GPU prices could follow RAM's big rise OpenAI's house of cards seems primed to collapse In 2025, it fell behind the one company it couldn't lose ground to: Google. OpenAI CEO Sam Altman speaks during the US Federal Reserve Board of Governors' Integrated Review of the Capital Framework for Large Banks Conference at the Federal Reserve in Washington, DC, on July 22, 2025. OpenAI is in a far less commanding position than it was following the public release of ChatGPT a few short years ago. Back in 2022, the sudden popularity of ChatGPT sent Google into a panic . The company was so worried about the possibility of the upstart chatbot disrupting its Search business, executives sounded a code red alert inside of the company and called Sergey Brin and Larry Page out of retirement to help it formulate a response to OpenAI.

PCWorld explores ChatGPT's image generation capabilities, covering prompt techniques, editing features, and the new Gallery for organizing GPT-4o images. Effective AI image creation requires clear, specific descriptions while avoiding overly detailed prompts that confuse the system.

Plus: Australia's social media ban for teens has just come into force. Stardust Solutions believes that it can solve climate change--for a price. The Israel-based geoengineering startup has said it expects nations will soon pay it more than a billion dollars a year to launch specially equipped aircraft into the stratosphere. Once they've reached the necessary altitude, those planes will disperse particles engineered to reflect away enough sunlight to cool down the planet, purportedly without causing environmental side effects. But numerous solar geoengineering researchers are skeptical that Stardust will line up the customers it needs to carry out a global deployment in the next decade. MIT Technology Review Narrated: Is this the electric grid of the future?

With a quarter of people in the UK using AI to find products, marketers must not only appeal to shoppers directly but to AI bots and their opaque decision-making process. With a quarter of people in the UK using AI to find products, marketers must not only appeal to shoppers directly but to AI bots and their opaque decision-making process. 'What to buy Dad for Christmas': is retail ready for the AI shopping shift? Consumer test drive: can AI do your Xmas gift shopping for you? While traditional internet search, social media - especially TikTok and Instagram - and simply wandering a local high street will still be the main routes to presents for most this year, about a quarter of people in the UK are already using AI to find the right products, according to PricewaterhouseCoopers.

GPU prices could follow RAM's big rise You can start using the apps for free, with some limitations. A ChatGPT user asks the chatbot to make an image more vibrant through Photoshop. At the time, the company said more software was on the way, and now one of the most popular professional applications is available through the chatbot. Starting today, you can access Photoshop, Acrobat and Adobe Express inside of ChatGPT. All the apps are free to use through OpenAI's website, though before you can begin generating PDFs and illustrations using Acrobat and Adobe Express, you'll need to sign into your Adobe account.

Keio University President Kohei Ito (left) and OpenAI Chief Strategy Officer Jason Kwon sign a memorandum of understanding on Tuesday in Tokyo. Keio University is working with OpenAI to integrate artificial intelligence into its education system. Keio University President Kohei Ito and OpenAI Chief Strategy Officer Jason Kwon signed a memorandum of understanding Tuesday, making Keio the first Japanese university to form a strategic partnership with the producer of ChatGPT. "We will develop an environment where students and researchers can proactively learn and utilize AI," Ito said. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Sam Altman's appearance on is part of a larger charm offensive currently being waged by the tech establishment. OpenAI CEO Sam Altman was at the center of Silicon Valley's most visible publicity push in recent memory Monday night when he appeared on . In a predictably softball interview with host Jimmy Fallon, Altman explained how ChatGPT has helped him alleviate the anxiety that comes with being a new parent. It was a distinctly clever, if somewhat surprising, choice from Altman who has mostly kept his personal life out of the media spotlight. But Altman is a salesman, and a good salesman understands the optics of good television.

This paper proposes a novel diffusion-based posterior sampling method within a plug-and-play (PnP) framework. Our approach constructs a probability transport from an easy-to-sample terminal distribution to the target posterior, using a warm-start strategy to initialize the particles. To approximate the posterior score, we develop a Monte Carlo estimator in which particles are generated using Langevin dynamics, avoiding the heuristic approximations commonly used in prior work. The score governing the Langevin dynamics is learned from data, enabling the model to capture rich structural features of the underlying prior distribution. On the theoretical side, we provide non-asymptotic error bounds, showing that the method converges even for complex, multi-modal target posterior distributions. These bounds explicitly quantify the errors arising from posterior score estimation, the warm-start initialization, and the posterior sampling procedure. Our analysis further clarifies how the prior score-matching error and the condition number of the Bayesian inverse problem influence overall performance. Finally, we present numerical experiments demonstrating the effectiveness of the proposed method across a range of inverse problems.

The emergence of large language models (LLMs) has sparked much interest in creating LLM-based digital populations that can be applied to many applications such as social simulation, crowdsourcing, marketing, and recommendation systems. A digital population can reduce the cost of recruiting human participants and alleviate many concerns related to human subject study. However, research has found that most of the existing works rely solely on LLMs and could not sufficiently capture the accuracy and diversity of a real human population. To address this limitation, we propose CrowdLLM that integrates pretrained LLMs and generative models to enhance the diversity and fidelity of the digital population. We conduct theoretical analysis of CrowdLLM regarding its great potential in creating cost-effective, sufficiently representative, scalable digital populations that can match the quality of a real crowd. Comprehensive experiments are also conducted across multiple domains (e.g., crowdsourcing, voting, user rating) and simulation studies which demonstrate that CrowdLLM achieves promising performance in both accuracy and distributional fidelity to human data.

Abstract--We present a Fourier-enhanced recurrent neural network (RNN) for downscaling electrical loads. The model combines (i) a recurrent backbone driven by low-resolution inputs, (ii) explicit Fourier seasonal embeddings fused in latent space, and (iii) a self-attention layer that captures dependencies among high-resolution components within each period. Energy policy and infrastructure investment decisions require an integrated system-wide perspective that captures the interdependencies of supply, conversion, and end-use sectors, as well as feedback from macroeconomic, technology-cost, and policy drivers. Many such energy modeling systems exist [1], of which the National Energy Modeling System (NEMS), developed by the U.S. Energy Information Administration (EIA) [2], is widely used by policymakers and stakeholders for this very reason. However, as noted in the study of energy plant pollution studies provided by NEMS [3], using temporally and spatially averaged data may significantly miss essential features and pricing signals.