Sam Altman, the CEO of artificial intelligence lab OpenAI, told a Senate panel he welcomes federal regulation on the technology "to mitigate" its risks. The artificial intelligence field needs an international watchdog to regulate future superintelligence, according to the founder of OpenAI. In a blog post from CEO Sam Altman and company leaders Greg Brockman and Ilya Sutskever, the group said – given potential existential risk – the world "can't just be reactive," comparing the tech to nuclear energy. To that end, they suggested coordination among leading development efforts, highlighting that there are "many ways this could be implemented," including a project set up by major governments or curbs on annual growth rates. "Second, we are likely to eventually need something like an IAEA for superintelligence efforts; any effort above a certain capability (or resources like compute) threshold will need to be subject to an international authority that can inspect systems, require audits, test for compliance with safety standards, place restrictions on degrees of deployment and levels of security, etc." they asserted.

Every time you post a photo, respond on social media, make a website, or possibly even send an email, your data is scraped, stored, and used to train generative AI technology that can create text, audio, video, and images with just a few words. This has real consequences: OpenAI researchers studying the labor market impact of their language models estimated that approximately 80 percent of the US workforce could have at least 10 percent of their work tasks affected by the introduction of large language models (LLMs) like ChatGPT, while around 19 percent of workers may see at least half of their tasks impacted. In other words, the data you created may be putting you out of a job. When a company builds its technology on a public resource--the internet--it's sensible to say that that technology should be available and open to all. But critics have noted that GPT-4 lacked any clear information or specifications that would enable anyone outside the organization to replicate, test, or verify any aspect of the model.

Researchers at America's Pacific Northwest National Laboratory (PNNL) are developing machine learning techniques to help the Feds crack down on potentially rogue nuclear weapons. Suffice to say, it's generally illegal for any individual or group to own a nuclear weapon, certainly in the United States. Yes, there are the five officially recognized nuclear-armed nations – France, Russia, China, the UK, and the US – whose governments have a stash of these devices. And there are countries that have signed the United Nations' Treaty on the Prohibition of Nuclear Weapons, meaning they've promised not to "develop, test, produce, acquire, possess, stockpile, use or threaten to use" these gadgets. So if anyone has a nuke in their possession, it's because they are a country in the official nuclear-armed club, they are a government that's produced its own nukes, a terrorist who stole, bought, or somehow built one themselves, or some other sketchy scenario, in America's eyes at least.

Technology developed at Argonne can help narrow the field of candidates for molten salts, a new study demonstrates. Scientists are searching for new materials to advance the next generation of nuclear power plants. In a recent study, researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory showed how artificial intelligence could help pinpoint the right types of molten salts, a key component for advanced nuclear reactors. The ability to absorb and store heat makes molten salt important to clean energy and national climate goals. Molten salts can serve as both coolant and fuel in nuclear power reactors that generate electricity without emitting greenhouse gases.

Abstract: Having the Fifth Generation (5G) mobile communication system recently rolled out in many countries, the wireless community is now setting its eyes on the next era of Sixth Generation (6G). Inheriting from 5G its focus on industrial use cases, 6G is envisaged to become the infrastructural backbone of future intelligent industry. Especially, a combination of 6G and the emerging technologies of Digital Twins (DT) will give impetus to the next evolution of Industry 4.0 (I4.0) systems. Here we provide a vision for the future 6G industrial DT ecosystem, which shall bridge the gaps between humans, machines, and the data infrastructure, and therewith enable numerous novel application scenarios. Subsequently, we explore the technical challenges that are brought by such ambitions, and identify the key enabling technologies that may help tackle down these issues.

On the evening of Sunday, Sept. 23, 1962, millions of American families finished their dinners, turned on their televisions and were introduced to The Jetsons, a cartoon sitcom produced by the legendary team of Hanna-Barbera. Set in 2062, The Jetsons captured the technological optimism of the time and projected it into a space-age, gadget-fueled vision of the future, inviting its viewers to imagine the dazzling possibilities that the current wave of technological achievement could one day realize. In the end, The Jetsons was a rather tame, pedestrian sitcom about a family that reinforced traditional gender and family roles, knew little of the social issues of the time (it was, for example, unbearably white), and effectively glorified the consumerist, suburban lifestyle. But as a template for a technology-driven American future, it was no less than iconic. The Jetsons debuted five years after the Soviets had launched Sputnik, four years after the opening of the first commercial nuclear power plant in the U.S., and 16 months after President John F. Kennedy set a goal of putting a man on the moon by the decade's end. Fifteen years earlier, scientists at AT&T's Bell Labs invented the transistor, and soon after, miniature (by contemporary standards) transistor radios were found in many households.

Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! The world has averted the climate crisis thanks to finally adopting nuclear power for the majority of power generation. Conventional wisdom is now that nuclear power plants are a problem of complexity; Three Mile Island is now a punchline rather than a disaster. Fears around nuclear waste and plant blowups have been alleviated primarily through better software automation.

Unlike fossil fuel-fired power plants, nuclear power plants provide large amounts of low-carbon electricity. But the expense of running these plants has made it difficult for them to stay open. Researchers at the U.S. Department of Energy's (DOE) Argonne National Laboratory are building systems that could make nuclear energy more competitive using artificial intelligence. Argonne is midway through a $1 million, three-year project to explore how smart, computerized systems could change the economics. Funded by the DOE Office of Nuclear Energy's Nuclear Energy Enabling Technologies program, the project aims to create a computer architecture that could detect problems early and recommend appropriate actions to human operators.

Argonne scientists are building systems to streamline operations and maintenance at reactors. Nuclear power plants provide large amounts of electricity without releasing planet-warming pollution. But the expense of running these plants has made it difficult for them to stay open. If nuclear is to play a role in the U.S. clean energy economy, costs must come down. Scientists at the U.S. Department of Energy's (DOE) Argonne National Laboratory are devising systems that could make nuclear energy more competitive using artificial intelligence.

LEMONT, Ill.--(BUSINESS WIRE)--Nuclear power plants provide large amounts of electricity without releasing planet-warming pollution. But the expense of running these plants has made it difficult for them to stay open. If nuclear is to play a role in the U.S. clean energy economy, costs must come down. Scientists at the U.S. Department of Energy's (DOE) Argonne National Laboratory are devising systems that could make nuclear energy more competitive using artificial intelligence. Nuclear power plants are expensive in part because they demand constant monitoring and maintenance to ensure consistent power flow and safety.