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How Humans and Everyday Tech Can Outmatch AI

YoungUpstarts

There’s an increasing awareness that machine-learning algorithms encode biases and discrimination into outcomes. After all, algorithms simply look for patterns in the data. Whatever is embedded in the data is what the algorithms will repeat. Algorithmic problem-solving is also severely hampered by the quality of data it’s fed.

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Episode 1: Business Loans, Website Tips, and the Apple Watch – The Bcast

Up and Running

Twenty-three year-olds in New York City running a small business. Next week actually Google is rolling out a new algorithm that if your website is not mobile friendly and people are searching on mobile devices, they’re actually going to deprecate your results. We weren’t just weak. We were terrible.

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Lessons Learned: Five Whys

Startup Lessons Learned

Because five whys kept turning up a few key metrics that were hard to set static thresholds for, we even had a dynamic prediction algorithm that would make forecasts based on past data, and fire alerts if the metric ever went out of its normal bounds. You can even read a cool paper one of our engineers wrote on this approach).

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How Netflix Creates Immersive Experiences with Exceptional Design and UX

ConversionXL

This data is then used as inputs in the Netflix algorithm to “jump-start” personalized recommendations (more on personalization based on their algorithm in a moment). Once watching commences, their behavior supersedes initial preferences as their algorithm continuously populates the homepage with newly relevant media.

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