If you've been dreaming about spending your summer whispering sweet nothings into the digital ears of one of the seductive ChatGPT voice assistants that OpenAI showed off last month, you'll have to dream a little longer. On Tuesday, the company announced that its "advanced Voice Mode" feature needs more time in the oven "to reach our bar to launch." The feature will be available to a small group of users to gather feedback, and then launch to all paying ChatGPT customers in the fall. "We're improving the model's ability to detect and refuse certain content," OpenAI posted on X. "We're also working on improving the user experience and preparing our infrastructure to scale to millions while maintaining real-time responses." We're sharing an update on the advanced Voice Mode we demoed during our Spring Update, which we remain very excited about: We had planned to start rolling this out in alpha to a small group of ChatGPT Plus users in late June, but need one more month to reach our bar to launch.… Voices have been a part of ChatGPT since 2023.

The rise of artificial intelligence in our media and entertainment industries has raised a lot of concerns about programs like Open Al's text-to-video maker Sora replacing the artistic endeavors and aspirations of humans. If those AI made movies are anything like a new brand film about the Toys'R' Us toy store chain's origin story, the only thing we'll have to fear is watching them. Toys'R' Us's current owner WHP Global worked with the Emmy nominated creative agency Native Foreign to create a short brand film called The Origin of Toys'R' Us using OpenAI's text-to-video creator Sora. The film premiered at the 2024 Cannes Lions International Festival of Creativity and can currently be viewed on the toy retailer's website. The Origin of Toys'R' Us is only a little over a minute long but it's a mix of confusing and eerie.

The macOS ChatGPT desktop app is now available to everyone. That is, provided you're running an Apple Silicon Mac (sorry, Intel users) and your computer is on macOS Sonoma or higher. OpenAI rolled out the app gradually, starting with Plus subscribers last month. ChatGPT now has an official macOS client before it has a Windows one. Of course, Windows 11 has the OpenAI-powered Microsoft CoPilot baked into its OS, which likely explains the omission.

OpenAI plans to block people from using ChatGPT in China, a country where its services aren't officially available, but where users and developers access it via the company's API anyway. Securities Times, a Chinese state-owned newspaper reported on Tuesday that OpenAI had started sending emails to users in China outlining its plans to block access starting July 9, according to Reuters. "We are taking additional taps to block API traffic from regions where we do not support access to OpenAI's services," an OpenAI spokesperson told the publication. The move could impact several Chinese startups which have built applications using OpenAI's large language models. Although OpenAI's services are available in more than 160 countries, China isn't one of them.

Can you solve this puzzle? A set of puzzles that will challenge even today's most sophisticated artificial intelligence models, while being relatively easy for people, aims to encourage AI developers to create new techniques. Any AI that solves the puzzles will net its creators a share of a 1 million prize fund. But this isn't because the models are reasoning intelligently like humans, says Mike Knoop at…

ChatGPT is now available with many Volkswagen models, including all vehicles in the electric ID family, the new Golf, Tiguan and Passat. This integration is only in Europe, for now, with North America coming soon. What does this mean exactly? ChatGPT has been integrated into Volkswagen's own voice assistant IDA to complement the service and add more features, sort of like how Apple is handling its own partnership with OpenAI's platform. This means that customers can better communicate with the vehicle using natural language, which allows the assistant to "answer questions about various topics." IDA could already handle voice-controlled climate adjustments and navigation, but the addition of ChatGPT should make everything run a bit smoother.

The frontier of AI just got pushed a little further forward. On Friday, Anthropic, the AI lab set up by a team of disgruntled OpenAI staffers, released the latest version of its Claude LLM. The company said Thursday that the new model – the technology that underpins its popular chatbot Claude – is twice as fast as its most powerful previous version. Anthropic said in its evaluations, the model outperforms leading competitors like OpenAI on several key intelligence capabilities, such as coding and text-based reasoning. Anthropic only released the previous version of Claude, 3.0, in March.

The advent of transformers has fueled progress in machine translation. More recently large language models (LLMs) have come to the spotlight thanks to their generality and strong performance in a wide range of language tasks, including translation. Here we show that open-source LLMs perform on par with or better than some state-of-the-art baselines in simultaneous machine translation (SiMT) tasks, zero-shot. We also demonstrate that injection of minimal background information, which is easy with an LLM, brings further performance gains, especially on challenging technical subject-matter. This highlights LLMs' potential for building next generation of massively multilingual, context-aware and terminologically accurate SiMT systems that require no resource-intensive training or fine-tuning.

As Machine Learning (ML) models grow in size and demand higher-quality training data, the expenses associated with re-training and fine-tuning these models are escalating rapidly. Inspired by recent impressive achievements of Large Language Models (LLMs) in different fields, this paper delves into the question: can LLMs efficiently improve an ML's performance at a minimal cost? We show that, through our proposed training-free framework LlmCorr, an LLM can work as a post-hoc corrector to propose corrections for the predictions of an arbitrary ML model. In particular, we form a contextual knowledge database by incorporating the dataset's label information and the ML model's predictions on the validation dataset. Leveraging the in-context learning capability of LLMs, we ask the LLM to summarise the instances in which the ML model makes mistakes and the correlation between primary predictions and true labels. Following this, the LLM can transfer its acquired knowledge to suggest corrections for the ML model's predictions. Our experimental results on text analysis and the challenging molecular predictions show that \model improves the performance of a number of models by up to 39%.

Recent advancements in Large Language Models (LLMs) have significantly enhanced their ability to generate and manipulate human language, highlighting their potential across various applications. Evaluating LLMs in languages other than English is crucial for ensuring their linguistic versatility, cultural relevance, and applicability in diverse global contexts, thus broadening their usability and effectiveness. We tackle this challenge by introducing a structured benchmark using the INVALSI tests, a set of well-established assessments designed to measure educational competencies across Italy. Our study makes three primary contributions: Firstly, we adapt the INVALSI benchmark for automated LLM evaluation, which involves rigorous adaptation of the test format to suit automated processing while retaining the essence of the original tests. Secondly, we provide a detailed assessment of current LLMs, offering a crucial reference point for the academic community. Finally, we visually compare the performance of these models against human results. Additionally, researchers are invited to submit their models for ongoing evaluation, ensuring the benchmark remains a current and valuable resource.