Federated Learning is a leading framework for training ML and AI models collaboratively across numerous user devices or databases. We study the trade-offs among estimation accuracy, privacy constraints, and communication cost for differentially private (DP) federated M estimation. The two standard methods in the literature are FedAvg, which may suffer from high federation bias, and FedSGD, which can incur high communication cost. Aimed at improving accuracy at a reduced communication cost, we propose FedHybrid, which uses FedSGD starting with an improved initialization by the FedAvg estimator. We propose FedNewton, which averages local Newton iterations to reduce bias in FedAvg, achieving an estimation accuracy comparable to FedSGD with much fewer communication rounds when the number of clients grows sufficiently slowly. We establish finite sample upper bounds on the mean-squared error rates of the DP versions of these estimators as functions of the number of clients, local sample sizes, privacy budget, and number of iterations. We further derive a minimax lower bound on the MSE of any iterative private federated procedure that provides a benchmark to assess the optimality gap of these methods. We numerically evaluate our methods for training a logistic regression and a neural network on the computer vision datasets MNIST and CIFAR-10.

Many tasks in modern machine learning are observed to involve heavy-tailed gradient noise during the optimization process. To manage this realistic and challenging setting, new mechanisms, such as gradient clipping and gradient normalization, have been introduced to ensure the convergence of first-order algorithms. However, adaptive gradient methods, a famous class of modern optimizers that includes popular $\mathtt{Adam}$ and $\mathtt{AdamW}$, often perform well even without any extra operations mentioned above. It is therefore natural to ask whether adaptive gradient methods can converge under heavy-tailed noise without any algorithmic changes. In this work, we take the first step toward answering this question by investigating a special case, $\mathtt{AdaGrad}$, the origin of adaptive gradient methods. We provide the first provable convergence rate for $\mathtt{AdaGrad}$ in non-convex optimization when the tail index $p$ satisfies $4/3

Elon Musk, left, and Sam Altman. Elon Musk, left, and Sam Altman. How Sam Altman's victory over Elon Musk clears way for OpenAI's trillion-dollar ambitions OpenAI's plans now seem all but guaranteed, given that the world's richest man couldn't put a stop to them On Monday morning, a jury in Oakland, California, handed a resounding victory to Sam Altman and OpenAI in their long, bitter courtroom battle with Elon Musk. The federal jury found Altman, OpenAI and its president, Greg Brockman, not liable for Elon Musk's claims that they unjustly enriched themselves and broke a founding contract made with Musk when founding the startup. The unanimous verdict, delivered after less than two hours of deliberation, is a stark rebuke of Musk and his lawyer's claims that Altman "stole a charity" through his leadership of OpenAI.

Pope Leo XIV holds the weekly general audience in St. Peter's Square at the Vatican on May 13. | REUTERS VATICAN CITY - Pope Leo will address the rise of artificial intelligence in his first in-depth text outlining his concerns, the Vatican said on Monday, adding that it would be unveiled on May 25 by the pontiff himself. The document, known as an encyclical, is likely to decry the use of AI in warfare and address how the technology is challenging workers' rights, according to sources. It will be titled "Magnifica Humanitas" (Magnificent Humanity) and was formally signed by the pope on Friday ahead of publication, a Vatican statement said. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right.

Researchers at the University of Cambridge are using satellite data and AI in an effort to slow the decline in Britain's hedgehog population. Using an AI tool called Tessera, which analyses detailed images of the UK gathered from space, experts can precisely determine locations of hedgehog habitats - and where these are disappearing. The resulting maps capture landscapes in minute detail, including down to individual hedgerows, while AI can accurately predict hedgehog-friendly places obscured by cloud cover. Those behind the project hope it will help to shed light not just on where hedgehogs live across the UK, but barriers preventing them from finding food and mates. The researchers say Tessera's outputs can be used to track the impact of new housing developments and other environmental changes on landscapes that could affect hedgehogs over time.

People attend a jobs fair in London. Only 24% of the members of public surveyed thought AI was a positive thing for humanity. People attend a jobs fair in London. Only 24% of the members of public surveyed thought AI was a positive thing for humanity. One in three university students think AI will wipe out jobs so rapidly it will trigger civil unrest, according to a survey by King's College London (KCL).

The federal jury in Oakland, California, found Altman, OpenAI and its president, Greg Brockman, not liable for Elon Musk's claims that they unjustly enriched themselves and broke a founding contract made with Musk when founding the startup. The verdict, delivered after less than two hours of deliberation, is a stark rebuke of Musk and his lawyer's claims that Altman "stole a charity" through his leadership of OpenAI . It also provides the AI firm with a clear path ahead to pursue going public later this year at about a $1tn valuation . The jury's finding is a non-binding, advisory verdict that left Judge Yvonne Gonzalez Rogers with ultimate power to issue her own ruling in the case. Gonzalez Rogers immediately said that she would agree with the jury's decision and dismissed Musk's claims.

The complaint says park visitors don't get sufficient notice they're being scanned. Disney is being sued over use of facial recognition technology at its amusement parks. The class action lawsuit alleges that the entertainment brand does not adequately inform guests that it scans people's faces at the entrances to Disneyland and California Adventure. The complaint is seeking at least $5 million on behalf of park visitors. Guests should be able to expressly opt in to this type of sensitive facial recognition technology with written consent -- the onus of privacy rights should not be on the victim, writes Blake Yagman, a lawyer for the proposed class of visitors, in the complaint.

Elon Musk just lost another lawsuit. Elon Musk, the world's richest man, has not been winning in court lately. His loss on Monday in his lawsuit against OpenAI and its co-founder Sam Altman is the latest in a string of legal defeats or settlements. Late last year he agreed to settle with former Twitter executives and thousands of former employees of the social platform, which he has renamed X, after fighting for years to pay them nothing. Then in March, he lost a case brought against him by investors of Twitter, who claimed they were misled by public statements he made during the takeover.

Sony is ending PC releases for future major single-player narrative games like Spider-Man and God of War to strengthen its PlayStation console business. PCWorld reports this significant shift affects PC gamers who previously enjoyed these popular PlayStation exclusives on their platform. Existing PC ports will remain available, and co-op titles like Helldivers 2 may still come to PC as Sony refocuses against Nintendo, Microsoft, and Valve competition. Well, we knew it was coming, but now it's more or less official. According to reports coming out of a PlayStation Studios meeting today, major single-player narrative games from Sony's first-party publisher will no longer be coming to PC. That marks the end of a short but enjoyable time of games like and coming to PC gamers. Oh, and if you were still hoping for, maybe just give up on that particular pony.