If you're tackling a degree in science, technology, engineering, or mathematics, there's nothing more frustrating than a machine that can't keep up with the apps you need for your coursework. Here's where a powerful gaming laptop proves its mettle. With GPU acceleration, your machine delivers super-fast image processing, real-time rendering for complex component designs, and it lets you work quickly and efficiently. For engineering students, this means more interactive, real-time rendering for 3D design and modeling, plus faster solutions and visualization for mechanical, structural, and electrical simulations. For computer science, data science, and economics students, NVIDIA's GeForce RTX 30 Series laptops enable faster data analytics for processing large data sets -- all with efficient training for deep learning and traditional machine learning models for computer vision, natural language processing, and tabular data.
The world's first high-resolution 3D image of a monkey brain has been revealed, in a breakthrough that could pave the way for treatments for human diseases including Parkinson's. A detailed map of a complete macaque monkey brain was created using fluorescent imaging techniques by a team from the Chinese Academy of Sciences in Beijing. The team used a new technique to show how nerve cells are organised and connected within the monkey brain at a'micron resolution'. The human brain comprises nearly a hundred billion nerve cells with delicate and complex connections, and while up to 17 times larger than that of a macaque, it is similar enough for comparisons to be made between the two, researchers claim. Until now, a mouse brain was the largest to be mapped, taking days to create a complete 3D image, but the new technique made it possible to move up to a macaque brain, which is about 200 times larger in volume than that of a mouse.
A reverse image search is a technique that allows finding things, people, brands, etc. using a photo. While performing a regular search you usually type a word or phrase that is related to the information you are trying to find; when you do a reverse image search, you upload a picture to a search engine. In the results of regular searches, you receive a list of websites that are connected to these phrases. When you perform a reverse image search, in the results you receive photos of similar things, people, etc, linked to websites about them. Reverse search by image is the best solution to use when looking for similar images, smaller/bigger versions of them, or twin content.
You are free to share this article under the Attribution 4.0 International license. New biomarkers in the eyes could help manage diabetic retinopathy, and perhaps even diabetes, according to new research. During its early stages, diabetes can affect the eyes before the changes are detectable with a regular clinical examination. New research shows these changes can be measured earlier than previously thought with specialized optical techniques and computer analysis. The ability to detect biomarkers for this sight-threatening condition may lead to the early identification of people at risk for diabetes or visual impairment, as well as improve physicians' ability to manage these patients.
Griffith University researchers have developed an AI video surveillance system to detect social distancing breaches in an airport without compromising privacy. By keeping image processing gated to a local network of cameras, the team bypassed the traditional need to store sensitive data on a central system. Professor Dian Tjondronegoro from Griffith Business School says data privacy is one of the biggest concerns with this technology because the system has to constantly observe people's activities to be effective. "These adjustments are added to the central decision-making model to improve accuracy." Published in Information, Technology & People, the case study was completed at Gold Coast Airport which, pre-COVID-19 had 6.5 million passengers annually with 17,000 passengers on-site daily.
In this decade, companies across the globe have embraced the potential of artificial intelligence for digital transformation and enhanced customer experience. One important application of AI is enabling companies to use the pools of data available with them for smart business use. BMW is one of the world's leading manufacturers of premium automobiles and mobility services. BMW uses artificial intelligence in critical areas like production, research and development, and customer service. BMW also runs a project dedicated to this technology called Project AI, for efficient use of artificial intelligence.
AI in medicine, particular in pediatric medicine holds much promise in taking scarce human expertise and making it available throughout rural America and to the rest of the world. Rwanda has one pediatric cardiologist in the country. In 2015, when neural network technology succeeded in building computer algorithms which were better than humans at image recognition signaled the beginning of this renaissance in AI. But, as the above chart courtesy of Jeff Dean, head of Google Brain shows, the only way to get increasing degrees of accuracy is to have more and more data. Any of you in major metro areas will see Waymo vans driving around collecting more and more data to feed autonomous driving software development.
The power of deepfake tech to hone digital effects into incredibly realistic video can't be underestimated. We've seen a top-level Tom Cruise impersonator transformed with a high-level deepfake artist, and now companies -- and film studios -- are taking notice. Luke Skywalker's CGI face in The Mandalorian was met with a lot of criticism, and one fan's efforts to improve it resulted in a new job. Lucasfilm has hired YouTuber Shamook to ensure future projects won't have wobbly representations of actors that are either much older or perhaps even deceased now. The latter, however, remains an ethical conundrum in itself, as demonstrated by the recent Anthony Bourdain documentary.
Technology and Technological developments in this decade have led to some of the most awe-inspiring discoveries. With rapidly changing technology and systems to support them and provide back-end processing power, the world seems to be becoming a better place to live day by day. Technology has reached such new heights that nothing our ingenious mind today thinks about looks impossible to accomplish. The driving factor of such advancements in this new era of technological and computational superiority seems to be wrapped around two of the most highly debated domains and topics, namely Machine Learning & Artificial Intelligence. The canvas and ideal space that these two domains provide are unfathomable.
In the nine years since AlexNet spawned the age of deep learning, artificial intelligence (AI) has made significant technological progress in medical imaging, with more than 80 deep-learning algorithms approved by the U.S. FDA since 2012 for clinical applications in image detection and measurement. A 2020 survey found that more than 82% of imaging providers believe AI will improve diagnostic imaging over the next 10 years and the market for AI in medical imaging is expected to grow 10-fold in the same period. Despite this optimistic outlook, AI still falls short of widespread clinical adoption in radiology. A 2020 survey by the American College of Radiology (ACR) revealed that only about a third of radiologists use AI, mostly to enhance image detection and interpretation; of the two thirds who did not use AI, the majority said they saw no benefit to it. In fact, most radiologists would say that AI has not transformed image reading or improved their practices.