Nov 5, 2019
So, What Is Artificial Intelligence?
Do you want to learn more about artificial intelligence (AI) and how it can help your business? AI is flourishing, and subject matter experts need to take advantage of it to level the playing field. Continue reading to learn more about AI and its potential impacts on your organization.
What Is Artificial Intelligence?
- What Major AI Technologies Are Used Today?
- What Does the Future Look Like for AI?
- What Comes After AI?
- How Can You Ensure AI Works for You?
What Is Artificial Intelligence?
A term coined in the 1950s, artificial intelligence is the name given to the technology that allows computers to learn and spot patterns in data. Whether it’s a self-autonomous vehicle or a chess-playing machine, AI technologies rely heavily on both deep learning and natural language processing. As a result, computers can be trained to accomplish tasks and learn from the experience without the need for a human controller.
Early AI technologies have helped solve many problems, such as street mapping with Google Street View. Today, the market is full of AI models that now deal with automation and formal reasoning.
What Major AI Technologies Are Used Today?
AI has come a long way in recent decades. At this moment, enterprises around the world are using major AI technologies to further their bottom line. Forbes points out that nearly two thirds of companies use AI in some form today, an increase of 30 percent since 2017. This bump, among other factors, has led to the industry being valued at close to $50 billion. Here are some of the main AI technologies available today:
Natural Language Generation (NLG)
NLG is an AI subdiscipline that converts data into text. Essentially, it enables computers to communicate with people. It’s widely used throughout the customer service and report generation industries, as it’s effective at compiling reports and summaries. The accuracy of NLG allows businesses to streamline their processes and provide reliable information.
Speech Recognition
Speaking into a remote control or small device is a popular method of searching for information. Siri and Alexa aren’t the only digital entities that can understand you — the likes of Google and OpenText rely on speech recognition, too.
Transcribing volumes of data just by listening is a powerful tool for businesses as it offers an instant service in a world where impatience is everywhere. Users don’t have time to waste, and speech recognition ensures they get what they want in a matter of seconds.
Virtual Agents
Organizations invest many resources in virtual agents because they provide a superior level of customer service. A prime example of virtual agents are chatbots. A chatbot is a piece of software capable of interacting with individuals who visit your website, so your business doesn’t have to make prospects or customers wait. A chatbot is the face of the company in many respects, providing a warm welcome, figuring out customers’ needs and answering FAQs.
Another excellent feature of chatbots is the ability to offer 24-hour assistance. Having a website alone is a good start, but a chatbot interacts regardless of the time, meaning you can improve lead generation and sales.
Machine Learning
One aspect of AI technologies that many people are familiar with is machine learning, which occurs when computer science engineers develop techniques that encourage programs to learn — and it’s not a harbinger of the apocalypse. Instead, machine learning is implemented into businesses’ strategies for prediction and classification purposes.
AI Hardware
Considering AI tends to be web based, hardware doesn’t sound like it could be classified as AI,. However, manufacturers are using AI hardware in a variety of ways to make hardware friendlier than usual. For instance, manufacturers are developing chips that contain an intelligent processing unit that can be easily integrated with mobile devices.
Deep-learning applications are increasingly centered on artificially intelligent hardware.
Decision Management
Given the unavoidable gaps in human knowledge, decision-management tools allow leaders and employees to outsource some of their responsibilities. Intelligent computers can use rules and logic to clear up gray areas and aid in the decision-making process. As a result, they’re fantastic partners in the training and maintenance sectors.
When decisions are tweaked to implement the strengths and weaknesses of software and humans, there’s more scope to enhance value generation.
Deep Learning
Deep learning is another useful form of AI that uses data to influence decisions. The way it works is simple: machines produce and use artificial neural circuits to sort through data sets more quickly than humanly possible. Think of deep learning as an analytics program with the power to sift through reams of numbers and text in minutes.
With a computer that’s capable of recognizing patterns and trends in large volumes of data, businesses can more easily factor the new information into their plans.
Biometrics
AI technologies are developing to the point where software can identify, measure and analyze human behavior. This allows for smoother communications between humans and machines regarding the senses (mainly touch, hearing and speech). The advanced capabilities of biometrics give people with sense deficiencies another way to boost their lifestyle.
Compliance
Companies big and small must be aware of their duties if they want to avoid penalties and negative press coverage. Not complying with rules and regulations opens your business up to lawsuits, which can quicklly bring an organization to its knees. AI technologies like NLG and deep learning offer one way to help.
NLG scans documents and matches keywords in a bid to show businesses the changes they need to introduce to comply with new laws. This solution was incredibly useful when the EU bolstered its data protection legislation in 2018. Deep learning, on the other hand, applies business policies to transactions and spots anything untoward. An excellent example of deep learning doing its job is the flagging of fraudulent transactions that don’t match usual spending habits.
