"Are we alone in the universe?" is one of humanity's biggest questions. But now, some of the world's top scientists and tech companies are setting out to answer an even bigger question: "Are we being visited?" This used to be seen as a silly topic for debate, confined to conspiratorial subreddits filled with stories of reptilian alien overlords covertly living among us. But things are starting to change. Last year, not only did US president Biden approve a new US government office to study the nature of unidentified flying objects, but a distinguished academic, Professor Avi Loeb -- the longest serving chair of Harvard's Department of Astronomy -- launched The Galileo Project, a search for UFOs.

The U.S. Defense Department has a new office dedicated to advancing the use of AI throughout the military. Now the money from a $249 million blanket purchase agreement is starting to flow to several AI tech providers that also work with enterprises in other industries, including companies like Arthur that help monitor AI models to avoid bias and inaccuracy. Arthur's software tracks performance of AI models including computer vision and natural-language processing models. Arthur is among a burgeoning sector of companies providing software and services for auditing how machine-learning and AI models are built, and monitoring them for problems after they're in use. The company collected $15 million in series A funding in December 2020.

Data sharing is not always required when firms use information to their advantage. The European Union is positioning data sharing as a central piece of its online economic strategy. For decades, European courts have imposed mandatory data sharing as antitrust remedies. The Magill decision in 1995, IMS in 2004, and Microsoft in 2007, among others, established precedent for data sharing remedies. The data shared in these cases often did not include user data but instead data on dominant companies' processes, structures, and internal documents.

There's a strand of thinking, from sci-fi films to Stephen Hawking that suggests artificial intelligence (AI) could spell doom for humans. But conservationists are increasingly turning to AI as an innovative tech solution to tackle the biodiversity crisis and mitigate climate change. From camera trap and satellite images to audio recordings, the report notes: "AI can learn how to identify which photos out of thousands contain rare species; or pinpoint an animal call out of hours of field recordings – hugely reducing the manual labour required to collect vital conservation data." AI is helping to protect species as diverse as humpback whales, koalas and snow leopards, supporting the work of scientists, researchers and rangers in vital tasks, from anti-poaching patrols to monitoring species. With machine learning (ML) computer systems that use algorithms and models to learn, understand and adapt, AI is often able to do the job of hundreds of people, getting faster, cheaper and more effective results.

Artificial Intelligence (AI) and robots often seem like fun science fiction, but in fact already affect our daily lives. For example, services like Google and Amazon help us find what we want by using AI. Every aspect of how Facebook works is based on AI and Machine Learning (ML). The reason your phone is so useful is it is full of AI -- sensing, acting, and learning about you. All these tools not only make us smarter, their intelligence is based partly on what they learn both from us and about us when we use them.

Computers have become very, very good at generating photorealistic images of human faces. What could possibly go wrong? A study published last week in the academic journal Proceedings of the National Academy of Sciences confirms just how convincing "faces" produced by artificial intelligence can be. In that study, more than 300 research participants were asked to determine whether a supplied image was a photo of a real person or a fake generated by an A.I. The human participants got it right less than half the time.

Abu Dhabi – The United Arab Emirates and its allies warned Sunday of the rising threat of drone attacks, as Middle East militants rapidly acquire a taste for the cheap and easily accessible unmanned systems. But while the countries called for a collective effort to protect airspaces against the small and often hard to detect targets, one question remains: how can you reliably stop a drone attack? "We have to unite to prevent the use of drones from threatening civilian safety and destroying economic institutions," Mohammed bin Ahmed al-Bowardi, United Arab Emirates' (UAE) Minister of State for Defense Affairs, said at a defense conference in Abu Dhabi. The Unmanned Systems Exhibition (UMEX), running until Wednesday, began in the UAE capital with regional and Western military and industry representatives, including from the United States, Britain and France. Speakers addressed the importance of developing such systems for civil and military uses but also acknowledged their dangers when used by groups deemed a threat to the region.

We proposed signal-specific adversarial attack (SSA) and signal-agnostic adversarial attack (SAA) methods to attack learning models for classification of power quality signals by generating adversarial signals in the Smart Grid. We proposed and evaluated black-box attacks based on transferable characteristics and the above two methods. We adopted adversarial training to defend learned models against adversarial signals. Experimental results show that our proposed SSA provides less perturbation compared to the state-of-the-art FGSM which was adapted for power signal analysis, while the SAA can generate the universal perturbation that can fool learned models. The attack method based on the universal signal-agnostic algorithm has a higher transfer rate of black-box attacks than the attack method based on the signal-specific algorithm, which is a huge and practical threat for CNN based PQ classification.

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"Everything we love about civilization is a product of intelligence, so amplifying our human intelligence has the potential of helping civilization flourish like never before -- as long as we manage to keep the technology beneficial" Artificial intelligence (AI) is based on the notion that human thought processes have the ability, which can be replicated and mechanised. It is not a new word and not a new technology. The technology is much older as there are stories of mechanical men in ancient Greek and Egyptian myths. Philosophers thought over the idea that artificial beings, mechanical men and other automatons had existed or could exist in some fashion. Electronic Brain AI became more tangible throughout the 1700s and beyond. Philosophers contemplated how human thinking could be artificially mechanised and manipulated by intelligent non-human machines.