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On November 15, 2018, FLOlmsted commented on Walking on the Sidewalk: Building the future of cities in Toronto :

An interesting read that sums up how Sidewalk Labs is driving urban innovation. As you mention, machine learning presents opportunities for a city to operate more efficiently and sustainably. The examples you provide of ML to enhance transit and sustainable resource use seem relatively uncontroversial to me. Data on passenger trends and transit usage is already collected by urban transit agencies – and passengers are likely to appreciate the efficiencies that come with better matching supply and demand. Similarly, tracking weather patterns, temperature, and energy usage is an extension of current practices conducted by landlords and weather forecasters. Where ML becomes challenging is in more personal collection of data, as you mention, and the potential to attach user habits to individuals. I’m curious to track how Sidewalk Labs deals with data privacy and surveillance as it moves forward in Toronto.

On November 15, 2018, FLOlmsted commented on Google and Gmail: Machine Learning for Defense, Not Disruption :

I’m not surprised to learn that Google is heavily investing in machine learning and AI. I believe that no other company is as well positioned as Google to develop predictive algorithms. In fact, I think that Google is at a tremendous advantage because of its existing access to data. I’d be curious to learn if Google records the content of personal emails and messages, and using that text to inform its algorithm. It likely does. Additionally, Google can integrates learnings from Google searches with Gmail, using Google searches to enhance its understanding of how people think and write. Integrating its existing data with expertise and code from its acquisitions should be a formula for success.

On November 15, 2018, FLOlmsted commented on Building a Better Future – 3D Printed Housing at WinSun :

Thanks for sharing this article about WinSun! I was not familiar with the company and it seems it has the potential to disrupt the construction industry in China. I see value in the company’s ability to standardize the construction process and offer lower, more reliable rates. As we’ve been learning in FRC, trust is critical to building a thriving market, and this company is creating trust in a market current plagued by corruption. My question, however, is what makes this company unique relative to others using 3D printing. Without a competitive advantage, it seems like this approach can be easily replicated. Additionally, I wonder if the bulk of the value delivered here is related to the provision of affordable housing. How do we avoid creating a new version of Levittown – a community of cookie-cutter houses? I agree with your intuition that WinSun could create value for customers by focusing on high quality design. By creating more custom design, however, does the efficiency of 3D printing go away?

There does appear to be a race to the top when it comes to autonomous vehicles. Companies like Ford, Tesla, and Lyft are all competing to innovate and acquire companies that will give them a competitive edge in the development of AI related to mobility. Perhaps Ford is at an advantage due to its well-established supply chain and production processes; however, as you mention, I believe the most successful AV companies will be those that invest heavily in new technology, attract top talent, and engage in partnerships, particularly with government which has a vested interest in keeping roads as they are today. Challenges include safety hazards and foregone taxes from parking tickets. To standout in what’s quickly becoming an oversaturated industry, Ford must focus on the technology integrated in its vehicles and how that technology speaks to other devices in the “internet of things”.

On November 13, 2018, FLOlmsted commented on Machine Learning at YouTube: Removing Abusive Content :

Very interesting take on how YouTube is grappling with the limitations of machine learning as a tool to filter inappropriate content. I am impressed by the success of machine learning in removing this content before it hits viewers’ eyes. However, not mentioned is the implications of this for freedom of speech. While YouTube can and should be accountable for policing harmful content, if its algorithm results in the over-blocking of content, including content incorrectly construed as offensive (assuming this happens) it could compromise the openness of the platform. I’m curious to see how YouTube is able to refine its algorithm to capture bad content and code it to pick up on the workarounds described, while not over censoring uploads.

On November 13, 2018, FLOlmsted commented on When Chanel trades sewing machines for 3D printers :

I loved this blog and how it brought to light the tension between traditional couture, which is handmade and labor intensive, and new-age couture, which can rely on additive manufacturing to create complex designs. I had the chance to go to the The Metropolitan Museum’s 2016 special exhibit called Manus x Machina: Fashion in the Age of Technology which delved into how technology is transforming fashion today. Clearly, 3D printing is already being integrated into fashion at the most creative, high-end side of the spectrum with designers like Issey Miyake and Chanel. It will be incredibly interesting to see how this tool transforms the commercial side of fashion, as you mention. While I don’t see 3D printers entering the home any time soon, I can foresee lines like Zara and H&M using this technology to further optimize their supply chains. Similarly, I can see custom tailoring and design being automated; however, I do think there will remain demand for the human side of these services. For the same reason many still favor a human checkout process at convenience and grocery stores, there will likely be resistance to complete automation in the world of design and tailoring as well.