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) …
TL;DR: A lifetime subscription to the language-learning app Mondly is on sale for £79, saving you 95% on list price. Learning used to be fun when we were kids, right? Just because we're adults now doesn't mean we can't learn new things, and it certainly doesn't mean we can't have fun doing it. It's definitely not too late to master a new language, and there are some pretty fun ways to do it as a fully-fledged adult. Mondly is a top-rated language learning app that uses state-of-the-art speech recognition software to listen to your words and give positive feedback only when you speak clearly and correctly.
Artificial Intelligence in healthcare is becoming more crucial with early detection of various diseases with better accuracy. Cancer is one the widespread deadly disease can be now detected through machine learning and AI-enabled automated machines. Breast cancer is most common among women worldwide. However, more than 90% of women diagnosed with breast cancer at the earliest stage survive their disease for at least 5 years compared to around 15% for women diagnosed with the most advanced stage of the disease, which is now possible with AI. Though, AI is already diagnosing the breast cancer but owing to accuracy, the reliability among the doctors was less.
Digital generated image of data. When it comes to AI, much of the attention has been on deep learning. This part of the AI world has seen great strides, such as with image recognition. But of course, there are other areas of AI that look promising, such as reinforcement learning. Keep in mind that cutting-edge companies like Google's DeepMind and OpenAI have already made breakthroughs with this approach.
Kennisnet Technology Compass 2019-2020, y que comienza así: Please note: This report is written from a Dutch perspective and with the Dutch educational system and its structure in mind. Please take this into account when reading this report. What will you find in this technology compass? If someone had told you 25 years ago – roughly at the time the internet started to rise – that in 2019, you would be swiping on your smartphone for multiple hours a day, and that thanks to the internet you'd know exactly what time your aunt in France was drinking her latte, or that teenagers could become drone pilots during their vocational studies, would you have believed that person? Probably not, as nobody can predict the future.
Private and public entities around the world, particularly in the health care and governance sectors, are developing and deploying a range of artificial intelligence (AI) systems in emergency response to COVID-19. Some of these systems work to track and predict its spread; others support medical response or help maintain social control. Indeed, AI systems can reduce strain on overwhelmed health care systems; help save lives by quickly diagnosing patients, and assessing health declines or progress; and limit the virus's spread. But there's a problem: The algorithms driving these systems are human creations, and as such, they are subject to biases that can deepen societal inequities and pose risks to businesses and society more broadly. In this article, we look at data on the pandemic, share two recent applications of AI, and suggest a number of ways nonprofit and business leaders can help ensure that they develop, manage, and use transformative AI equitably and responsibly.
In 1965, Intel co-founder Gordon Moore predicted that the number of transistors that could fit on a computer chip would grow exponentially -- and they did, doubling about every two years. For half a century, Moore's Law has endured: Computers have gotten smaller, faster, cheaper, and more efficient, enabling the rapid worldwide adoption of PCs, smartphones, high-speed internet, and more. This miniaturization trend has led to silicon chips today that have almost unimaginably small circuitry. Transistors, the tiny switches that implement computer microprocessors, are so small that 1,000 of them laid end-to-end are no wider than a human hair. And for a long time, the smaller the transistors were, the faster they could switch.
Robots are increasingly being deployed in retail environments. The reasons for this include: to relieve staff from the performance of repetitive and mundane tasks; to reallocate staff to more value-added, customer-facing activities; to realize operational improvements; and, to utilize real-time in-store generated data. Due to the impact of the 2020 Coronavirus outbreak, we can now add a new reason to use robots in retail: to assist with customer and employee safety. In this Research Article, the Retail Analytics Council at NWU presents information on the benefits associated with deploying robots in stores. Estimates of the size of the global retail robot market are advanced.
You know robotics has'made it' when Silicon Valley Bank (SVB) is reporting on it. Just five years ago, SVB barely had a hardware division, let alone a robotics and frontier tech team. This report itself shows the maturity of the field of robotics, and that's also one of the key takeaways. There may be fewer deals in robotics, but the deals are getting bigger, as consolidation in new robotics markets starts to happen. The number of industrial robots, a key component of Industry 4.0, is accelerating.
The response to protests against police brutality, ignited by the murder of Geoge Floyd, have been nothing short of draconian. While government forces on the ground gleefully beat protesters and passersby with batons and doused them with tear gas, the US Border Patrol has deployed Reaper drones to surveil citizens from the skies and the DEA has been tasked with tracking protesters. The outsized surveillance response displayed so far by the Feds has driven concerns from privacy advocates over the potential use of more insidious forms of snooping, from facial recognition algorithms to cell-site simulation (aka the Stingray and Crossbow systems.) People stuck in traffic are witnessing NYPD beat up folks on their way home. "All the technology we have been warning about for a while are starting to come to fruition in these protests," Dave Maass, a senior investigative researcher at digital rights group the Electronic Frontier Foundation, told Reuters on Monday.