Each year that goes by, there seems to be dozens of new technologies that are sold to us as ‘life-changing’ or as something that will ‘save the world.’ Some of these technologies you will never hear about, others will last, and one or two will actually do what they say. However, in 2018, when it seems like a new technology comes out every week, consumers are bound to have questions like “What is machine learning?” or “How much does my Alexa actually hear?”

In the pursuit of helping answer these questions, we have put together ten of the most frequently asked questions that we receive. Our hope is to answer these for you, not just so you can stay up to date on new technologies, but potentially find opportunities to use these platforms for future success. Without further ado, let’s jump into some FAQs.

what is machine learning?

What is machine learning?

Recently, there has been a lot of talk about machine learning, leading many to wonder exactly this term means. In simple terms, machine learning is the process of teaching a computer system how to make accurate predictions when fed data. Think about when you log into Netflix and see recommendations based on your watch history. This is rudimentary machine learning in action.

The main distinction between machine learning and typical computer programs is that instead of basing predictions based off code written by a human programmer, the technology ‘learns’ by reviewing the data set. While this is great for sorting and finding patterns in data, machine learning is fairly limited when it comes to finding unique solutions.

What’s the difference between machine learning and AI?

Along with asking, “What is machine learning?” another common question we come across relates to the difference between artificial intelligence and machine learning. While they come from similar backgrounds, using the two interchangeably is simply not accurate. Machine learning is just one small aspect of true artificial intelligence, which was defined in the 1950s as a machine or technology performing tasks equal to human intelligence.

Thus, while machine learning is an important aspect of building out a true AI software, the capabilities compared to AI are still drastically different. When AI is fully realized, machine learning will be one feature alongside planning, reasoning, problem solving, knowledge representation, perception, motion, manipulation, and, to a lesser extent, social intelligence and creativity.

How will AI and machine learning affect the future?

Despite the fact that those asking “What is machine learning?” maybe disappointed to discover it isn’t quite artificial intelligence, machine learning will still have a significant effect on our future. Machine learning can be used to run complicated programs, greatly improve the efficiency of software products, and even help us save the world.

Moving forward, it will be the job of those in charge of this technology to not get caught up in the pursuit of some AI singularity. Instead, developers should take time to understand what machine learning can do and us it within those confines, rather than waste time trying to fit a circle into a square hole.

What is AR and how is it different from VR?

Along with artificial intelligence, another initial you might have seen on news articles recently is AR or Augmented Reality. Made popular through apps like Pokémon GO, AR has slowly grown in sophistication and many large companies are jumping on board. Unlike VR where the entire vision of a user is captured by a visual display, AR uses a combination of real images and overlaid digital displays to explore a new territory.

While many uses of VR are focused on video games and entertainment experiences, AR has picked up ground in business and industrial settings, providing needed information right to a worker using an AR rig. Although there are still a handful of use cased for AR, the technology is rapidly expanding and investors are betting on its future every quarter.

How will AR affect the future?

Already we are seeing how this investment in AR is paying off, with brands like Wayfair now allowing customers to see how their products would look in their homes simply by using their app. However, many still wonder how AR will affect the future beyond these fun, although somewhat limited, use cases. As it turns out, with all of the investment going into augmented reality, there are already plenty of industries lining up to get their hands on this technology.

For instance, travel brands are positioning themselves to us AR to show tourists exactly what they are looking at in a new city. On the other, hand medical professionals are imagining a more efficient healthcare community with patient charts and diagnoses generating in front of them as they work. While we can’t predict how AR will affect the future, it is clear that it will have a part in defining it.

What is Kanban software development?

Another common question that we receive, due to our extensive work with Agile development, is “What is Kanban software development?” Like asking ‘What is machine learning?,’ this shows a baseline knowledge that simply needs clarification. Similar to Scrum, Kanban is a development framework based on Agile principles that teams use to improve the efficiency of their projects and create better products.

Now, while Kanban is often less popular than a development methodology like Scrum, it has inherent benefits that other frameworks don’t provide. For example, with far less structure in Kanban development, teams have room to grow creatively. On top of this, by seeing the entire project laid out at once, it can be far easier to plan ahead and work on the most pertinent parts of the development first to ensure a robust core product.

What is a Chatbot?

Finally, our last FAQ that we will look at is the topic of chatbots and chatbot technology. While chatbots have existed in a rudimentary form since the 1960s, in 2018 it’s hard to come across any customer facing website without a chat box popping up in the bottom right corner. But how do chatbots actually work? Some believe they have to do with AI and machine learning, but the answer is actually far less clear cut.

While chatbots may eventually evolve to incorporate machine learning and artificial intelligence technologies, currently they operate based on pre-written interactions. To be fair, it is true that chatbots are becoming more adept at understanding language patterns and providing adequate responses, but we have a long way to go before anything resembling a turing test would be performed.

Should I use a Chatbot on my website?

Often, if you are curious about chatbots, you might wonder if you should use one on your own website. In response to this, we would point to the statistics showing that even something as small as a greeting from an automated messenger is enough to increase conversions on a website.

However, we should also state that unless you are committed to investing in your chatbot, you would do better to forgo the entire idea. Like UX design, half-assing the job is far worse than just not doing anything at all.

Have any more questions? Let us know!

This brings us to the end of this installation of Snyxius’ frequently asked questions, we hope that you were able to find what you were looking for. Have questions of your own around topics like machine learning, blockchain, and artificial intelligence? Talk with us today here or email [email protected] to be included in our next FAQ post.