The virtual try-on service which you described made me immediately think of the Snapchat filters. These filters are playful AR experiences that transform you or the world around you. Filters can be creative effects such as for example beards, hats or new hair you can add to your face. I feel like this is similar to the virtual try-on service of L’Oreal but probably less advanced when it comes to details. I am convinced that such virtual try-ons will be extremely popular in the future, especially when it comes to clothes. However, I could well imagine that in the future it will be a winner takes most / all market as the best solution will probably be implemented by many or most of the customers. As you described in your post, the color matching using computers is pretty difficult as coloration is not always accurately depicted using computers. I think solving this problem requires an enormous amount of resources and specialists that L’Oreal may not have at its disposal. Therefore, I agree with you that it might be better for L’Oreal to outsource this service in the future and focus on its core business.
For me, the introduction of new technologies (in this case AI and machine learning) in the sports industry is always very fascinating and at the same time questionable. Formula 1 and sailing are both sports which, before the introduction of artificial intelligence, were already very dependent on the sports equipment being used. I would say that at the very highest level, all the athletes can sail or drive a car exceptionally well at similar levels. It’s just nuances that make the difference between winning and losing. From my point of view, the use of sports equipment that is superior to its competitors distorts the competition (as for example Mercedes in the previous 7 Formula 1 seasons). With the use of AI and ML, at some point it will no longer be the personal skills of the athletes that matter, but which team has the best algorithm or, in the case of the America’s Cup, the best simulator. On the other hand, this could even out in the long run, because in the event of success, all teams will rely on such technologies, as we saw in the Hoffenheim case with the footbonaut.
To briefly address Patric’s point, at some point McKinsey will probably have to face the question of whether they can sell the same technology to competing teams. Since they have already had a lot of experience with TNZ, I wonder to what extent they will be allowed to work with new teams from the same industry and pass on the knowledge and further developed model from their previous projects.
That’s an exciting use case of analytics in in sports! Just recently I attended a meeting with the Harvard Sports analytics association where we had the chief data of Manchester City as a guest speaker. It was super interesting! However, he was mainly focusing about the valuation and early scouting of youth players. We discussed that compared to baseball or american football, soccer just has a few more unknown variables, which has so far prevented the adoption of data analytics at the scale we are used to in the US. But I absolutely agree that by evaluating biological data of soccer players, the load in training and competition can be controlled much better and thus injuries can be better prevented. However, I have some doubts in the data set at this time. Since the reference data has been collected between 2019 and 2021, several games took place without spectators. On an athlete’s level, this takes away a certain amount of stress, as the perceived mental pressure in the stadium is not quite the same (for a penalty kick for example the heart rate is way lower). Therefore, it could be that the model is possibly somewhat biased for the time after.
Super exciting use case, thank you!
That was really interesting Isabella! As mentioned in the comments before, I’m very surprised that the 9 output fields exclusively show beach vacations. Considering the already quite sophisticated capabilities of this AI system, I would have expected slightly more variety or at least a distinction between summer and winter holidays. However, I agree with Nthato that Craiyon probably leverages a lot on exisitng popular search results which in turns leads to skewed output results. Nevertheless, I am surprised that they did not fix this issue yet since this seems rather easy to me. I guess there are just bigger things to care about such as the faces for instance.
Funny thoughts Sultana! As far as I can remember, Dany can’t have children at all, which would have made it even more exciting to get a clear answer from the AI. Let’s hope for some light in the dark in a few years.
As for the spaceship of the dog, I noticed that it always looks similar with the dog in a small window. I could have imagined or I expected this in hundreds of other ways. I wonder if the input data in this case was somewhat skewed so that there was only this one sort of spaceship in the learning sample.
That’s an interesting approach Feifei. I have to admit I am not an expert in art at all but I was wondering in the past whether Artificial Intelligence could take over the innovative thinking part for humans. If I translate this approach to the business world I am wondering whether a sophisticated algorithm might one day actually be able to suggest new ideas and business models for us. When I visualize this, it is certainly super exciting but also quite scary.
Super cool app that I have been missing in Europe and especially in Switzerland for years! Sure, digital booking systems for different sports venues is no rocket science but I see a fantastic added value in the matching tool. Too often I was looking to play tennis or squash and all my known sparing partners were not available. However, the question I always ask myself with this matching is the difficulty of self-assessing one’s own level. When players are not officially ranked, it may not always be easy to find the appropriate match right away – be it for your own under- or overestimation.
