Posts

5 Ways Machine Learning is Transforming the Business World

Today’s forward-thinking organizations are leveraging the power of artificial intelligence to automate the decision making process. In fact, corporate investment in AI is predicted to reach $100 billion by the year 2025. As a result of this rapid digital transformation, many changes are underway in the workplace. In particular, there are a number of ways that machine learning is already making an impact for companies in every industry. Here are a few to consider.

Personalizing the customer experience.

One of the most exciting benefits machine learning can have for businesses is the fact that it can help improve the customer experience while also lowering costs. Through things like deep data mining, natural language processing and continuous learning algorithms, customers can receive highly personalized support with little to no human intervention. And people are warming to the idea. In fact, 44% of US consumers say they actually prefer chatbots to human agents.

Improving loyalty and retention.

With machine learning, companies can do a deep dive into customer behavior to identify those who are at a higher risk of churning. This enables organizations to develop and implement next steps designed to target and retain those high-risk customers. The more proactive a company is in this area, the more profitable it will be over time.

Enhancing the hiring process.

When asked about the most difficult part of their job, corporate recruiters and hiring managers almost unanimously list the task of shortlisting qualified candidates for job openings. With dozens and sometimes even hundreds of applicants, sifting through and narrowing down the options can be a monumental task. Machine learning is fundamentally changing the way this process is handled by letting software do the dirty work, quickly identifying and shortlisting those candidates that are the best fit.

Detecting fraud.

Did you know that the average organization loses up to 5% of their total revenue each year due to fraud? Machine learning algorithms can be used to track data and apply pattern recognition to identify anomalies. This can help risk management detect fraudulent transactions in real-time so they can be prevented. This type of “algorithmic security” can also be applied to cybersecurity, leveraging AI to quickly and accurately pinpoint threats so they can be addressed before they are able to do damage.

Streamlining IT operations.

Another way AI and machine learning are revolutionizing how organizations operate is through intelligent automation. Powered by machine learning algorithms, agentless automation and orchestration platforms become force multipliers, driving efficiency and helping enterprises save time on manual and repetitive tasks, accelerate mean time to resolution, and maintain greater control over IT infrastructure.

Want to see machine learning in action? Schedule a free product demo today!

Free eBook! Get Your Own Copy Today

What will 2019 have in store for AI and machine learning?

There’s been plenty of hype about machine learning and artificial intelligence and that buzz isn’t expected to slow down anytime soon.As we prepare for another new year, it’s always a good idea to consider what’s in store for technology and all indications point to 2019 being a major year for AI and ML.

What might we expect to unfold over the coming months? Well,for starters, next year is poised to be one in which those who have been teetering on the fence about adopting machine learning are likely to finally take the plunge. Let’s take a closer look at a few other trends to watch for in 2019.

Cross-Industry Infiltration of Machine Learning

To put it plainly, there simply isn’t a single industry that would not benefit in some way from machine learning technology. As more decision-makers begin to recognize this, more widespread adoption will occur alongside the ideation of newer and more innovative ways to use ML.

A great example of this is the U.S. Army. Over the next year, they will be rolling out the use of machine learning sensors to predict when combat vehicles are in need of repair. The health care industry is another field that is finding new uses for AI. For instance, algorithms now exist that can predict – with 95% accuracy – the probability of a patient’s death. Physicians can use this data to literally save lives.

It’s safe to say that as we ramp up adoption of AI and ML,forward-thinking companies will continue to discover new ways to leverage these technologies to read, interpret and apply data for greater success.

Increasing Use of Chatbots

Most of us utilize AI assistants on a daily basis, whether it’s asking Alexa to play our favorite song list or checking with Siri to see how traffic will be for the commute home. These basic interactions are really just the tip of the iceberg.

In 2019, development of chatbots will snowball, making AI assistants an even bigger part of our everyday lives. Not only will they be in our pockets and in our homes, but chatbot technology will continue to make its way into the business world.

For instance, in the IT service management realm, chatbots will be used increasingly to enable end-users to self-remediate while simultaneously freeing up human talent to be focused on more complex projects and business initiatives.

Deepening Interactions between Humans and Machines

The concept of AI being a robot merely capable of performing repetitive, mundane tasks has become antiquated. To the contrary, more and more organizations are recognizing artificial intelligence as an integral part of their workforce, working alongside their human employees and playing a pivotal role in their success. This relationship will only continue to evolve as we push onward into2019 and beyond.

