Honey Badger

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On November 15, 2018, Honey Badger commented on Grupo Aval: Utilizing open innovation to build a new business model :

Thanks for sharing this! I think we consistently hear about machine learning in the fintech context, and rarely about open innovation. I wonder whether there is a way to combine the two – sourcing insights from entrepreneurs/employees based on ideas generated through machine learning techniques. I also like your idea to team up with both internal and external voices – having one without the other is unlikely to get an outcome free of outside noise that many can buy into.

Really interesting to read! I think this is a brilliant move by Pepsi – millennials love to have input on things they consume and interact with, so product launches like these tie the consumer to the brand and, I would think, drive brand loyalty. Your idea around machine learning is really interesting – if people could vote based on flavors that a machine learning algorithm can produce, I think that would be the optimal combination.

On November 15, 2018, Honey Badger commented on Additive manufacturing of hearing aid requiring anatomical precision :

Super interesting article! I think this a very interesting product – if they can scale it, it would definitely be a hit. Thinking about the elderly crowd, there is significant opportunity to tie something like this to Medicare. I see your point on the texture of 3D printing now, but I have to assume that as it continues to innovate, there will soon be the ability to print on many more surface types. Will certainly be keeping an eye out for this!

On November 15, 2018, Honey Badger commented on Ford Races Ahead in Additive Manufacturing :

Really interesting article! It’s an interesting question to think about whether 3D printing goes against Ford’s core assembly line – I would actually argue that it is part of its brand image. Since its inception, Ford was known for pushing the envelope in its assembly processes – this is simply the new age of innovation. I think doubling down here and making it part of the strategy makes a lot of sense.

Interesting! I have a tough time thinking about large financial institutions making these types of loans using machine learning without human involvement given their fiduciary obligations as financial institutions. This is why I think startups have had such traction, and why the idea to connect to regulatory bodies makes so much sense. We spoke about the idea of “garbage in, garbage out” in class, so I think multiple data sets would be best. Very interested to see where they continue to expand with this product – doing it in-house or building via acquisitions.

On November 15, 2018, Honey Badger commented on Vodafone: leveraging Machine Learning in an (almost) 5G world :

I enjoyed reading about this! It seems to me there is a large opportunity to expand the B2B market. The great part is that I don’t think this needs to be predicated on individual consumer data, as call patterns which can inform consumer activity can be used across many industries as companies look to roll out de novo location strategies. I think the question will be exactly how to package and monetize this – I think there are enough capabilities within their information now, but how they choose to roll out this platform could be tricky. I also wonder whether the cost-cutting strategy can offset some of their revenue losses as well when thinking about the bottom line.