Australia on Friday shrugged off Chinese anger over its decision to acquire US nuclear-powered submarines, while vowing to defend the rule of law in airspace and waters where Beijing has staked hotly contested claims. US President Joe Biden announced the new Australia-US-Britain defence alliance on Wednesday, extending US nuclear submarine technology to Australia as well as cyber defence, applied artificial intelligence and undersea capabilities. Beijing described the new alliance as an "extremely irresponsible" threat to regional stability, questioning Australia's commitment to nuclear non-proliferation and warning the Western allies that they risked "shooting themselves in the foot". China has its own "very substantive programme of nuclear submarine building", Australian Prime Minister Scott Morrison argued Friday in an interview with radio station 2GB. "They have every right to take decisions in their national interests for their defence arrangements and of course so does Australia and all other countries," he said.

Australia on Friday shrugged off Chinese anger over its decision to acquire US nuclear-powered submarines and vowed to defend the rule of law in airspace and waters where Beijing has staked multiple hotly contested claims. US President Joe Biden announced the new Australia-US-Britain defence alliance on Wednesday, extending US nuclear submarine technology to Australia as well as cyber defence, applied artificial intelligence and undersea capabilities. China's government described the alliance as an "extremely irresponsible" threat to regional stability, questioning Australia's commitment to nuclear non-proliferation and warning the Western allies that they risked "shooting themselves in the foot". China has its own "very substantive programme of nuclear submarine building", Australian Prime Minister Scott Morrison said Friday in an interview with radio station 2GB. "They have every right to take decisions in their national interests for their defence arrangements and of course so does Australia and all other countries," he said.

The United States announced a new alliance Wednesday with Australia and Britain to strengthen military capabilities in the face of growing rivalry with China, including a new Australian nuclear submarine fleet and cruise missiles. The announcement of the alliance -- made in a video meeting by President Joe Biden, Australian Prime Minister Scott Morrison and his British counterpart Boris Johnson -- is sure to raise hackles in Beijing. It also met with swift pushback from France, which has been negotiating a multi-billion-dollar sale of conventional submarines to Australia. Biden said the work to enable Australia to build nuclear-powered submarines would ensure that they had "the most modern capabilities we need to maneuver and defend against rapidly evolving threats." The submarines, stressed Biden and the other leaders, will not be nuclear armed, only powered with nuclear reactors.

Echo-sounder data registered by buoys attached to drifting FADs provide a very valuable source of information on populations of tuna and their behaviour. This value increases when these data are supplemented with oceanographic data coming from CMEMS. We use these sources to develop Tuna-AI, a Machine Learning model aimed at predicting tuna biomass under a given buoy, which uses a 3-day window of echo-sounder data to capture the daily spatio-temporal patterns characteristic of tuna schools. As the supervised signal for training, we employ more than 5000 set events with their corresponding tuna catch reported by the AGAC tuna purse seine fleet.

The multivariate time series forecasting has attracted more and more attention because of its vital role in different fields in the real world, such as finance, traffic, and weather. In recent years, many research efforts have been proposed for forecasting multivariate time series. Although some previous work considers the interdependencies among different variables in the same timestamp, existing work overlooks the inter-connections between different variables at different time stamps. In this paper, we propose a simple yet efficient instance-wise graph-based framework to utilize the inter-dependencies of different variables at different time stamps for multivariate time series forecasting. The key idea of our framework is aggregating information from the historical time series of different variables to the current time series that we need to forecast. We conduct experiments on the Traffic, Electricity, and Exchange-Rate multivariate time series datasets. The results show that our proposed model outperforms the state-of-the-art baseline methods.

Much of the U.S. artificial intelligence (AI) discussion revolves around futuristic dreams of both utopia and dystopia. However, it bears remembering that AI is also becoming a real-world economic fact with major implications for national and regional economic development as the U.S. crawls out of the COVID-19 pandemic. Based on advanced uses of statistics, algorithms, and fast computer processing, AI has become a focal point of U.S. innovation debates. Even more, AI is increasingly viewed as the next great "general purpose technology"--one that has the power to boost the productivity of sector after sector of the economy. All of which is why state and city leaders are increasingly assessing AI for its potential to spur economic growth.

