Sebastian Wilner

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On November 15, 2018, Sebastian Wilner commented on Adidas Lives its Slogan, Impossible is Nothing, with 3-D Printed Sneakers :

Hi KO, I loved this article.

To your question: “Will 3-D printing be an enduring technological innovation in the retail space?”. To me it’s unclear when it will happen, but my bet is that it will be so, especially in the apparel space. I think this because people have really different body sizes and styles, yet today most of us have to buy from the 4 or 5 sizes that each product comes on. If Adidas is able to customize clothing to my exact body shape and preference, it will have a huge advantage over its competitors. I can imagine going once to a store, getting my measures taken and then just ordering online the designs that I like and have them made to fit exactly to me.

I think they did a fantastic job by partnering with a cutting edge startup working on the space, and should consider acquiring them given the huge market potential of this initiative.

On November 15, 2018, Sebastian Wilner commented on Block by Block: Harnessing Open Innovation at The LEGO Group :

This article is so popular, congratulations! I think Lego was very smart in reacting to a decline in sales and realizing it has to connect more deeply with its customers to develop new business ideas.

Regarding your question: “Is Lego over-reliant on the external knowledge of it’s users? Should Lego have concerns about key knowledge control?”. I don’t think so: choosing the right idea to develop and having the right decision and testing process is something extremely difficult to replicate. Any other company can grab the thousands of ideas that LEGO probably receives but wouldn’t know how to execute on them. They should only be careful with keeping patents on everything they are developing and establishing clear royalty rules for each new product, but my guess is that they are handling that part of the process quite well!

On November 15, 2018, Sebastian Wilner commented on Kevin Stein at TransDigm Group :

Hi CPM. First of all: I loved your writing style, absolutely memorable.

Second, I think this is a fantastic take on the AM technology. It is clear that AM will be a perfect fit for TDG *at some point in time*: they carry very rare pieces and have to hold inventory for years. To your question, I don’t see the threat as imminent, so my intuition is that TDG has time to develop this technology in house, which is probably the cheapest option given that there doesn’t seem to be an immediate competitor taking business away from them today. It is likely that in the long term TDG will have to shift their business from supplying the parts that the airlines need to providing the 3D printers that airlines will have at their warehouses where they just print the parts they need. That’s why I see their business unit as a strategic in-house department.

The only alternative I see is that they can find an AM focused company to buy that meets some very specific criteria. My guess is that it will have to be a AM startup that specializes in really high quality / reliability printing, with very special materials (used for aerospace) and huge printers.

On November 14, 2018, Sebastian Wilner commented on Using Machine Learning for Crime Prediction :

Good questions Jack, jumping in here just for fun. In terms of biases, I would tolerate zero biases. For example, as soon as the system is establishing that the main driver for a certain threat is the person is from a certain race, I’d stop it immediately. ML systems can release that information if asked to do so. Regarding privacy, I think security comes first. As long as the data is properly handled I’d be happy to lose “a very big portion” of my privacy if it meant that my risk of being robbed or attacked is reduced significantly. But I think it’s a very personal decision and understand that some people would prefer to be less safe and keep their privacy.

On November 14, 2018, Sebastian Wilner commented on The Unilever Foundry – bringing innovation to 400 brands, under one roof :

Hi M. Interesting article. I’m fascinated with the topic of how established companies are dealing with the tech revolution, and I think this is a good example (or at least starting point) on how to embrace change within an organization.

My biggest concern, as you mention, is how real is this change? Would Unilever be OK with scaling a direct to consumer soap brand that poses a real challenge to Dove? If the answer is that they would, or that they would at least acquire the startup and incorporate its management to Dove’s executive team I’d be bullish on Unilever’s future. If they only focus on pushing companies that don’t disrupt their business then they’ll have a problem… because someone else will come and disrupt it!

On November 14, 2018, Sebastian Wilner commented on BlackRock: Is the Future of Investing in Machine Learning? :

Hi CG. Amazing topic choice, really interesting perspective on how Blackrock is taking the lead in the AI space within Finance. Some thoughts on this: firstly, I think most of the advancements in Machine Learning in this space until today have been related to structured learning, meaning that data scientists are more or less guiding the systems in terms of goals and available datasets. My intuition is that the big leap forward in investing will come from unstructured learning. Once an algorithm can successfully scan the whole web in search of market predictors I think we will start seeing real advances: for example measuring people’s mood in real time or establishing ultra complex relationships in real time between an article the newspaper in Nepal and the share price of GAP.

To your question on would humans tolerate an AI investor who outperforms the market but whose methods are indecipherable or unintuitive? I would 100%. I currently fly on an airplane 30000 feet from the ground completely managed by a computer while the pilots are taking naps… I think that’s way more risky than having a computer manage my 401k!

On November 14, 2018, Sebastian Wilner commented on Using Machine Learning for Crime Prediction :

Really interesting essay. This example of Machine Learning showcases both the immense potential that this technology has to make our society better and the tremendous risks that are come along with it, especially on the biases side.

Regarding your question on how governments should deal with this technology I think that Silicon Valley is kind of trying to reinvent the wheel here: humans have been debating about ethical problems involving new technologies for centuries. I think that once the problem and its risks become evident (and luckily they seem to be very clear here), the solution is to involve policy makers, social scientists, cientists, groups that represent the affected groups and build standards of engagement that guarantee transparency. What NY has done seems like a good first step!

On November 13, 2018, Sebastian Wilner commented on Can Machine Learning Save Us From Being Stuck in Traffic? :

Thanks Amina! I wanted to do a public sector example and there isn’t much published out there yet, this was one of the only neat examples I could find.