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Machine Learning's Limits
Jul. 03, 2018 – Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs.
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SE: How much of what goes wrong in machine learning depends on the algorithm being wrong, or one piece of hardware that's different from another running the same algorithm? What's the source of errors?
Soheili: At the end of the day, we're dealing with statistics about what's right. So we may be looking at 87% versus 90% accurate.
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