Chip designer Nvidia said that US officials told it to stop exporting two top computing chips for artificial intelligence work to China, a move that could cripple Chinese firms' ability to carry out advanced work like image recognition. The company on Wednesday said the ban, which affects its A100 and H100 chips designed to speed up machine learning tasks, could interfere with completion of developing the H100, the flagship chip Nvidia announced this year. Nvidia said US officials told it the new rule "will address the risk that the covered products may be used in, or diverted to, a'military end use' or'military end user' in China." Asked for comment, the US department of Commerce would not say what new criteria it has laid out for AI chips that can no longer be shipped to China but said it is reviewing its China-related policies and practices "keep advanced technologies out of the wrong hands. "While we are not in a position to outline specific policy changes at this time, we are taking a comprehensive approach to implement additional actions necessary related to technologies, end-uses, and end-users to protect US national security and foreign policy interests," a spokesperson told Reuters.

AI software has detected more than 20,000 secret private swimming pools in aerial photography, helping French tax officials bag about €10 million (£ 8.6 million) in extra property levies. Home improvements, such as the addition of a loft or a pool, can boost the value of a property and increase the taxes homeowners pay in the Euro nation. A 30-square-metre pool, for example, could set you back an extra €200 (£170) a year. People are required to declare these kinds of constructions, though some keep quiet to avoid having to fork out more money. In a bid to catch tax dodgers out, nine departments working under France's tax office tested out machine-learning software to automatically find undeclared swimming pools from overhead photos.

Team's algorithm could lead to pivotal discovery of new materials for solar cells. It will be doing so for billions more years. Yet, we have only just begun tapping into that abundant, renewable source of energy at affordable cost. Solar absorbers are a material used to convert this energy into heat or electricity. Maria Chan, a scientist in the U.S. Department of Energy's (DOE) Argonne National Laboratory, has developed a machine learning method for screening many thousands of compounds as solar absorbers.

Artificial Intelligence promises an exciting future and tremendous growth, provided that legal professionals able to navigate their business in this novel environment. Many companies make massive investments in artificial intelligence (AI), and more and more AI products and technologies are being launched by companies that are not traditional software companies. This signals a transition where traditional engineering companies invest in software capabilities and position AI as a critical way to disrupt their markets and gain market share. That transition does not come without challenges for legal teams. Lawyers need to keep abreast of new and fast-evolving technologies and familiarise themselves with novel technical concepts like "machine learning" or "black box AI".

Chip designer Nvidia on Wednesday said that U.S. officials told it to stop exporting two top computing chips for artificial intelligence work to China, a move that could cripple Chinese firms' ability to carry out advanced work like image recognition and hamper a business that Nvidia expects to generate $400 million in sales this quarter. Nvidia shares fell 4% after hours. The company said the ban, which affects its A100 and H100 chips designed to speed up machine learning tasks, could interfere with completion of developing the H100, the flagship chip Nvidia announced this year. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites.

Using aerial photos and artificial intelligence, French tax officials have reportedly identified more than 20,000 previously untaxed residential swimming pools--potentially netting the French government a windfall of more than 10 million euros ($10 million). And that total likely represents only a fraction of the cheese-eating tax cheats out there. According to The New York Times, the photo-scanning A.I. tool developed in tandem by a French IT firm and Google has been deployed so far in just nine of the county's 96 administrative districts. But it has been so successful that French officials are planning a national effort in the coming months. Swimming pools matter because the French property tax system is based on the theoretical rental value of a home and its surrounding lands.

Chip designer Nvidia Corp on Wednesday said that U.S. officials told it to stop exporting two top computing chips for artificial intelligence work to China, a move that could cripple Chinese firms' ability to carry out advanced work like image recognition and hamper a business Nvidia expects to generate $400 million in sales this quarter. Nvidia shares fell 4% after hours. The company said the ban, which affects its A100 and H100 chips designed to speed up machine learning tasks, could interfere with completion of developing the H100, the flagship chip Nvidia announced this year. Shares of Nvidia rival Advanced Micro Devices were down 2% after hours. An AMD spokesman told Reuters it had received new license requirements that will stop its MI250 artificial intelligence chips from being exported to China but it believes its MI100 chips will not be affected.

In this work, we propose a framework for energy-efficient trajectory design of an unmanned aerial vehicle (UAV)-based portable access point (PAP) deployed to serve a set of ground nodes (GNs). In addition to the PAP and GNs, the system consists of a set of intelligent reflecting surfaces (IRSs) mounted on man-made structures to increase the number of bits transmitted per Joule of energy consumed measured as the global energy efficiency (GEE). The GEE trajectory for the PAP is designed by considering the UAV propulsion energy consumption and the Peukert effect of the PAP battery, which represents an accurate battery discharge profile as a non-linear function of the UAV power consumption profile. The GEE trajectory design problem is solved in two phases: in the first, a path for the PAP and feasible positions for the IRS modules are found using a multi-tier circle packing method, and the required IRS phase shift values are calculated using an alternate optimization method that considers the interdependence between the amplitude and phase responses of an IRS element; in the second phase, the PAP flying velocity and user scheduling are calculated using a novel multilap trajectory design algorithm. Numerical evaluations show that: neglecting the Peukert effect overestimates the available flight time of the PAP; after a certain threshold, increasing the battery size reduces the available flight time of the PAP; the presence of IRS modules improves the GEE of the system compared to other baseline scenarios; the multi-lap trajectory saves more energy compared to a single-lap trajectory developed using a combination of sequential convex programming and Dinkelbach algorithm.

The open domain knowledge base is very important. It is usually extracted from encyclopedia websites and is widely used in knowledge retrieval systems, question answering systems, or recommendation systems. In practice, the key challenge is to maintain an up-to-date knowledge base. Different from Unwieldy fetching all of the data from the encyclopedia dumps, to enlarge the freshness of the knowledge base as big as possible while avoiding invalid fetching, the current knowledge base updating methods usually determine whether entities need to be updated by building a prediction model. However, these methods can only be defined in some specific fields and the result turns out to be obvious bias, due to the problem of data source and data structure. The users' query intentions are often diverse as to the open domain knowledge, so we construct a topic-aware graph network for knowledge updating based on the user query log. Our methods can be summarized as follow: 1. Extract entities through the user's log and select them as seeds 2. Scrape the attributes of seed entities in the encyclopedia website, and self-supervised construct the entity attribute graph for each entity. 3. Use the entity attribute graph to train the GNN entity update model to determine whether the entity needs to be synchronized. 4.Use the encyclopedia knowledge to match and update the filtered entity with the entity in the knowledge base according to the minimum edit times algorithm.

Autonomous driving is a key technology towards a brighter, more sustainable future. To enable such a future, it is necessary to utilize autonomous vehicles in shared mobility models. However, to evaluate, whether two or more route requests have the potential for a shared ride, is a compute-intensive task, if done by rerouting. In this work, we propose the Dynamic Longest Common Subsequences algorithm for fast and cost-efficient comparison of two routes for their compatibility, dynamically only incorporating parts of the routes which are suited for a shared trip. Based on this, one can also estimate, how many autonomous vehicles might be necessary to fulfill the local mobility demands. This can help providers to estimate the necessary fleet sizes, policymakers to better understand mobility patterns and cities to scale necessary infrastructure.