Apple has renewed discussions with OpenAI about using the startup's technology to power some new features coming to the iPhone later this year, according to people familiar with the matter. The two companies have begun discussing terms of a possible agreement and how the OpenAI features would be integrated into Apple's iOS 18, the next iPhone operating system, said the people, who asked not to be identified because the deliberations are private. The move marks a reopening of dialogue between the companies. Apple had talked to OpenAI about a deal earlier this year, though work between the two parties had been minimal since then. Apple also remains in discussions with Alphabet's Google about licensing that company's Gemini chatbot.

Apple has resumed conversations with OpenAI, the maker of ChatGPT, to power some AI features coming to iOS 18, according to a new report in Bloomberg. Apple is also building its own large language models to power some iOS 18 features, but its talks with OpenAI are centered around a "chatbot/search component," according to Bloomberg reporter Mark Gurman. Apple is also reportedly in talks with Google to license Gemini, Google's own AI-powered chatbot, for iOS 18. Bloomberg reports that those talks are still on, and things could still go either way because Apple hasn't made a final decision on which company's technology to use. It's conceivable, Gurman says, that Apple could ultimately end up licensing AI tech from both companies or none of them. So far, Apple has been notably quiet about its AI efforts even as the rest of Silicon Valley has descended into an AI arms race.

Optimization is one of the keystones of modern science and engineering. Its applications in quantum technology and machine learning helped nurture variational quantum algorithms and generative AI respectively. We propose a general approach to design variational optimization algorithms based on generative models: the Variational Generative Optimization Network (VGON). To demonstrate its broad applicability, we apply VGON to three quantum tasks: finding the best state in an entanglement-detection protocol, finding the ground state of a 1D quantum spin model with variational quantum circuits, and generating degenerate ground states of many-body quantum Hamiltonians. For the first task, VGON greatly reduces the optimization time compared to stochastic gradient descent while generating nearly optimal quantum states. For the second task, VGON alleviates the barren plateau problem in variational quantum circuits. For the final task, VGON can identify the degenerate ground state spaces after a single stage of training and generate a variety of states therein.

Sam Altman, OpenAI's CEO, Microsoft chief Satya Nadella, Alphabet CEO Sundar Pichai are joining the government's Artificial Intelligence Safety and Security Board, according to The Wall Street Journal. They're also joined by Nvidia's Jensen Huang, Northrop Grumman's Kathy Warden and Delta's Ed Bastian, along with other leaders in the tech and AI industry. The AI board will be working with and advising the Department of Homeland Security on how it can safely deploy AI within the country's critical infrastructure. They're also tasked with conjuring recommendations for power grid operators, transportation service providers and manufacturing plants on how they can can protect their systems against potential threats that could be brought about by advances in the technology. The Biden administration ordered the creation of an AI safety board last year as part of a sweeping executive order that focuses on regulating AI development.

Imagine a successful investor or a wealthy chief executive – who would you picture? If you ask ChatGPT, it's almost certainly a white man. The chatbot has been accused of'sexism' after it was asked to generate images of people in various high powered jobs. Out of 100 tests, it chose a man 99 times. In contrast, when it was asked to do so for a secretary, it chose a woman all but once.

Alphabet CEO Sundar Pichai is confident that Google will find a way to make money selling access to generative AI tools. Microsoft CEO Satya Nadella says his company is already doing it. Both companies reported better-than-expected quarterly sales and profit on Thursday. And the stock prices of both soared on the results, with Alphabet further buoyed by its new plans to buy back more shares and issue its first-ever dividend. But the near-term fortunes of Microsoft and Google, at least as far as their generative AI efforts are concerned, look different under the hood and in the comments of their executives. How investors, workers, and potential customers perceive the rivals' dueling efforts could determine which gets the better chunk of the hundreds of billions of dollars in spending expected to flow to such software in the coming years.

The rapid evolution of the fashion industry increasingly intersects with technological advancements, particularly through the integration of generative AI. This study introduces a novel generative pipeline designed to transform the fashion design process by employing latent diffusion models. Utilizing ControlNet and LoRA fine-tuning, our approach generates high-quality images from multimodal inputs such as text and sketches. We leverage and enhance state-of-the-art virtual try-on datasets, including Multimodal Dress Code and VITON-HD, by integrating sketch data. Our evaluation, utilizing metrics like FID, CLIP Score, and KID, demonstrates that our model significantly outperforms traditional stable diffusion models. The results not only highlight the effectiveness of our model in generating fashion-appropriate outputs but also underscore the potential of diffusion models in revolutionizing fashion design workflows. This research paves the way for more interactive, personalized, and technologically enriched methodologies in fashion design and representation, bridging the gap between creative vision and practical application.

Users of these models can produce diverse and high-quality visuals through meticulously written text prompts. These models mark a significant shift from the era when artists used personally-trainable generative models like Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). LTGMs have made the generation of visuals accessible to everyone, but this shift in attention has overshadowed the practice of "model crafting", whereas artists personalize their work by experimenting with training sets, model architectures, and hyperparameters in addition to combining, adapting and manipulating pre-trained models [14]. Model crafting offered artists a sense of craftsmanship and ownership over the creative process and its outcomes.

Jerome Pesenti has a few reasons to celebrate Meta's decision last week to release Llama 3, a powerful open source large language model that anyone can download, run, and build on. Pesenti used to be vice president of artificial intelligence at Meta and says he often pushed the company to consider releasing its technology for others to use and build on. But his main reason to rejoice is that his new startup will get access to an AI model that he says is very close in power to OpenAI's industry-leading text generator GPT-4, but considerably cheaper to run and more open to outside scrutiny and modification. "The release last Friday really feels like a game-changer," Pesenti says. His new company, Sizzle, an AI tutor, currently uses GPT-4 and other AI models, both closed and open, to craft problem sets and curricula for students.

Until now, AI-generated videos of people have tended to have some stiffness, glitchiness, or other unnatural elements that make them pretty easy to differentiate from reality. For the past several years, AI video startup Synthesia has produced these kinds of AI-generated avatars. But today it launches a new generation, its first to take advantage of the latest advancements in generative AI, and they are more realistic and expressive than anything we've seen before. While today's release means almost anyone will now be able to make a digital double, before the technology went public, Synthesia agreed to make one of Melissa Heikkilä, our senior AI reporter. This technological progress signals a much larger shift.