With heavy hitters like Amazon, Google, and Facebook swooping into the Artificial Intelligence (AI) market, you may be wondering about the implications of AI for your business. Machine learning is not limited to the big industries. Even the smallest companies can benefit from AI. While Hollywood likes to paint AI as evil, this is mere typecasting. If a movie executive produces a film starring a robot and a human where one of them must play the villain, it will always be the robot.
This is an unrealistic and unfair representation of AI. In fact, many people interact with and use AI in everyday situations. While some are meant to amuse, there are plenty of machine learning applications that are snagging the attention of businesses everywhere. Read more to learn how businesses are incorporating AI to improve their operations and increase revenues.
The Amazon Example
Unsurprisingly, Amazon jumped at the opportunities AI presents. Amazon has been at the forefront of several major retail revolutions, including the ecommerce boom that is decimating brick and mortar competitors. Earlier this year, Amazon unveiled a cloud program designed to help companies make predictions based on their current data. This benefits any organizations that use complex spreadsheets or massive sets of data. The program allows individuals to input their data to help the program learn. The program can then provide outputs the company is seeking.
Current uses include:
- Predicting one out of two potential outcomes such as a yes or no question. For example, is the provided address an apartment
- Predicting one out of three potential outcomes as well as the probability of each one. Amazon’s example is determining whether a product is a book, a movie, or apparel.
- Predicting a number based on regression. For example, how many clear fingernail polishes should a company stock?
The Google Example
There is an increasing need for businesses to offer bilingual services, but this is not always possible. Budget constraints or lack of qualified candidates can create a bottleneck in services. There are basic translation tools available online, but they create a literal translation that can cause confusion. However, with Google Translate API, this is no longer an issue. The service allows individuals to build a dynamic translation service that learns what your business’ jargon means. It accomplishes this by learning what a word means rather than building a databank of direct translations of individual words. It is even able to parse figures of speech, which are often lost in translation.
The Facebook Example
One of Facebook’s most front-facing methods of machine learning is facial recognition. When you post a picture of yourself, Facebook’s algorithms are able to identify you as you. It then auto-tags you without you having to do it yourself. It saves time and is a cool feature for many users. However, in this instance, the algorithm does not know the individual in the picture is you. It is only able to identify that an individual in one photo is the same as an individual in another. Since most users only tag a limited number of people, it is a simple matter for the algorithm to link a name to a face.
While this may seem like a tool that is only useful to social media, there are several implications for facial recognition technology. Police officers use it to track down criminals, dating sites use it to match people with similar facial features (based on the theory that we are attracted to our own image), deluxe hotels can welcome their guests by name upon arrival, and bars and restaurants can identify underage drinkers despite their fake ID.
Medical Advances to Save Lives
While the previous examples show how AI can make jobs easier, AI can also help save lives. One company, Atomwise, raised millions of dollars to fund its drug research initiative. Their algorithms compare the side effects of known drugs and search for other drugs to resolve medical issues. In essence, it finds new ways to use existing medications. It is capable of doing so much faster than a human can thus leading to faster drug discoveries. This is no pipe dream either. This company’s first big achievement was discovering two compounds that help combat and reduce the spread of the Ebola virus.
AI Applications to Reduce Costs, Generate Revenue, and Boost Productivity
Data Analytics
AI does not need to be huge to be effective. For example, analytics are not much use if you cannot make sense of them. Today’s dashboards are so complex that companies are hiring data analysts to untangle the information and draw meaningful insights and trends from it. As there is a shortage of data analysts, businesses are turning to AI to analyze and explain what the data means. This allows businesses to draw conclusions and make decisions based on the data.
Virtual Assistants
Another way businesses can use AI is as a virtual assistant. In fact, many individuals do so already. If you have ever asked Siri to schedule an appointment in your calendar, you have used a virtual assistant. Other applications for virtual assistants are as chatbots. These virtual assistants can interact with customers to learn how to resolve common problems and answer frequently asked questions. Such applications can free up customer service representatives to focus on more complex problems. This enhances productivity and makes the best use of the representative’s time.
The primary purpose of machine learning is to help humans make sense of the abundance of digital information we produce each day. While many are concerned machines will take over their jobs, this is not the intent or the reality of AI. Instead, AI allows the human workforce to focus on their most important tasks without interruption to resolve tedious, menial tasks. To learn more about how AI can improve productivity and boost revenue for your business, contact Bright Apps.
