We live in an innovation renaissance, and artificial intelligence is the hottest new tech to explode into the zeitgeist in a long time. So much is powered by AI now; there’s no denying how handy and helpful some of these solutions can be. If you’re interested in keeping up with new technologies, you might face the challenge of understanding what exactly AI is and how it can be tacked onto existing technologies. Here’s a small breakdown of AI as we have it now, including some functional types you’ll likely encounter online.
Mirroring Human Intelligence With Degrees of Success
The human mind is powerful, constantly processing thousands of megabytes of information. It makes sense that we would want our computers to function similarly, with the same level of efficiency and autonomy.
The prospect of functional artificial intelligence has existed for a long time. However, AI has recently made significant strides in implementing deep learning methods, which revolve around neural network technology.
This technology takes inspiration from neural biology, which makes perfect sense when you consider how AI tries its best to replicate brain function. Building on this, here are some functional types of artificial intelligence you’re bound to encounter either on the internet or in your favorite applications.
Narrow Artificial Intelligence
Technology that falls under this category should be easier to understand. Narrow artificial intelligence is similar to modules in an application. These are AI-powered tools built to solve specific problems. They exceed at whatever task they were designed to do and cannot effectively branch out into other tasks.As such, narrow AI doesn’t accomplish the task of modeling human intelligence, as these solutions aren’t built to learn or evolve. An example you probably use daily is the digital assistants built into smartphones. Services like Siri, Alexa, and more. These technologies are designed to recognize a user’s voice and perform simple tasks related to what the user is saying. Oddly enough, robots used in industrial complexes are also examples of narrow AI. They are often designed to perform a single task, like lifting an object precisely.
Neural networks are more closely modeled to the human brain and make organic connections between preexisting knowledge. However, they aren’t the best at representing this knowledge and might be better suited for quantitative analysis. Deep learning builds upon a neural network’s foundational principles by adding several connections between the input and output layers.
One cutting-edge application of neural networks is implemented in self-driving cars. This works great because of the need to react to situations on the fly as you travel from place to place. While the technology is still rough around the edges, it is constantly being polished, and it shouldn’t be long before a car can safely drive itself.
Reactive Machine Artificial Intelligence
One major aspect of what makes us human is our ability to react to stimuli. We block our eyes when the light is too bright and move away from painful experiences. A lot of this happens reflexively, and it is this reactionary aspect of human brain chemistry that Reactive Machine AIs are built to model.Sadly, they don’t store information based on the information they ‘perceive’ and cannot learn. However, they are programmed to react in specific situations and provide help when needed. One easy-to-grasp example of this is a chatbot.
Imagine if you had a tool equipped to help you solve the most complex of problems in your field. It would be difficult to program such a tool with ordinary means, where Expert systems come into play. These aren’t AI in the traditional systems but still fall under the umbrella term.
Expert systems provide solutions to field-specific problems, and the information they produce is further vetted by experts before passing it on to users. Expert systems tackle provided tasks with the same seasoned and experienced eye, and experts would and can be trusted with more sensitive tasks.However, they are very expensive to produce and can only be found at the highest level of most industries.
Self-Aware Artificial Intelligence
This is considered the current peak of artificial intelligence and is likely what you think about when considering the concept. It has been done and overdone in cinema but hasn’t been perfected yet. While it is possible to establish and train an artificial intelligence to recognize itself, it would be much harder to get it to cultivate a sense of self.
Computers deal with facts and logic, and you can understand how difficult it would be to help a machine learn emotions. Fuzzy logic isn’t as absolute as numbers, but it still doesn’t provide a realistic representation of the human emotional spectrum. Should this technology be perfected, it could be used in therapy.
We can agree that human intelligence varies from person to person. While we’re all capable of thinking at high levels, not everyone thinks the same way. It’s also safe to say that we are yet to see the pinnacle of human intelligence. But what if we could teach a machine to think beyond what a human can?This is a question that the field of AI superintelligence aims to answer. A good way to look at it is to consider unsolved scientific problems.
These problems show the current limit of human intelligence. And each time an issue is resolved, we see human intelligence take another step forward.Theoretically speaking, a super-intelligent system would take the base of human knowledge and push it further, allowing whatever agent has been gifted this knowledge base to answer some of the world’s unsolved mysteries.
However you choose to articulate it, there’s no denying just how helpful AI-based applications and systems have been in recent years. Many tech companies recognize how these systems can bridge the gap, and we see a near-constant implementation of in-house developed and thought AI. The more they evolve, the further the field expands, making us dream how far we can go. Consider the types listed above as a starting point, and let your curiosity take you down the knowledge well that is the field of artificial intelligence.