As AI technology advances further, we can expect features and functionality that mimics human behavior in much greater detail. Imagine a chatbot that not only recognizes what a human is saying, but the tone and nuances behind those words. The possibilities are virtually limitless.

And as AI continues to become ingratiated into the fiber of how organizations operate, the fear and uncertainty that clouded human workers in the past will begin to dissipate. In its place will be a newfound respect and an optimism for the new opportunities these innovative technologies will create.

Without question, 2019 will be a critical year for both machine learning as well as AI. The three predictions above may very well just be scraping the surface of what’s truly in store. One thing’s for certain:these technologies are here to stay and they’re changing our world in ways beyond what we ever thought possible.

Want to experience the power of AI and machine learning for yourself?Start your free 30 day trial of Ayehu today!

Free eBook! Get Your Own Copy Today

Using Intelligent Automation to Cut Costs and Skyrocket Service

Using Intelligent Automation to Cut Costs and Skyrocket ServiceFor several decades now, IT automation has been developed,refined and continuously improved to help streamline operations and take on the manual, repetitive tasks that nobody wants to complete. It’s becoming more widely accepted that most of these work duties can be handled by software. Beyond these simple, basic tasks, however, enterprises across the globe are now leveraging artificial intelligence to do even more. It’s called intelligent automation and it’s helping organizations of every shape, size and industry cut costs, improve service and remain a step ahead of the competition.

Intelligent automation is being leveraged as a solution to many common issues large businesses face, particularly those in the financial sector. One such area where intelligent automation is proving to be significantly beneficial is in meeting compliance requirements. Big banks,telecom companies, insurance firms and other businesses that deal with a high number of transactions, especially those that are sensitive in nature, are under increasing pressures to remain compliant. Relying on human workers to achieve this is not only expensive, but also more prone to costly error.

Another critical area where intelligent automation is having a positive impact is in the very volume of data itself. These days,there is so much information flowing into an organizations, from inquiries and transactions to authentications and a whole host of other business processes that businesses are finding it challenging to keep up. With smart technology,much of this data can be gathered, analyzed, sorted and prioritized without the need for human intervention, saving the organization time, money and a ton of aggravation.

Think Smarter, Not Bigger

In reality, even larger enterprises rarely have the luxury of increasing staff levels to the degree that is required to keep up with the rising demands being placed on them. Not only does this equate to increased costs, but it also opens the door to increased risk as well. C-suite executives, board members and other key decision makers are often too focused on other critical business initiatives to worry about growing the IT department.

The good news is, today’s intelligent automation software provides the opportunity to develop into a more efficient, highly productive,error-free environment without the need to beef up personnel. It’s providing organizations a way to work smarter instead of bigger while also lowering risks and keeping costs at a minimum. Unlike the rudimentary technology of just a few decades ago, today’s automation solutions are fully capable of analyzing,learning and responding to a mountain of data in real-time.

In reality, with the right strategy and intelligent automation technology, a business can successfully transition up to 90% of all IT functions from human to machine. This includes everything from repetitive, labor-intensive activities to complex workflows. IT automation is also playing a key role in helping companies establish and maintain a much more effective defense against cyber-attacks, providing the added protection of round-the-clock detection, analysis and response.

How Does Intelligent Automation Work?

Once an intelligent automation solution is adopted and implemented, the IT department determines which tasks are to be automated. Essentially, the software is “taught” what to do, when to do it and how each function should be carried out. Beyond the basics, like robotic process automation, intelligent automation is designed to deal with situational data and use that information to perform appropriate contextual functions. The software essentially uses relevant knowledge to decide on how to proceed in much the same way humans do.

Furthermore, intelligent automation also creates complete documentation of the entire decision-making and execution process, providing the ability for IT personnel to view, track, analyze and evaluate the automated process, both during as well as after the fact. This documentation contains all of the necessary details, including the relevant background and contextual information that was used in the decision-making process. Best of all, this information is stored and can be easily accessed in one centralized location.

The Benefits are Astounding

By adopting intelligent automation, organizations are able to achieve significant cost savings while also improving overall operation and service levels at the same time. When the majority of IT service management functions are shifted from human to machine, skilled personnel can focus on more important business initiatives. This promotes an IT environment that is much more efficient, agile, flexible and compliant, all of which can be translated to improved quality and satisfaction. The more complex the IT system, the greater the benefit automation can provide.

