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Re:MARS Insights - Part 1 - AI For All



It felt like I was living a dream. I got to spend 4 days in Las Vegas talking about Artificial Intelligence at Amazon's Re:MARS conference. MARS stands for Machine Learning, Automation, Robotics, and Space. If you know me, you know how much I love all those things (and Vegas).


Over the course of the next 3 blog posts, I'll hit on some of the key takeaways of the event, and how the latest trends in the industry will impact your business.


Part 1: AI For All - The Democratization of AI (this one)


Part 2: Best Practices from Top Artificial Intelligence Minds


Part 3: What's Next - Mind Blowing AI Use Cases


First things first, this conference was thrown by Amazon, so these posts will hit on the capabilities of Amazon Web Services (AWS). We utilize AWS services to activate pieces of AI in our client work because they make it easy to do so.


AI For All - The Democratization of AI


A broad sweeping theme of the conference was how AWS is "Democratizing AI". What does that even mean?


To date, Artificial Intelligence has received a ton of press, but many of the highlighted use cases seem unattainable for most companies. As if it's only meant for the biggest companies with the greatest AI-talent. This may have been the case then, but no longer!


Amazon has been hard at work making AI more attainable. Tools like Amazon SageMaker provide users with the tools and work flow to prepare their data and run machine learning algorithms. When your algorithm is just right, this tool set allows for a faster mechanism to get from data to real world use. 


Hands On Sessions


Hands On Sessions at Re:MARS are basically workshops where you actually get to build an AI product. (read: ridiculously cool interactive experience) 


In one, we taught an algorithm to look through hundreds of images and identify which had bees in them. To do so, we took a data set of images, labeled them, and sent them over to Mechanical Turks (a program that helps humans in data labeling) to label a few more. We then let the machine go through a few hundred images and label the rest. After about 45 minutes or so, we had our results. The machine was able to pick out the images with bees. It wasn't perfect, but it was pretty darn close - a lot of images of bees.


In another session, we used computer vision, reinforcement learning, and machine learning to help us win hands of Blackjack. Within a few hours, we were able to use our system to play a real dealer in Blackjack. The machine told us when to hit, or stay, increasing our chances of winning drastically. It was amazing!


AI for Anyone?


Can anybody start building AI? Not really, but almost. It still takes a good amount of knowledge of Artificial Intelligence, like how to execute AI projects, computer science, and data science (among other things). But for those that already have the knowledge, AWS's latest developments help expedite quite a bit.


So has Amazon fully democratized AI? Not completely, but it's made it a lot easier for a lot of people and businesses to get AI into their companies.


While Amazon is doing their part to make it easier, it's still quite challenging to build AI solutions for your business. At Louder Co., we help you discover applications for AI that will revolutionize the way you do business so you can become the best in your industry. We make AI even easier, really.


Curious about how AI can work for you? We offer a free 1-hour strategy session here. You’ll leave our conversation with a few tangible ideas. 


You can also find our Intro to AI deck here. 


Your guide, 

Andrew