We consider a setting in which $N$ agents aim to speedup a common Stochastic Approximation (SA) problem by acting in parallel and communicating with a central server. We assume that the up-link transmissions to the server are subject to asynchronous and potentially unbounded time-varying delays. To mitigate the effect of delays and stragglers while reaping the benefits of distributed computation, we propose \texttt{DASA}, a Delay-Adaptive algorithm for multi-agent Stochastic Approximation. We provide a finite-time analysis of \texttt{DASA} assuming that the agents' stochastic observation processes are independent Markov chains. Significantly advancing existing results, \texttt{DASA} is the first algorithm whose convergence rate depends only on the mixing time $\tau_{mix}$ and on the average delay $\tau_{avg}$ while jointly achieving an $N$-fold convergence speedup under Markovian sampling. Our work is relevant for various SA applications, including multi-agent and distributed temporal difference (TD) learning, Q-learning and stochastic optimization with correlated data.

Data augmentation is vital to the generalization ability and robustness of deep neural networks (DNNs) models. Existing augmentation methods for speaker verification manipulate the raw signal, which are time-consuming and the augmented samples lack diversity. In this paper, we present a novel difficulty-aware semantic augmentation (DASA) approach for speaker verification, which can generate diversified training samples in speaker embedding space with negligible extra computing cost. Firstly, we augment training samples by perturbing speaker embeddings along semantic directions, which are obtained from speaker-wise covariance matrices. Secondly, accurate covariance matrices are estimated from robust speaker embeddings during training, so we introduce difficultyaware additive margin softmax (DAAM-Softmax) to obtain optimal speaker embeddings. Finally, we assume the number of augmented samples goes to infinity and derive a closed-form upper bound of the expected loss with DASA, which achieves compatibility and efficiency. Extensive experiments demonstrate the proposed approach can achieve a remarkable performance improvement. The best result achieves a 14.6% relative reduction in EER metric on CN-Celeb evaluation set.

As social media is increasingly being used as people's primary source for news online, there is a rising threat from the spread of malign and false information. With an absence of human editors in news feeds and a growth of artificial online activity, it has become easier for various actors to manipulate the news that people consume. Finding an effective way to detect malign information online is an important part of addressing this issue. RAND Europe was commissioned by the UK Ministry of Defence's (MOD) Defence and Security Accelerator (DASA) to develop a method for detecting the malign use of information online. The study was contracted as part of DASA's efforts to help the UK MOD develop its behavioural analytics capability.

With an aim to help warship crews make quick decisions and process data efficiently, the U.K.'s Ministry of Defense recently announced contracts to use AI-based (artificial intelligence) technology in warships. According to a source, Defense and Security Accelerator (DASA) will be funding £1 million (around US$1.3 million) for AI contracts as part of its "Intelligent Ship – The Next Generation" competition, which is aimed at using innovative approaches for Human-AI and AI-AI teaming for various defense platforms like warships, aircraft, and land vehicles. James Heappey, U.K.'s Defense Minister, said, "The astonishing pace at which global threats are evolving requires new approaches and fresh thinking to the way we develop our ideas and technology. The funding will research pioneering projects into how AI and automation can support our armed forces in their essential day-to-day work." DASA's warship competition, in alliance with the Defense Science and Technology Laboratory (Dstl), is intended to enhance the designs of future defense platforms by using advances in automation, autonomy, machine learning, and AI.

With an aim to help warship crews make quick decisions and process data efficiently, the U.K.'s Ministry of Defense recently announced contracts to use AI-based (artificial intelligence) technology in warships. According to a source, Defense and Security Accelerator (DASA) will be funding £1 million (around US$1.3 million) for AI contracts as part of its "Intelligent Ship – The Next Generation" competition, which is aimed at using innovative approaches for Human-AI and AI-AI teaming for various defense platforms like warships, aircraft, and land vehicles. James Heappey, U.K.'s Defense Minister, said, "The astonishing pace at which global threats are evolving requires new approaches and fresh thinking to the way we develop our ideas and technology. The funding will research pioneering projects into how AI and automation can support our armed forces in their essential day-to-day work." DASA's warship competition, in alliance with the Defense Science and Technology Laboratory (Dstl), is intended to enhance the designs of future defense platforms by using advances in automation, autonomy, machine learning, and AI.

Yes, companies use AI to automate various tasks, while consumers use AI to make their daily routines easier. But governments–and in particular militaries–also have a massive interest in the speed and scale offered by AI. Nation states are already using artificial intelligence to monitor their own citizens, and as the U.K.'s Ministry of Defence (MoD) revealed last week, they'll also be using AI to make decisions related to national security and warfare. The MoD's Defence and Security Accelerator (DASA) has announced the initial injection of £4 million in funding for new projects and startups exploring how to use AI in the context of the British Navy. In particular, the DASA is looking to support AI- and machine learning-based technology that will "revolutionise the way warships make decisions and process thousands of strands of intelligence and data."

Yes, companies use AI to automate various tasks, while consumers use AI to make their daily routines easier. But governments–and in particular militaries–also have a massive interest in the speed and scale offered by AI. Nation states are already using artificial intelligence to monitor their own citizens, and as the UK's Ministry of Defence (MoD) revealed last week, they'll also be using AI to make decisions related to national security and warfare. The MoD's Defence and Security Accelerator (DASA) has announced the initial injection of £4 million in funding for new projects and startups exploring how to use AI in the context of the British Navy. In particular, the DASA is looking to support AI- and machine learning-based technology that will "revolutionise the way warships make decisions and process thousands of strands of intelligence and data."

Yes, companies use AI to automate various tasks, while consumers use AI to make their daily routines easier. But governments–and in particular militaries–also have a massive interest in the speed and scale offered by AI. Nation states are already using artificial intelligence to monitor their own citizens, and as the UK's Ministry of Defence (MoD) revealed last week, they'll also be using AI to make decisions related to national security and warfare. The MoD's Defence and Security Accelerator (DASA) has announced the initial injection of £4 million in funding for new projects and startups exploring how to use AI in the context of the British Navy. In particular, the DASA is looking to support AI- and machine learning-based technology that will "revolutionise the way warships make decisions and process thousands of strands of intelligence and data."

The funding aims to revolutionise the way warships make decisions and process thousands of strands of intelligence and data by using Artificial Intelligence (A.I.). Nine projects will share an initial £1 million to develop technology and innovative solutions to overcome increasing'information overload' faced by crews as part of DASA's Intelligent Ship – The Next Generation competition. The astonishing pace at which global threats are evolving requires new approaches and fresh-thinking to the way we develop our ideas and technology. The funding will research pioneering projects into how A.I and automation can support our armed forces in their essential day-to-day work. Intelligent Ship is focused on inventive approaches for Human-AI and AI-AI teaming for defence platforms – such as warships, aircraft, and land vehicles – in 2040 and beyond.

The UK government has approved £2 million ($2.57 million) worth of funding for 18 projects that will develop anti-drone and drone detection technologies. The funding comes part of a competition held by the Defence and Security Accelerator (DASA) program under the UK's Ministry of Defence (MOD). MOD officials approved funding earlier this year, in April, after a series of amateur drone incursions froze air travel at several airports across the UK. Infamous is a three-day incident at the Gatwick Airport in London just before Christmas last year, and another day of flight cancellations in January, at Heathrow, London, one of the world's largest airports. In April, MOD, through DASA, asked the private sector for solutions to detect and neutralize "small UAS (unmanned aerial system) threats."