A group of current and former employees at leading AI companies OpenAI and Google DeepMind published a letter on Tuesday warning against the dangers of advanced AI as they allege companies are prioritizing financial gains while avoiding oversight. Thirteen employees, eleven of which are current or former employees of OpenAI, the company behind ChatGPT, signed the letter entitled: "A Right to Warn about Advanced Artificial Intelligence." The two other signatories are current and former employees of Google DeepMind. The coalition cautions that AI systems are powerful enough to pose serious harms without proper regulation. "These risks range from the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction," the letter says.

A group of current and former employees at prominent artificial intelligence companies issued an open letter on Tuesday that warned of a lack of safety oversight within the industry and called for increased protections for whistleblowers. The letter, which calls for a "right to warn about artificial intelligence", is one of the most public statements about the dangers of AI from employees within what is generally a secretive industry. Eleven current and former OpenAI workers signed the letter, along with two current or former Google DeepMind employees – one of whom previously worked at Anthropic. "AI companies possess substantial non-public information about the capabilities and limitations of their systems, the adequacy of their protective measures, and the risk levels of different kinds of harm," the letter states. "However, they currently have only weak obligations to share some of this information with governments, and none with civil society. We do not think they can all be relied upon to share it voluntarily."

It'll soon be Apple's turn to talk about its next major operating system updates, giving developers a chance to get their apps ready ahead of a broad rollout this fall. The company's Worldwide Developers Conference is right around the corner. Apple is sure to reveal some of the main features of iOS 18 and iPadOS 18, as well as what's ahead for the likes of watchOS, macOS and visionOS at WWDC 2024. Given the current tech climate, though, it seems likely that Apple is about to follow its rivals by making a big leap into the realm of generative AI. That could be a major focus of the keynote, since those are the only two letters investors seem to give a hoot about hearing these days. The Apple rumor mill never stops churning, so we've heard some bits and pieces about what WWDC will perhaps entail.

A group of current and former OpenAI employees have issued a public letter warning that the company and its rivals are building artificial intelligence with undue risk, without sufficient oversight, and while muzzling employees who might witness irresponsible activities. "These risks range from the further entrenchment of existing inequalities, to manipulation and misinformation, to the loss of control of autonomous AI systems potentially resulting in human extinction," reads the letter published at righttowarn.ai. "So long as there is no effective government oversight of these corporations, current and former employees are among the few people who can hold them accountable." The letter calls for not just OpenAI but all AI companies to commit to not punishing employees who speak out about their activities. It also calls for companies to establish "verifiable" ways for workers to provide anonymous feedback on their activities.

The letter called for AI companies to commit to four principles to allow for greater transparency and whistleblower protections. Those principles include a commitment to not enter into or enforce agreements that prohibit criticism of risks; a call to establish an anonymous process for current and former employees to raise concerns; supporting a culture of criticism; and a promise to not retaliate against current and former employees who share confidential information to raise alarms "after other processes have failed."

Generative AI tools such as OpenAI's ChatGPT and Microsoft's Copilot are rapidly evolving, fueling concerns that the technology could open the door to multiple privacy and security issues, particularly in the workplace. In May, privacy campaigners dubbed Microsoft's new Recall tool a potential "privacy nightmare" due to its ability to take screenshots of your laptop every few seconds. The feature has caught the attention of UK regulator the Information Commissioner's Office, which is asking Microsoft to reveal more about the safety of the product launching soon in its Copilot PCs. Concerns are also mounting over OpenAI's ChatGPT, which has demonstrated screenshotting abilities in its soon-to-launch macOS app that privacy experts say could result in the capture of sensitive data. The US House of Representatives has banned the use of Microsoft's Copilot among staff members after it was deemed by the Office of Cybersecurity to be a risk to users due to "the threat of leaking House data to non-House approved cloud services." Meanwhile, market analyst Gartner has cautioned that "using Copilot for Microsoft 365 exposes the risks of sensitive data and content exposure internally and externally."

But ChatGPT has been hit with a major outage this morning, users unable to access the app or website. According to DownDetector, hundreds of people globally have been affected since 8am BST. OpenAI, the firm behind ChatGPT, has acknowledged the outage with a statement saying: 'We are currently investigating this issue.' Down Detector gets network status updates from various sources including social media and reports submitted to its website. According to the site, 79 per cent of those affected said they had problems with ChatGPT generally, while others were more specific – 15 per cent said they had trouble with the app and 6 per cent with the website.

Jensen Huang and Lisa Su -- both born in Taiwan and now local celebrities for leading U.S. tech powerhouses -- employed different tacks in conveying their expertise during back-to-back shows at the world's largest computing conference in Taipei. Nvidia's CEO repeatedly voiced his 2.8 trillion company's dominance in the accelerators that OpenAI and Microsoft rely on to build generative AI services such as ChatGPT. Huang went as far as to tease a chip envisioned for 2026 he dubbed Rubin -- after Vera Rubin, the American woman who helped discover dark matter. The chip, which will succeed the Blackwell family, will be key to sustaining its runaway leadership.

Generative AI has received much attention in the image and language domains, with the transformer neural network continuing to dominate the state of the art. Application of these models to time series generation is less explored, however, and is of great utility to machine learning, privacy preservation, and explainability research. The present survey identifies this gap at the intersection of the transformer, generative AI, and time series data, and reviews works in this sparsely populated subdomain. The reviewed works show great variety in approach, and have not yet converged on a conclusive answer to the problems the domain poses. GANs, diffusion models, state space models, and autoencoders were all encountered alongside or surrounding the transformers which originally motivated the survey. While too open a domain to offer conclusive insights, the works surveyed are quite suggestive, and several recommendations for best practice, and suggestions of valuable future work, are provided.

The rise of Large Language Models (LLMs) such as ChatGPT and Gemini has posed new challenges for the academic community. With the help of these models, students can easily complete their assignments and exams, while educators struggle to detect AI-generated content. This has led to a surge in academic misconduct, as students present work generated by LLMs as their own, without putting in the effort required for learning. As AI tools become more advanced and produce increasingly human-like text, detecting such content becomes more challenging. This development has significantly impacted the academic world, where many educators are finding it difficult to adapt their assessment methods to this challenge. This research first demonstrates how LLMs have increased academic dishonesty, and then reviews state-of-the-art solutions for academic plagiarism in detail. A survey of datasets, algorithms, tools, and evasion strategies for plagiarism detection has been conducted, focusing on how LLMs and AI-generated content (AIGC) detection have affected this area. The survey aims to identify the gaps in existing solutions. Lastly, potential long-term solutions are presented to address the issue of academic plagiarism using LLMs based on AI tools and educational approaches in an ever-changing world.