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The Free Hand of Mickey Mouse & The Hobbyist Printer
abc123
Last modified on November 13, 2018 at 4:29 pm
The effects of at-home 3D printing on licensed merchandise through the vantage point of Disney

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On November 15, 2018, abc123 commented on Teladoc about Machine Learning :

I too agree with the question being asked, though I would stress that for the foreseeable future, this ought to be treated mainly as another resource (albeit an important one) provided to physicians to enable them to make more accurate decisions, i.e. a diagnosis. The reason why I am skeptical to replace doctors with Teladoc, even despite the possibility that Teladoc may be more accurate, is two-fold. First, physicians will always be at least as accurate as Teladoc because they will use the AI to help them make a diagnosis (the overriding assumption here is that since decision-making is still in the hands of the physician, if the physician decides not to concur with the AI, it is because the AI made the wrong diagnosis). Second, physicians do more than just diagnose and treat. They also help provide guidance on daily management of a condition and more importantly, can provide a patient comfort via human-to-human interaction. Therefore, while I think a trend towards more diagnoses from AI is beneficial, the counterweight should be in conjunction with a physician to provide more complete care to a patient beyond just a diagnosis.

On November 15, 2018, abc123 commented on Soft robotics – How 3D printing enables technological advancements to explore oceans and save lives :

3D printing stands to disrupt and revolutionize many industries. As you pointed out, Robotics is no different. Soft Robotics offers a new realm of possibilities while answering many traditional robotic problems such as delicate and finesse movements. I think that applications of soft-robotics will have a broad range of applications but will require significant specialization to be fully articulated in each specific market/application. ABB should try to predict what will be the first wave of uses for soft-robotics and then double-down on fully developing that technology. ABB should prioritize developing soft-robotics that mimic human hand movements. From here ABB would be a player in many markets from the medical industry: prosthetics and providing sanitary ‘human touch’ to babies in the NICU to consumer markets: mass creating fine art that has human-like qualities to the brush strokes and painting techniques.

On November 15, 2018, abc123 commented on Open Innovation for League of Legends :

League of Legends is a fascinating lens to view the rise of e-sports. I think League not only has the potential to have the staying power of basketball but to be far bigger than any-other traditional sport. The logic is two-fold. First, League is not tied to one specific culture and you don’t have to have a particular cultural upbringing to be exposed to League. It is not like Cricket and England nor is it like Basketball and the United States. Anyone with a computer can participate in the League world, and as the developing world continues to develop the number of potential League players develops along with it. Second, League fans have unique fan loyalty because anyone can download and play the game at any skill-level at any moment of the day. Basically, every fan is also a user. It would be analogous to every football fan also playing amateur football. This intimate relationship with the sport creates a unique level of by-in and fan loyalty. In 20 years, parents will excitedly be teaching their kids League strategies and be comparing KDAs (Kill, Death, Assist) ratios rather than shooting hoops. Open Innovation will be a plus if League can deploy it in a way that excites and engages its fan base without tarnishing the soul of the game or the basic structure the fans grew up with.

On November 15, 2018, abc123 commented on Expanding Open Innovation at NASA :

The ability to successfully execute long term projects should not be effected by expanding Open Innovation if NASA can strike a balance. NASA would be wise to increase its reliance on Open Innovation for discrete problems, or open problems that do not require project management. For example, using online crowdsourced platforms to have enthused members of the public search data for new asteroids, planets, and stars is a great way to employ crowdsourcing to solve an open problem [1]. Similarly, as discussed by the article and peer responses, discrete tasks such as an issue with one aspect of a project is an ideal way to free up resources and increase efficiency through Open Innovation. However, NASA should retain a strong core team of engineers and support staff for larger projects such as manned and rover missions. The nature of these projects requires strong project management skills and a cohesive team of engineers that are familiar with the project as a whole. Relying too heavily on Open Innovation could comprise these projects by miss managing the complexity and many moving parts integral to these project’s success.

Regarding confidentiality, NASA should navigate the confidentiality issues by treating Open Innovation like any other contracting service. The U.S. government loves to contract out services even on top secret projects such as weapon development and counter-intelligence. For more confidential issues, NASA could offer the Open Innovation challenge to a smaller list of pre-approved and trusted Open Innovators. Perhaps it will evolve to a point where Open Innovators will have to hold some sort of security clearance to bid on government Open Innovation challenges. A niche Open Innovation market could evolve.

[1] Garner, Rob. “Funded Website Lets Public Search for New Nearby Worlds.” NASA. February 15, 2017. Accessed November 15, 2018. https://www.nasa.gov/feature/goddard/2017/nasa-funded-website-lets-public-search-for-new-nearby-worlds.

On November 15, 2018, abc123 commented on GM and Machine Learning Augmented Design :

The question you posed regarding the viability of machine learning augmented design in relation to traditional manufacturing techniques is interesting. As mentioned in your paper, with smaller non drivetrain components prototyping via machine learning has been proven to increase efficiency and reduce costs. However, I feel that with larger more complex components creating the array of suggested prototypes for testing may pose challenging with traditional manufacturing techniques. The answer may rest with additive manufacturing or 3D printing. Prototype parts could be produced with 3D printers and tested. The final, selected part could then be mass produced. In fact, 3D printing companies like Stratasys have emerged to specifically “prototype, test, and produce all manners of tools, jigs, fixtures, and street-ready parts with unprecedented speed and efficiency” for the automotive industry [1]. While complex drivetrain printing technology could still be on the horizon, the technology is developing rapidly and could be a practical solution in the near future.

[1] “Automotive 3D Printing Solutions | Stratasys.” 3D Printing Solutions by Stratasys. Accessed November 15, 2018. http://www.stratasys.com/automotive.

User deleted this comment on November 15, 2018
On November 15, 2018, abc123 commented on Teladoc about Machine Learning :

I too agree with the question being asked, though I would stress that for the foreseeable future, this ought to be treated mainly as another resource (albeit an important one) provided to physicians to enable them to make more accurate decisions, i.e. a diagnosis. The reason why I am skeptical to replace doctors with Teladoc, even despite the possibility that Teladoc may be more accurate, is two-fold: 1) physicians will always be at least as accurate as Teladoc because they will use the AI to help them make a diagnosis (the overriding assumption here is that since decision-making is still in the hands of the physician, if the physician decides not to concur with the AI, it is because the AI made the wrong diagnosis); and 2) physicians do more than just diagnose and treat. They also help provide guidance on daily management of a condition and more importantly, can provide a patient comfort via human-to-human interaction. Therefore, while I think a trend towards more diagnoses from AI is beneficial, the counterweight should be in conjunction with a physician to provide more complete care to a patient beyond just a diagnosis.

On November 15, 2018, abc123 commented on Vojd: filling the Void in Luxury Design with Additive Manufacturing :

I definitely agree with the opening paragraph of this comment. In my mind, the high-end fashion industry is predicated on providing a product that is hand-made and will enable the consumer to feel special when donning the article/product. Where I disagree is where you mention that it might be cost-prohibitive for discount brands to copy it. While copying may initially be cost-intensive, there will surely be discount brands who can generate the capital necessary to replicate this process. And if the latter happens, then there is no point-of-difference between the “luxury brand” and the “discount brand”. Therefore, it is not in the interest of luxury brands to use additive manufacturing for fear that they will dilute their brand identity.