Is your organization taking advantage of these and the many other benefits that intelligent automation can offer? Get started today by downloading your free 30 day trial.

New Call-to-action

The Real Truth Behind the Top 3 Machine Learning Myths

Machine learning has been proven to be so effective that many make the mistake of assuming it applies to all situations and can solve every single problem. As with any technology, there is a time and a place for machine learning – particularly when it comes to existing problems you simply couldn’t tackle due to a lack of resources. If you plan on leveraging ML at any point in the future, you’ll have much greater success if you cut through the noise, avoid the following misconceptions and gain a more accurate understanding of what machine learning can and can’t do.

Myth #1 – Machine learning and AI are one and the same.

The terms machine learning and artificial intelligence are often used interchangeably, but the reality is, they aren’t synonyms. To break it down to simplest of explanations, machine learning is a technique that’s being applied in real-world scenarios. AI is actually a much broader expression that encompasses a spectrum of areas including robotics, natural language process and computer vision. While the results may appear “intelligent,” machine learning is really about learning patterns, applying statistics and predicting outcomes based on data.

Myth #2 – Machine learning will replace people.

It’s a common fear that artificial intelligence technology and its many applications (including machine learning) will ultimately eliminate the need for human workers. While it will most certainly change the jobs being performed and how they are handled, the main purpose of ML isn’t to replace but rather to augment personnel. In actuality, it’s predicted to create more new roles than it will make obsolete. This means greater opportunity for human workers to learn new skills and apply their cognitive and creative talents to more meaningful initiatives.

Myth #3 – Anyone can build a machine learning platform.

Google “how to build machine learning” and you’ll inevitably get pages of results featuring various open source tools and courses. But the fact remains that machine learning is a highly specialized technique. For it to be successful, you must understand exactly how to prepare and partition data for testing and training, know how to choose the most appropriate algorithm and – most importantly – know how to turn that information into a productive system. Furthermore, you must also monitor that system to ensure consistently relevant results.

Getting machine learning right takes time and lots of experience. If you’re just getting started, your best bet is to work with partner that already specializes in this advanced technology and can handle the complexities and nuances on your behalf. Ayehu NG features built-in, highly sophisticated machine learning algorithms and can have you up-and-running in just minutes. Try it free today!

New Call-to-action

The 5 Step Strategy for Optimizing HR with Intelligent Automation

Artificial intelligence has made our lives infinitely easier. Smart home devices can turn lights on and off and adjust the thermostat without us having to get off the couch. Cars automatically hit the brakes to avoid crashes and are capable of parking themselves. But intelligent automation isn’t just something that can benefit our personal lives. The ability to automate time-laden, manual tasks and business processes increases employee productivity and frees skilled personnel to focus on more high-value work. One area that can gain tremendous value from intelligent automation is HR. Here’s how.

Identify processes and workflows that could (and should) be automated.

While human resources is, indeed, a prime candidate for intelligent automation, not every process will be appropriate. It’s imperative that business leaders are careful not to try and automate too much, otherwise they risk losing momentum and failing to reap the true benefits of AI technology. This is why the first step in optimizing HR should always involve a careful analysis of processes and workflows to determine which could be made more efficient through intelligent automation.

Map out a strategy.

Again, in order for intelligent automation to be effective, there must be order to its adoption. Prior to implementation, a plan should be mapped out – preferably one that involves a strategic combination of artificial intelligence and human skills. Create a roadmap that covers everything from the initial introduction of AI to the desired end result. Bear in mind that some processes may be better redesigned from scratch as opposed to trying to modify them.

Keep the lines of communication open and ever-flowing.

Like it or not, people naturally fear change. With intelligent automation, this is compounded by the concern over robots taking over human jobs. Yet, in order to successfully roll out automation, you simply must have buy-in from everyone involved. The best way to accomplish this is to quell your staff’s fear through open, honest and ongoing communication. Be sure to drive home the benefits that automation will provide to them (less drudgery, more opportunity to perform engaging, meaningful work, the chance to learn new marketable skills, etc.). Remind them that automation ultimately drives the demand for soft skills, such as creative problem solving and collaboration.

Make sure the C-suite is also onboard.

