We present a novel approach to efficiently compute tight non-convex enclosures of the image through neural networks with ReLU, sigmoid, or hyperbolic tangent activation functions. In particular, we abstract the input-output relation of each neuron by a polynomial approximation, which is evaluated in a set-based manner using polynomial zonotopes. While our approach can also can be beneficial for open-loop neural network verification, our main application is reachability analysis of neural network controlled systems, where polynomial zonotopes are able to capture the non-convexity caused by the neural network as well as the system dynamics. This results in a superior performance compared to other methods, as we demonstrate on various benchmarks. Keywords: Neural network verification neural network controlled systems reachability analysis polynomial zonotopes formal verification.

In this paper, we present a transcribed corpus of the LIBE committee of the EU parliament, totalling 3.6 Million running words. The meetings of parliamentary committees of the EU are a potentially valuable source of information for political scientists but the data is not readily available because only disclosed as speech recordings together with limited metadata. The meetings are in English, partly spoken by non-native speakers, and partly spoken by interpreters. We investigated the most appropriate Automatic Speech Recognition (ASR) model to create an accurate text transcription of the audio recordings of the meetings in order to make their content available for research and analysis. We focused on the unsupervised domain adaptation of the ASR pipeline. Building on the transformer-based Wav2vec2.0 model, we experimented with multiple acoustic models, language models and the addition of domain-specific terms. We found that a domain-specific acoustic model and a domain-specific language model give substantial improvements to the ASR output, reducing the word error rate (WER) from 28.22 to 17.95. The use of domain-specific terms in the decoding stage did not have a positive effect on the quality of the ASR in terms of WER. Initial topic modelling results indicated that the corpus is useful for downstream analysis tasks. We release the resulting corpus and our analysis pipeline for future research.

Among the many unique experiences of reporting on A.I. is this: In a young industry flooded with hype and money, person after person tells me that they are desperate to be regulated, even if it slows them down. In fact, especially if it slows them down. What they tell me is obvious to anyone watching. Competition is forcing them to go too fast and cut too many corners. This technology is too important to be left to a race between Microsoft, Google, Meta and a few other firms.

The next generation of artificial intelligence (AI) systems is likely to include a machine more complex than the human brain, since the existing 100 trillion connections of GPT-4 are only a factor of 6 shy of the number of synapses in the human brain. Although the machine will be trained on human-made texts, it will develop its own qualities of mind by learning from new personal experiences. It will likely mature similarly to the way that children become independent adults who take legal responsibility for their actions. Humanity gave birth to an alien baby in its technological belly. Alarm bells are starting to sound about the existential risk that AI may bring as an alien entity.

US Commerce Secretary Gina Raimondo, recounting her recent meeting with Prime Minister Narendra Modi, said that India and America would lead the artificial intelligence revolution. Ms Raimondo, who visited India in March, said the best of India was at display during her visit, in terms of culture, tradition and celebrations. Pictures and video clips of her playing Holi have gone viral on social media and reflect the strong relationship between the US and India. Addressing a gathering of Indian Americans at the India House, the commerce secretary fondly remembered her Holi celebrations this year in India. "I was recently in India. I went a day earlier so that I could have the opportunity to participate in Holi. And the defence minister was so gracious to host me with his family," Ms Raimondo said on Saturday.

Campaigners, trade unions and MPs are calling for stricter oversight of the use of artificial intelligence in the workplace, amid growing concerns about its effect on staff rights. The Trades Union Congress (TUC) is holding a half-day conference on Tuesday to highlight the challenges of ensuring workers are treated fairly, as what it calls "management by algorithm" becomes increasingly prevalent. "Making work more rewarding, making it more satisfying, and crucially making it safer and fairer: these are all the possibilities that AI offers us," said Mary Towers, an employment lawyer who runs a TUC project on AI at work. "But what we're saying is, we're at a really important juncture, where the technology is developing so rapidly, and what we have to ask ourselves is, what direction do we want that to take, and how can we ensure that everyone's voice is heard?" The TUC has highlighted the growing use of employee surveillance. The Royal Mail chief executive, Simon Thompson, recently conceded some postal workers' movements were minutely tracked using handheld devices, with the data sused for performance management, for example.

Just a few years ago, the promise seemed limitless: Automate cars and bring an end to traffic accidents, the biggest killer in the United States. Automate construction, with robot dozers, excavators, and other heavy machinery, and US housing and infrastructure shortfalls could be solved. Built Robotics began testing autonomous excavators in 2017 with the goal of training machines to do more on construction sites. At the time, CEO Noah Ready-Campbell predicted that fully autonomous equipment would become commonplace on construction sites before fully autonomous cars hit public roads. But after nearly seven years of digging trenches with autonomous excavators, Built Robotics last month announced plans to shift its focus from general construction projects to installation of solar farms.

A US military programme has begun testing autonomous all-terrain vehicles without any human drivers onboard – showing how robotic vehicles can race across rough landscapes dotted with dangerous obstacles. The off-roading robots navigated steep hills and ditches while avoiding rocks and trees as they sped across the Mojave Desert at the US Army's National Training Center in Ft.

The Financial Times recently found that ChatGPT (along with Bard, Google's own experimental chatbot) can tell a joke at least passably well, write an advertising slogan, make stock picks, and imagine a conversation between Xi Jinping and Vladimir Putin. It is understandable that a new technology with such seemingly vast powers would raise concerns. But much of the distress is misplaced. AI's detractors tend to understate the pace of technological change that advanced economies have already been living through. In 1970, US employment was roughly evenly divided across occupations, with low-skill, medium-skill and high-skill jobs accounting for, respectively, 31 per cent, 38 per cent, and 30 per cent of total hours worked.

Artificial intelligence (AI) has recently been a hot topic among academics, policymakers, and business titans. There is rising concern that we could be on the verge of an artificial arms race between the US and China due to the development of sophisticated AI models like ChatGPT and the usage of AI in military weaponry. Let's investigate this matter in greater detail. AI weapons have developed into a key source of concern as the globe deals with escalating technological breakthroughs. These weapons are particularly frightening since they have the capability to unleash mass destruction without human participation.