Bets in AI - Computer Vision

Despite the sometimes exaggerated expectations of the potential applications of AI in everyday life and work in the past 10 years, there are a few elements within the domain that continue to show promise with advances made by researchers and industry fairly regularly. One of those is Computer Vision (CV), which is fundamental to a number of technologies with practical uses, like Augmented Reality. As with applications of other areas of AI, the most practical here is decision support.

Below is a great article on the team and vision at Paige, which is using CV for medical imaging purposes:

https://venturebeat.com/2019/12/18/paige-raises-45-million-to-detect-cancer-with-computer-vision/

Augmented Intelligence

Great write-up that takes a more rational stance on the potential wins from broader adoption of AI / machine learning. I’ve been borrowing the term “augmented intelligence” when describing the (hyped up in recent years) acronym of “AI”. The algorithms that sift through large amounts of historical data, and then try to make suggestions on data that’s input to the model by the end-user — are most effective at suggesting the next step / action for the human — rather than replacing people’s decisions entirely. This will be especially evident in healthcare, where doctor / clinician decisions will never be replaced, but rather only augmented by output from systems.

https://blogs.scientificamerican.com/observations/does-ai-have-a-place-in-medicine/

Expansion of core tech by the industry

Great to see a top industry player like Google investing in core research that expands the possibilities of tech applications. Just like they did with opening up and supporting Android for developers, this will expand the scope of what’s possible for developers to solve for, using software — in this case, expanding to another one of the human senses.

http://ai.googleblog.com/2019/10/learning-to-smell-using-deep-learning.html

Focus on making life easier for your users

I’m a big believer in the success of technology that makes a user or community’s day in the life, easier. In other words, the “practical tech” tends to win out in terms of mass adoption, over tech that has potential but keeps to abstract use-cases or ones that carry value for a niche set of users.

A good example of this in the recent years, has been the rollout of Augmented Reality (AR) and Virtual Reality (VR) tech and applications - for enterprise and consumer spaces. Both carried the promise to improve our experience at home and at work.

Thus far, as per the above, AR carried much more practical applications to everyday life with it, and VR has realized much fewer of these.

Google’s recent decision to focus on its AR efforts show their teams’ understanding of where they have impact on the everyday lives of their users.

https://venturebeat.com/2019/10/15/google-discontinues-daydream-vr/