What is the Future of AI looking like to you in business?

Blake,

In my industry, we are pulling in billions of data points for our customers. As the internet grows and the volume of data grows exponentially, our customers need help to make sense of those billions of data points for their business. AI will help us get there. Patterns, insights, and analysis help the world run more efficiently and positively impact people in their everyday lives, but we can't do it alone, AI will help us find patterns and insights.

I expect use AI and machine learning to continue to grow quickly in a lot of businesses. The technology and frameworks used in machine learning are still just starting to find practical uses, so there's a lot of room for growing careers and new ideas in how to use AI to solve problems.

You're also absolutely right that ethics is an important part of growing use of AI. So I really hope that people who are excited to learn about history and sociology and culture also join the work of building AI.

My company works to help other companies build better software. AI and machine learning are definitely one of the tools many companies in my industry are turning to when we're trying to help humans understand really complicated systems and finding useful data to look at when there's an overwhelming amount of data to look through. I think there are some big opportunities for AI to help make people more effective at their jobs.

AI is going to become a lot more integrated into our lives over the years. It will start with AI solving challenges that are mundane and repetitive. For example - look at what gmail has done over the last 6 months. It auto completes the sentence that you are trying to write. Progressively it would get into more complex situations - last week I was working with a company that uses AI for suggestions around how to do supply chain planning. However, one of the important things to notice and know is that AI is not taking jobs aways, it is removing certain kinds of jobs and creating others. The gmail auto complete shifts your focus from language and grammar is to what your message is.

Hi Blake! Thanks for the interesting question! You're right that movies give people weird ideas about AI. At the end of the day, I see AI as a way to use math to make decisions based on lots of pieces of data (or information). When you see it that way, the ways for it to be improved are simple: 1) It will be faster or more efficient so that it can happen in real time or based on really really big sets of information, and 2) it will be more accurate.

I work in tech security (keeping the bad guys out of our website) so I see AI helping me in trying to decide which attacks I need to follow up on. Our website is pretty big, so we get thousands of people trying to hack us every day. To use AI to help I would give it thousands of examples of past attacks, and maybe a score between 1-10 on how bad each attack is. Then when my AI program looks at the new attack it can compare it to past attacks and give it a score. That way, I can focus on the 9-10s rather than the 1-2s.

Future of AI is not only limited to futuristic robots, but in the way we are seeing data. The entire concept of data mining, natural language processing, data intelligence, information retrieval are inter-connected and these are being adopted across the industry to achieve better projections, productivity and hence, profits.

Hi Blake,

That's a great question! There are a ton of uses for machine learning, and a lot of different tools and techniques that fall under that general category. You have a good insight about how people will often just think of it as self-aware computers, but there are really a lot of incremental steps between your cell phone and the fictional movie version of AI.

On the simple end of the scale, statistics are really powerful, and are at the foundation of most if not all machine learning techniques. Where I work at New Relic, Inc., we help people solve problems in their software, and our AI folks use simple statistics to learn and detect what is important for them to see to solve these problems. They're also working with some more advanced techniques to learn patterns and predict and analyze events relating to those computer systems.

I see new uses for machine learning all over. Just like computers went from being special tools used by only a few people, to being in people's pockets, cars, microwaves, and everywhere else, machine learning is become more a part of our lives every day. Many of the useful features of the apps and sites we use daily are driven by it.

AI techniques are used all over the internet to learn what people want to see and will respond to. These tools can be used to help accomplish most any goals, so the ethics of uses for machine learning has been an increasing topic. While concerns of a SkyNet are likely very far away, machine learning is an increasingly powerful tool, and thinking about what we want to accomplish with it for our societies is very important.

If you are interested in getting into learning about machine learning and AI, there are a bunch of great, free resources online. Coursera has a lot: https://www.coursera.org/courses?query=introduction%20to%20machine%20learning It can feel intimidating at first, if you are new the math. It did for me :) Learning some basic statistics can help you understanding the concepts. But just getting a general idea from real-world examples and visuals is great, even if the math is more than you get at first.

Hey Blake!

Fantastic question! I'm currently leading a team of software engineers (with almost solely web development backgrounds), but we just hired an engineer with a data science background that is to be mostly focused on utilizing the data we collect to help our customers in any way we see fit. We will be relying on this individual to teach the rest of us how we can best utilize customer data in order to create great user interface experiences that delight and "wow" customers. We also have a team at our company solely focused on correlating data to come up with amazing insights into our customers own data so that they can learn from it and optimize from there. I think ML is a great field to get into and the opportunity will only grow from here.

I think we have to distinguish between the "applied AI" and the "AI hype".

AI already had a "boom" many decades ago, and has been used since them in many common applications. Initially, there was a lot of hype but then the topic went to background when we realized that we would not have "human-like" intelligence inside computers.

Since then, the AI has continued evolving and its presence has been silently growing until the explosion of deep learning and hardware-accelerated neural networks. The amazing (even scary) new applications of it gained a lot of traction in the media and raised a second "hype", which probably made us to put too many expectatives in AI.

I envision AI to continue growing in the long term, but in a more moderate-but-sustained rate, after the current bubble deflates.

In my opinion, the future of AI looks like it will only continue to evolve throughout the business industry as a whole. I work in the real estate field and we constantly discuss the benefits of AI such as automating processes for appraisal reviews, loan applications and data analysis. There is inherent risk with the data but our use for AI is more for internal review rather external.

While the idea of AI and data gathering seems scary to some people, always remember that there will always be a need for people to be behind the scenes and make judgement calls that AI and technology cannot. For example, in my company we utilize tools that provide a predetermined decision like applying for a credit card but sometimes there are exceptions that require a human second look. The exception process allows us to take a "2nd" look process for additional approve or decline review.