Great post. I think Natura is getting a head of the game by engaging in open innovation as a mean to bring in new ideas from the public. The community of beauty industry strikes me as an excellent target source for ideas due to the passion of beauty product users and the pride they take in the products they wear or use. The second part of the equation is as important as the first which is how to filter the ideas that are coming your way to make a meaningful innovation. I also wonder if there is a potential to use the input that is coming from Natura Campus or Cocriando Natura as information to feed your marketing department on what products already resonate well with your customer. This also seems to be a potential candidate for machine learning to help Natura make sense of all of this information to make sound decisions provided that ML is worth the investment.
This is an amazing post. When thinking of applications for 3D printing, food rarely comes to mind. I can see the potential in some cool types of food like cakes or sweets however I wonder if it has potential beyond niche types of food. At current costs and efficiencies, I am not sure that a 3D printed pasta would be the worthwhile investment. I think for additive food manufacturering to hit large scsle commercialization it will need to prove that it is solving bigger problems or bringing larger values to stakeholders in the value chain, manufacturers, distributors and consumers.
Those are great opportunities indeed. I would argue, however, that the highest potential of machine learning for LYB is in the maintenance space. If they can use the data from sensors such as mechanical seal temperature of pumps or spell back rate of compressors they can unlock huge value in predicting equipment failure. Moreover, they can use the help of ML to chose the turnaround windows based on the season of the slowest demands and perhaps have shorter spread shutdowns instead of one large major turnaround every 5 years or so. The energy market is positioned well to take advantage of ML.
Great post Emma. While detecting honesty is not going to be part of a loan application, LendingClub’s powerful ability bridges a key gap in the traditional loan system. Synthesizing large data to detect patterns gives LendingClub is a great advantage but I am not sure if large computing powers are needed to warrant a full scale machine learning tool. One may argue that the algorithm is already being implemented in house by traditional banks using a mix of human and less sophisticated computer analysis. Nevertheless , I think it is a matter of time before a machine learning scheme of some form becomes the mainstream in loan application analysis.
Excellent post. I wonder however what are the risks of a malfunctioning system and whether I trust it over a human pilot. Afterall, statistically speaking the number of flight collisions compared to the total global flying hours remain very small. Also, is the cost if the system low enough to warrant the investment? I am of the opinion that ADS-B will be a nice to have but not yet a necessity unless other features are added.
Great post and great innovation by Amazon. I am not so much concerned about the lack of face to face interaction in AmazonGo as if anything I think it is a plus for the new grocery. However, customers will need to be confident and comfortable about the accuracy of their receipt upon leaving without worrying that there may be mistake and having to always double check. I wonder, however, if the trend towards online shopping will make this brick-and-mortar store worth the investment. Will brick-and-mortar grocery stores remain a strong hold in the face of online retail or will the wave of online retail take over traditional grocery stores? I am a believer of the former but online time can prove that.
Brilliant post! Many have the perception that the old oil business has reached saturation in terms of innovation which is far from the truth. The old mentality of “run to fail” which once thought to reduce maintenance cost has proven to be wrong as the cost of unplanned shutdown in terms of lost production and expedited repair far exceeds that savings of preventive and predictive maintenance. The infrastructure to collect data for expensive machines such as compressors, turbines and large pumps is already there in terms of instruments and sensors, what is left is processing this data in smart machines to make informed decisions about maintenance.
Great post! I am surprised that Amazon Studios has shutdown the project without picking up good ideas. While I think that navigating through 27,000 submissions is very hard they could have used algorithm or machine learning to help filter good contents. I am sure that some of those submissions are indeed worth an investment and if Amazon studio does not take advantage of that competitors will soon do in some shape or form.
Interesting post indeed. I think sport shoes has a large potential for additive manufacturing given the relatively simple shape of the product. I wonder however, if the company will be able to drive down the cost to be comparable to traditional manufacturing methods especially given the low labor costs in some countries. Also, will printers have the ability to print different types of materials for different types of shoes. Also, Adidas will need to move quickly as there is no reason why competitors can’t follow suit.
There is indeed a great potential to utilise the data produced in infants’ intensive care units to inform doctors and scientists in the medical fields to make better decisions. Unlike Watson, the machines don’t need to make decisions but rather synthesise data to make evidence backed recommendations that a human doctor must review with a critical eye and make a recommendation accordingly.
I am glad that your daughter left the hospital after 28 days and I hope she is healthy now.
This is really interesting piece that touches on a potential revolution of a very old industry. I wonder however, if the world has enough feedstock material to support a large scale commercialisation of this 3D construction. Also, can the world keep up with manufacturing the building material and scrap the well established steel and cement industries?