John Smith

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YouTube | Machines Cleaning Up Human Content
John Smith
Posted on November 13, 2018 at 7:46 pm
Every minute, over 400 hours of video are uploaded to YouTube. What role can AI and Machine Learning have in monitoring content to ensure it is safe and suitable for the platform and viewers?

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On November 15, 2018, John Smith commented on MOO-ve Over Alexa, Meet the Udderly Efficient IDA (a.k.a. the Intelligent Dairy Farmer’s Assistant): How One Food Conglomerate Helped Pilot Machine Learning to Make the Dairy Industry More Sustainable :

Loved this article! It would be fascinating to hear a local farmer’s point of view on the leveraging IDA and other IoT products into farming. I am curious if they see any ethical/animal safety issues from applying these types of products to the animals. I am also curious if Danone has done any product testing – does the milk and dairy coming from these cows noticeably taste better? Is it actually healthier?

On November 15, 2018, John Smith commented on Open Innovation at Amazon Alexa: Crowd-sourcing Its Way to Platform Dominance :

Fascinating article! To answer your question on how to out-beat Google and Facebook, I believe it will be critically important that Amazon look for ways to integrate the Alexa Voice service into other third-party products. Partnerships with voice-enabled consumer products such as televisions, laundry machines, light switches will become important to grab and maintain market share. Amazon should look to the biggest manufacturers and sway them to be their “voice partner of choice” before Google and Facebook beat them to it.

On November 15, 2018, John Smith commented on Glossier: Changing the Face of the Beauty Industry by Crowdsourcing the Magic Formula :

Really interesting article! What I find most striking is that Glossier was born out of a media publication. It was incredibly smart of Emily Weiss to harness her significant consumer following and data that revealed customers wants/needs into a product line. I bet if Glossier had launched its products before launching Into The Gloss, it would not have been nearly as successful. It will be interesting to see if Glossier continues to be successful as a business, or if it will be surpassed by another D2C product line.

On November 15, 2018, John Smith commented on Leveraging Technology for Global Health: 3D printing in Rwanda :

Thank you for writing this piece, and focusing in on how this new technology can be harnessed for good. I see partnering with developing nations like Rwanda as a win-win for both the local communities and the companies funding the projects. Not only does this provide jobs and opportunity for underserved communities, but it also serves as an opportunity for a corporation to boost their brand image and fulfill their corporate-social responsibility.

On November 15, 2018, John Smith commented on AI chatbot behind Alibaba’s $31 billion Single’s Day sales miracle :

Great article! As a consumer, I really appreciate when a ChatBot is able to not only answer the questions I have, but also anticipate and provide additional relevant information with little prompting. I am curious if/how Alibaba works with advertisers. For example, if a shopper asks AliMe for a recommendation, what powers the answer? Is it based on past purchasing behavior, or can brands pay to have their products show up in the responses, similar to SEO/SEM?

On November 15, 2018, John Smith commented on Sephora and Artificial Intelligence: What does the future of beauty look like? :

Very interesting article! It was fascinating to read how Sephora is leverage AI to make more personalized recommendations to consumers. While reading this, I wondered what the risks are associated with the reliance upon AI. For example, I could see how a computer might recommend a product that would cover up a beauty mark on ones face. While it might be considered “imperfect” to a machine, it could be offensive to the consumer if Sephora hones in on that feature. This could be extended to sensitives around skin-tone and race as well. Sephora will need to ensure they put safeguards in place so they do not inadvertently offend or turn off their consumers. These are mistakes that a human would likely not make (as they’d rely upon good judgement) but are difficult to teach a machine powered by AI.