Malicious shell commands are linchpins to many cyber-attacks, but may not be easy to understand by security analysts due to complicated and often disguised code structures. Advances in large language models (LLMs) have unlocked the possibility of generating understandable explanations for shell commands. However, existing general-purpose LLMs suffer from a lack of expert knowledge and a tendency to hallucinate in the task of shell command explanation. In this paper, we present Raconteur, a knowledgeable, expressive and portable shell command explainer powered by LLM. Raconteur is infused with professional knowledge to provide comprehensive explanations on shell commands, including not only what the command does (i.e., behavior) but also why the command does it (i.e., purpose). To shed light on the high-level intent of the command, we also translate the natural-language-based explanation into standard technique & tactic defined by MITRE ATT&CK, the worldwide knowledge base of cybersecurity. To enable Raconteur to explain unseen private commands, we further develop a documentation retriever to obtain relevant information from complementary documentations to assist the explanation process. We have created a large-scale dataset for training and conducted extensive experiments to evaluate the capability of Raconteur in shell command explanation. The experiments verify that Raconteur is able to provide high-quality explanations and in-depth insight of the intent of the command.

Are you scared yet, human? Artificial intelligence (AI) has proliferated with transformative effects in recent years, in sectors from autonomous vehicles to personalised shopping. But the latest deployment of AI to generate content such as text, images or audio has caused quite a stir. ChatGPT, a particularly superior language model, even passed the US medical speciality exam. That's not to say there haven't been some bloopers.

The AI era is upon us, with what seems like new advances every week, pushing the technology to new heights. Between Google, OpenAI, Microsoft and a raft of other companies, new developments that can ease the way we live and work are accessible to people more than ever before. It's little wonder, then, that businesses are starting to consider how best to integrate AI into their processes to reap the benefits. But thinking before acting is vital in such a fast-moving space. The first-mover advantage that businesses seek out can quickly be negated by the regulatory risks of irresponsible use of AI. "Lots of companies talk about AI, but only a few of them can talk about responsible AI," says Vikash Khatri, senior vice-president for artificial intelligence at Afiniti, which provides AI that pairs customers and contact-centre agents based on how well they are likely to interact. "Yet, it's vital that responsibility be front of mind when considering any deployment of AI – the risks of not considering that are too great."

Erik Brynjolfsson is in great demand. The US professor whose research focuses on the relationship between digital tech and human productivity is nearing the end of a European speaking tour that's lasted nearly a month. Speaking via Zoom as he prepares for his imminent lecture in Oxford, the director of the Digital Economy Lab at the Stanford Institute for Human-Centered AI is enthused by recent "seminal breakthroughs" in the field. Brynjolfsson's tour – which has included appearances at the World Economic Forum in Davos and the Institute for the Future of Work in London – is neatly timed, because the recent arrival of ChatGPT on the scene has been capturing human minds, if not yet hearts. The large-scale language model, fed 300 billion words by developer OpenAI, caused a sensation with its powerful capabilities, attracting 1 million users within five days of its release in late November 2022.

Search for a description of knowledge management (KM) and you're likely to have a better chance of finding an agreed version of the best Avenger hero. Atlassian describes KM as "the process of creating, curating, sharing, using and managing knowledge across an organization, even across industries". Gartner takes a similar view, positing that "KM promotes a collaborative and integrative approach to the creation, capture, organization, access and use of information assets, including the tacit, uncaptured knowledge of people" – but there still remains no single, accepted definition. This positions KM as an esoteric discipline, but consensus suggests that when it is implemented effectively, KM is a collective endeavour; an organisational movement where technology intersects with the levers of people, process, tools and content. Of these parts, people are arguably the key to successfully embedding KM into an organisation.

It wasn't meant to happen like this. Yes, the robots were always going to come for everyone's jobs, but it was the menial ones that were set to go first. Freed from the need to fill out spreadsheets and perform administrative duties, we were all supposed to have extra time to indulge in more creative, fulfilling pursuits. Yet Microsoft Excel still exists while AI algorithms are producing works of art that are both commercially viable and critically respected. An AI artist, Jason Allen, recently caused outrage among old-school digital artists by winning a digital art competition. One of the writers of US publication The Atlantic, Charlie Warzel, provoked the ire of illustrators around the world by choosing to adorn an article about controversial radio host Alex Jones with an AI-generated caricature as opposed to using a stock photo or commissioning a portrait.

Technology powered by artificial intelligence (AI) is enabling organisations to improve their customer experience and boost loyalty and revenues. The role of customer data has never been more crucial. A recent expert roundtable discussed the importance of personalisation and how data drives smart decision making. It outlined why employees need the right skills and should feel empowered to take action on the insights being generated every day. Excellent data management, powered by AI-enabled platforms, can result in improved customer experience, engagement and loyalty.

The graph represents a network of 2,070 Twitter users whose tweets in the requested range contained "iot ai", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 17 August 2022 at 11:27 UTC. The requested start date was Wednesday, 17 August 2022 at 00:01 UTC and the maximum number of tweets (going backward in time) was 7,500. The tweets in the network were tweeted over the 1-day, 18-hour, 9-minute period from Monday, 15 August 2022 at 05:51 UTC to Wednesday, 17 August 2022 at 00:00 UTC. Additional tweets that were mentioned in this data set were also collected from prior time periods.

The graph represents a network of 4,286 Twitter users whose tweets in the requested range contained "smartcity OR smartcities", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Friday, 09 September 2022 at 00:34 UTC. The requested start date was Friday, 09 September 2022 at 00:01 UTC and the maximum number of days (going backward) was 14. The maximum number of tweets collected was 7,500. The tweets in the network were tweeted over the 3-day, 22-hour, 21-minute period from Sunday, 04 September 2022 at 04:39 UTC to Thursday, 08 September 2022 at 03:00 UTC.

Just over a century since The Manifesto of Futurist Architecture declared the city must be rethought and rebuilt like an "immense and tumultuous shipyard" – "everywhere dynamic", and the house like a "gigantic machine", it may be that author Antonio Sant'Elia had things the wrong way around. Because although his machine-fetishising sketches inspired our common vision of a science-fiction future – as in Fritz Lang's 1927 film Metropolis, with its technological Tower of Babel an imposing centrepiece – it might be the gigantic machines that are making our houses. Architecture and AI visionaries – forming especially around MIT in the 1950s, through to the later work of MIT Media Lab co-founder Nicholas Negroponte – and design pioneers have long thought about automating the creation of our environments. Now the technology is catching up to their ideas, and a radical shift into AI-assisted design is taking hold, with implications that could radically transform the form, feel and function of the places we inhabit. Completely automated design is not quite there yet. This crop of generative, AI-assisted tools is rather new.