Enormously entertaining talk by who could go do standup comedy if book tour fails. But good points that deep learning is not good solution if outlier detection is important, not good at surmounting bias, & needs augmenting for experimentation. ML failure modes 😂🤣👇
Conversation
“Until we have deep comprehension as well as deep learning, we won’t have AI that we can trust”
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McKinsey analysis - value of AI market $3.5T to $5.8T. Must be reasonable error bars on that prediction... #MKT4INTEL
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Solid advice from McKinsey that transformation of business to using AI to solve problems really requires top down education and change at most senior executive mgmt level. The scale of the change in approach required means it’s not going to trickle up from one team.
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I’m going to shamelessly steal all of mckinsey’s data for every business case I write at , and you should too.
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If we were able to label the data of audience participation in this room with “took photo of slide” and “has business owner job” there is an enormous spike right now on that intersection during McKinsey talk. Great great data and lessons learned. #MKT4INTEL
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“50% of the effort and cost in scaling AI is in operating model change. Don’t underestimate it”
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“95% of all human requests to alibaba are handled by a bot” - Michael Evans, President alibaba group 🤯
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“We think chatbots save us 160,000 hours a day” - alibaba. Of course at that ROI and scale, alibaba are able to invest huge huge resources into developing / scripting their bots to get to that level of coverage. I doubt many other companies are anywhere close to 95%.
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The scale that alibaba operates at is insane. But it also means their ROI calculations on AI efforts are not going to be the same as most companies. Their scale mean essentially anything plausibly feasible w a marginal value would be worth investing at any cost. #mkt4intel
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It is a lot of zeros indeed