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How to trick deep learning algorithms into doing new things

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This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence. Two things often mentioned with deep learning are "data" and "compute resources." You need a lot of both when developing, training, and testing deep learning models. When developers don't have a lot of training samples or access to very powerful servers, they use transfer learning to finetune a pre-trained deep learning model for a new task. At this year's ICML conference, scientists at IBM Research and Taiwan's National Tsing Hua University Research introduced "black-box adversarial reprogramming" (BAR), an alternative repurposing technique that turns a supposed weakness of deep neural networks into a strength.


Using Artificial Intelligence Authentically and Ethically

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Heather Chmura '16 launched her career at the age of 14 as the youngest franchise owner of a Wetzel's Pretzels in Las Vegas, managing more than 50 employees. Busy with her business, she went to high school online. But she decided to attend college in person. After searching for a small school with overseas programs and a good religious studies department, she joined her sister, Becky Chmura '14, at Westmont. She majored in economics and business, participated in the Westmont in Northern Europe semester, took Emmaus Road trips to Japan, South Korea and Taiwan and studied Business at the Bottom of the Pyramid with professor Rick Ifland to help establish microfinance businesses in Haiti.


Machine-learning tool could help develop tougher materials

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For engineers developing new materials or protective coatings, there are billions of different possibilities to sort through. Lab tests or even detailed computer simulations to determine their exact properties, such as toughness, can take hours, days, or more for each variation. Now, a new artificial intelligence-based approach developed at MIT could reduce that to a matter of milliseconds, making it practical to screen vast arrays of candidate materials. The system, which MIT researchers hope could be used to develop stronger protective coatings or structural materials -- for example, to protect aircraft or spacecraft from impacts -- is described in a paper in the journal Matter, by MIT postdoc Chi-Hua Yu, civil and environmental engineering professor and department head Markus J. Buehler, and Yu-Chuan Hsu at the National Taiwan University. The focus of this work was on predicting the way a material would break or fracture, by analyzing the propagation of cracks through the material's molecular structure.


Tesla Model 3 'on Autopilot mode' crashes into truck in Taiwan

Daily Mail - Science & tech

Security cameras watching a highway in Taiwan captured the moment a white Tesla Model 3 vehicle plowing into truck that was rolled over on its side. Reports say the driver of the Tesla did not see the overturned Truck while cruising with the Autopilot driver assistant feature activated. The footage also shows that the car's emergency automatic braking system was applied at the last second, due to smoke coming from the tires moments before the collision. An image of the aftermath shows the entire front-end of the Tesla pierced through the roof of the truck, but reports note that neither of the drivers were injured. Tesla's Autopilot features allow the vehicle to steer, accelerate and brake automatically within a lane.


IIT-Ropar and TSW Launch a PG Programme in Artificial Intelligence

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IIT-Ropar, one of the eight new IITs established by the Ministry of Human Resource Development (MHRD), Government of India, and TSW, the executive education division of Times Professional Learning (a part of The Times of India Group), have launched a Post Graduate Certificate Programme in Artificial Intelligence & Deep Learning. The programme will be coordinated by The Indo-Taiwan Joint Research Centre (ITJRC) on Artificial Intelligence (AI) and Machine Learning (ML), at IIT-Ropar. Supported by the Ministry of Science and Technology, Taiwan, ITJRC is a bilateral centre for collaborative research in disruptive technologies like AI and ML. The programme, with its focus on Artificial Intelligence and Deep Learning, has an eligibility criterion of a minimum of 2 years of work experience in the IT industry. Though an engineering degree is a desirable prerequisite for this programme, one does not need a coding or mathematics background to be eligible.


IIT-Ropar and TSW Launch a PG Programme in Artificial Intelligence

#artificialintelligence

IIT-Ropar, one of the eight new IITs established by the Ministry of Human Resource Development (MHRD), Government of India, and TSW, the executive education division of Times Professional Learning (a part of The Times of India Group), have launched a Post Graduate Certificate Programme in Artificial Intelligence & Deep Learning. The programme will be coordinated by The Indo-Taiwan Joint Research Centre (ITJRC) on Artificial Intelligence (AI) and Machine Learning (ML), at IIT-Ropar. Supported by the Ministry of Science and Technology, Taiwan, ITJRC is a bilateral centre for collaborative research in disruptive technologies like AI and ML. The programme, with its focus on Artificial Intelligence and Deep Learning, has an eligibility criterion of a minimum of 2 years of work experience in the IT industry. Though an engineering degree is a desirable prerequisite for this programme, one does not need a coding or mathematics background to be eligible.


Stanley Chen posted on LinkedIn

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We are living in a age of information technology really advanced,how to making use of these advantagement of artificial intelligence technology to solute our human being the vital problems of both aging society and lower birth rates. Above those problems also happened in Japan,Taiwan and USA. If we don't arrange solutions these two things that will be dangerous for our national security guard and society healthcare. According to researching results artificial intelligence can do 1.detecting lung,skin cancers 2.analysing eye scans,X-ray 3.developing researching drug.


Machine-learning tool could help develop tougher materials

#artificialintelligence

For engineers developing new materials or protective coatings, there are billions of different possibilities to sort through. Lab tests or even detailed computer simulations to determine their exact properties, such as toughness, can take hours, days, or more for each variation. Now, a new artificial intelligence-based approach developed at MIT could reduce that to a matter of milliseconds, making it practical to screen vast arrays of candidate materials. The system, which MIT researchers hope could be used to develop stronger protective coatings or structural materials -- for example, to protect aircraft or spacecraft from impacts -- is described in a paper in the journal Matter, by MIT postdoc Chi-Hua Yu, civil and environmental engineering professor and department head Markus J. Buehler, and Yu-Chuan Hsu at the National Taiwan University. The focus of this work was on predicting the way a material would break or fracture, by analyzing the propagation of cracks through the material's molecular structure.


For This High-Yield Stock, 5G and Artificial Intelligence Outweigh Coronavirus

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The technology sector is in an interesting place today. On the one hand, technology has historically tended to be cyclical, with technology demand fluctuating with GDP growth. On the other hand, technology is achieving more extraordinary feats by the day, and is helping to solve a lot of the problems caused by coronavirus. That may actually lead to a surge in demand for some tech products and services due to the stay-at-home economy. These cross-currents came into focus in the first quarter earnings release of technology bell-weather Taiwan Semiconductor Manufacturing (NYSE: TSM).


For This High-Yield Stock, 5G and Artificial Intelligence Outweigh Coronavirus The Motley Fool

#artificialintelligence

The technology sector is in an interesting place today. On the one hand, technology has historically tended to be cyclical, with technology demand fluctuating with GDP growth. On the other hand, technology is achieving more extraordinary feats by the day, and is helping to solve a lot of the problems caused by coronavirus. That may actually lead to a surge in demand for some tech products and services due to the stay-at-home economy. These cross-currents came into focus in the first quarter earnings release of technology bell-weather Taiwan Semiconductor Manufacturing (NYSE:TSM).