How Does AI Work? The Technology, the Tools, the Applications, and More

How Does AI Work?

Simply speaking, AI developers teach machines to mimic human learning processes. With more information, their knowledge and capabilities develop. However, unlike how you teach a child, computers rely more on deep learning technologies like natural language processing (NLP), natural language understanding (NLU), and other algorithmic training. Through these methods, machines can process large amounts of data and learn patterns from the analysis. For instance, feeding a chatbot examples of text conversations can simulate lifelike exchanges between people. 

Essentially, AI programming covers three cognitive functions. These are:

• Learning: This first aspect focuses on acquiring data for the machine to learn and teaching it how to analyze the data. The step-by-step instructions provide an algorithm for the machine to process the data into actionable intel. 
• Reasoning: The second phase deals with how machines convert information into desired results. How does Siri accurately respond to questions and other instructions in general? This is largely concerned with algorithms and how they dictate the behavior of smart technologies. 
• Self-Correction: This iterative feature of AI programming is aimed at continuous algorithm optimization and ensuring better accuracy. Just as people can grow in understanding, AI allows computing devices to expand their knowledge and improve their functionality through machine learning. Each time an AI system processes data, it evaluates its own performance and makes necessary improvements.

Thanks to recent scientific advancements, AI technology has significantly improved. Here are some of the technologies that have considerably improved the functionality of artificial intelligence.

• Larger Data Sets: AI thrives on data and thanks to the Internet of Things (IoT), along with growing data sets, machines can now easily access more information to expand their capabilities. Big data and artificial intelligence have developed a relationship of codependency and mutualistic benefits. AI is useless without data, and analyzing huge amounts of data is insurmountable without AI. As interconnectivity improves and more information continues to find its way online, AI systems equally develop their expertise. 
• Advanced Data Analytics: Access to large sets of data is important for AI advancements. However, all that data would be useless without a powerful medium for filtering it into meaningful information. Processing massive amounts of data requires in-depth analysis and advancements in this area have helped polish the algorithms that dictate AI operations. Newer and better algorithms allow smart machines to analyze data faster, and often, simultaneously. By empowering AI to process data sets more efficiently, advanced analytics technologies allow machines to better understand complex systems and improve result accuracy.
• Optimized Graphical Processing Systems: Graphical Processing Units (GPUs) are one of the key facilitators of AI’s rising value. Although the original purpose of GPUs is to improve computer graphics, they can also improve AI networks since they also rely on linear algebra computations. GPUs speed up computational processes for AI by enabling it to perform millions of calculations in little time. In a sense, they fuel the advanced analytics needed in AI to process and interpret big data.
• Application Processing Interfaces (APIs): APIs are powerful technological tools in the software development sphere. An artificial intelligence API enables developers to add AI features to traditional computer programs and softwares, consequently enhancing their ability to identify and understand complex data patterns. A good example is the face recognition technology that most smartphones now have. Many applications, particularly fintech apps, also utilize this technology. 

5 Popular Areas of AI Application

Intelligent machines influence several facets of daily living. Here are five areas where  AI is thriving outside the tech space.

1. Business

Data released by New Vantage Partners, a business consulting firm, shows that over 90% of leading businesses have increased their investments in artificial intelligence. This is no surprise since AI has revolutionized the business sphere, particularly in the area of customer service. Additionally, it would be impossible to effectively analyze big data for actionable insights without the help of artificial intelligence. By the looks of it, the relationship between AI and the business world has become an economic necessity. 

2. Healthcare

The benefits of artificial intelligence in the healthcare sector are innumerable. AI has produced groundbreaking results from diagnostic methods to treatments, recovery estimates, and patient monitoring. The combined efforts of artificial intelligence and medical expertise have transformed global healthcare systems into a smarter, faster, and more efficient ecosystem. According to CNN Health, over 7 million people are misdiagnosed yearly in the US. Since AI can efficiently process tons of data, it offers accurate diagnosis and treatment suggestions

3. Finance

From chatbots to fraud detection and other automated tasks, AI is revolutionizing how customers and financial institutions manage their finances. Traditional banking methods are becoming outdated as consumers are evolving with digitalization. Consequently, banks are finding newer ways of incorporating modern technology into their services. For instance, chatbots can now support typically jam-packed customer service departments 24/7. With AI-integrated web design for finance apps and websites, chatbots can guide disgruntled customers through their financial transactions.

4. Education

According to UNESCO, AI has the potential to address some of the biggest challenges in the education sector. One palpable example is the introduction of innovative teaching methods like virtual learning and intelligent tutoring systems (ITS). It also improves grading methods with the use of softwares that accurately grade students, especially when their numbers are large. 

