Born out of an internal hackathon, Amazon's Autonomous Threat Analysis system uses a variety of specialized AI agents to detect weaknesses and propose fixes to the company's platforms. As generative AI pushes the speed of software development, it is also enhancing the ability of digital attackers to carry out financially motivated or state-backed hacks. This means that security teams at tech companies have more code than ever to review while dealing with even more pressure from bad actors. On Monday, Amazon will publish details for the first time of an internal system known as Autonomous Threat Analysis (ATA), which the company has been using to help its security teams proactively identify weaknesses in its platforms, perform variant analysis to quickly search for other, similar flaws, and then develop remediations and detection capabilities to plug holes before attackers find them. ATA was born out of an internal Amazon hackathon in August 2024, and security team members say that it has grown into a crucial tool since then.

The AI job cuts are here - or are they? Amazon's move this week to slash thousands of corporate jobs fed into a longstanding anxiety: that Artificial Intelligence is starting to replace workers. The tech giant joined a growing list of companies in the US that have pointed to AI technology as a reason behind layoffs. But some question whether AI is fully to blame - and have voiced scepticism that recent high-profile layoffs are a telling sign of the technology's effect on employment. Chegg, the online education firm, cited the new realities of AI as it announced a 45% reduction in workforce on Monday.

Former Google CEO Eric Schmidt warns that AI systems can be hacked to remove safety guardrails, comparing the technology to nuclear weapons needing global controls.

On May 16, 2023, Sam Altman appeared before a subcommittee of the Senate Judiciary. The title of the hearing was "Oversight of AI." The session was a lovefest, with both Altman and the senators celebrating what Altman called AI's "printing press moment"--and acknowledging that the US needed strong laws to avoid its pitfalls. "We think that regulatory intervention by governments will be critical to mitigate the risks of increasingly powerful models," he said. The legislators hung on Altman's every word as he gushed about how smart laws could allow AI to flourish--but only within firm guidelines that both lawmakers and AI builders deemed vital at that moment.

The problem with the UK, according to the former Google boss Eric Schmidt, is that it has "so many ways that people can say no". However, for some critics of the Labour government, it has a glaring issue with saying yes: to big tech. Schmidt made his comment in a Q&A conversation with Keir Starmer at a big investment summit in October last year. The prominent position of a tech bigwig at the event underlined the importance of the sector to a government that has made growth a priority and believes the sector is crucial to achieving it. Top US tech firms have a big presence in the UK, including Google, Mark Zuckerberg's Meta, Amazon, Apple, Microsoft and Palantir, the data intelligence firm co-founded by the Maga movement backer Peter Thiel.

In the spring of 2014, a trans-anarchist Google engineer petitioned the White House to arrest our national decline. The plan was snappy: "1. Schmidt, then the chairman of Google, was an avatar of technocratic liberalism. Two decades earlier, as the largely unknown C.T.O. of Sun Microsystems, he helped Bill Clinton set up the first White House Web site, and, by the time of the Obama Administration, he served as Silicon Valley's unofficial consul to the Democratic Party. Schmidt was not himself a company "founder," a technologist's most regal credential, but he had performed as an able steward: when Larry Page and Sergey Brin struggled to reconcile their competing visions for Google's first corporate jet--Brin wanted a California king bed, Page did not--Schmidt negotiated a compromise. He was sensible and civic-minded. He was the adult in the room.

Google's former chief executive has warned that artificial intelligence could be used by rogue states such as North Korea, Iran and Russia to "harm innocent people". Eric Schmidt, who held senior posts at Google from 2001 to 2017, told BBC Radio 4's Today programme that those countries and terrorists could adopt and misuse the technology to develop weapons to create "a bad biological attack from some evil person". The tech billionaire said: "The real fears that I have are not the ones that most people talk about AI – I talk about extreme risk. "Think about North Korea, or Iran, or even Russia, who have some evil goal. This technology is fast enough for them to adopt that they could misuse it and do real harm."

When Melissa Kono, the town clerk in Burnside, Wisconsin, began training election workers in 2015, their questions were relatively mundane. They asked about election rules, voter eligibility, and other basic procedures. The job was gratifying and enjoyable; they helped their neighbors while sipping coffee. But over the past few years, everything has changed. Kono now finds herself fielding questions about what to do when approached by suspicious voters who ask provocative questions or gripe about fraud.

There are so many ways to fiddle while Rome burns, or as this season's weather would have it, gets torn apart by hurricanes and tornadoes and also goes underwater – and, in other places, burns. One particularly pernicious way comes from the men in love with big tech, who are forever insisting that we need some amazing new technology to solve our problems, be it geoengineering, carbon sequestration or fusion – but wait, it gets worse. At an artificial intelligence conference in Washington DC, the former Google CEO Eric Schmidt recently claimed that "[w]e're not going to hit the climate goals anyway because we're not organized to do it" and that we should just plunge ahead with AI, which is so huge an energy hog it's prompted a number of tech companies to abandon their climate goals. Schmidt then threw out the farfetched notion that we should go all in on AI because maybe AI will somehow, maybe, eventually know how to "solve" climate, saying: "I'd rather bet on AI solving the problem than constraining it." Eventually is not good enough. A distinguished group of scientists said in a paper published on 8 October: "We are on the brink of an irreversible climate disaster.

Explaining why and how a tree $t$ structurally differs from another tree $t^*$ is a question that is encountered throughout computer science, including in understanding tree-structured data such as XML or JSON data. In this article, we explore how to learn explanations for structural differences between pairs of trees from sample data: suppose we are given a set $\{(t_1, t_1^*),\dots, (t_n, t_n^*)\}$ of pairs of labelled, ordered trees; is there a small set of rules that explains the structural differences between all pairs $(t_i, t_i^*)$? This raises two research questions: (i) what is a good notion of "rule" in this context?; and (ii) how can sets of rules explaining a data set be learnt algorithmically? We explore these questions from the perspective of database theory by (1) introducing a pattern-based specification language for tree transformations; (2) exploring the computational complexity of variants of the above algorithmic problem, e.g. showing NP-hardness for very restricted variants; and (3) discussing how to solve the problem for data from CS education research using SAT solvers.