Huge strides are being made in the tech industry, especially when it comes to the capabilities of AI (artificial intelligence) and ML (machine learning). Advancements in these fields lend well to growth with API integrations, hiring a UX designer for UI/UX work, and other custom software development niches. You might not think much of AI or ML beyond its integration with Siri or Alexa, but there’s a surprising amount of overlap in your daily life–and endless potential for the future.
UI/UX: Examples of Modern AI and ML
One of the most prevalent examples of AI is through UI/UX. When you consider hiring a UX designer, you will most likely also employ some sort of ML or AI setup, too. That’s because these processes have made the design methods for UI/UX more streamlined and automated.
For example, AI and ML are able to analyze large quantities of data to determine the best UI/UX route to take when it comes to delivering the best interface and experience. From application development to prototypes to system updates, ML and AI help provide the least biased and most efficient solutions.
Enhancing UI/UX with AI
AI and ML use algorithms based on historical user data that enable the best wireframes to be select for creation and implementation. Once the most viable options have been created, AI and ML can then conduct A/B testing on users to decide which model is best for a hired UX designer to move forward with. After launch, AI and ML can monitor for bugs or determine any areas of growth to optimize user experience. These processes make it easier for a hired UX designer to focus on the more human components of design work.
So…What Are AI & ML?
The truth is, AI and ML have a rich history that dates back as far as the 1950s. Key players like Alan Turing and John von Neumann began exploring how it could be possible for machines to have human-like capabilities. The high expectations of these tech pioneers seemed impossible back then, but with modern research, are actually more attainable than once expected. Here’s where we’re currently at with AI and ML:
Weak AI (Narrow AI)
Weak AI, or narrow AI, is a type of AI that is able to do a single or a narrow set of tasks. All of the AI that we have today falls under this category. Even if the AI is capable of completing several narrow tasks, the result is still a collection of weak AI tasks. Even Alexa, Siri, Cortana, and other seemingly intelligent virtual assistants are merely collections of weak AI. They are all limited to their specialized tasksets and cannot create their own intelligence.
Strong AI (General AI)
Strong AI, or general AI, is completely theoretical. It’s the concept of a super intelligence that rivals that of the human brain, perhaps one day exceeding it. The goal of this form of AI would fulfill the movie cliches: this type of AI would be able to think and act independently, intelligently, and without guidance.
Machine Learning
ML is the concept of application enable decision making. Essentially, the machine evaluates sets of data and helps make decisions based on the results of said data. Examples of this type of custom software development are API integrations. Common API integrations you may have experienced are facial recognition and spam filtering.
ML can be broke down into 2 separate subsets: supervised learning and unsupervised learning. Supervised learning requires sets of input and output data to train the machine. After this training period is complete, the machine can start making its own sets of connections. Unsupervised learning doesn’t require training sets to start up. The machine makes its own models and classifications to interpret data.
Deep Learning
“Deep learning” is a form of custom software development that goes a step further than supervised and unsupervised learning, although it is another subset of machine learning.The goal of deep learning is to create algorithms that are as close as possible to the human brain, so that machines are able to emulate human thinking and decision capabilities.
A key difference between deep learning and traditional ML is that ML requires machines to work with “fixed models,” while deep learning encourages models to be develope independently by the machine via artificial neural networks.
Computer Vision
Another subset of AI, computer vision is what enables machines to comprehend various photos or videos. You’ll most likely experience this through facial recognition on your mobile device. More recent and impactful applications of computer vision are in the medical field. Machines can cross-reference a patient’s x-ray results with historical data to help determine potential health issues or offer a diagnosis.
Natural Language Processing
Natural Language Processing, or NLP, is an AI subset which references how machines process natural language. It’s appropriately named, and you’ve most likely encounter it through Siri and Alexa or other virtual assistants which require voice recognition and responses.
AI and ML Future Prospects
Currently, AI and ML are a form of custom software development meant to make tech tasks easier, streamlined, and less human involve (at least when it comes to redundant tasks). AI and ML have helped automate systems when it comes to hired UX designers for UI/UX work, API integrations, and other data oriented fields.We’ve made unthinkable progress, but there’s still tons of work to be done in order to reach the sci-fi dreams of strong AI.
Even though it may not be achieve within our lifetimes, there’s no doubt that machine learning and artificial intelligence have already left a mark on the average person’s everyday life.
Start putting AI and ML to work for you today by reaching out to our 245TECH team at (865) 465-4040.
