Those of us in the technology sector are quick to celebrate advances in artificial intelligence (AI). From applications that can detect fraudulent transactions to those that can predict disease progression, AI is poised to optimize business automation processes and drive powerful research breakthroughs. So why is it that a 2021 survey by the Pew Research Center found that a greater share of Americans reported being "more concerned than excited" about AI's increasing presence, and how can our community address this? Aside from the proverbial fear of job loss (and I, Robot uprisings), public mistrust of AI stems from the field's lack of ethical oversight. Professor Frank Rudzicz of the University of Toronto and the Vector Institute outlines the three biggest ethical concerns for AI today: First, what AI is actually used for may not be what we intended; second, access to AI is not always equal; and lastly, AI can very easily adopt and amplify unconscious human biases in our society.

Deep reinforcement learning is one of the most interesting branches ofartificial intelligence. It is behind some of the most remarkable achievements of the AI community, including beating human champions at board and video games, self-driving cars, robotics, and AI hardware design. Deep reinforcement learning leverages the learning capacity of deep neural networks to tackle problems that were too complex for classic RL techniques. Deep reinforcement learning is much more complicated than the other branches of machine learning. But in this post, I'll try to demystify it without going into the technical details.

Artificial intelligence is here and it's increasingly improving businesses and lives. Companies or industries that invested in AI are already receiving its impact with powerful technologies that leverage business ideas. Although AI is making waves in the technological world, it is no surprise to see many having misconceptions about what it truly is. Some believe it is fiction and reject the idea. Others refer to it as robots and believe it would take over the world.

Machine learning models and artificial intelligence solutions have been rapidly adopted as part of enterprise solutions and consumer products. AI tech has quickly advanced, and is now applicable for diverse and large-scale use cases. It's imperative that organizations look to ethics for guiding the tech's development, applications, and deployment in such a scenario. Such guidelines are critical when it finds application in sectors like education, enterprise solutions for healthcare, justice, public welfare, etc. CIOs believe that it's essential that AI tech and application be transparent and trustworthy as they are widely implemented at both enterprise and consumer levels. Very few of them are comfortable with enterprises that deploy AI solutions for interaction.

AI will take your job, AI can sort out even the messiest data, AI will take over the world, AI is new. AI has been touted in the recent past, with it comes myths that often lead to misunderstanding of the technology. Eliezer Yudkowsk says that "By far the greatest danger of Artificial Intelligence is that people conclude too early that they understand it." In this article, we take a look at the top myths about Artificial intelligence we get to see what is true and what is not. "understanding is much deeper than knowledge there are very many people who know artificial intelligence but very few understand AI" AI dates back to the 19th century when an English mathematician and writer, Lady Ada Lovelace predicted that "a machine might compose elaborate and scientific pieces of music of any degree of complexity or extent" this was later advanced in the 1940s when a Bombe machine was created by Alan Turing.

In reality, the most popular methods for assessing the accuracy of an AI model aren't as trustworthy as you might think... You just watched The Shining and your neighborhood's seen an unusual number of burglaries in recent weeks. You're on edge, but then you remember: your new security system. It's state of the art, with a camera that promises to recognize not just strange movements but also a stranger's face, in real-time. You trust that this system will alert you if someone suspicious approaches your home, so you sleep soundly.

India is a hub of all the hype created around Artificial Intelligence. The country receives 65% of the global IT off-shore work and 40% of global business processing work. This leaves a great potential for intelligent automation as tech experts claim that about 70% of jobs in India's formal employment sector will be automated by 2030. While these numbers may paint a pretty gloomy picture, there are financial takeaways to cheer about. On one hand, automation will escalate technology adoption across industries, economies of scale that the country offers will put it as a favourite among the global off-shore business, especially after Covid-19.

In simple terms, artificial intelligence refers to situations where computers carry out work that would have previously been done by actual people. This is something that doesn't sit well with some, with many fearing that AI is going to negatively impact the world we live in.

When you think about service robots, what comes to mind? Maybe you think about that little CGI trash-compacting robot that was all alone cleaning up a future, wasted earth. Or maybe you think about a faraway robot rover scouring the surface of Mars, searching for signs of life. Perhaps you recently saw a robot your local grocery store mopping up spills. There are plenty of misconceptions about the nature of service robots.

In today's world, it's almost impossible to avoid Artificial Intelligence (AI). From daily interactions with Voice assistants and smartphones to the content recommended to you by media streaming services; everybody is already interacting with AI in some shape or form, even if they don't realize it. The workplace is no exception. AI is rapidly reinventing the way we work across every industry, with 70 percent of organizations set to assist workers with AI solutions by 2021. Terms like'AI', 'Automation' and'Machine Learning' are now commonplace in offices throughout the world, where they are often used arbitrarily, incorrectly and even interchangeably.