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Translation for tomorrow: Understanding the impact of Neural Machine Translation on Language Service Providers
Language_Services
Posted on November 13, 2018 at 4:38 pm
This paper explores the impact of machine learning on the Language service providers, which provide translation and localization services for businesses.

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On November 15, 2018, Language_Services commented on Put Your Money Where Your Mouth Is. Align’s Approach to Additive Manufacturing :

Gabe, thanks for your work putting this together. Super interesting!

I agree that Align technologies is facing some significant challenges going forward. As you pointed out, the extremely low barriers to entry in this market spell trouble for a company that has existed as the only major player in the market thus far. To your question, I see aligns main competition as the major manufactures, as they will be able to produce at the lowest cost at the end of the day due to their scale.

I don’t think the start-ups will be a major competitor because while they can initially compete on price, the competition will respond and eventually price will be driven down to marginal cost. In my view, the best way to combat this is marketing and relying on the history of the brand. Viagra, for example, was able to hold on to their market share after their patent expired due to marketing. Align would need to do something similar to survive.

Thanks, again, for sharing!

On November 15, 2018, Language_Services commented on Open Innovation at Tesla – Time for a Change? :

Thanks for sharing this and for your efforts putting it together!

From my perspective, the question of whether this is good policy depends partially on what Tesla’s goal is. If they are purely a profit maximizing firm, I think it is likely a bad policy. The “rising tide lifts all boats” impact will likely not compensate for the lost market share from sharing their innovations. On the other hand, if their overall goal is to improve the world from reducing emissions, the lost revenues for them would be made up in spades through the long-term benefit to our global society. Of course, this is dependent on Telsa maintaining enough profits to fund future R&D.

On November 15, 2018, Language_Services commented on Open Innovation at Amazon Alexa: Crowd-sourcing Its Way to Platform Dominance :

Really interesting article — thanks for your work putting this together! One other application that lives that intersection of crowd sourcing and machine learning is using the recordings of commands Alexa is asked and when she makes “mistakes” to help inform what changes need or additions need to be made to the platform. I’m not sure if Amazon is already doing this (even though I have an Alexa myself…) but I would imagine they would run into ethical / legal questions: is it okay to use a recording of someone without their express knowledge or consent in order to improve a product?

On November 15, 2018, Language_Services commented on Fighting Fraud with Machine Learning at American Express :

Thanks for sharing this, Andy! Really interesting to see how much this has saved AmEx. Regarding your questions on jobs, I think this presents and interesting question for automation more broadly; how do we think about this trade-off in the context of our economy? Overall, I think it’s important to continue to pursue technological advances even if it does replace roles. If we think to other areas of automation, generally they have had a positive impact society even if the short term effect is fewer jobs.

Thanks, again, for sharing!

On November 15, 2018, Language_Services commented on How Stryker Hopes to Win with Additive Manufacturing :

Thank you for sharing this — really fascinating application of 3D printing! One potential application for this that comes to mind would be having a 3D printer in a hospital, so that the hospital can print out individualized medical devices for patients on site rather than needing to send in specifications to have them made in a factory. I could see this being useful in contexts where the patient needs emergency surgery and doesn’t have the time to wait for a part to be printed and shipped to a hospital. I wonder if costs would of the printer would ever come down far enough to make this a reality.

Thank you again for sharing!

On November 15, 2018, Language_Services commented on H&M Bets Big on Machine-Learning to Survive :

Tina — thank you for sharing this! A really interesting read. I’m curious to learn more about how H&M has used machine learning today in their stores. You mention that they used some machine learning techniques to understand that most of their customers in their Östermalm store were women; this, however, seems like an insight that could have been gleaned from a simple visit to the store.

I also wonder how they might be able to use machine learning in other parts of the their retail struggles. Could they potentially use AI to optimize their store footprint or help predict the customer trends you mention they have struggled to keep up with?

Looking forward to seeing what the future holds for them!