AI, or artificial intelligence, is a hot topic in many sectors today, as companies from every industry seek ways to leverage the technology to streamline business processes, improve outcomes, and boost the bottom line. But, what is artificial intelligence exactly, and how does it work?
Definition of Artificial Intelligence
Artificial Intelligence (AI) allows machines to adapt and learn from the world the way humans do. We learn by adjusting to the inputs coming at us from different directions. Current applications of AI seek to allow the devices we use to do the same thing based on input we key in, speak out loud, or send from other online resources.
Dartmouth math professor John McCartney came up with the phrase In 1955 while preparing for a two-month conference intended to be an in-depth exploration of machine learning. AI capabilities continue to be explored for use in real-world applications.
How Artificial Intelligence Works
Machines use their own language to interpret what we’re saying to provide the answer we’re looking for. AI-enabled applications use Natural Language Processing (NLP) to break human language down into machine dialogue. It still has no idea what we’re looking for at this point.
NLP and NLU
That’s where Natural Language Understanding (NLU) kicks in. It takes the syntax given to it by NLP and converts it to a format it can make sense of. It uses internal algorithms to interpret your intent, looks for the most logical response match, and come up with the answer in its own language.
The information gets fed back to the NLP processor, which still doesn’t know what we’re asking for. It only knows it’s responsible for converting the NLU’s language back into a human response we can understand. It’s given back to us as a verbal or written response depending on the device being used.
The underpinnings of the machine learning driving NLP and NLU generally relies on statistical methods in designing algorithms. The evolution of deep learning looks to help machines overcome certain difficulties arising when trying to interpret intent from human users.
Deep learning gets its inspiration from the neural networks of the brain itself. It tries to simulate how we think. The idea behind deep learning is naturally deriving the intent of our requests to make more accurate assessments of what will satisfy our needs.
Applications of Artificial Intelligence
The expansion of speedy broadband internet around the world over the past ten years spurred developers on in creating devices designed to connect to and utilize it. This Internet of Things (IoT) system connects numerous AI-enabled devices together to control many aspects of our daily lives.
Amazon’s Alexa allows people to place orders from the company using voice commands. They can also request musical playlists, get directions, and perform many other common tasks. Large technology giants like Google and Microsoft continue to expand their own IoT offerings.
How Artificial Intelligence Benefits Companies
Businesses continue searching for ways to use AI in process improvement. Investing in AI technology and working to improve learning algorithms offer businesses the opportunity to save on staff and operating costs.
You already see instances of AI technology when visiting websites and getting a personalized response from chatbots. Chatbot usage isn’t limited to the internet. Customer service centers use AI-powered chatbots to handle customer calls requiring simple responses or route callers to the appropriate representative by asking a series of questions and analyzing responses.
The chatbots use language processing in interpreting and providing answers to multiple requests at a time. This helps companies provide faster responses and avoid dropped calls, freeing up more experienced associates to handle more involved calls.
Companies also use AI technology in performing repetitive tasks and searches. Others use AI in controlling power usage in data centers and coming up with strategies for stock market trading.
Challenges Presented By Artificial Intelligence
Human language and how we use it evolves over time. Machines learning still runs into problems trying to understand things like slang usage and the context in which we use certain words. How can a machine understand when we’re using a word like “sick” to describe someone being ill or to admire the way something looks?
Most AI still relies on pattern recognition in many instances. Scientists still struggle to get past the wall beyond which lies problems unable to be solved this way. Learning from entirely new experiences AI hasn’t been programmed to understand causes confusion and misinterpretations.
Best Practices for Leveraging Artificial Intelligence
Using AI the right way means acknowledging that it’s not a catch-all for every situation. Many situations will always require the intervention of a human component.
The goal of AI shouldn’t be trying to wipe out all instances of manual intervention. It should make life easier for those using it and provide the ability to adapt and evolve it to handle new situations.
Companies making the investment should be prepared to feed its AI structure steady streams of new data sets allowing it to adapt to a changing world. It can’t be allowed to remain stagnant, forever regurgitating old information that doesn’t allow it to change.
AI used the right way can be an effective tool in streamlining business processes, as well as easing ordinary tasks for individuals. Accepting and understanding current limitations makes it possible to overcome them in the future.