Since the release of iOS 18.2 on December 11, ChatGPT integration has been an integral part of Apple Intelligence. Provided you own a recent iPhone, iPad or Mac, you can access OpenAI's chatbot directly from your device, with no need to go through the ChatGPT app or web client. ChatGPT is a generative AI chatbot created by OpenAI and powered by a large language machine-learning model. In addition to the capability to interact with people using natural language, ChatGPT can search the web, solve complex math and coding problems, as well as generate text, images and audio. As of the writing of this article, the current version of ChatGPT is based on OpenAI's GPT-4o and 4o mini models.

In the spring, the US saw what was likely its first AI candidate. In a brief campaign for the mayor of Wyoming, virtual integrated citizen (VIC), a ChatGPT-based bot created by real human Victor Miller, promised to govern entirely by AI. At the outset of 2024, many suggested that even if not winning office, generative AI would play a pivotal role in--and pose significant risks to--democratic elections, as more than 2 billion people voted in more than 60 countries. But now, experts and analysts have changed their tune, saying that generative AI likely had little to no effect at all. So were all those prognostications that 2024 would be the AI election year wrong?

"This is a powerful technology that will sweep through American offices with potentially very significant geographic implications," said Mark Muro, a senior fellow at the Brookings Institution, where he studies the regional effects of technology and government policy. "We need to think about what's coming down the pike." At issue is a new and rapidly growing breed of the technology known as generative A.I., which can quickly draft business reports, write software and answer questions, often with human-level skill. Already, predictions abound that generative A.I. will displace workers in call centers, software developers and business analysts. That pattern of technology disruption has happened before.

While new technologies emerge, human errors always looming. Software supply chain is increasingly complex and intertwined, the security of a service has become paramount to ensuring the integrity of products, safeguarding data privacy, and maintaining operational continuity. In this work, we conducted experiments on the promising open Large Language Models (LLMs) into two main software security challenges: source code language errors and deprecated code, with a focus on their potential to replace conventional static and dynamic security scanners that rely on predefined rules and patterns. Our findings suggest that while LLMs present some unexpected results, they also encounter significant limitations, particularly in memory complexity and the management of new and unfamiliar data patterns. Despite these challenges, the proactive application of LLMs, coupled with extensive security databases and continuous updates, holds the potential to fortify Software Supply Chain (SSC) processes against emerging threats.

The need for and challenges of teaching artificial intelligence (AI) at primary, secondary, and upper-secondary levels have been a major focus of recent academic discussions [1],[2],[3]. Often referred to as AI4K12 [4], this area explores global initiatives that introduce AI to students from kindergarten through high school. The rapid advancements in deep learning and generative AI technologies suggest AI will become a transformative force. This realisation has prompted governments and policymakers to recognise the need to prepare future citizens for a world heavily influenced by AI. As AI becomes increasingly integrated into information systems, concerns are mounting about citizens' ability to use these systems responsibly and understand the consequences of not doing so [5]. Furthermore, anxieties regarding AI's potential impact on societal sustainability highlight the need to equip future workforces with the skills to combine human creativity with AI's potential to create sustainable systems.

Days after New Hampshire voters received a robocall with an artificially generated voice that resembled President Joe Biden's, the Federal Communications Commission banned the use of AI-generated voices in robocalls. The 2024 United States election would be the first to unfold amid wide public access to AI generators, which let people create images, audio and video – some for nefarious purposes. Institutions rushed to limit AI-enabled misdeeds. Sixteen states enacted legislation around AI's use in elections and campaigns; many of these states required disclaimers in synthetic media published close to an election. The Election Assistance Commission, a federal agency supporting election administrators, published an "AI toolkit" with tips election officials could use to communicate about elections in an age of fabricated information.

What is appropriateness? Humans navigate a multi-scale mosaic of interlocking notions of what is appropriate for different situations. We act one way with our friends, another with our family, and yet another in the office. Likewise for AI, appropriate behavior for a comedy-writing assistant is not the same as appropriate behavior for a customer-service representative. What determines which actions are appropriate in which contexts? And what causes these standards to change over time? Since all judgments of AI appropriateness are ultimately made by humans, we need to understand how appropriateness guides human decision making in order to properly evaluate AI decision making and improve it. This paper presents a theory of appropriateness: how it functions in human society, how it may be implemented in the brain, and what it means for responsible deployment of generative AI technology.

Today's generative AI systems are tuned to present information by default rather than engage users in service of learning as a human tutor would. To address the wide range of potential education use cases for these systems, we reframe the challenge of injecting pedagogical behavior as one of \textit{pedagogical instruction following}, where training and evaluation examples include system-level instructions describing the specific pedagogy attributes present or desired in subsequent model turns. This framing avoids committing our models to any particular definition of pedagogy, and instead allows teachers or developers to specify desired model behavior. It also clears a path to improving Gemini models for learning -- by enabling the addition of our pedagogical data to post-training mixtures -- alongside their rapidly expanding set of capabilities. Both represent important changes from our initial tech report. We show how training with pedagogical instruction following produces a LearnLM model (available on Google AI Studio) that is preferred substantially by expert raters across a diverse set of learning scenarios, with average preference strengths of 31\% over GPT-4o, 11\% over Claude 3.5, and 13\% over the Gemini 1.5 Pro model LearnLM was based on.

A generative AI model visualizes how floods in Texas would look like in satellite imagery. The original photo is on the left, and the AI generated image is in on the right. Visualizing the potential impacts of a hurricane on people's homes before it hits can help residents prepare and decide whether to evacuate. MIT scientists have developed a method that generates satellite imagery from the future to depict how a region would look after a potential flooding event. The method combines a generative artificial intelligence model with a physics-based flood model to create realistic, birds-eye-view images of a region, showing where flooding is likely to occur given the strength of an oncoming storm.

OpenAI's ChatGPT search tool may be open to manipulation using hidden content, and can return malicious code from websites it searches, a Guardian investigation has found. The Guardian's journalism is independent. We will earn a commission if you buy something through an affiliate link. OpenAI has made the search product available to paying customers and is encouraging users to make it their default search tool. But the investigation has revealed potential security issues with the new system.