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Artificial intelligence technique in detection of early esophageal cancer

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Esophageal cancer (EC) is the eighth most common cancer and the sixth leading cause of cancer death worldwide[1]. EC mainly consists of esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC). EAC is the most common pathological type in Western countries, more than 40% of patients with EAC are diagnosed after the disease has metastasized, and the 5-year survival rate is less than 20%[2,3]. Although the incidence of EAC has been increasing globally, ESCC remains the most common pathological type (80%) of all ECs with the highest incidence across a'cancer belt' extending from East Africa and across the Middle East to Asia. Only 20% of patients with ESCC survive longer than 3 years, primarily due to late-stage diagnosis[4].


The Case for Transparent AI

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I can trace it back to when I watched a video of America's Got Talent. It started with singers, but soon it moved on to other categories, including illusionists. That was enough to tell Facebook's algorithms that I had to be interested in magic and that it should show me more of what it deduced I wanted to see. Now I have to be careful, because if I click on any of that content, it will reinforce the algorithm's notion that I must really be interested in card tricks, and pretty soon that's all Facebook will ever show me. Even if it was all just a passing curiosity.


OpenAI's CLIP is the most important advancement in computer vision this year

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CLIP is a gigantic leap forward, bringing many of the recent developments from the realm of natural language processing into the mainstream of computer vision: unsupervised learning, transformers, and multimodality to name a few. The burst of innovation it has inspired shows its versatility. And this is likely just the beginning. There has been scuttlebutt recently about the coming age of "foundation models" in artificial intelligence that will underpin the state of the art across many different problems in AI; I think CLIP is going to turn out to be the bedrock model for computer vision. In this post, we aim to catalog the continually expanding use-cases for CLIP; we will update it periodically.


7 Online Video Editing Tools that use Artificial Intelligence

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The latest AI-powered cameras are clicking high-end pictures and help in face recognition in pictures and videos. In addition, the same application has found benefits in ease of video editing. From scanning text scripts to recognizing faces on videos, it can match the elements and automate the video editing task. If you have to do this daily, it is better to choose software that is artificial intelligence or AI-powered. The list below would help you go for the right one and make the most of it for editing purposes.


Top 12 High-Growth Artificial Intelligence Stocks

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AI is a large, complex universe covering many industries and technology megatrends. Here are 12 high-growth stocks that harness the power of artificial intelligence.


AI Analyzes Facial Expressions in Videos to Help Detect Parkinson's

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An artificial intelligence (AI) tool was able to distinguish, with great accuracy, Parkinson's patients from healthy peers by analyzing short videos of facial expressions, particularly smiles, a small study shows. The predictive accuracy of the new tool was comparable to that of video analysis that uses motor tasks to detect Parkinson's, pinpointing facial expressions as a potential digital, diagnostic biomarker of the disease. This type of biomarker could allow remote diagnosis without the need for personal interaction and extensive testing. This would be particularly relevant in situations such as a pandemic, in cases of reduced mobility, or in underdeveloped countries where few neurologists exist but most people have access to a phone with a camera, researchers noted. The study, "Facial expressions can detect Parkinson's disease: preliminary evidence from videos collected online," was published as a brief communication in the journal npj Digital Medicine.


Hacked Tesla FSD Beta demo from Ukraine validates Elon Musk's Autopilot vision

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Tesla's approach to full self-driving is different from that of autonomous "leaders" like Waymo and Cruise. Instead of relying on an army of sensors like LiDAR and high-definition maps, Tesla is practically betting its future on a vision artificial intelligence approach. The idea is simple: if humans could effectively drive with their eyes and brain, then cars should also be able to navigate safely with a suite of cameras and a trained neural network. This approach has caused a lot of controversy and criticism against Tesla and its FSD strategy. A yearly report from Guidehouse Insights, for example, consistently ranks Tesla dead last among companies currently working on autonomous driving technologies.


Machine Learning for designers and visual artists -- cunicode / Digital Craftsmanship

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Deep Fakes - Deep Fakes is an artificial intelligence-based human image synthesis technique. It is used to combine and superimpose existing images and videos onto source images or videos.


World of Modern Robotics – Galactik Views

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Robotics have acquired the centerstage of Industrial activity and are making a way into day-to-day life. They are performing various impossible tasks in deep space, oceans, defence applications, working in radioactive environment, extreme temperature furnace, and many other areas, where human presence is challenging. In healthcare, robotics has applications in performing critical surgeries, in financial world, major financial institutions across the world are resorting to robotics-based process automation. Humanity has been long fascinated by the concept of robots and artificial intelligence. It has been a collective pipedream to automate mundane tasks which one would prefer to not have to do themselves.


How AI in Video Will Enhance Work in the Modern-Day Work Environment - ReadWrite

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Shaking off the dust from what could be described as the longest year known to man -- remote work is a hot topic in the world of employment. By establishing both its benefits, as well as its challenges, remote work has people talking about its permanence. What is more, employees have become accustomed to remote working, in fact, many of them actually prefer it to the office. According to a FlexJobs survey, 65% of employee respondents reported wanting to be full-time remote post-pandemic, and 31% want a hybrid remote work environment -- that's 96% who desire some form of remote work. These numbers inevitably mean that the methods in which we worked during the pandemic, primarily via the screen and through video calls, will have some longevity.