Machine learning

Machine learning (22)

How Is Machine Learning Changing?

 Machine learning (ML) is altering the landscape of all segments and industries such as education, transport, healthcare, and entertainment, among others. It will impact operations in other areas such as housing, shopping and cars. This technology is used in robotic process automation and making predictions that give business decision-makers insight regarding operations. As machine learning technology continues advancing, here are some trends that prove that it is changing:

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How Machine Learning May Change Education

Artificial Intelligence (AI) is now part of almost every industry. From parking systems to smart sensors, AI is promising to alter the way we do things through technologies such as computer vision and machine learning, and others. This technology provides tools that can be used to revolutionize education and training institutions. Its potential in this industry is enormous, ranging from robotic teachers, personalized learning, coaching using artificial intelligence, and automating administrative tasks in schools to reduce the cost of operations and enhance efficiency. Here are some ways in which machine learning may change education:

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Thinking that Machine Learning Isn't Making an Impact?

Artificial intelligence is a topic that we keep hearing now and then during discussions in different tech and business circles. Some people still associate it with science fiction movies, but the truth is, it is here with us and chances are, you might be interacting with it daily. The popular AI inventions include Siri and Alexa, both of which make our lives easy. These inventions have made AI a household name and Alexa is the evidence of its presence in our lives. While some people may see it as a new phenomenon, the concept is not new. It first came into existence as early as 1956, although it took decades to make progress towards making it a reality. Here are top AI and machine learning trends in 2021:

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Here's What's Coming in Machine Learning in 2021

Machine learning and artificial intelligence have been the leading topics of discussion in 2020. The coronavirus pandemic has made these technologies highly crucial than before, as they have shown the potential to help in many ways. Machine learning is now the driving force behind multi-billion industries such as medical diagnostics companies and autonomous vehicle companies, among others. With this immense potential, almost every industry is investing in it. Here are some trends that you should expect in 2021 going forward.

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Starting a Machine Learning Initiative?

Machine Learning and Artificial Intelligence (ML and AI) have become some of the most talked about technologies in the recent years. This has been occasioned by the prominence that these technologies have gained and the advancements in this area. As such, big tech companies such as Google, Microsoft Azure and Amazon are the leaders in this area, having developed different ML platforms. While AI and ML may appear to be alien terminologies to many, we have been experiencing it without us even being aware of it. Some of the areas that you might have come into close contact with this technology are in image tagging by Facebook as well as spam detection by email providers. For Facebook, for example, uploaded images are tagged automatically using face or image recognition algorithms while email providers such as Gmail use ML to recognize patterns or selected words then filter spam messages accordingly. Now let us look at some problems that arise from machine learning.

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The Evolution of Telematics

Imagine you walk into your dispatch office and see that your vehicle has broken down, your driver is running out of available hours, and inclement weather is delaying your next job. As the fleet manager, you now have to decide how best to handle this perilous situation. You have relied on disparate data sources to get ahead of the problem, but still you struggle for insights that can drive good decisions. Enter: Telematics 2.0 – the evolution of telematics.

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Bias is Everywhere - Can AI Help Identify and Reduce It?

 Bias is one of the biggest documented weaknesses of humans. This can be seen from implicit tests that show that we are not even aware of some of our biases. Although we may say that these biases are part of human nature, experiments have shown that they can affect our judgments and outcomes. Over the past few years, there has been an argument on whether human biases can be solved by artificial intelligence or whether these biases can make their way into AI systems and cause harm. This comes at a time when AI is being deployed by many companies across different industries. The industries need to be aware of the risks of biases ad how AI can be affected by it.

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A Look At CraftAssist, Facebook’s Collaborative AI Assistant Bot For Minecraft

Minecraft is a popular sandbox multiplayer online building game. It starts with a generated world where terrain and features are created with building blocks. There are also generated characters called “mobs” that appear throughout the world. The two types of gameplay in Minecraft are survival mode and creative mode. In survival mode the player can be harmed and has limited resources. In creative mode the player does not have to worry about being harmed and has access to all resources. In creative mode the player’s imagination is the limit and there have been endless creative projects that have been carried out in the game including recreations of cities and landmarks among others. 

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AI is Being Mutated to Get Faster

For decades, artificial intelligence has been seeking to mimic humans and nature. The main goal here is to create systems that have the ability to make decisions like humans. As such, most AI systems are brain-inspired, and scientists behind it have always attempted to mimic neural networks, a term borrowed from biology. With computers now able to think like humans, computer scientists are now focused on a different goal as they seek to revise artificial intelligence by transitioning it into smarter and more efficient systems. Initially, most of the research was devoted to training AI through machine learning to enable algorithms to learn how to recognize objects and how to perform basic tasks. Now that this has been achieved, these techniques are being deployed to create more advanced systems that can work autonomously without human intervention.

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AI Still Needs Training To Understand Us

While artificial intelligence (AI) continues making headlines and breaking barriers that were thought to be impossible a decade ago, humans are now looking at it with both awe and fear. This is understandable because no one can allow their work to be taken away or to be replaced in places where they have for years looked for their daily bread. When people hear that companies are building AI-powered assistants to help in different tasks, they get afraid that AI is close to becoming independent of humans. The questions that they often ask are; Is AI close to matching human intelligence? Are we close to the fictional Skynet predicted in the Terminator? Is AI smart in its own and will it take positions long occupied by humans?

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