An IBM researcher holds a silicon wafer with embedded IBM Telum chips designed to maximize artificial intelligence capabilities. The chips were developed at Albany Nanotech and made in partnership with Samsung. The Albany area was recent cited by the Brookings Institution for having the potential to create an AI sector. ALBANY -- The Capital Region is one of 87 "potential adoption centers" in the United States for companies and researchers focused on the use of artificial intelligence, or AI, according to a new report from the Brookings Institution, a left-leaning think tank. The San Francisco Bay area is No. 1 in AI, while other upstate cities, Buffalo, Rochester and Syracuse, were also listed as potential adoption centers.

Deepcell, a life science company pioneering AI-powered cell classification and isolation for cell biology and translational research, today announced the appointment of Kevin Jacobs as the Vice President of Bioinformatics. Jacobs will be responsible for the company's bioinformatics strategy, implementation and its integration with other areas and into the company's offerings. This appointment is the latest addition to Deepcell's rapidly expanding team of scientists, engineers and computer science experts. Deepcell had acquired $20 million in Series A funding last year. Currently, Deepcell is helping to advance precision medicine by combining advances in AI, cell classification and capture, and single-cell analysis to deliver novel insights through an unprecedented view of cell biology.

A new study warns that the American AI industry is highly concentrated in the San Francisco Bay Area and that this could prove to be a weakness in the long run. The Bay leads all other regions of the country in AI research and investment activity, accounting for about one-quarter of AI conference papers, patents, and companies in the US. Bay Area metro areas see levels of AI activity four times higher than other top cities for AI development. "When you have a high percentage of all AI activity in Bay Area metros, you may be overconcentrating, losing diversity, and getting groupthink in the algorithmic economy. It locks in a winner-take-most dimension to this sector, and that's where we hope that federal policy will begin to invest in new and different AI clusters in new and different places to provide a balance or counter," Mark Muro, policy director at the Brookings Institution and the study's coauthor, told WIRED.

Sooner or later, the concept of digitization will completely take over all repetitive tasks. Today, with the help of big data, advanced technologies like automation, artificial intelligence, IoT, and machine learning are leveraging unimaginable amounts and types of information to work from. It is streamlining tedious, repetitive, and difficult tasks, which tend to slow down production and also increases the cost of operation. Owing to the evolution of technology, artificial intelligence startups are mushrooming like never before. The companies are driving the world into a new phase of digitization with a mixture of disruptive statistical methods, computational intelligence, soft computing, and traditional symbolic AI. Artificial intelligence is the combination of two amazing concepts namely science and engineering. With the infusion of disruptive trends and human intelligence, intelligent machines and intelligent computing programs are emerging. Slowly, the flare of innovations moved away from IT and entered into diverse industries including healthcare, education, finance, marketing, business, telecommunication, etc. Organizations realized that by digitizing repetitive tasks, an enterprise can cut the cost of paperwork and labor which further eliminates human error, thus boosting efficiency. Automating processes involve employing artificial intelligence solutions that can support digitization and deliver data-driven insights. Artificial intelligence startups emerge as a ready-made solution provider that supports every company's individual needs. AI startups in 2021 use big data to sophisticated AI models and leverage new solutions that could better serve customers. Analytics Insight has listed the top 100 artificial intelligence startups that are driving the next-generation development in technology. It democratizes the way investments are done by bringing sophisticated elite trading technology to laymen. Accrad is a health tech company that assists radiologists to reduce their workload with the precision of artificial intelligence. Radiologists work under different circumstances and deadlines and might find diagnosis through x-rays a bit difficult. Therefore, Accrad has come up with a futuristic solution to help with accurate and fast image diagnosis. The company has made x-ray processing more convincing and simpler. Its signature product CheXRad, a deep learning algorithm that identifies locations in the chest radiograph has the capability to predict 15 different diseases including Covid-19. Affable.ai is a data-driven influencer marketing platform where customers can find relevant and authentic influencers and manage marketing operations. By using cutting-edge computer vision algorithms on social media posts, the company delivers actionable insights about micro-influencers and their audience. Similar to how Google has sophisticated its search and promote relative ads to users, Affable.ai has also built one-click marketing at a shorter scale.