thunderfromdownunder

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On November 15, 2018, thunderfromdownunder commented on Building Blocks: Winsun’s Application of 3D Printing in the Construction Industry :

I think the technological hurdle a company like Winsun faces is higher than many others. Chinese construction companies are already under extreme levels of scrutiny from regulators, the government and the public for having taken serious shortcuts that, in many instances, have resulted in catastrophic consequences. Winsun will need to ensure the fool-proof nature of its technology before it will be able to roll it out more broadly. This is difficult for a young company to do, given the investment developing AM technology requires. Hopefully, the investors in Winsun are mindful of the long-term nature of the company’s aspirations and are generous enough to support the company through even more stages of R&D, prototyping, customer development, public trust building and most importantly, wider commercialization.

On November 15, 2018, thunderfromdownunder commented on Additive Manufacturing at GE Aerospace :

Your questions carry significant weight, especially given the current turmoil that GE’s management (and stock price) are facing. How can a company, in the midst of a corporate restructuring, even begin to dedicate investments into something as long-term and experimental as AM? To adopt our model from LEAD, this vision needs to be endorsed from the top-down level. What’s challenging now, however, is how do you sustain an investment project across different generations of leaders? As the company continues to evolve its leadership, it will be ever more important to be wholly committed to these long-term projects such that they can cling onto their competitive advantage before it’s too late.

On November 15, 2018, thunderfromdownunder commented on Broad use of Machine Learning at Ford :

Data scientists are now a scarce resource in the job market. To acquire enough to build out a sophisticated AI technology team might be a lofty goal. I believe partnership with AI specialists may be the best route for Ford to take. Many car companies have now embedded similar (though not identical) operating software systems into their cars. This makes data aggregation, standardization and analysis slightly easier. However, specialist skills still need to be applied to this data in order to be able to extract the most important insights. This capability is relatively commoditized nowadays with the myriad of AI start ups that have been founded. Ford should partner closely with a few of these companies to obtain the insights, and invest its own resources into areas it knows best – embedding these insights to make cars better.

On November 15, 2018, thunderfromdownunder commented on Pinterest knows what you want before you do :

Concerning your first question, I wonder how Pinterest is actually compensated for investing in technology of this type of sophistication. I believe their revenue stream is predominantly advertising driven. While AI improves the consumer’s experience, can it necessarily be tied to revenue generation opportunities, especially given the difficult nature of attribution? If not, the case for Pinterest continuing to spend a significant amount of resources on AI technology may be waning, therefore eroding Pinterest’s competitive advantage. All this is to say, is Pinterest’s business model sustainable in the long run?

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

Alibaba is unique, not only because of its scale but because of its sovereignty. China, in the eyes of many nations, already poses severe security threats. I wonder if its investment into AI and collection of consumer data will naturally prevent other countries from welcoming it into their markets. Data of this sort can be easily manipulated, hacked and abused without the right type of infrastructure. Even if Alibaba invests in heightening the level of security its systems operate under, I wonder if it can convince other nations of the reliability of its technology to allow foreign governments to feel at ease.

I wonder if brick and mortar can actually be enabled by AI learning algorithms. Many brands are, in fact, starting as online brands solely for the purpose of collecting consumer data about trends, preferences and styles. With this data, brands are able to effectively open brick and mortar locations that are optimized for the specific fashion trends and tend to see better outcomes because of the data intensity that was invested into the project. I wonder if Kapsula has thought about monetizing the data they are collecting to benefit the myriad of other brands trying to penetrate the brick and mortar market.