In addition to constant communication and transparency with employees, it’s equally critical that executives and key decision-makers are also onboard with intelligent automation. Sure, a detailed and measurable implementation strategy is essential, but enacting organizational change takes more than simply carrying out a set of ordered steps. Change management starts at the top and trickles downward. As such, senior leadership must be visible and vocal in its participation and support.

Teach employees the skills they need for success.

We’ve become quite comfortable with automation in our personal lives, but that comfort level doesn’t necessarily translate to the workplace. Don’t just assume your employees possess the skills they need to leverage intelligent automation. For instance, your HR team likely already has the soft skills they need to do their jobs effectively, but they may need guidance in understanding how to interact with automation technology. Be proactive in educating them.

While there are certainly areas of the human resources function that a human touch is still needed, such as discussing sensitive matters with employees, the vast majority of today’s HR processes can easily be automated. In order to do this, however, HR professionals must be willing to adapt and evolve. The five steps listed above should help in this regard.

Want to experience intelligent automation for yourself? Request an interactive demo or better yet, click here to try the full product, free for 30 days!

New Call-to-action

Have you fallen for these 3 common AI misconceptions?

Artificial intelligence has been around for decades, though it just recently became a hot topic in the business world. During this time, many individuals have confused AI with automation, sometimes going as far as using the two terms interchangeably. The reality is, while the general concept may be similar, the two are distinctly different. Furthermore, this confusion has led to a number of other myths and misconceptions. We’d like to clarify a few things, beginning with the difference between AI and automation.

IT process automation involves programming technology to perform routine, manual tasks based on a prescribed set of instructions. Artificial intelligence takes this concept several steps further by using intelligent machines which are capable of displaying human behavior, thought and decision processes. Where automation is essentially set in stone (unless manually modified), an AI machine increases its own intelligence and can adapt its actions automatically, based on information it receives.

From a business perspective, artificial intelligence has the power to help organizations make more informed decisions. It can extract valuable information from mountains of data, analyze and organize it in a logical manner and essentially close the gap between insight and action. Given its complexity, however, AI is still often viewed in a negative light. To change this, we’d like to dispel three of the most common misconceptions as follows.

Artificial intelligence is a distant dream.

Many people believe that AI is a technology that won’t be readily available and practically applied until many years into the future. The truth is, widespread adoption of AI, both in our professional and personal lives, is much closer to becoming a reality than you may think. In fact, given that so many organizations across all industries and around the world are already employing automation to some degree, the idea that AI could be worked into the mix isn’t all that far-fetched.

Artificial intelligence isn’t really going to make that much of an impact.

The idea that AI is somehow inapplicable in the business world stems largely from the technologies complexity. People tend to discount things they have difficulty understanding. The reality is that AI is not only practical for business use, but it’s incredibly beneficial. The machine learning component of AI means that computers will have the ability to learn without the need for programming. It also has the capability of mining and analyzing big data to extract valuable insights which can then be put into action to achieve better results. These are things every organization can benefit from.

Artificial intelligence is going to eliminate the need for human workers.

While it’s certainly true that AI will make human workers redundant to some degree (think routine, repetitive tasks like reporting and data entry), this technology will not fully replace humans. This is particularly true in certain fields that require high-touch interactions, like HR, health care and consulting.

Likewise, while intelligent automation will streamline and optimize operations for many organizations, it cannot and will not replace the need for the development and nurturing of customer relationships. AI can, however, leverage data to provide human workers with the insight they need to deliver better, more personalized service.

And because implementing and managing new technology will always require some degree of human input, new roles and responsibilities will naturally evolve, which means that for many, AI will present great opportunities.

Like it or not, AI isn’t going anywhere. In fact, 61% of businesses are already implementing artificial intelligence to some degree. By addressing and overcoming the biggest misconceptions about AI, companies can harness the power of intelligent automation to streamline operations and provide competitive advantage.

Want to see AI in action? Click here to request a demo. Or better yet, claim your free 30-day trial today!

New Call-to-action

Reskilling Your IT Team for Digital Transformation

The number of job openings for data scientists is steadily on the rise, with IBM predicting a 93% growth rate in data science skills, followed by 56% predicted growth for machine learning skills. Without question, artificial intelligence experts, machine learning developers and data scientists are in high demand, and as that demand rises, the number of qualified candidates to fill open roles will dwindle.

