Why Machine Learning Should Matter to You?

In recent years, machine learning has taken the world by storm as more people attempt to automate processes and build their data faster. As a method of analyzing data, machine learning development allows companies to learn from the information they are able to gather without using much human interference. With the artificial intelligence being exposed to more and more data, they can adapt, learn, and produce decisions based off of that data.

 

As the world grows and changes, being able to analyze the trends in the market and wants of its users is absolutely crucial for a company to be on top of their industry. Machine learning services, therefore, is incredibly important. In fact, almost every single industry is using machine learning in some capacity.

 

Machine Learning Frees Your Employees

 

Machine learning lets your employees learn new skills that they would not have had time for otherwise. Rather than analyzing extensive sets of data for hours at a time, employees can focus more on things that artificial intelligence is unable to do for the business (things that fluctuate or that need human interaction in to work). Using machine learning, you can also take out the human error that can occur as well.

 

Using Machine Learning Allows You to Stand Up Against Competitors

 

Automating your processes and analyzing data with machine learning can help you do things quicker and more efficiently than your competitors. Some companies even analyze public information about competing firms with their AI, as it can clue them in on what steps that company might be taking in the future. Complex problems are suddenly turned into simple ones as data trends that were previously undetectable, are easy to find with machine learning.

 

Scale with Machine Learning

 

With the added time your employees have and the extra money your company will save by using machine learning, scalability is much more attainable. Problems that could not be solved before, are now made easy with AI and allow you to focus on combined solutions to streamline business – and in the end, scale your business.

 

When a company can improve their productivity, efficiency, and the processes by which they make decisions, they are exponentially better prepared to handle more work. As the company scales, their machine learning continues to adapt alongside the business and provide more solutions. Charter Global can help you implement a Machine Learning development strategy specific for your application and business. Call today to set up a free consultation.

3 Ways Artificial Intelligence (AI) Services will Impact the Economy in 2020 and Beyond

1) Increasing efficiency and accuracy in our everyday work.

It’s tempting to believe that artificial intelligence services can do just about anything. If tech experts are to be believed, artificial intelligence (AI) has the potential to transform the world. Tech entrepreneur, Elon Musk, says this would be a threat to humanity and life as we know it.

Even though thinking among AI researchers has evolved over the years, the future impact of AI is strongly debated among experts.

Currently, AI and machine learning solutions power self-driving cars, complex ad-tech audience optimization, and a host of intelligent agents such as Alexa, Cortana and Siri. At the same time, leading AI experts, business owners, and analysts caution against an overly rosy view of its current capabilities.

The hype surrounding AI’s potential has misled many into overlooking its current utility. Eventually, AI will redefine industries and build technologies we never thought possible. However, business leaders and AI experts say the real value in today’s AI lies in increasing efficiency and accuracy in our everyday work.

2) Preparing for The Future – The Government’s Role

Artificial Intelligence (AI) Solutions holds the potential to be a major driver of economic growth and social progress. If industries, society, government, and the public work together to support development of this technology with thoughtful attention to its potential and managing its risks, then everyone will benefit.

The U.S. government has several roles to play. Participation in conversations about important issues is key; this is to help set the agenda for public debate. In fact, this initiate can monitor the safety and fairness of applications as they develop, and adapt regulatory frameworks to encourage innovation while protecting the public.

Another utility the government can provide is public policy tools to ensure that disruption in the methods of work enabled by AI increases productivity while avoiding negative economic consequences for certain sectors of the workforce. Not only this, but the government can support basic research and the application of AI to public good. One of those features is to support development of a skilled, diverse workforce.

Government can apply AI to serve the public faster, more effectively, and at a lower cost. Many areas of public policy, from education, to defense, to environmental preservation, and criminal justice, will see new opportunities and new challenges driven by the continued progress of AI.

To enable these policies, it’s crucial for the U.S. government to understand and adapt to these changes.

3) Economic and Social Morality

As the technology of AI continues to develop, practitioners must ensure that AI-enabled systems are governable. This is to ensure they are open, transparent, and understandable. In essence, AI must work effectively with people, so that their operation will remain consistent with human values and aspirations.

Researchers and practitioners have increased their attention to these challenges, and should continue to focus on them.

Developing and studying machine learning development services can help us better understand and appreciate our human intelligence. Used thoughtfully, AI can augment our intelligence and help us to chart a better and wiser path.

Charter Global offers AI resources to a variety of different types of projects. Consult us for expert help, and learn more about what we can do to achieve your AI goals.

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Understanding the Difference Between Machine Learning vs. Artificial Intelligence | Charter Global

Machine Learning Development Service

ML is technically a subset of AI. Essentially, ML provides systems the ability to automatically learn and improve from experience without being explicitly programmed; focusing on the development of computer programs that can access data and use it learn for themselves.

In other words, Machine Learning Development Service relies on processing big datasets, while detecting trends and patterns within that data and essentially “learning” about these trends along the way.

Like people, machines have the ability to “learn,” acquiring knowledge and/or skills through their unique experiences. For example, say you have an ML program with lots of images of skin conditions, along with what those conditions mean.

The machine learning algorithm examines the images and identifies patterns, allowing it to analyze and predict skin conditions in the future.

When the machine learning algorithm is given a new, unknown skin image, it will compare the pattern in the current image to the pattern it learned from analyzing past images. In the instance of a new skin condition, however, or if an existing pattern of skin conditions changes, the algorithm will not predict those conditions correctly.

This is because one must feed in all the new data so that the algorithm can continue to predict skin conditions accurately.

Artificial Intelligence (AI)

Unlike machine learning services, AI learns by acquiring and then applying knowledge. The goal of AI is to find the most optimal solution possible, by training computers a response mechanism equal to or better than that of a human being.

In the instance of adaptation in new scenarios, Artificial Intelligence services is perhaps the most ideal.

Let’s take a simple video game, for example, where the goal is to move through a minefield using a self-driving car. Initially, the car does not know which path to take in order to avoid the landmines.

After enough simulated runs, large amounts of data are generated concluding which path works and which paths do not. When we feed this data to the machine learning algorithm, it is able to learn from the past driving experience and navigate the car safely.

But, what if the location of the landmines has changed? The machine learning algorithm does not know these individual landmines exist, rather, it only exclusively knows the all it knows the pattern resulting from the initial data.

Unless we feed the algorithm the new data so it can continue learning, it will continue to guide along that (now incorrect) path.

Enter, AI – capable of analyzing new data in an algorithm to determine multiple factors; answering questions like, why did the paths change? Which direction is most ideal, given the new circumstances, and where are the new hot-spots? It will then codify rules of those hot-spots where the land mines exist.

Slowly, AI will begin to avoid them altogether by following the new trails – just like people, learning and adapting to new boundaries and environmental challenges.

The Future is Now with AI and ML

So, by now, you’ve learned the basic differentiating factors between ML and AI. Machine learning uses past experiences to look for learned patterns, while Artificial Intelligence services uses the experiences to acquire knowledge and skills, then applies that knowledge to new scenarios.

It’s clear that both AI and machine learning have valuable business applications, empowering companies to respond quickly and accurately to changes in customer behavior and solve critical business problems.

As the adoption of AI and ML become more commonplace, namely predictive analytics and data science will see a massive uptake in virtually all industries across the marketplace.

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