Deep Learning (DL) based downscaling has become a popular tool in earth sciences recently. Increasingly, different DL approaches are being adopted to downscale coarser precipitation data and generate more accurate and reliable estimates at local (~few km or even smaller) scales. Despite several studies adopting dynamical or statistical downscaling of precipitation, the accuracy is limited by the availability of ground truth. A key challenge to gauge the accuracy of such methods is to compare the downscaled data to point-scale observations which are often unavailable at such small scales. In this work, we carry out the DL-based downscaling to estimate the local precipitation data from the India Meteorological Department (IMD), which was created by approximating the value from station location to a grid point. To test the efficacy of different DL approaches, we apply four different methods of downscaling and evaluate their performance. The considered approaches are (i) Deep Statistical Downscaling (DeepSD), augmented Convolutional Long Short Term Memory (ConvLSTM), fully convolutional network (U-NET), and Super-Resolution Generative Adversarial Network (SR-GAN). A custom VGG network, used in the SR-GAN, is developed in this work using precipitation data. The results indicate that SR-GAN is the best method for precipitation data downscaling. The downscaled data is validated with precipitation values at IMD station. This DL method offers a promising alternative to statistical downscaling.

As AI proliferates, countries and their legal systems are trying to catch up. AI regulation is emerging at industry level, city and county level, and at country and region level. The European Union AI Act could well serve as a template for AI regulation around the world. In this post, we describe three key things you should know about AI Regulation: Context - what is already around us, AI Act - the key elements of the upcoming EU legislation, and What all this is likely to mean to businesses and individuals. The AI Act is not the first piece of AI regulation.

Artificial intelligence (AI) is rapidly evolving and becoming ubiquitous across virtually every industry. AI solutions allow organizations to achieve operational efficiencies, gain insights into customer behavior, measure key performance indicators (KPIs), and leverage the power of big data, among other things. Similarly, the electric vehicles (EV) market has gained traction in recent years. It's more common to see drivers cruising in EVs, whether a Tesla, Chevy Bolt, or Nissan Leaf. EVs are becoming popular among eco-conscious consumers because they offer more eco-friendly benefits than traditional gas-powered vehicles.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A crewless robotic boat retracing the 1620 sea voyage of the Mayflower has landed near Plymouth Rock. The sleek Mayflower Autonomous Ship met with an escort boat as it approached the Massachusetts shoreline Thursday, more than 400 years after its namesake's historic journey from England. It was towed into Plymouth Harbor -- per U.S. Coast Guard rules for crewless vessels -- and docked near a replica of the original Mayflower that brought the Pilgrims to America.

Despite being released more than a decade ago, NASA's turbofan engine degradation simulation dataset (CMAPSS) remains popular and relevant today. In this series, I plan to demonstrate and explain multiple analysis techniques while providing a solution for more complex datasets. The Turbofan dataset has four datasets of increasing complexity. Engines start normally but develop a malfunction over time. For train sets, engines are run to fail, while on test sets the time series expires'a period' before they fail.

Stanford, CA, June 16, 2022: CARPL.ai, a technology platform that connects Artificial Intelligence (AI) applications... CARPL - the world's first testing and deployment platform for radiology automation has recently been... Accelerating model validation and clinical adoption of AI solutions built by Thomas Jefferson University using... CARPL is the world's first end-to-end platform for the development, testing and deployment of medical imaging AI Incubated at India's leading diagnostics provider, CARPL works with 40 HCPs, AI Developers and Med Tech Companies

The Israeli military is using AI-powered detection system that lets soldiers see through walls before attacking. Designed in part with Camero-Tech, Xaver 1000 uses algorithms to track targets behind an obstacle, which are then displayed on a screen fitted in the center of the device. Xaver 1000, which users place directly on the wall, produces such high resolution displays that users can determine if a person is sitting, standing or lying down. The system is also capable of providing measurements of targets and determining if the image is of an adult, child or animal, allowing soldiers or police officers to know what they are up against on the other side of the wall. The device is designed like a diamond with four flaps that open outward.

The Expedition 67 crew members tended to plants and explored artificial intelligence aboard the International Space Station today. The four astronauts and three cosmonauts also split their day configuring a U.S. airlock and investigating how microgravity affects the human body. NASA Flight Engineer Bob Hines worked in the Columbus laboratory module on Thursday afternoon processing radish seeds germinating for the XROOTS space botany study. The investigation uses soilless techniques, such as hydroponics and aeroponics, to nourish and grow plants for producing crops on a larger scale for future space missions. Hines also joined NASA Flight Engineers Kjell Lindgren and Jessica Watkins configuring the NanoRacks Bishop airlock for its first trash disposal task this weekend.

Recurrent neural networks have been shown to be effective architectures for many tasks in high energy physics, and thus have been widely adopted. Their use in low-latency environments has, however, been limited as a result of the difficulties of implementing recurrent architectures on field-programmable gate arrays (FPGAs). In this paper we present an implementation of two types of recurrent neural network layers -- long short-term memory and gated recurrent unit -- within the hls4ml framework. We demonstrate that our implementation is capable of producing effective designs for both small and large models, and can be customized to meet specific design requirements for inference latencies and FPGA resources. We show the performance and synthesized designs for multiple neural networks, many of which are trained specifically for jet identification tasks at the CERN Large Hadron Collider.

You might not notice it, but you've likely adopted artificial intelligence into your daily life. It can be as simple as personalizing your news feeds, searching for products on shopping sites or voice-to-text conversion on smartphones. It can also be applied to more sophisticated tasks like predicting court outcomes in cases involving employment law or used for robotic welding applications. The transformative power of AI is also an economic growth driver, which is why the Canadian government has given the green light to advancing the country's AI strategy. According to a recent announcement from Minister of Innovation, Science and Industry François-Philippe Champagne, more than $443 million in Budget 2021 is designated for the second phase of the pan-Canadian Artificial Intelligence Strategy.