In fact, according to the 2018 State of the CIO report, 36% of respondents cited difficulty filling roles for business intelligence and data analytics. AI roles also made the top 10. Rather than hiring new employees, many organizations are instead looking to reskill existing staff to prepare them for the roles needed to achieve digital transformation.

Let’s take a look at how some companies across various industries are preparing their existing personnel for the AI era of tomorrow.

Back to School

There is no shortage of formal training programs available at higher education institutions across the globe where those interested in gaining expertise in the way of AI, machine learning and data science can pursue their professional development. The most advanced training typically takes anywhere between a year to a year and a half to complete. It also requires basic programming skills and a solid understanding of programming. There are also a variety of online courses and programs to consider.

Forward thinking companies looking to transform their existing workforce can offer tuition reimbursement and flexible work schedules in order to encourage employees to go back to school. The promise of a newer, better role at a higher pay grade can also be great incentive.

Formal In-House Training

Another way organizations are getting existing employees prepared for digital transformation is to create in-house training centers. These will often include test environments in which trainees can experiment with AI and other disruptive technologies. As employees learn and skills are mastered, the training can then be extended to other teams and departments, including the C-suite.

For those companies that don’t have the capacity to create learning centers, availing themselves of vendor-provided training can be the next best thing. For instance, Ayehu offers a free Customer Success Program as well as free Webinars each month aimed at accelerated training of various AI and machine learning applications.

Peer-to-Peer, On-the-Job Training

As companies begin to build up a pipeline of skilled internal talent, they can then begin investing in peer-to-peer mentoring opportunities to further spread knowledge and education. For instance, a department might attend a starter course to familiarize themselves with the concepts of AI, machine learning, etc. and then transition to a mentoring strategy thereafter.

This approach begins by incrementally exposing employees to smaller areas where the use of disruptive technologies can have a large-scale impact. Once comfortable, they can then move toward improving workflows and tackling other, more complex projects – all under the supervision of experience mentors. Many business leaders utilizing this approach feel that it’s much more effective and that employees learn, absorb and build upon critical skills much faster than they would in a traditional classroom setting.

Keeping Pace with Change

The challenge of reskilling to facilitate digital transformation is that technology is evolving at an incredible rate. Keeping pace with the rate of innovation is the key to success. That means developing and fostering new skills on an ongoing basis.

To address this, some organizations invest in regular educational sessions and AI-related training held either ad hoc or at specified intervals. Access to routinely updated educational resources, like online tutorials, onsite training and industry/sector conferences is another option. The thing to remember is that, given the rapid rate of change, you simply cannot overeducate your employees.

With a staffing shortage that’s growing by the day, business leaders must compensate by reskilling existing employees. Otherwise, they risk losing ground in the race to digital transformation.

Give your team a solid foundation by investing in top-of-the-line, Next Generation Automation and Orchestration. Give it a try free for 30 days. What do you have to lose?

New Call-to-action

Have you fallen for these AI myths?

artificial intelligence AI mythsArtificial intelligence has been around for decades, though it just recently became a hot topic in the business world. During this time, many individuals have confused AI with automation, sometimes going as far as using the two terms interchangeably. The reality is, while the general concept may be similar, the two are distinctly different. Furthermore, this confusion has led to a number of other myths and misconceptions. We’d like to clarify a few things, beginning with the difference between AI and automation.

Intelligent automation involves programming technology to perform routine, manual tasks based on a prescribed set of instructions. Artificial intelligence takes this concept several steps further by using intelligent machines which are capable of displaying human behavior, thought and decision processes. Where automation is essentially set in stone (unless manually modified), an AI machine increases its own intelligence and can adapt its actions automatically, based on information it receives.

From a business perspective, artificial intelligence has the power to help organizations make more informed decisions. It can extract valuable information from mountains of data, analyze and organize it in a logical manner and essentially close the gap between insight and action. Given its complexity, however, AI is still often viewed in a negative light. To change this, we’d like to dispel three of the most common misconceptions as follows.

Artificial intelligence is a distant dream.

Many people believe that AI is a technology that won’t be readily available and practically applied until many years into the future. The truth is, widespread adoption of AI, both in our professional and personal lives, is much closer to becoming a reality than you may think. In fact, given that so many organizations across all industries and around the world are already employing automation to some degree, the idea that AI could be worked into the mix isn’t all that far-fetched.

