SoftBank Group, OpenAI and Oracle are forming a half-a-trillion dollar venture in the United States that will develop artificial intelligence infrastructure with warp-speed-type support from the U.S. government. SoftBank Chairman and CEO Masayoshi Son will be the chairman of Stargate, the new company being formed, while SoftBank will be responsible for financial management of the venture. Arm Holdings, a Nasdaq-listed subsidiary of SoftBank, will provide chip technology. Microsoft, Nvidia and Oracle will also be key vendors.

OpenAI kicked off the AI race in 2022 with the launch of its ChatGPT bot, which offered lifelike responses to questions and showcased the rapid advances in the technology. It has prompted a gush of investment, including in the specialised data centres needed to power the computing. But the projected surge in demand for the centres, which will require huge amounts of power to run and money to be built, has raised concerns about the impact on energy supplies and questions about the role of foreign investors. In one of his final acts in the White House, former President Joe Biden put forward rules that would restrict exports of AI-related chips to dozens of countries around the world, saying the move would help the US control the industry. He also issued orders related to the development of data centres on government land, which spotlighted a role for clean energy in powering the centres.

President Donald Trump on Tuesday talked up a joint venture investing up to 500 billion for infrastructure tied to artificial intelligence by a new partnership formed by OpenAI, Oracle and SoftBank. The new entity, Stargate, will start building out data centers and the electricity generation needed for the further development of the fast-evolving AI in Texas, according to the White House. The initial investment is expected to be 100 billion and could reach five times that sum. "It's big money and high quality people," said Trump, adding that it's "a resounding declaration of confidence in America's potential" under his new administration. Joining Trump fresh off his inauguration at the White House were Masayoshi Son of SoftBank, Sam Altman of OpenAI and Larry Ellison of Oracle.

United States President Donald Trump has announced a 500bn joint venture with Texas-based tech firm Oracle, Japan's SoftBank and ChatGPT-maker OpenAI to advance artificial intelligence infrastructure. Trump made the announcement at a White House event on Tuesday that was joined by Softbank CEO Masayoshi Son, OpenAI CEO Sam Altman, and Oracle Chief Technology Officer Larry Ellison. Trump said the venture would be the largest AI infrastructure project in history "by far" and represented "a resounding declaration of confidence in America's potential" under his new administration. As you know, there's great competition for AI and other things and they are coming in at the highest level," Trump said. Shares of Tokyo-based Softbank Group soared more than 8 percent on Wednesday following the announcement.

OpenAI CEO Sam Altman, Oracle founder Larry Ellison and SoftBank CEO Masayoshi Son comment on President Trump's Stargate AI investment project on'Special Report.' The three tech CEOs who have joined forces in President Donald Trump's multi-billion dollar artificial intelligence infrastructure project defended the venture as an investment that "impacts all of humanity." "This is a very large investment that affects all of humanity," Oracle founder Larry Ellison told Fox News chief political anchor Bret Baier on "Special Report" on Tuesday. President Trump unveiled a massive AI infrastructure project from the private sector on the first full day of his second term in office on Tuesday. During a speech at the White House, Trump announced that Softbank, OpenAI and Oracle have joined forces for a project called Stargate to build data centers in the U.S. for powering AI.

OpenAI did not respond to questions about its lobbying efforts. But perhaps more important, the disclosure is a clear signal of the company's arrival as a political player, as its first year of serious lobbying ends and Republican control of Washington begins. While OpenAI's lobbying spending is still dwarfed by its peers'--Meta tops the list of Big Tech spenders, with more than 24 million in 2024--the uptick comes as it and other AI companies have helped redraw the shape of AI policy. For the past few years, AI policy has been something like a whack-a-mole response to the risks posed by deepfakes and misinformation. But over the last year, AI companies have started to position the success of the technology as pivotal to national security and American competitiveness, arguing that the government must therefore support the industry's growth.

Generative AI technologies, particularly Large Language Models (LLMs), have transformed information management systems but introduced substantial biases that can compromise their effectiveness in informing business decision-making. This challenge presents information management scholars with a unique opportunity to advance the field by identifying and addressing these biases across extensive applications of LLMs. Building on the discussion on bias sources and current methods for detecting and mitigating bias, this paper seeks to identify gaps and opportunities for future research. By incorporating ethical considerations, policy implications, and sociotechnical perspectives, we focus on developing a framework that covers major stakeholders of Generative AI systems, proposing key research questions, and inspiring discussion. Our goal is to provide actionable pathways for researchers to address bias in LLM applications, thereby advancing research in information management that ultimately informs business practices. Our forward-looking framework and research agenda advocate interdisciplinary approaches, innovative methods, dynamic perspectives, and rigorous evaluation to ensure fairness and transparency in Generative AI-driven information systems. We expect this study to serve as a call to action for information management scholars to tackle this critical issue, guiding the improvement of fairness and effectiveness in LLM-based systems for business practice.

Deep generative models, such as generative adversarial networks and diffusion models, have recently emerged as powerful tools for planning tasks and behavior synthesis in autonomous systems. Various guidance strategies have been introduced to steer the generative process toward outputs that are more likely to satisfy the planning objectives. These strategies avoid the need for model retraining but do not provide any guarantee that the generated outputs will satisfy the desired planning objectives. To address this limitation, we introduce certified guidance, an approach that modifies a generative model, without retraining it, into a new model guaranteed to satisfy a given specification with probability one. We focus on Signal Temporal Logic specifications, which are rich enough to describe nontrivial planning tasks. Our approach leverages neural network verification techniques to systematically explore the latent spaces of the generative models, identifying latent regions that are certifiably correct with respect to the STL property of interest. We evaluate the effectiveness of our method on four planning benchmarks using GANs and diffusion models. Our results confirm that certified guidance produces generative models that are always correct, unlike existing guidance methods that are not certified.

Donald Trump has unveiled what he called "the largest AI infrastructure project in history" – a 500bn joint venture between OpenAI, Oracle and SoftBank that aims to build a network of data centres across the US. The new partnership, dubbed Stargate, aims to construct essential data centers and computing infrastructure needed to power artificial intelligence development and, according to Trump, create over 100,000 American jobs "almost immediately". The launch marks one of Trump's first major business initiatives since returning to office and comes as the US looks for new ways to maintain an edge against China in AI capabilities. "China is a competitor and others are competitors. We want it to be in this country," Trump said during the White House announcement, flanked by Oracle's Larry Ellison, SoftBank's Masayoshi Son and OpenAI's Sam Altman.

This paper proposes a vine copula autoencoder to construct flexible generative models for high-dimensional, structured data in three steps. By exploiting vine copulas, the proposed approach can transform any already trained autoencoder into a flexible generative model at a low computational cost, and its good performance was nicely demonstrated. This is a nice contribution to the field of constructing deep generative models.