Sam D.

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Machine Learning and AI at Delta Air Lines
Sam D.
Posted on November 13, 2018 at 12:30 pm
Understanding how AI and machine learning are affecting Delta and the world's airlines.

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On November 15, 2018, Sam D. commented on UNICEF: Open innovation to tackle humanitarian crises :

Really interesting stuff. My biggest concern is what are the institutions and organizations withing the UN architecture that ensure the best ideas from these open innovation sources that eventually decide what is put into place. As an organization with so many different stakeholders and often competing objectives, and essentially huge amounts of information and priorities, what are the structures in place to bring these ideas forward and make sure that all relevant ideas are given their fair share.

On November 15, 2018, Sam D. commented on New Story: Remodeling Affordable Housing Through 3D Printing :

Super interesting insights and information. One thing I would be skeptical about is that this technological leap in terms of 3D printing is presented as a solution for the world’s homeless population. Much like increased food production promised the end of malnutrition, distribution and willingness of governments seem to be the largest impediment to providing every person with shelter. Thus, does driving costs down alone actually lead to more home ownership or less homelessness? Moreover, is their a potential misuse of this type of technology and could it potentially concentrate wealth in the hands of a very few who can purchase this technology while doing away with large amounts of laborers?

On November 15, 2018, Sam D. commented on The Additive Artisan: Richemont’s Use of 3D Printing in Mechanical Watchmaking :

Great article about a topic you are clearly passionate about. The concern you mention is central to success of 3D printing in the high-end watch industry. Where I do think this has already taken the industry by storm is in the lower end and more mass produced watches such as Swatch. Do you believe this is the case? Also, if 3D printing can remove a big chunk of the artisanal aspect of hand-made watches, and this in turns drive down watch costs, do you think that watch prices will come down? Or will companies be increasingly reliant on their brand to keep prices high and in turn increase their margins.

On November 15, 2018, Sam D. commented on Letting Go at LEGO: How Open Innovation Reinforces Product Creativity and Design :

I think this is a great topic that covers Open Innovation with exceptional detail. I fully understand how LEGO–unlike many of its peers–fully embraced the open innovation revolution and the impact it has had on its product line. I am less unsure of the negative aspects and the eventual impact of this decision. What risks do we further incur as a traditionally children’s toy company in outsourcing ideas to a largely adult class of people? Have any other competitors started to follow-suit?

On November 15, 2018, Sam D. commented on EasyJet: Reducing Delays with Machine Learning :

Really interesting essay that I enjoyed reading. Much like previous comments, I am curious to know more about the iterative nature of the systems. More importantly, the size of the dataset here seems critical in creating really valuable information across all airlines. However, it seems as if airlines are only developing these systems with their own proprietary data. Is this the case? If so, what limitations and shortcomings are there? Is there anyway to encourage more sharing of flight data and incident reports across airlines and even across airplane manufacturers that may help us get a better understanding of delays.

On November 15, 2018, Sam D. commented on Do More with Less: Can Machine Learning Help Feed the Growing Population? :

Really interesting essay that helps me better understand the cross-section of machine learning, big data and agriculture. One thing that would be helpful to understand is where the data feeding this software comes from and how reliable it is. Is this data open source or is this data proprietary to Monsanto? Are there risks or biases in the data that could companies or people could use in dangerous ways? Furthermore, i would be curious to learn about the iterative nature of the system. Right now it seems like a single output comes from a series of inputs but how is Monsanto bringing new data into the system and constantly iterating on it?