence and data go hand in hand together, whether
that’s as data used to train AI models or as AI models used to analyze and
retrieve data. In the industrial world, there’s a fine balance between leveraging
data to fine-tune shop floor AI systems meaning data intelligence is an equ…
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BEARBEITEN
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