If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
In this article, you learn how to make Automated Dashboard for Classification Neural Network in R. First you need to install the rmarkdown package into your R library. Assuming that you installed the rmarkdown, next you create a new rmarkdown script in R. The result of the above coding are published with RPubs here.
Apache Spark has fast become the most popular unified analytics engine for big data and machine learning. It was originally developed at UC Berkeley in 2009 by the team who later founded Databricks. Since its release, Apache Spark has seen rapid adoption. Today's most cutting-edge companies such as Apple, Netflix, Facebook, and Uber have deployed Spark at massive scale, processing petabytes of data to deliver innovations -- from detecting fraudulent behavior to delivering personalized experiences in real-time -- that are transforming every industry. Behind these groundbreaking innovations are a small, but fast growing group of talented engineers, developers, and data scientists with deep knowledge of Apache Spark.
Every Data Scientist should be analytical. However, the Pure Analytical Data Scientist is a numbers cruncher. Linear Algebra and Statistics are the core of its solutions. Typical backgrounds for this kind of Data Scientist are mathematics, statistics, physicists and even economics. Frequently, these profiles are proficient with numbers but less experienced with complex software and data pipelines.
Up until recently, compliance has mainly relied on people. And as a result of the significant increase in regulatory reporting requirements for financial institutions over the last decade, demand for compliance professionals has surged. Companies have had no choice but to hire more and more compliance staff, in an effort to tackle the growing regulatory burden. However, over the last few years, technology has begun to play a much larger role within compliance. Financial institutions and regulators have realised that by harnessing the power of technology, and more specifically, the power of artificial intelligence (AI) and machine learning (ML), a considerable proportion of the compliance function can actually be automated, reducing the burden on institutions and compliance professionals.
AI is a term that gets bandied about a lot these days. But what does it really mean? Luis Perez-Breva is a lecturer and research scientist at MIT's School of Engineering and the originator and lead Instructor of the MIT Innovation Teams Program. He's the author of Innovating: A Doer's Manifesto for Starting from a Hunch, Prototyping Problems, Scaling Up, and Learning to Be Productively Wrong. He knows a lot about what AI is and how it will impact our lives going forward. He also knows a lot about what AI isn't. I recently got a chance to pick his brain, and hopefully clear a few things up.
Hoobox Robotics, a robotics company based in São Paulo, Brazil, has developed the "Wheelie 7", a wheelchair controlled using facial recognition technology. Incorporating AI developed by Intel, the technology allows users to control the movements of a motorized wheelchair using just their faces. The technology is envisaged as being particularly helpful for users who cannot use their hands to control a motorized device. The tech consists of a 3D camera that records a user's facial expressions (no body sensors are required) and an on-board computer that interprets the expressions and sends commands to control the movement of the wheelchair. The company claims that their facial recognition system is so sensitive that it can differentiate ten different levels of pain, detect drowsiness, agitation, and sedation, and can even detect when a person will sneeze before the event occurs.
The first wave of digital transformation was built upon leveraging cloud, mobile and big data, to create a platform for organisations to achieve greater operational efficiencies, better business insights, and deeper customer engagements. These efforts helped provide competitive advantages for organisations as they started to work smarter and more efficiently. The commitment to digital transformation is as strong as ever. According to IDC, global enterprises will spend $1.7 trillion on digital transformation in 2019. As manufacturers continue digital transformation journeys they are now looking to enter the transformation 2.0 phase, in which they will use new technologies to create even more opportunities and address new challenges on the factory floor.
Are you curious about the ways in which Artificial Intelligence, machine learning, and the range of cognitive technologies are helping improve Cybersecurity and respond better to emerging threats? Check out this infographic from Cognilytica that outlines some key stats as well as key ways in which AI is improving cybersecurity.
Russian president Vladimir Putin stated - "AI is the future and whoever becomes leader in AI will become the ruler of the world". Chinese president Xi Jinping declared that "China wants to be the world leader in AI by 2030". US White House administration voiced - "America has been the global leader in AI, and the Trump administration will ensure our great nation remains the global leader in AI". Similarly, National strategy for Artificial Intelligence, India published by NITI Aayog indicates its vision as "AI-for-All in India". These statements clearly indicates that the race for the supremacy in the field of Artificial Intelligence had already taken a great momentum and AI has managed to influence even main stream politics and the world leaders in a great way. On the other hand, many experts across the globe are already in a big hurry to proclaim which country is going to be the AI superpower and who is already ahead in the race.
Artificial intelligence is one of the most powerful technologies for reshaping business in decades. It has the ability to optimize many processes throughout organizations and is already the engine behind some of the world's most valuable platform businesses. In our view AI will become a permanent aspect of the business landscape and AI capabilities need to be sustainable over time in order to develop and support potential new business models and capabilities. Specifically, we believe that companies need to establish dedicated organizational units to entrench AI. This is an important business tool that cannot be left to bottom-up whimsy.