What is Artificial Intelligence (AI)?
Artificial intelligence (AI) covers a branch of computer science dealing with the creation of intelligent, computer-based software systems that can reason, learn from data, and act autonomously from their programmers on tasks that would typically rely on human intelligence.
This technology can be applied effectively in a vast range of ways, ranging from recreational gaming to medical AI research has been highly successful in developing effective techniques for solving a wide range of problems, recreational game playing to saving lives with next-level medical diagnosis.
Types of AI
- Machine Learning: This type of AI enables computer programs to learn without being explicitly programmed to do so. Algorithms related to machine learning are “trained” by sampling large datasets, and use these sets to provide predictive text, decisions, pattern-based music and/or video, and more.
- Natural Language Processing: This field of computer science deals with the way computers interact with natural human languages (as contrasted with programming languages). Natural language processing requires humans to develop algorithms and models that enable computers to interpret, understand, and ultimately generate human language that comes across as natural and meaningful.
- Computer Vision: This covers the understanding and interpretation of visual data by computer systems, including algorithms and techniques designed to empower programs to analyze, process, extract, and deliver meaningful and usable information from digital images and video.
- Robotics: This multidisciplinary field combines computer science, engineering, and other fields with the purpose of designing, developing, and deploying real-world, physical machines (robots). These robots can be programmed to perform useful tasks autonomously, perceive their environment, make decisions, and execute actions as assigned by humans. These tasks may be in as everyday an environment as a home, hospital or factory, or an environment that is potentially dangerous or difficult for a human to access such as a perilous cave or in outer space.
- Expert Systems: These computer programs use AI to mimic the decision-making ability of a human with expertise in the subject area. These programs help solve complex problems by evaluating large bodies of knowledge and data. Applications can range from medical diagnostics (diagnosing disease) to customer service, legal advice, financial planning, and more.
- Deep learning: This type of machine learning is based on artificial neural networks that are inspired by the human brain. Systems powered by deep learning can be used to solve a wide range of problems, including image recognition, natural language processing, and speech recognition.
- Rule-Based Systems: Often used in expert systems, rule-based systems use a set of rules, typically designed by human experts in the field, to provide advice, predictions, or recommendations within an area of expertise.
AI also has two categorizations:
- Narrow AI: Also called “Weak AI”, these systems are intentionally limited for specific tasks, such as speech recognition, fraud detection systems, or self-driving cars; they’re typically very good at the task they’re built for, but unable to generalize to other tasks.
- General AI: These AI systems can understand, learn, and perform tasks in a way that mimics human intelligence. More a theoretical concept than one that exists in practice, they would be able to take on any task the same way a human being could do, across various fields and range of accomplishments.
Computer vision, mentioned above, is a particularly relevant segment of AI to the work Veritone accomplishes, such as shown in the capabilities of our IDentify and Illuminate products. Some common applications of Computer Vision include the following:
- Image Classification: Identifying and analyzing labels and categories to images based on their content, leading to recognition of objects, scenes, or patterns contained therein.
- Object Detection and Recognition: Analyzing and processing an image or video stream to locate and identify specific objects.
- Image Segmentation: Dividing the contents of an image into meaningful segments or regions based on specific visual properties.
- Object Tracking: Continuous identification of the movement and trajectory of objects across video or a sequence of images.
- Facial Recognition: Searching and analyzing video or images to identify or verify individuals within the content.
- Scene Understanding: The extraction of complicated, high-level information about a scene, including the overall context, the object’s relationship to things around it, and the spatial arrangement of figures within the scene.
- Visual Question Answering (VQA): This brings together computer vision AI with natural language processing to empower systems to answer questions relating to visual content.
Applications of AI
Artificial Intelligence is being used in a vast amount of ways, with applications expanding dramatically in particular years and projected to continue to grow even more rapidly in the future. Below are just a few of the more common ways that AI are being applied:
- Virtual assistants: AI-based systems such as Amazon’s Alexa or Apple’s Siri are designed to understand and respond to natural-language commands and inquiries. They’re also connected to smart devices, and are able to provide useful day-to-day information like weather, traffic, and local information.
- Self-driving cars: While still a developing technology, self-driving cars are designed to perceive the world around them via a variety of sensors. This allows them to navigate roads efficiently and without collision while making decisions about when to accelerate, brake, and turn.
- Fraud detection systems: These AI systems are designed to identify and curb potentially fraudulent activities related to credit card and insurance fraud by analyzing transaction patterns, customer behavior, and identifying known suspicious activities.
- Image recognition systems: As mentioned above, these systems rely on artificial intelligence to recognize objects and scenes within images. They’re useful for many tasks, including object detection, facial recognition, and even medical image analysis.
The field of AI continues to advance rapidly, with ongoing research and development pushing the boundaries of what machines can achieve.
Challenges Related To Artificial Intelligence
- Bias: AI systems can reflect human bias as well as building their own bias based on a limited data set. This means that their results may be unfair or discriminatory.
- Security: AI systems may become accessible to hackers or cyberattacks, which could lead to their abuse, or of theft of sensitive data.
- Ethics: The ethics of AI in its many applications is a complicated topic – one that’s exploration has really just begun. There is great potential for AI to be used for manipulative, dangerous and/or harmful purposes, as well as it being applied for various crimes against humanity.
As AI continues to develop, it is important to address the challenges that it poses and to ensure that AI is used for good.
While AI is still in early stages, it promises to be transformative to humanity in many, if not all, respects. We’re only scratching the surface of what it’s capable of – for good or evil – and how it promises to change our lives. For the time being, it has begun to flex out of its previously harmless idiosyncrasies and limitations and is proving to be a powerful and extensively applicable human advancement.