30 Mar What Is AI and How Does It Work?
In our business, we talk about artificial intelligence (AI) often. We tell you how our AI system will answer your prospects’ questions, follow up with them, and connect them with a live sales rep. AI can even reactive your old leads and schedule meetings with them.
Sometimes our clients are curious to understand the science behind the magic and ask, “What is AI, and how does it work?” If this describes you, let’s explore this topic together.
What Is AI?
Artificial intelligence can refer to a computer system that can do work that humans have done in the past and the complex techniques that computer scientists use to give human-like abilities to machines.
Some AIs are developed through machine learning or deep learning systems, which allow them to grow independently. But an AI system can also be programmed with rules that govern its behaviors.
A Brief History
A classic textbook on AI states that there have historically been four goals of AI programming, which are to give computers the ability to:
- Think in human ways
- Think in rational ways
- Act in human ways
- Act in rational ways
Researchers first started using the term “artificial intelligence” in 1956. They worked to find ways to explain problems to computers, get them to solve them, and imitate human neural networks.
By the 60s, the US Department of Defense was working on making computers think rationally. In the 70s, the government also used computers to map streets. By 2003, personal assistant software was created.
The possibilities for AI today are even greater. There is more data available for AI systems to draw on. Plus, better algorithms (formal, repeatable processes) have been developed, and computers are faster. Finally, machine learning and deep learning are allowing AI systems to improve themselves.
Artificial Intelligence and Machine Learning
AI scientists train machines to successfully complete tasks that humans can do. One method to accomplish this is to code, or program, a set of instructions for every situation. Whenever a new situation comes up, the programmer inputs new instructions to cover it.
But a more advanced approach, which is one area of AI science, is called machine learning, a way of letting the machine create new codes and rules itself.
When developing AI through machine learning, programmers give the AI several examples of a task and let the machine learn from them. To improve its own algorithms, the system then repeats many cycles of learning, which may include:
- Collecting more data from examples
- Testing those examples in new situations
- Receiving feedback
- Improving algorithms using that feedback
- Seeking even more improvements by collecting more data, and so on
This style of AI development is feasible today, thanks to enormous volumes and diversity of data available for AI systems to use.
How AI Works
The power of current AI systems is built on technologies such as:
- Neural Networks: A system of artificial, interconnected “neurons” that work together to find patterns and solve problems.
- Machine Learning: A method of programming AI that allows the computer to learn from data.
- Deep Learning: A more advanced form of machine learning that creates layers and patterns of algorithms to make better decisions and is used in speech recognition and other applications.
- Computer Vision: An AI ability to accurately identify the content of images and videos.
- Cognitive Computing: An area of AI research that seeks to make computers speak naturally with humans.
- New Algorithms: New processes are constantly being developed that help AI systems analyze data and make decisions in even better ways.
- Application Programming Interfaces (APIs): Software go-betweens that allow AI functions to be added to current products.
- The Internet of Things (IoT): Devices that provide data through the internet, which AIs can then analyze.
How AI Is Used
In real life, AI is not like in the movies. Engineers don’t try to create artificial life. Instead, they try to perfect an AI’s performance in certain tasks or roles, such as:
- Self-driving cars: Machine learning systems can scan their environment and react to the world around them through features like predictive breaking.
- News readers: A consumer can ask a system to read, for example, the news plus their stock numbers, and the AI can both read the relevant items and give a brief analysis of them.
- Retail: Software can improve inventory management and store layouts, as well as give personalized shopping assistance to consumers.
- Health care: AI can accurately read medical scans and provide important health-related reminders to patients.
- Banking: AI can calculate credit scores quickly, manage large amounts of financial data, detect fraud in transactions, and avoid data entry mistakes.
- Manufacturing: A modern factory can connect many of its machines and items through a wireless network, and an AI can use that data to predict future needs.
We don’t need to worry that AI will take over all our jobs. Instead, we humans create these task-oriented AI systems to multiply our own productivity. When an AI helps us make fewer data-entry mistakes or predict our fastest workflows, it simply makes our work more effective and frees us up for more complex and enjoyable tasks.
Why Is Artificial Intelligence Important?
Industries that don’t currently use AI might see great strides forward as they adopt it. For example, some industries are not using the power of analytics to improve their efficiency or to find new insights. AI could help them make faster decisions and innovate.
AI might also help connect more people with each other. Systems can now recognize and translate human speech into different languages and dialects. This can allow faster communication, which might even help some people rise out of poverty as they join the global community.
AI can make certain vital processes more accurate. When we perform online searches for information, powerful algorithms can find what we need, even when data is stored on computers in other countries. Or AI can accurately identify the shape of cancer on a medical scan. Such feats of concentration and accuracy enhance the work of human employees and entrepreneurs.
Future Challenges
Just like each human, every AI system has limitations. The main one is that today’s AIs have all been created just to complete certain tasks. They don’t have a general intelligence. A program that plays chess can’t also organize a factory floor. An AI that coaches medical patients can’t also sell medical devices.
Second, AIs can only work with the data they are given. Machine learning systems are developed using data and examples, so if the data is flawed, the resulting system will incorporate flaws into its design. There may even be undetected prejudices in the data.
Finally, no AI is truly independent. They are bound to certain tasks and environments. Although they’re much better at analyzing complex data than they were in the past, they cannot truly grow into new areas or become something else than we have created them to be.
How Do Marketers Use AI?
A businessperson may dream that someday, an AI could conceive of a marketing campaign, set it up, execute it, and bring in sales—all on its own. But the reality is that humans still decide how to market, buy advertising space, test messages, and so on.
However, AIs are great at connecting consumers with businesses that meet their needs. They can run in chatbots to quickly answer questions. Also, search engine AI decides which businesses, ads, and maps to display when someone performs a search.
This means you need to have relevant information and a stellar track record in place to impress visitors when the AI shows them your ad or website. Make sure to pay attention to any changes announced about your favorite search engine so that a new algorithm won’t punish your messaging.
In summary, what Is AI, and how does it work? AI systems take care of certain tasks that require great memory, extreme focus, pattern recognition, data analysis, and other tasks. It can help improve aspects of any industry, including yours. If you’re not taking advantage of some machine learning systems in your business, take steps to find out how you can use AI to accelerate your success.
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