Jona Babi

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Affectiva’s emotion AI humanizes how people and technology interact
Jona Babi
Posted on November 13, 2018 at 1:55 am
When machines understand human emotions ...

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On November 15, 2018, Luna commented on Unilever and Open Innovation: How does the emergence of digitally native brands change what it means to innovate? :

In my opinion it is very realistic for Unilever to identify promising brands earlier if they partner up with startups or academia. They will see a huge benefit in diversifying their products and getting into very new and trendy products. I think they can develop the capability quickly if they set up the collaboration correctly, their management teams and the communication part with the new partners. The only problem that I would find more difficult to solve is how are they going to avoid all the patent clashes and the proprietary information. Since Unilever is a for profit organization they need to have some very specific contracts on where the profit will go if they partner with startups/academia without completely buying the brands.

On November 15, 2018, Luna commented on Shooting for the Stars :

I do not think the distraction risk is so big. As long as NASA has hired a few very talented specialists in the area which can filter the big amount of new ideas, should be fine. They definitely need to structure the innovation funnel and make sure they review all of the ideas to not miss the good ones.
Intellectual property issues are very complicated in a open source system and especially when an organization like NASA is involved. I think the way to go about it is to not aim for any patents or monopolization of the technology. I think that the ultimate goal is to explore the space using the best technology and not making money or stopping other companies using it. As long as anyone can contribute and at the same time use the system or build on it, there will be no big problems.

On November 15, 2018, Luna commented on CIA to CAI? Spycraft in the Era of Machine Learning :

I think CIA should not develop these capabilities internally. Even if CIA is able to attract some good talent it wont be able to develop as much as all the big tech firms together. The companies are scattered all around the states and the people are motivated from very different things. I don’t think a marketing campaign and raising salaries will be enough to get the best data scientists on board. There is much more than that.
What I propose instead is for them to partner with the tech giant companies or academia and have them develop the technology that they want. This will need a lot of rules to be set and potentially difficult agreements to be reached, but I think is a good way to get the best of all the technology developments and at the same time monitor what is going on in terms of AI potential harmful uses.

On November 15, 2018, Luna commented on Hinge: A Data Driven Matchmaker :

In general machine learning is not able to identify biases if the data used to train the machine has biases. In the dating case I think is a lot easier to quantify the biases. Since we have info such as age, college, height, preferences we should be able to know when a person is liking 99% of a certain race, career or height. We can go even further by analyzing what kind of pics are attracting the attention of a person. But i think the easy part is in identifying the biases, many women/men know their biases and call them “my type”. The difficult part is eliminating biases. Hinge can probably focus on one bias at a time. For example do not show anyone that has gone to the top 10 colleges to a person that only likes people that have an ivy league college in their profile. And then observe if the behavior changes and actually the person starts talking to other people not in her previous bias. Then the ultimate job in eliminating has to be done from the person himself.

On November 15, 2018, Luna commented on Does a 3-D Printing Startup Have a Solution to the Affordable Housing Epidemic? :

I think that is not Contour Crafting that has to think about what are the job displacement from the new technology. I think is a bad idea to stop the technology research and improvements because of reasons like job shortage. The government has to worry about this issue and create the mechanisms/policies that society should use.
In my opinion the company’s job is to advance technology as much as possible and make profits. The decision making process of where are these houses going to be used has to be decided from the government policy makers. It would be great if these houses can be used to help people in need, but this is not the company’s priorities unless it is operating in the social enterprise or non profit area.

On November 15, 2018, Luna commented on 3D Printing Straighter Smiles :

I used Invisalign myself 3 years ago and I was very happy with the results and the price. I moved across the country and I told my orthodontist how are they going to get my mold for my retainers 5 years from now and she answered that since my model is saved I can just order them and they will ship them to me, no more new moldings to be taken.

I think that the company definitely has the advantage of being first. The 5 million people data that they have is a very big asset. I think they should use that data for their marketing (which areas should they target, which group age), for their product development improvements, etc. For example, back in the days I would think kids were the ones getting braces, but nowadays there are a lot of adults getting Invisalign. The company can find out what is the exact dynamic for this example and use it to their advantage. On the product development side they can use their learnings from the past years to improve their operations and become more cost efficient. The company has created relationships with their suppliers and they can use it to get materials at a cheaper price.