Artificial intelligence isn’t really going to make that much of an impact.

The idea that AI is somehow inapplicable in the business world stems largely from the technologies complexity. People tend to discount things they have difficulty understanding. The reality is that AI is not only practical for business use, but it’s incredibly beneficial. The machine learning component of AI means that computers will have the ability to learn without the need for programming. It also has the capability of mining and analyzing big data to extract valuable insights which can then be put into action to achieve better results. These are things every organization can benefit from.

Artificial intelligence is going to eliminate the need for human workers.

While it’s certainly true that AI will make human workers redundant to some degree (think routine, repetitive tasks like reporting and data entry), this technology will not fully replace humans. This is particularly true in certain fields that require high-touch interactions, like HR, health care and consulting.

Likewise, while intelligent automation will streamline and optimize operations for many organizations, it cannot and will not replace the need for the development and nurturing of customer relationships. AI can, however, leverage data to provide human workers with the insight they need to deliver better, more personalized service.

And because implementing and managing new technology will always require some degree of human input, new roles and responsibilities will naturally evolve, which means that for many, AI will present great opportunities.

Like it or not, AI isn’t going anywhere. In fact, according to IDC research, worldwide spending on artificial intelligence is expected to reach $19.1 billion this year – an increase of more than 54% over last year. By addressing and overcoming the biggest misconceptions about AI, companies can harness the power of intelligent automation to streamline operations and provide competitive advantage.

Want to see AI in action? Click here to request a demo.

Free eBook! Get Your Own Copy Today

5 Ways the Service Desk can Use Chatbots

Pull up any IT related website and you’ll undoubtedly see dozens of headlines dedicated to artificial intelligence, machine learning and chatbots. Some of what’s being published relates to the threat of job replacement. And while that’s certainly true to some degree, AI isn’t something to fear – even for those who work in IT support. To the contrary, the service desk is ripe with opportunity to leverage chatbots to benefit both the end user as well as the support team. Let’s take a look at a few ways this technology can be used in tandem with the service desk.

Human Resource Optimization

Whether it’s resource planning or the redirection of work away from the service desk, AI can be used to make smarter use out of service desk personnel. For instance, machine learning algorithms are capable of analyzing patterns to predict future workload and plan staffing needs accordingly. Routine IT support tasks, such as password resets and remote restarts, can be shifted to chatbots, essentially supplementing (not replacing) help desk workers.

Improved Decision-Making

Decision support is another powerful way AI technology can aid the help desk. From low level automation of workflows to the prediction of future trends in the IT service realm, such as the demand for new or different IT services, the sky is really the limit with how this can be applied. Predictive analytics can even be used to forecast future customer satisfaction levels based on the impact of various factors that occurred in the past.

Self-Service IT Support

There are many different use cases, including intelligent search, through which machine learning algorithms apply meaning and context and draw from previous search successes to deliver more accurate search results. Intelligent autoresponders can provide automated resolution to service tickets without the need for human intervention. And, of course, the use of chatbots to provide a more engaging IT support interface using artificial intelligence and automated solutions. This not only takes much of the heat off of busy IT professionals, but it also empowers end-users and boosts productivity.

Proactive Service Improvement

In addition to identifying and addressing common IT problems that are occurring presently, predictive analytics can also be utilized to project possible high-impact issues that may occur in the future but have not yet been realized. This enables IT support staff to take proactive measures in reducing the risks of those possible future issues, often stopping them before they occur. And thanks to the technology’s advanced learning capabilities, it can improve on its own, getting better over time.

Improved Customer Experience

Each of the four points above contribute to a better customer – or in this case, end-user – experience. From better solutions to faster, more efficient support to self-service options (including chatbots and autoresponders) to proactive problem resolution and more. AI will undoubtedly continue to play a critical role in IT support’s customer experience journey, improving as time goes on.

These are, of course, just a handful of the many ways the service desk can leverage AI technology. There will be many other opportunities to use chatbots in the not-so-distant future. The most important thing to note is that artificial intelligence technology is already here and those in IT support that are currently using it will remain a step ahead of the competition.

Don’t get left behind. Schedule a free product demo of Ayehu today and learn how you can leverage chatbots to bring your service desk to the next level!

