/ AI

Bot (R)evolution

Recently I was fortunate enough to be invited to talk about Mycroft, bots, and A.I. on the last episode of Coder Radio. The conversation between Michael, Chris, and I was great - and I found it invigorating to talk about the future of artificial intelligence, and how that will shape our interactions with our devices and services going forward. I think the coming bot "revolution" represents a significant change in computing, and an opportunity for a lot of wealth to be generated for those able to apply A.I. to existing and new industries.

The first point I'd like to make in this blog post is that while I think we are on the verge of an incredible explosion of A.I. powered apps, bots, and services - this does not necessarily represent a new paradigm. Big companies have been applying machine learning to their products for a good while now. Netflix, Google, Amazon, Yahoo, and Microsoft have talked about their use of machine learning in the past to improve their offerings. The difference now is the barrier of entry has fallen as the cost and resources needed have dropped, thus opening up the same type of tools to a wider set of companies and developers.

The result of tools like Google's Tensor Flow, Amazon's DSSTNE, and Yahoo's Caffe being open sourced means that developers have gained access to the code of some of the most state-of-the-art machine learning libraries. Not only are these libraries state-of-the-art, but they are from the tech giants of our time and have surely benefitted from an immense amount of R&D. For Amazon and Google, it makes sense to share this software freely as a way to funnel companies into their cloud services that offer machine learning. By making their technology open source, it becomes easier for developers to familiarize themselves with how the software works, and move from there to take advantage of the services - saving them from having to spin up the complex infrastructure required on their own. Two important services to bare in mind here are Amazon's Machine Learning on AWS and Google's Cloud Machine Learning products on Google Cloud.

Beyond the big players, there are startups also working hard to expose these same type of services to the world. These startups tend to be more focused on specific applications of AI/ML. One of my personal favorites, and happens to be a fellow Sprint Accelerator Techstars alumnus, is Stride.ai. They have a focus on text analytics, but over time they have grown their offerings and have made an amazing product that can be used through their API to improve your own products and services. Beyond that there are other startups that are pursuing "AI as a service", those being startups like chatbots.io and Orbit.ai. But these are still young services and have some room for growth, definitely good to watch.

Regardless of whether a set of startups or large, established companies end up attracting the most developers to their platforms and services is inconsequential when compared to the bigger insight that can be drawn from all this growing interest in AI. Chatbots, intelligent personal assistants, and trained models for recommendations will represent a monumental shift across industries and it looks as though that may be sooner rather than later.

Ryan Sipes

Ryan Sipes

Community builder, organizer, technologist, open source enthusiast, and all-around rabble rouser. Community Manager at System76.

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