As more organizations migrate their data science work to the cloud, they naturally want to bring along their favorite data science tools, including RStudio, R, and Python. While RStudio provides many different ways to support an organization's cloud strategyOpens a new window, we've heard from many customers who also use Amazon SageMaker. They wanted an easier way to combine RStudio's professional products with SageMaker's rich machine learning and deep learning capabilities, and to incorporate RStudio into their data science infrastructure on SageMaker. Based on this feedback, we are excited to announce RStudio on Amazon SageMaker, developed in collaboration with the SageMaker team. Amazon SageMakerOpens a new window helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning models quickly by bringing together a broad set of capabilities purpose-built for machine learning.

As more organizations migrate their data science work to the cloud, they naturally want to bring along their favorite data science tools, including RStudio, R, and Python. While RStudio provides many different ways to support an organization's cloud strategyOpens a new window, we've heard from many customers who also use Amazon SageMaker. They wanted an easier way to combine RStudio's professional products with SageMaker's rich machine learning and deep learning capabilities, and to incorporate RStudio into their data science infrastructure on SageMaker. Based on this feedback, we are excited to announce RStudio on Amazon SageMaker, developed in collaboration with the SageMaker team. Amazon SageMakerOpens a new window helps data scientists and developers to prepare, build, train, and deploy high-quality machine learning models quickly by bringing together a broad set of capabilities purpose-built for machine learning.

Video analytics represents something of a holy grail to those in the security industry. Computers have long been able to scan text and even audio for keywords or phrases, but analyzing video -- especially in real time -- is considerably more challenging. In recent years, however, major improvements to artificial intelligence (AI), machine learning and deep learning capabilities have given rise to impressive new tools capable of analyzing video with minimal input from security personnel. As companies look to invest in these new technologies, it's important to establish a baseline understanding of what terms like artificial intelligence, machine learning and deep learning actually mean -- and what these technologies are capable of. Education will be increasingly critical as we move away from relying on human-based security and lean more on technology to identify and alert us to anomalous or troubling behavior.

Video analytics represents something of a holy grail to those in the security industry. Computers have long been able to scan text and even audio for keywords or phrases, but analyzing video -- especially in real time -- is considerably more challenging. In recent years, however, major improvements to artificial intelligence (AI), machine learning and deep learning capabilities have given rise to impressive new tools capable of analyzing video with minimal input from security personnel. As companies look to invest in these new technologies, it's important to establish a baseline understanding of what terms like artificial intelligence, machine learning and deep learning actually mean -- and what these technologies are capable of. Education will be increasingly critical as we move away from relying on human-based security and lean more on technology to identify and alert us to anomalous or troubling behavior.

During the Intel AI Summit earlier this month where the company demonstrated its initial processors for artificial intelligence training and inference workloads, Naveen Rao, corporate vice president and general manager of the Artificial Intelligence Products Group at Intel, spoke about the rapid pace of evolution in the AI space that also includes machine learning and deep learning. The Next Platform did an in-depth look at the technical details Rao shared about the products. But as noted in the story, Rao explained that the complexity of neural network models – when talking about the number of parameters – is growing ten-fold every year, a rate that is unlike any other technology trend we have ever seen. For Intel and the myriad other tech vendors getting making inroads into the space, AI and components like machine learning and deep learning already is a big business and promises to get bigger. Intel's AI products are expected to generate more than $3.5 billion in revenue for the chip maker this year, according to Rao.

In the aftermath of a natural disaster, response and recovery efforts can be drastically slowed down by manual data collection. Traditionally, insurance assessors and government officials have to rely on human interpretation of imagery and site visits to assess damage and loss. But depending on the scope of a disaster, this necessary process could delay relief to disaster victims. Article Snapshot: At this year's Esri User Conference plenary session, the United Services Automobile Association (USAA) demonstrated the use of deep learning capabilities in ArcGIS to perform automated damage assessment of homes after the devastating Woolsey fire. This work was a collaborative prototype between Esri and USAA to show the art of the possible in doing this type of damage assessment using the ArcGIS platform.

Artificial intelligence has been trending upward for years now. AI is being used for all different types of applications and technology. In the past, I've covered the marketing skills you need to survive in the age of AI. That's because marketers have been using AI technology to reshape the way that consumers are targeted. Brands and websites are using AI chatbots to improve communication with website visitors. They're also using this technology to analyze big data.

The vast amount of information encoded in an individual's DNA tells great tales of one's health and disease conditions. When the first human genome was sequenced, the project that began in 1990 took over 10 years and cost around $2.7 billion. According to Andrew Underwood, CTO, HPC & Artificial Intelligence, Dell EMC, Australia and New Zealand, data intensive computing is fast becoming a dominant approach. Especially in R&D, it is a rapidly growing field of research built on data that is generated from scientific instruments, people, machines and IoT devices. Data comes in high velocities and in large volumes – requiring scientists to harness the power of high performance computing to analyze data faster for timely insights in their field of research.

Humankind has been long fascinated with the concept of machine learning or artificial intelligence. Vast literature and artwork have been created to express the idea that one day, machines will develop their own sense of learning and process information by themselves, without the need for constant human programming. Movies like "Tobor the Great" (1954), "The Terminator" (1984), "A.I." (2001), "iRobot" (2004), and "Transcendence" (2014) featured these futuristic technologies where computers/robots even get to acquire the cognitive ability of man, nay, even at some point surpass it beyond belief. Believe it or not, these technologies exist now. Since its public breakthrough in 2012, artificial intelligence (AI) has since began to spread in the commercial sphere to further streamline business processes, boost product functionality, and aid in customer services.

The Artificial Intelligence revolution is here. We are moving further into an age, where the imagination stirred from our childhood spent watching movies, is now becoming reality. Leading us into this age are the typical (and untypical) tech giants, who are fiercely competing for the next break through. Project Oxford is Microsoft's venture into the world of artificial intelligence and deep learning. It takes in several key areas, including image, facial, text and speech recognition, and hopes to implement the technology into its computer operating systems and smartphone software.