People use AI to help them navigate online, pick movies they may enjoy, run their household appliances and thermostats, recognize bogus news and much more. They also leverage it to assist them with work-related tasks and even learn new skills.
However, many still believe that AI is a scary, robot-overlord kind of thing from sci-fi movies from decades ago. Despite this, it has become an everyday utility for most people.
Machine learning is a type of AI that uses algorithms to learn from data and predict future outcomes. This form of AI is used in applications such as fraud detection, recommendation systems (e.g., for e-commerce and streaming services), autonomous vehicles and more.
Reactive AI is programmed to react to specific inputs and optimize outputs based on those inputs, such as a chess-playing algorithm. Unlike reactive AI, limited memory machines can adapt to past experiences, though this updating process is relatively slow. Autonomous cars, for example, use this kind of AI to “read” the road and make decisions without human intervention.
This form of AI is often referred to as black box AI, since it can be difficult to explain how the system made its decision. The next step up in the hierarchy of AI is artificial general intelligence, or AGI, which would give machines a consciousness and the ability to perform tasks that surpass human capabilities.
Natural Language Processing (NLP)
Using machine learning algorithms, NLP software learns to interpret written and spoken language. It can also replicate language and understand context. The better it learns, the more useful it becomes.
For example, search engines use NLP to provide relevant results. They can also identify different meanings of words such as homonyms (Tom/He) or coreference resolution (Tom/Volvo). They can break out keywords that describe emotions or other concepts, and they can understand metaphors.
Navigation apps rely on NLP and computer vision to help drivers navigate road traffic, find parking spaces, or pre-plan their routes. They can even notify you of new construction or other road closures in real time. AI-powered robotics, warehousing and supply chain management systems make processes faster and more efficient, while sentiment analysis can help companies optimize customer service.
A more advanced form of machine learning, deep learning relies on a huge amount of data to identify patterns and insights. It requires complex algorithms, computational thinking and high-level programming skills.
AI can be found in many areas of our daily lives including smart thermostats that help save energy, voice assistants for easier mobile phone use and language translation software. AI is also enabling faster and more accurate diagnoses in healthcare, helping with patient outreach, and reducing the impact of natural disasters by providing early warnings.
Most Americans are aware that there is AI at work behind the scenes in social media (with 57% correctly identifying customized music playlists as a use of artificial intelligence), in online shopping with personalized product recommendations (71%), customer service chatbots (64%), security cameras that recognize faces (57%), and in GPS navigation systems (48%). The majority of people think that the benefits of AI outweigh the concerns.
While the concept of inanimate objects endowed with intelligence has been around since ancient times, artificial intelligence as a technological advancement first gained widespread public attention when IBM’s Deep Blue computer beat world champion Garry Kasparov at chess in 1996.
AI algorithms are used in many applications today, from recommendation engines that suggest movies and music to you based on your past purchases, to chatbots that converse with you online. AI is also a crucial part of self-driving cars, allowing them to analyze road conditions and navigate safely.
Other uses include helping to prevent cyberattacks by analyzing network traffic and identifying suspicious behavior, and improving customer service by automating tasks and responding to requests. One of the main concerns about AI is that it may eliminate jobs or change business processes.
Machine vision is the technology behind Google Autocomplete that displays predictions as you type a search term on your mobile device. It’s also used in facial recognition systems to allow only authorised payments to go through and in automated warehousing to track and manage inventory.
It’s used in the medical world to develop new drugs and treatments and diagnose diseases. In finance, it can help detect fraud, optimize asset management and reduce investment risks. In retail, it can personalize recommendations and improve customer service. In transportation, self-driving cars and drones rely on this technology to navigate roads and avoid obstacles. It’s also used in the Internet of Things (IoT) to connect and control devices in homes and businesses. It’s also an essential component of thermal imaging to help with early warnings for natural disasters like fires or floods.