Autonomous This Autonomous That

The Autonomous Age

Technology today is changing at a record breaking pace, and I believe that now more than ever it is vital to understand what the hell we are talking about when it comes to "buzz words". Often times we hear about the words that we in Silicon Valley publicize. A year ago it was “Big Data”, today it is “Artificial Intelligence” and “Machine Learning”.

Lets start with a high level overview of "AI" and some categories that it includes:

1)     Computer Vision – Building an algorithm which trains a computer to identify objects inside of images (i.e. looking at a picture of a women wearing sunglasses the computer can identify that it is a women and she is wearing sunglasses)

2)     Machine Learning – These are algorithms that are trained to based on inputs and outputs. So examine factors x,y, and z and if a certain factor is realized than the computer will execute on a decided action.

3)     Process Automation: Creating triggers for certain events to automate mundane tasks (i.e. if I am an employee and click on this button then I will get this result)

But where did AI come from? Artificial Intelligence actually came from mathematics and scientific experiments meant to improve efficiency in cognitive processes. A couple of huge leaps forward for AI were: IBM Deep Blue beating Gary Kasparov, IBM Watson winning Jeopardy, and Google DeepMind beating GO Champion.

Those in Business Development for the technology industry lets look at different "win stories" and high level impacts that you can use in your conversations within different industries.

Healthcare:

This is one of the most government regulated industries and many people view healthcare as“behind the curve” from a technology perspective. This is true for the vast majority, but the minority who are continuously investing in innovation are doing some amazing things. Let me outline a project I just worked on with a large enterprise healthcare provider:

Imagine this scenario. John walks into the hospital for a knee operation. John’s operation is scheduled for 2:00PM and to be completed at 4:00PM. John gets wheeled into the operating room which has smart sensors everywhere to analyze both audio and visual data. The operating doctor puts on digital glasses which have computer vision built into them which in Augmented Reality show the doctor precisely where to make the incision on John, how many stiches he will need, what nerves and tissues to watch out for, etc. The doctor now knows all the risks and the precise time that the surgery will take, down to the second. The doctor finishes surgery and John gets wheeled into his room. Before John even wakes up, the hospital has already analyzed John’s social media profiles and recent transaction history. They find that he commented 13 times on Pizza Hut advertisements and transactions show he has purchased Pizza Hut more than any other recent food item. The hospital then orders a pie of John’s favorite pizza to John’s room and bills it right to John’s card that they have on file. When John wakes up he has his favorite food waiting for him and if the algorithm made an error, John has the option to be refunded in full. The patient experience has just been improved tremendously.

For more of a deep dive into healthcare I will be posting more content in the days/weeks to come about Innovation in the Healthcare Industry.

Transportation: We are already seeing this industry be revolutionized with the likes of Uber and Tesla. In fact, Tesla just outsold Mercedes-Benz in the United States for the first time. So what is going on behind the hood?

Tesla vehicles are built with NVidia Processing chips which allow the cameras to process at an extremely high rate the images that they are seeing. We at Oracle use the latest NVidia chips for our Deep Learning Cloud Service. Then using the algorithms the car can compute what to do in certain situations. For example, if the computer picks up that there is a child playing in the street and the car is going 60 mph, it can analyze precisely what the best outcome would be and what to do in order to achieve it. Statistically, smart driving cars are much safer than human drivers.

Finance: Today, many of the large banks run on Machine Learning and Artificial Intelligence Algorithmic Platforms. We recently worked with one of the largest banks in the world on a Fixed Income and Currency Algorithmic Project. The client had wanted to build AI to analyze every single trade occurring in real time and then have a computer modeled algorithm built in to execute certain actions based on identified triggers (if x happens then we do y). We were able to assist them in creating a model where every trade that happens gets analyzed, and then in real time the algorithm will analyze whether the bank made money or lost money and then act accordingly to sell off necessary assets if there was indeed a recognized loss.

One of the best reads of all time, Sapiens by Yuval Harrari, outlines an event which happened in 2014. A terrorist hacker organization gained control of the White House Twitter account and posted a malicious tweet. Twitter of course picked up on this immediately and shut them down. However, something far more interesting happened in the stock market. The Dow plummeted hundreds of points and left individuals scratching their heads. Only later did some of the big banks come out and say that they have Artificial Intelligent algorithms analyzing in real time the White House Twitter account. When event x happens they automatically sell of the appropriate assets to minimize risk.  After the news broke out that this was a one off hack, the AI was able to pull the Dow back to within a couple of points prior to the drop.

Hopefully this article provides value to those in the technology industry in being able to discuss different use cases, impacts, and concepts when discussing “Autonomous” Technologies.

Let me know what you guys think in the comments or messaging me personally to discuss!