lill janglas

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Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure
lill janglas
Posted on November 12, 2018 at 11:16 pm
Demand for applying digitization and machine learning to current operations has increased significantly for manufacturing companies today. Can one company expand its reach to help all industries reach their goal of digital transformation?

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On November 15, 2018, lill janglas commented on Amazon Studios’ experiment in crowdsourcing scripts: were they right to abandon open innovation in developing new content? :

Uh yeah, Amazon Studios should have kept open source movie/TV show ideas as a publicity stint! I don’t feel like there is harm or foul in this. I wonder what they offered the winner of the show and if there was potential for a submitted idea that one would feel was “copied”. This could create a potential risk to the whole process.
I liked your article quote: “If you’re betting on one show, it’s got to be right down the middle of the fairway, but if you’ve got 14, you can allow people to try new things”. Knowing this, I think it makes sense that Amazon ditched the open source. It’s not about the quantity of ideas, its about quality of a few and I’m guessing there were too many ideas to sort through on this platform.

On November 15, 2018, lill janglas commented on The Missing Piece: How Lego Found Open Innovation at a Critical Time :

Instead of creating an open source platform of ideas and an internal LEGO member choosing a winner, I think this competition would be best set up as a social media voting system. That way there is no one offering an idea and accusing LEGO of “stealing” it to make a bunch of money. People would be incentivized to present their ideas more clearly.
I actually think this use of open innovation may be more about launching a marketing campaign, than it is about gathering more “outside-the-box” ideas. There’s really no harm, no foul for LEGO to give this a try!

On November 15, 2018, lill janglas commented on Machine Learning: Schneider Electric Positions Itself to Lead Digital Transformation of Infrastructure :

Thanks, Julien! On your comment about not knowing that SE was so proactive about digitization… they actually just rebranded this year!

On November 15, 2018, lill janglas commented on Can it be? A Solution to Lack of Innovation in the Engineering and Construction Industry……….? :

HTL makes a good point in calling out the conservatism and sluggishness of the construction industry. I think the biggest factor is that there is generally a huge learning curve to adopting new practices. You mentioned the need to retrain all of the designers, engineers and architects – and you are absolutely correct. Then, the 1-5 projects after the initial training will most likely take a huge productivity hit (think of “Englishitization” case from class!). There’s a chance that this would make the industry more productive, but it would take a steep learning curve for people gather experience first.

Your question at the end also mentioned a risk of the new technology having potential to collapse, cause injury, etc… TONS of testing would have to be performed before a change like this made it into the building code so I wouldn’t worry too much. I think AECOM would want full certainty that this technology is allowed in building code before deciding to invest in it.

On November 15, 2018, lill janglas commented on How Birchbox Stays Competitive using Machine Learning :

I find it interesting that Birch Box started as an online subscription company and now is moving into retail! It will be cool to see if Birch Box finds different preferences in the store consumer vs. online consumer. I think one problem that they will run into moving to retail is the quality of data on consumer purchases and decision factors. Currently as an online store, they can match buyers by profiles. In Walgreens, they wont be able to match a repeat buy that purchased in Texas with one credit card and in Boston with another (I don’t think….). My guess is that retail will make it harder to draw conclusions on the success of their product selections and make it hard to scale their machine learning.

On November 15, 2018, lill janglas commented on Machine learning in the Chemicals industry: Lyondellbasell :

Tom, great article. You really hit the nail on the head with the industry’s use of computer programming to help make the decision in feedstock selection. I unfortunately do not believe this data or program is entirely valuable outside of internal use, because the programs are generally programmed for specific plants and not very scale-able. Overtime, using historic data, the programs can be iterated and improved in predicting the best feedstock, but ultimately human judgement makes the final decision.

To answer your discussion question, I don’t think the data LYB owns is valuable to third parties. I think third parties can be hired to help program more efficient machine automation systems in plants, but their data is best used for internal decision-making.

On November 13, 2018, lill janglas commented on Flying from Prototyping to Mainstream: 3D Printed Aircrafts Top Out at Speeds of 150mph :

The video and article feature one Aurora aircraft model that has found success in partnering with the US Military. I am curious what the next market and revenue stream that Aurora will try to serve with their next model. Or potentially their breakthrough AM technology can translate to Boeing’s own manufacturing process?