ZL1

  • Student

Activity Feed

Interesting read! I agree that most innovation within consumer good like razors need to carefully factorize cost component. While the design and idea is cool, I doubt many would purchase based on ‘how its manufactured’ and ‘what it looks like’ especially in this space of razor. Reasons are: razors are mostly used in private therefore the ‘show’ element of the product is reduced; (from what I understand) these razors are replaceable ones and therefore consumer wouldn’t prefer value for their money on regular purchase.

Apart from printing the body, would 3D mass production of blade an option for manufacturers like P&G to consider? if they would do so cost effectively…..

On November 15, 2018, ZL1 commented on The Beauty of Crowdsourcing :

Interesting piece on Natura!

While I am not certain how crowdsourcing could help address Natura’s channel challenge, I am very positive that this could become one of Natura’s key competitive advantage. One of the key reason is Natura will enjoy the first mover advantage in this space. First, Natura is being recognized as leader in innovation help building brand reputation. Second, through crowdsourcing programs, Natura is also building brand loyalty with potentially future buyers. Last, Natura would have more time and experience in understanding how to efficiently translate results from these programs into business.

Barilla certainly have some barill-iant ideas! I would personally love to see an efficient on site manufacturing process being developed. This could lower the requirement of the food storage and avoid excess product. Therefore revolutionize the food supply chain and ultimately reduce the food wastage and costs associated with it. However, one of the critical challenges is cost. As discussed, cost is one of the biggest element impeding the application of 3D printing technology, and the reason why 3D printing has been limited to high value and high tech application. Furthermore, given the current focus is in processed food, cost is an even more important factor for consideration.

How interesting! Amazon is certainly creative and happy to try new ideas!

One of the reason that this didn’t fly was the net they casted was too wide. Although there were a lot of responses in building stories, there was really no way in assessing the quality of the scripts. I read that Amazon relied on popularity of scripts as a way to filter what script/story they will read and further develop. I assume that would be driven by how many edits and comments of a particular script are used as a key indicator for popularity, and therefore consumer’s interests for a real show. This might not be the best way of evaluation as there could be a net-work effect where an average script that got early attention could prevent other to explore all other contents. Perhaps by providing more scope and guideline would have made opensource script a more successful story.

On November 15, 2018, ZL1 commented on Fighting Fake News with AI :

Thank you for such an interesting post on a very real problem in the world of contents! Most of us are already rattled by the amount of contents that are fed to us, and trying to evaluate the ‘truthfulness’ of each piece of information is just impossible. I personally feel this project has a lot of potential. The lower hanging fruits for me are contents related to Hate speech and abusive content, Spoof websits and extreme clickbait contents. However, when it comes to analysing opinion piece such as political content, more caution should be exercised. It would be challenging to develop algorithms that is completed free of biasis as we view the world through our own lenses, that are affected by cultural background, national and personal interests, education level and many others factors. This might limit the audience who find this app useful.

Interesting read on Schneider Electric! There have certainly been lots of advances in technological development that should enable traditional manufacturers (in this case, chemical manufacturers) to produce more efficiently. One of the challenges I see in this space that could also become a hurdle for Schneider Electric is the effectiveness of technologies adoption by large enterprises. Many large companies have been introduced to the new and powerful software and technologies, however, they are not fully tapped into the promised capabilities and benefits. I believe partly due to the difficulty faced in integrating of new technologies into their existing platform; partly due to the lack of talents both willing and able to implement and utilize. I believe these issues need to be addressed before SE can look into designing significant capital infrastructure for digitization.

What an interesting piece! I wonder how this knowledge would affect the individual farmers who own and lives off their own farmland, would this the new knowledge enabled by machine learning allow farmers to grow and farm more efficiently on their own farmland?
To the question posed, in my view, one way to combat potential negative consequence of findings being used as tools to hurt societies is to make this information public. If combating global food shortage is the main objective, sharing this data openly could foster collaboration between companies and governments to address global food challenge. Descartes could potentially become a service provider in this space, receiving less profit from a bigger customer group rather than selling at a high market to selected few.

On November 14, 2018, ZL1 commented on Combatting Food Shortages—Have No Fear, Machine Learning Is Here :

What an interesting piece! I wonder how this knowledge would affect the individual farmers who own and lives off their own farmland, would this the new knowledge enabled by machine learning allow farmers to grow and farm more efficiently on their own farmland?

To the question posed, in my view, one way to combat potential negative consequence of findings being used as tools to hurt societies is to make this information public. If combating global food shortage is the main objective, sharing this data openly could foster collaboration between companies and governments to address global food challenge. Descartes could potential become a service provider in this space, receiving less profit from a bigger customer group rather than selling at a high market to selected few.

On November 14, 2018, ZL1 commented on Machine Learning at Ant Financial (724 Words) :

Interesting question and perhaps we can reference some economies with mature credit score system to get a sense of the possible outcome/implications. Take US as an example, its credit score system is well-established and entrenched in everyday living. This allows better allocation of resources and access to captial for many. However, people who are more amped in managing their credit score rating seem to be benefiting more than those aren’t and this creates unfairness in the system. On the other hand, we also see that many other Nordic countires with mature credit system but their personal credit score system is being used to a far less degree than US. It seems apparent to me that the use of the technology, rather than the technology itself is responsible for the unintended consequences. Therefore, society, policy makers, and the financial insitutions collectively have a role to play in setting boundaries for the use of this type of innovation.