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For John Snow Labs, doing good with NLP is in their DNA (and yours)

For John Snow Labs, doing good with NLP is in their DNA (and yours) Read later Summary: Too often, the AI startup field comes off as a VC-funded money grab. But commercial NLP healthcare player John Snow Labs is doing things differently. Their Spark NLP open source library includes support for 375 languages. Here s why their approach stands out. (via Fotolia.com) Why was Dr. John Snow designated the Father of Epidemiology? His painstaking investigations of the outbreaks of deadly cholera in London in the 1850s led him to conclude that the disease was caused by contaminated water. His meticulous data gathering pinpointed the source at a single water pump.

The problem with Ethics by Design - why this WEF report gets AI Ethics wrong, and 25 techniques for producing trustworthy AI

Read later Summary: A recent WEF report called Ethics by Design reinforces problematic misconceptions about AI ethics. Here s where I think the report went wrong - and my own personal 25 point list for avoiding AI project speed bumps. I recently delved into a December 2020 WEF report, Ethics by Design: An organizational approach to responsibile use of technology. Unfortunately, this white paper underscores the numerous flaws in the current approach to AI ethics I ve been critiquing on diginomica. It essentially applies the theories of Richard Thaler, Daniel Kahneman, Amos Tversky, and especially, the paper, Treating Ethics as a Design Problem, by Nicholas Epley and David Tannenbaum. There is no counter-argument, as the paper seems to assume that these theses are entirely applicable.

Metadata Shmedadata - today s approaches to metadata are inadequate, and that s a problem

Read later Summary: Struggling with metadata is nothing new, but there s a misconception that advanced data tech and cloud storage solved this problem. That s not the case - so what is the way forward? I ve been thinking about metadata. I know that s a strange thing to think about, primarily when I used to refer to it as dead data in a drawer, neatly arranged. And it was. Our halting attempts to tag extracted data with a semblance of meaning always fell short - because it was just too hard. And it was even harder to figure out how to get application programs to use it effectively.

What FP&A teams need to know about AI/ML

What FP&A teams need to know about AI/ML Read later Summary: With a whole forest of abundant data to hand, how do finance leaders focus on the detail? Grant Halloran of Planful shares three reasons why AI and ML help enable continuous planning (© amenic181 - shutterstock) Finance leaders have more data at their fingertips than ever before. Then why is it so difficult to see the forest for the trees? Since the forest of data is so huge, finance professionals can find it difficult to pick out broader patterns, trends, or inconsistencies. These are the key insights that point to the bigger picture and ultimately, an organization s ability to be successful.

NRF 2021 - ZineOne takes up our hyper-personalization debate on AI and retail

Read later Audio version Summary: When you post a scorching critique of hyper-personalization, the last thing you expect to get is a reply - from a personalization vendor. As NRF 2021 winds down, the debate on personalization carries on. Here s what ZineOne has to say. (Manish Malhotra of ZineOne talks personalization) After my spleen vent on the myth of hyper-personalization, guess who I heard from? AI personalization and predictive marketing vendor ZineOne. When we kicked off our NRF 2021 retail interview, I asked the ZineOne team: why reach out to me, given my unhinged critique? As ZineOne s external PR lead Austin Edgington told me:

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