The rapid adoption and scrutiny around ChatGPT, the latest artificial intelligence model, highlights the exploding potential of AI. It also underscores a stark delta between AI's current capabilities and human willingness to embrace them. This untapped potential is perhaps most apparent in the public sector where AI is both championed and feared - offering exciting federal use cases but lacking policy guidance and maturity at scale. So how can agencies better leverage AI? Results of a recent SAIC survey uncover a need to improve overall AI readiness to enable the technology's integration and benefit from it. The independent survey of federal government executives revealed that while AI is on respondents' radar, fewer than one in five are "very" likely to adopt AI in the next year.

ChatGPT might well be the most famous, and potentially valuable, algorithm of the moment, but the artificial intelligence techniques used by OpenAI to provide its smarts are neither unique nor secret. Competing projects and open-source clones may soon make ChatGPT-style bots available for anyone to copy and reuse. Stability AI, a startup that has already developed and open-sourced advanced image-generation technology, is working on an open competitor to ChatGPT. "We are a few months from release," says Emad Mostaque, Stability's CEO. A number of competing startups, including Anthropic, Cohere, and AI21, are working on proprietary chatbots similar to OpenAI's bot.

TikTok and ByteDance officials have since 2019 been negotiating with a group of federal officials, known as the Committee on Foreign Investment in the United States, about which privacy standards and technical safeguards they'd need to adopt to satisfy U.S. national-security concerns. The company finalized its proposal in August and presented it to CFIUS, but it has yet to be approved, and CFIUS officials have declined to explain why.

Pearl, the global leader in dental AI solutions, and CareStack, a leading cloud-based dental practice management software, announced a partnership to integrate Pearl's Second Opinion real-time disease detection capabilities within CareStack's all-in-one practice management system, as well as extend CareStack users access to Pearl's clinical performance AI platform, Practice Intelligence . The partnership ensures that CareStack's customers have seamless comprehensive access to the most robust FDA-cleared AI feature set on the market. "CareStack equips a variety of dental practices around the country with the most transformative tools and technology designed to help streamline operations and optimize efficient workflows" "CareStack equips a variety of dental practices around the country with the most transformative tools and technology designed to help streamline operations and optimize efficient workflows," said Abhi Krishna, co-founder and CEO of CareStack. "Partnering with Pearl, we are able to help facilitate greater practice efficiency and improved patient outcomes by equipping our practitioners with dentistry's most advanced pathology detection and patient communication technology." Second Opinion, which will be available as a fully integrated service within CareStack's practice management system, is the first-and-only chairside AI software cleared by the FDA to help dentists detect numerous common conditions in both bitewing and periapical x-rays of adult teeth in patients as young as 12 years old.

Elon Musk's purchase of Twitter may have capped the opening chapter in the Information Wars, where free speech won a small but crucial battle. Full spectrum combat across the digital landscape, however, will only intensify, as a new report from the Brookings Institution, a key player in the censorship industrial complex, demonstrates. Reams of internal documents, known as the Twitter Files, show that social media censorship in recent years was far broader and more systematic than even we critics suspected. Worse, the files exposed deep cooperation – even operational integration – among Twitter and dozens of government agencies, including the FBI, Department of Homeland Security, DOD, CIA, Cybersecurity Infrastructure Security Agency (CISA), Department of Health and Human Services, CDC, and, of course, the White House. Government agencies also enlisted a host of academic and non-profit organizations to do their dirty work.

This month, French lawmakers are expected to pass legislation for the 2024 Paris Olympics, which, for the first time in France's history, will permit mass video surveillance powered by artificial intelligence (AI) systems. When governments embark on the slippery slope towards the expansion of surveillance powers, it has damning consequences for fundamental human rights, including the rights to privacy, equality and non-discrimination, as well as freedom of expression and peaceful assembly. Under the guise of ensuring security and fighting terrorism, the French authorities will be able to monitor the movements of millions of people from around the world, whether they are heading to or near stadiums, or using public transportation leading in or out of the premises of the grand sporting event. The need for security during the game is understandable, but transparency and legal justification are needed at every step of the way. Any proposal concerning security must comply with fundamental rights.

WASHINGTON, March 9 (Reuters) - The U.S. Chamber of Commerce on Thursday called for regulation of artificial intelligence technology to ensure it does not hurt growth or become a national security risk, a departure from the business lobbying group's typical anti-regulatory stance. While there is little in terms of proposed legislation for AI, the fast-growing artificial intelligence program ChatGPT that has drawn praise for its ability to write answers quickly to a wide range of queries has raised U.S. lawmakers' concerns about its impact on national security and education. The Chamber report argues policymakers and business leaders must quickly ramp up their efforts to establish a "risk-based regulatory framework" that will ensure AI is deployed responsibly. It added that AI is projected to add $13 trillion to global economic growth by 2030 and that it has made important contributions such as easing hospital nursing shortages and mapping wildfires to speed emergency management officials' response. The report emphasized the need to be ready for the technology's looming ubiquity and potential dangers.

Can you get excited about artificial intelligence (AI)? When I asked ChatGPT who my favourite artist was, it said I'd never publicly expressed a preference, because as an art historian I don't do "subjective opinions". Evidently, ChatGPT doesn't subscribe to The Art Newspaper. Even if it gave the correct answer--Van Dyck--I'd still not be excited. In a famous episode of the 1960s TV series The Prisoner, Patrick McGoohan's character is presented with an all-knowing computer which, he is told, will make man redundant.

For weeks now, Elon Musk has been preoccupied with worries about how many people are seeing his tweets. Last week, the Twitter CEO took his Twitter account private for a day to test whether that might boost the size of his audience. The move came after several prominent right-wing accounts that Musk interacts with complained that recent changes to Twitter had reduced their reach. On Tuesday, Musk gathered a group of engineers and advisors into a room at Twitter's headquarters looking for answers. Why are his engagement numbers tanking?

Adversarial attacks and defenses in machine learning and deep neural network have been gaining significant attention due to the rapidly growing applications of deep learning in the Internet and relevant scenarios. This survey provides a comprehensive overview of the recent advancements in the field of adversarial attack and defense techniques, with a focus on deep neural network-based classification models. Specifically, we conduct a comprehensive classification of recent adversarial attack methods and state-of-the-art adversarial defense techniques based on attack principles, and present them in visually appealing tables and tree diagrams. This is based on a rigorous evaluation of the existing works, including an analysis of their strengths and limitations. We also categorize the methods into counter-attack detection and robustness enhancement, with a specific focus on regularization-based methods for enhancing robustness. New avenues of attack are also explored, including search-based, decision-based, drop-based, and physical-world attacks, and a hierarchical classification of the latest defense methods is provided, highlighting the challenges of balancing training costs with performance, maintaining clean accuracy, overcoming the effect of gradient masking, and ensuring method transferability. At last, the lessons learned and open challenges are summarized with future research opportunities recommended.