Looking forward, I foresee an extraordinarily sustainable future for EasyCancha. With a large user base, countless applications and extensions are conceivable on this platform. I am thinking of coaching services, where for example tennis coaches can offer their services to a broader audience, or EasyCancha tournaments, where the best user of the platform is determined in a specific sport. Since the whole service is offered digitally, scalability does not seem to be a problem in the long term. I’m thrilled about this platform and looking forward for such a solution to catch up in Europe.
Incredibly exciting business, thank you Aditya for introducing us to this start up. You write in your post that Dunzo can deliver items spanning the entire gamu. I was wondering while reading if the company had to implement any ethical fundamentals or something like order filters which weeds out or prevents morally unacceptable orders. Furthermore, I asked myself whether a customer has to indicate the contents of the package to be delivered. I could well imagine that this great service could quickly fall victim to abuse. I am thinking of transporting drugs or criminal items, for instance. The question then also arises about who would be liable in the event of illegal transportation. In my view another interesting issue to observe will be a potential expansion into other countries where Dunzo has to consider whether cross-border services are going to be possible or not. All in all, a great idea, which from my point of view has or already had to clarify some pretty big legal questions.
Thanks a lot Feifei for your post. I have heard so much about Pinterest in the past few years but I have to admit, until now I never really understood why people are using Pinterest. I guess its really about finding inspiration and ideas for personal hobbies and interests as you said. Personally, I think I am never going to be a Pinner, however, I noticed that when I was looking for a fine recipe, I inevitably stumbled across Pinterest posts. Nevertheless, this happens so rarely that I will probably never consider having my own profile. I could well imagine that this recurrence of users could be a problem compared to other social media platforms such as facebook or instagram. Do you have any information on how often the average user dials in on the platform?
Super interesting casse Anand – thanks a lot!
The idea of bury real time sensor into fields makes perfect sense and seems highly scalable too me. As far as I understood it out of the second video, Bayer Croop Science is mainly operating in Britain and Western Europe but has now partnered with the world’s largest drone service provider, XAG, for digital farming and precision spraying in Japan, Southeast Asia, and Pakistan. This got me thinking. I agree with Bayer that the idea of digital farming would generate more added value in less developed countries such as Southeast Asia or Africa. However, I wonder if the use of drones in these regions is scalable. If you think about it, every field on the planet would be a potential target. How do you successfully get such delicate objects, as drones are, into a rough field and from there across the country without breaking them. I also wonder if every farmer in this area has access to a tablet or smart phone. Has anyone information about how Bayer plans to handle this or are they currently just focusing on large scale industry fields?
Something similar to Elizabeth happened to me five years ago. I traveled to Hong Kong and paid for the cab to the hotel with my only credit card. When I wanted to grab breakfast later, the card was already blocked and I was literally standing there without a cent in my pocket. This is not as easy as it seems in a time without Apple Pay and co. I therefore understand customers who are / were initially not particularly enthusiastic about machine learning algorithms in credit card fraud detection – especially people who are not tech aware.
But, as we learned from Manuels post, the beauty of these systems is that they are constantly learning! Hence, this has never happened to me again so far. In fact, I have often benefited from these systems by recovering amounts from incorrect transactions on my card in no time. I am therefore a huge supporter of such mechanisms and convinced that big data solutions like AMEX’ Enhanced Authorization system will bring even bigger added value in the future. I would also be willing to instantly provide more personal data (e.g. biometric data) for even better functioning algorithms.
Thanks Feifei. In your post you mentioned Starbucks’ mobile app which today has more than 17 million users. I read articles that the implementation of this App in 2011 marked the company’s point of entry into data and analytics. I was curious if that might had a visible influence on Starbucks’ financial numbers. So, I did a little back ground search and stumbled over 2 figures (which I unfortunately cannot insert here but I added the links below). The first shows that net revenue plateaued after 2008. The same can be stated for the number of Starbucks stores running worldwide. After 2011 (and the implementation of the app and data analytics) net revenue increased heavily and the Starbucks network experienced significant growth. I wonder how much is effectively due to the newly introduced data analytics system and to what extent this is due to normal growth following the global economic crisis.