Z

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Challenging privacy constraints is always a worthy conversation. Society wants to have access to enhanced products and sometimes this can best be achieved through people’s willingness to share personal data which can then be used to create a database that is analyzed. However, whenever receiving crowd sourced information, it is crucial to verify the reliability of the source because results are heavily dependent on the information provided. 23andMe should have an authentication process to ensure the efficacy of their results because incorrect generalizations can lead to detrimental effects on one’s health or measures one takes after being wrongfully notified of a predisposition to a certain ailment. Ensuring that the data submitted to 23andMe is kept confidential is a difficult issue. Their has been numerous cyber attacks on corporations that has led to leaked data and I believe that if this information gets into the wrong hands, people can be preyed upon because of their health vulnerability.

On November 15, 2018, Z commented on Open your open innovation to suppliers :

This write-up provides an intriguing argument on how open innovation in one’s supply chain can benefit all organizations within the supply chain. Oftentimes, when people think of open innovation, they consider only the end user of the product. Feedback of this form routinely leads to comments that focus on creating a product that increases usability and adoption. However suppliers are uniquely positioned to provide feedback that can reduce cost, improve design, leverage best practices or draw from other field, address technical constraints and streamline manufacturing or operating process inefficiencies. To gain buy in from suppliers, Dell needs to effectively and adequately communicate how supplier feedback can not only lead to a better final product but increase profits for its suppliers. The information should flow in both ways as both Dell and the supplier should start a two-way dialogue on how to optimize production and supply chain management. There could also be a monetary, contract or branding/marketing incentive of some kind that promotes collaboration of innovative ideas.

On November 15, 2018, Z commented on 3D Printing Straighter Smiles :

Thank you for sharing your thoughts on the impact additive manufacturing (AM) has had on the dental industry. Align’s use of 3D printing to create customized clear aligners for patients while improving the cumbersome method of braces installation for both orthodontists and patients has been revolutionary. This technology has arguably led to better customized braces without sacrificing time or labor efficiency on the part of the dental technicians. Align has shown that they are not fearful of breaking the mold and being the first mover. As a result, I believe that they will continue to adapt to newer methods to enhance the manufacturing of their braces and strive to reduce the cost to potential patients. They should and can leverage the historical and experimental data of their existing patient log to uncover the nuances of the market, improve design and uncover limitations of the technology to continue progressing regardless of the entrance of new competitors to the industry.

Having raised $86 million, the likely outcome for Glossier is an IPO or selling to a cosmetics conglomerate. History has shown that the result of such a liquidity event often leaves a company’s engaged audience feeling ostracized.

One way to avoid having its fans feeling like the company “sold-out” after liquidity is to also share the corporate journey. Not only will the consumers feel involved in helping with products, but they would likely remain loyalists if the founder shared her long-term vision and blogged about reaching each milestone.

In 1997, Amazon founder Jeff Bezos famously wrote his first letter to shareholders that stated, “We will continue to focus relentlessly on our customers.” The founder has remained true to his word, which is why Amazon is one of the few companies in the U.S. that is equally beloved by consumers and Wall Street.

On November 15, 2018, Z commented on Comcast: Don’t cut the cord :

Thank you for bringing to light the current inefficiencies in traditional cable and in particularly Comcast. I believe that although Comcast is entrenched as a cable behemoth, the company can undergo an incarnation using artificial intelligence and machine learning coupled with it’s sheer amount of data to provide an offering that can rival Netflix and Google. It is uniquely positioned to understand what has detered many users from watching traditional TV and eventually lead them to cut the cord.

I like the changes that Comcast has made to incorporate AI and machine learning into its business model. This is vital if it wants to be a major player in the media/telecom space. A radical and transformative change that embraces the use of technology to better understand customers and their viewership patterns will bode well as TV as we know it is declining.

On November 15, 2018, Z commented on Using 3D Printing to Break the Iron Triangle :

Thank you for your research into how technology can revolutionize an industry that has been in existence for over a century. I do concur with your view that 3D printing can enable engineers and companies to more adeptly plan and scrutinize projects by having a physical miniature design of the platform that they intend to build. Doing so would help to reduce cost and enhance innovation as workers are able to see how the construction or design of a particular feature on the facility impacts others. Oftentimes, oil and gas project engineers are not able to foresee how a particular design can hinder efficiency of production until it’s too late.

However, I do not believe that 3D printed equipment such as pipes can be used in the actual construction of a project. This is because there are so many safety standards and regulatory specifications that cannot yet be captured by 3D printing. Also, if a pipe were to burst leading to a leakage, how would it be fixed? Would an entirely new pipe have to be built?

The significance of the iron triangle cannot be understated as companies need to find innovative ways to reduce costs, especially when exploring unconventional basins or hard to reach resources. I assume that there could be a sweet spot in which we can make effieciences or enhancements in one direction without having to make sacrifices in the other. I believe that leveraging technology will be the best way to go about achieving this.

On November 15, 2018, Z commented on Can machines replace lawyers? :

I do not believe that machine learning algorithms will reduce or eliminate jobs in the legal industry. This is because the human element and judgment required in this field cannot be understated. However, AI could instead increase jobs because it would make becoming a lawyer more attainable as potential law students would not necessarily have to gain admission to top law programs. Artificial intelligence can also perhaps democratize lawyer’s ability to perform due diligence, document review and research.

Machine learning in this context may in fact hurt work life balance because access to artificial intelligence may compell lawyers to leverage as much information as possible to defend their case rather than prioritize what information is necessary. More information at one’s disposal isn’t always better.

I think law firms may be forced to reduce prices because the supply and demand nature of the industry could change as increased competition will ultimately lead to lower prices.

On November 15, 2018, Z commented on Hinge: A Data Driven Matchmaker :

This is an interesting article about online dating and how machine learning can optimize dating apps to help people find more suitable matches. I think that Hinge’s main goal should be to increase the number of suitable matches and leave it to the individual to find their perfect match. There are so many intangible factors that come into play when one choses a partner that I do not think can be captured by machine learning. However, Hinge can play a vital role in helping to initiate that first interaction and foster higher levels of compatibility.

The final sentence makes a compelling argument for Hinge to have more data points to enhance algorithm efficiency.