5. Entertainment

As consumer appetites grow, they expect movie makers to produce bigger projects, particularly in the action and sci-fi genres. AI has transformed movie-making and is now an indispensable part of the entertainment industry. Among other things, it creates better movie effects, suggests possible acting maneuvers, and simulates more believable scenes. In addition to saving time and resources, AI has allowed producers to match audience expectations.

How to Build a Chatbot Using AI

AI chatbots are one of the most interesting aspects of modern digital technology. From helping you place an order to offering assistance on complex web navigation issues, they can do a lot. Additionally, advanced AI chatbots sometimes feel human with their sophisticated interactions. They are definitely powerful tools that enhance user experience (UX). 

With their versatility and level of sophistication, some might assume that AI chatbots are overly complex. However, to build an AI chatbot, you mostly need a basic understanding of how they work and good software. Like all AI systems, chatbots receive input which they translate into relevant output. They are trained with tons of conversational data to understand the context of various queries. Consequently, chatbots can analyze a person’s words and determine the most suitable responses.

Building an AI chatbot involves two main phases; the preliminary stage of outlining possible conversations and the technical process of developing the chatbot. 

Conversation Design

This phase involves mapping out all possible interactions your chatbot can engage in. The key to mastering this phase is to first determine the purpose of your chatbot and what your audience will want from it. You also need to look at other aspects like the type of assistance it will provide, the kind of questions audiences will need answers to, and the points where it becomes necessary to redirect users to a live agent. Here is how you design conversions for an AI chatbot.

• Flow: This refers to all possible channels a conversation can take. The flow map is the foundation for conversation scripting. It shows you the likely directions that user interactions might take. Neglecting this stage could lead to dead ends in communication and consequently sabotage the user experience. You can map out the conversion flow with diagramming or mind-mapping tools like Lucidchart or XMind. 

• Context and Intent: An intelligent chatbot analyzes user queries by breaking them down into context and intent. It must understand the conditions and objectives surrounding user statements before it can accurately respond. It also picks up on keywords (entities) on the topic of conversation to better understand the interaction. 

• Scripting: After mapping out possible conversations and establishing how to process them, delivery is next. Since chatbots are for human interactions, they need relatable personas. Scripting involves teaching your chatbot how to respond to users. Friendly or formal? Talkative or curt? It is important to make these decisions with the user in mind because they determine how your audience perceives your bot. 

Chatbot Development 

This phase involves choosing from the available softwares (platforms or frameworks) to build the bot itself. Chatbot development platforms help non-developers to create chatbots easily. Depending on the platform you use, your chatbot can either be simple with canned responses, or advanced with more NLP and NLU functionality. Developers may turn to some frameworks to build their chatbots using various programming languages. Here are a few platforms for non-developers.

• Chatfuel: This is a popular choice for bots on Facebook. It collects and retains user information for predicting different conversation paths. It is also versatile and can handle a variety of content. 

• Botsify: This supports simple interfaces and is predominantly used for messenger bots. It stands out for its machine learning feature which enables it to fine-tune its capabilities over time. 

• Pandorabots: This is a more sophisticated platform so it’s helpful to have some programming experience. However, with patience and determination, you can build an advanced chatbot on it without prior programming knowledge.

Here are some of the Frameworks that developers can use to build chatbots.

• Dialogflow: Owned by Google, it leverages the search engine’s vast data network to aid the conversation design process. Additionally, it works well for both voice and text-based chatbots. Dialogflow also supports multiple languages.
• Amazon Lex: The platform uses the existing AI capabilities of Alexa and is a powerful tool for analyzing user intent. However, it only supports the English language. 
• IBM Watson Assistant: You may use this platform to build a variety of chatbots because of its multiple AI technologies like NLP, sentiment analysis, and voice recognition.

Similar to cloud services, major tech companies offer their own frameworks. Your choice significantly depends on the ecosystem you prefer.

Testing 

The final phase of building your chatbot is testing. Determine its level of success or otherwise before presenting it to users. You can either make minor adjustments or go back to the drawing board altogether. You can use testing tools like Botium for this final step. 

Conclusion 

The world of artificial intelligence is fascinating. It offers tremendous benefits to industries and consumers alike, aiding several digital interactions. While it may immediately conjure up the idea of advanced technologies that are mostly out of reach, AI is more involved in everyday life than most people think. From simple to complex, it has penetrated our everyday use of technology and is constantly gaining more ground.

If you need to incorporate AI into your web product, you can hire a digital marketing agency to help you get started. It would augment the user experience for your consumers and greatly benefit your business.