Much of the talk surrounding the topic of artificial intelligence these days is actually related more to the field of machine learning. While the two of them might have gotten conflated with one another, they’re very different. Machine learning uses statistical models to generate answers whenever prompted. Countless programmers are already using this technology in the form of large language models that help them develop apps faster than before. Here are three additional ways that the industry has started to ride the wave of machine learning-based advancements reshaping the way we do work online.
1. Computer Vision Services
In spite of the fact that webcams have been common for years, computers don’t truly see in the same way that biological organisms do. Processing images taken from real-life cameras requires the application of a neural network that learns more about the presence of certain markers that can tell a piece of software what an image contains. Developers who work for companies that compete in the healthcare space have found that they can use this technology to diagnose diseases based on information provided by medical imaging operations. Others are developing new apps that identify products based solely on a simple cell phone photo of them.
2. Natural Language Processing Technology
Almost every single app that uses online search tools has integrated natural language processing into its design in at least some way. Machine learning-based software design allows programmers to latch onto subtle aspects of human speech and use these as search terms in ways that weren’t traditionally possible. Conventional search engines employ such techniques to try and find as many matches as possible to phrases that might not always look like they might have anything to do with a certain topic. Cloud-focused apps can instead look through entire collections of user-made documents for answers to problems. Considering how the current chatbot boom has taken the world by storm, it’s quite possible that this will be the main way machine learning technology gets deployed going forward.
3. Interactivity Functions
Language models aren’t just being used for pure natural language processing research. Software studios that wouldn’t have ever included an interactive function in their apps before are adding chatbots that are trained on the specific information that was hard-coded into their own databases. That provides users with a variety of ways to use software they wouldn’t have ever been able to before. Some developers have employed machine learning algorithms to teach bots about all of the data stored inside of their own help files, which gives their users the opportunity to ask an app to explain how it should be used. Others have exposed reference APIs that can provide answers to tough questions nearly instantly.
Since machine learning is such a fast-growing field, it’s likely that many of the most dramatic applications of it have yet to be discovered. Engineers are constantly working on new solutions, so it’s a good idea to keep a close eye on any developments in the space. When developing a new app, consider implementing machine learning into the process.