Security
Cybersecurity continues to be a pressing concern for businesses and individuals alike, as hackers are ready to target weak and unsecured businesses to steal sensitive data. Fighting back isn’t straightforward, and success isn’t guaranteed, but AI makes it more manageable. By using machine learning in conjunction with AI, companies can create learning technologies that uncover suspicious activity.
Today, with as many as two billion files being breached every day — 69 percent of them falling into the category of identity theft — there has never been a better time for AI-based security.
What Does the Future Look Like for AI?
AI has leapt significantly forward in a short period of time, and it’s logical to assume it will continue on this trajectory. So, what can we expect for the future of AI?
Deep-Learning AI Technologies Will Be Left Behind
Deep learning has produced many innovations and helped pave the road for current AI technologies, but there is no room for sentiment in an ever-expanding world of data sets. Unfortunately, AI is limited by deep learning because developers can only use available information. And there isn’t a lot of it in some areas, such as the construction industry, where industrial accidents are rare.
But, with the help of reinforcement and transfer learning, algorithms will advance to the point where they can offer solutions without supervision. Transfer learning also means AI will be able to take information from other knowledge bases, generalize it and apply it in another context.
AI Technologies Will Develop Casual Reasoning Skills
When humans solve problems, they use two primary methods: 1) correlation and 2) cause and effect. At the moment, AI already implements the former to great effect because it can draw from a variety of variables. However, it’s reasonable to expect machines to use mental situations in the future to solve problems and make decisions. With causal reasoning, AI programs will be able to analyze laws and rules to figure out how a domain works.
This type of technology is a long way off though, as there are multiple roadblocks developers need to overcome first, including enabling computers to have near-human computing considerations, which are still controversial.
AI Will Explain Its Reasoning
The next step forward from causal reasoning is an explanation, and companies will rely on AI to show its work. Why? Because they don’t want to turn off the profitability tap unless it’s necessary. As an entrepreneur, imagine the effect a wrong decision could have on your bottom line if it’s made based on incorrect information. For instance, going offline because of a supposedly imminent security threat that doesn’t materialize isn’t a good business practice.
As AI progresses, explainability will become a central component of decision making so that leaders can better understand the reasons behind the strategy.
AI Will Act Automatically
At the moment, perception is the limit to AI’s abilities. However, some software is capable of acting without supervision. It requires the user to set the parameters, but it’s still able to make decisions based on these parameters and the data at hand. A prime example of this type of AI in action is investor software that takes care of asset management for beginners and novice investors.
In time, future AI will take this to a new level. We are already seeing automated cars, but what about unmanned aerial vehicles and self-governing power plants? The scope of what AI could bring to the military and energy sectors could revolutionize society.
What Comes After AI?
While we can make predictions, AI’s future is unknown because things can change anytime, and the technology is based on projections. Still, based on what we’ve seen so far, it’s not illogical to assume that AI will morph into something bigger and more powerful, such as:
Collaborators: Currently, AI is used as a tool for better business processes and lifestyle enhancements. But it could transform into a partner or collaborator when it advances to the point of interacting like a human. Rather than just a virtual assistant, you’ll have a team member that is capable of understanding and anticipating your needs. Being able to bounce ideas off AI could lead to programs such as Siri and Alexa morphing into worker-like entities.
Holistic technology: Although hearing someone talking to their phone — not just to another human via their phone — is a more common occurrence, it still turns heads. AI is gradually turning into an excellent aid for personal use; however, that will change in the not-too-distant future. Rather than revolving around individual devices, AI software will move into the public sphere. We have already seen drones that deliver packages and provide in-flight changes based on tracking software. Next, prepare to see AI technologies like taxi apps that automatically know where you want to go. Your wallet will become obsolete. Advancements in biometrics could lead to a point where concrete actions are no longer required, as your brain activity will reveal your intentions.
Lifestyle tweaks: The balance between AI and helping people is a moral dilemma. Regarding the lifestyle of society, though, there is no doubt AI will make tweaks to outdated ideas. Working a nine-to-five shift is a good example. As AI morphs into something more powerful, its ability to complete tasks — both complicated and rudimentary — should reduce our workloads. In the future, people can expect that their emphasis will be on achieving personal goals rather than focusing on work and career targets.
How Can You Ensure AI Works for You?
The best way to adopt useful AI processes is to invest in training. To help you prepare for the AI-infused future that lies ahead, ExitCertified offers training solutions that meet the needs of almost every individual or organization. With over 9,500 IT training courses to choose from, you can access our expert resources from anywhere in the world.
