Whether you are counting cars on a road or people who are stranded on rooftops in a natural disaster, there are plenty of use cases for object detection. Often times, pre-trained object detection models do not suit your needs & you need to create your own custom models. How can you use machine learning to train your own custom model without substantive computing power & time? How can you use your custom-trained model to detect objects, in real time, with complete user privacy, all on a device with limited computing power? In this workshop, you will learn how to build an app that lets you use your own custom-trained models to detect objects.

If artificial intelligence is truly our fasting moving technology, the law has been lagging far behind. Addressing the emerging legal issues requires an understanding of the technology and how it works. In his Technology Law column, Peter Brown examines how AI functions and some of its legal implications.

ServiceNow, based in Santa Clara, California, and led by former SAP SE Chief Executive Officer Bill McDermott, makes software used by large companies to handle requests for help to their information technology departments, among other uses. The newest version of its software, called "Orlando," aims to use artificial intelligence to ease common tasks, company officials said. For example, if an employee needs to reset a password to access human resources software, the person can talk to a virtual assistant in the ServiceNow system that can ask a few questions and reset the password automatically. The system uses a technology called natural language processing to understand the request, said Dave Wright, ServiceNow's chief innovation officer. "You only need to have that one conversation - you don't need to know how to change your password for 20 different systems," Wright told Reuters in an interview.

Timnit Gebru was wary of being labelled an activist. As a young, black female computer scientist, Gebru – who was born and raised in Addis Ababa, Ethiopia, but now lives in the US – says she'd always been vocal about the lack of women and minorities in the datasets used to train algorithms. She calls them "the undersampled majority", quoting another rising star of the artificial intelligence (AI) world, Joy Buolamwini. But Gebru didn't want her advocacy to affect how she was perceived in her field. "I wanted to be known primarily as a tech researcher. I was very resistant to being pigeonholed as a black woman, doing black woman-y things."

In May of 1896, Charles Moisson and Francis Doublier traveled to Moscow on behalf of the Lumière Brothers company, bearing with them the newly developed Lumière Cinématogaphe camera. Their purpose: to document the coronation of Tsar Nicholas II--the last Emperor of Russia, though no one would have known that at the time. The coronation was an extraordinary event, soon to be overshadowed by even more extraordinary events in the Revolutionary years to come. An enormous celebration followed, with gifts, bread, sausage, pretzels, beer, and a commemorative cup to revelers. The promise of these gifts led to what was later called the Khodynka Tragedy.

Technology is a tool that helps us live out our God-given callings. This is one of the most important things for us to learn as we engage the topic of technology and artificial intelligence. Because we often see the tremendous power that technology has over our lives, we are tempted to treat technology as more than a tool, as something with a value similar to our own if it is powerful enough or does enough work on its own. Technology will be misused and abused by broken people just like you and me. Nowhere in Scripture is a tool or a technology condemned for being evil.

Researchers from the University of Michigan (MI, USA) have developed a novel neuroprosthetic model involving muscle grafts with machine-learning algorithms, which allowed for ultra-precise movements in a prosthetic hand. This technology is considered to be a major advance in motor control for amputees and could significantly enhance quality of life for individuals with upper limb loss. Peripheral nerve interfaces control neuroprosthetics by registering nerve signals in the remaining limb and translating them into movements. This allows individuals who have lost limbs to intuitively control prosthetic replacements. However, one of the biggest challenges in mind-controlled prosthetics is establishing a strong and stable nerve signal to translate to the bionic limb that will allow for a range of precise and durable movements.

The global data visualisation market is growing by up to $900 million a year, and is expected to be worth over $9 billion by 2026, according to a statement from UK-based data visualisation provider Zegami. The statement outlines the results of analysing 360 Reports' research into the market. The statement claims this growth is fuelled by the huge proliferation in the amount of data being produced, the increased use of data visualisation in data analytics and business intelligence tools, and organisations looking to find ways to reduce their increased expenditure on data warehousing and storage costs. As well as the traditional use-case of providing insights that can aid in financial and business decision making, Data visualisation tools also have a role to play in compliance and meeting regulatory requirements. Zegami's statement claims that it will also be vital in the development of artificial intelligence, where machines and computers will increasingly make more decisions without human input.

In this article, we are going to discuss we difference between Artificial Intelligence, Machine Learning, and Deep Learning. Furthermore, we will address the question of why Deep Learning as a young emerging field is far superior to traditional Machine Learning. Artificial Intelligence, Machine Learning, and Deep Learning are popular buzzwords that everyone seems to use nowadays. But still, there is a big misconception among many people about the meaning of these terms. In the worst case, one may think that these terms describe the same thing -- which is simply false.

Deep-learning artificial intelligence is helping grapple with plenty of problems in the modern world. But it also has its part to play in helping solve some ancient problems as well -- such as assisting in the translation of 2,500-year-old clay tablet documents from Persia's Achaemenid Empire. These tablets, which were discovered in modern-day Iran in 1933, have been studied by scholars for decades. However, they've found the translation process for the tablets -- which number in the tens of thousands -- to be laborious and prone to errors. "We have initial experiments applying machine learning to identify which cuneiform symbols are present in images of a tablet," Sanjay Krishnan, assistant professor at the University of Chicago's Department of Computer Science, told Digital Trends.