Free eBook! Get Your Own Copy Today

Human Learning vs. Machine Learning – What’s the Difference

These days, artificial intelligence is all around us. If you’ve ever used Siri on your iPhone or the live chat feature of a website, you’ve interacted with AI. From a business perspective, the rise of AI can be both exciting and challenging. Furthermore, it’s a concept that isn’t necessarily easy for everyone to grasp. The most common question being asked by individuals who aren’t deeply involved with tech is, “What, exactly, is artificial intelligence?” Perhaps the easiest way to understand AI is to compare it to something that is already widely understood – human intelligence.

How Does Human Intelligence Work?

Generally speaking, human intelligence follows a simple, straightforward and typically predictable pattern. We gather information. We process that information. And we use that processed information to decide what to do next. These three basic steps can be summed up as follows:

Input —> Processing —> Output

Input occurs through sensing and perceiving the things all around us. The senses – eyes, ears, nose, etc. – gather raw input, such as the sight of light or the scent of a flower. The brain then processes that information and uses it to determine what action to take. In the processing stage, knowledge is formed, memories are retrieved, and inferences and decisions are made. Output then occurs in action based on the information processed. For instance, you might hear a siren, see an ambulance in your rear view mirror and subsequently decide to pull over to let it pass.

In order to safely navigate the world in which we live, we must effectively process all of the input we receive. This basic concept is the core of human intelligence, which can further be broken down into three definitive segments:

Knowledge/Memory

People gain knowledge through the ingestion of facts (i.e. the Pilgrims landed in 1620) as well as social norms (i.e. saying “Please” or “Excuse me”). Further, memory allows us to recall information from the past and apply it to present situations.

Inference/Decision

Inferences and decisions are made based on the raw input we receive, combined with our memories and/or built up knowledge. For instance, let’s say you tried a new food a few months ago that turned out to be way too spicy for your taste. The next time you’re offered that food, you politely decline.

Learning

There are a number of ways humans can learn, including observation, example and algorithm. With observation, we determine the outcome on our own. With example, we are told the outcome. Learning by algorithm, on the other hand, allows us to complete a task by following a series of steps. A good example of this would be solving a long division problem.

Human Learning vs. Machine Learninghuman learning vs. machine learning

The main aspects of human intelligence are actually quite similar to artificial intelligence. In the same way that humans gather information, process it and determine an output, machines can do this as well.

Of course, because machines do not have physical senses like people do, the way they gather input differs. For instance, rather than sight or smell, artificial intelligence gathers information through things like speech recognition, visual recognition and other data sources. Think about how a self-driving vehicle can sense obstacles in the roadway or how your Amazon Echo listens and recognizes your voice.

The processing piece of the formula also mimics how human intelligence works. Similar to the way people accrue memories and build knowledge, machines are capable of creating representations of knowledge and databases where information is stored. And, just as people draw inferences and make decisions, machines can predict, optimize and determine what the best ‘next steps’ should be in order to accomplish a particular goal.

Similarly, just as humans learn by either observation, example or algorithm, machines can also be “taught.” For instance, supervised machine learning is akin to learning by example: the computer is provided with a data set containing labels that act as answers. Over time the machine can essentially “learn” to differentiate between those labels to produce the correct outcome.

Unsupervised machine learning is like learning by observation. The computer recognizes and identifies certain patterns and subsequently learns how to distinguish groups and patterns on its own. Lastly, learning by algorithm is the process by which a programmer “instructs” the computer precisely what to do, line by line, using a software program. Ideally, the most effective form of artificial intelligence will utilize a combination of the above learning methods.

The output that results sums up how machines interact with the world around them, whether it’s speech generation, navigation, robotics, etc.

Take, for example, the business use case of cybersecurity threat detection. Artificial intelligence can scan enormous amounts of data and monitor an entire infrastructure in real-time. It can then, through a combination of unsupervised and algorithmic learning, pinpoint anomalies that could potentially represent data breaches. It can then use that information to investigate and test, automatically determining what the next steps should be, whether it’s escalation to a human agent or automatic remediation.

The Future is Now

We have, undoubtedly, only seen the tip of the iceberg as it relates to artificial intelligence and its potential impact on our lives – both personal and professional. As technology continues to evolve and improve at a breakneck speed, AI and machine learning capabilities will also evolve. Why wait? Get ahead of the curve and experience the next generation of automation and AI by taking Ayehu for a test drive today.

Free eBook! Get Your Own Copy Today