Sen. McConnell supports President Biden's authority for Iran airstrikes, urging stronger action against terrorist threats. President Biden's administration warned Iran of an impending terrorist attack prior to a blast that killed 94 people in early January, a U.S. official tells Fox News Digital. The bombing attack took place at a memorial ceremony for Iranian General Qasem Soleimani, who was killed by a U.S. drone strike on Jan. 3, 2020 under former President Trump's administration. The U.S. official did not detail Iran's response to the warning. "Prior to ISIS' terrorist attack on January 3, 2024, in Kerman, Iran, the U.S. Government provided Iran with a private warning that there was a terrorist threat within Iranian borders," the official told Fox. "The U.S. Government followed a longstanding'duty to warn' policy that has been implemented across administrations to warn governments against potential lethal threats. We provide these warnings in part because we do not want to see innocent lives lost in terror attacks," the official added.

Human Rights Watch said Thursday that Burkina Faso's security forces last year killed at least 60 civilians in three different drone strikes, which the group says may have constituted war crimes. The West African nation's government claimed the strikes targeted extremists, including jihadi fighters and rebel groups that have been operating in many remote communities. The accusation by the New York-based watchdog were the latest in a string of similar charges raised by various rights groups. "The government should urgently and impartially investigate these apparent war crimes, hold those responsible to account, and provide adequate support for the victims and their families," HRW said in a new report. A mural is seen in Ouagadougou, Burkina Faso, on March 1, 2023.

When I first reviewed the Ray-Ban Meta smart glasses, I wrote that some of the most intriguing features were the ones I couldn't try out yet. Of these, the most interesting is what Meta calls "multimodal AI," the ability for the glasses to respond to queries based on what you're looking at. For example, you can look at text and ask for a translation, or ask it to identify a plant or landmark. The other major update I was waiting for was the addition of real-time information to the Meta AI assistant. Last fall, the assistant had a "knowledge cutoff" of December 2022, which significantly limited the types of questions it could answer. But Meta has started to make both of these features available (multimodal search is in an "early access" period").

Even the cleverest, most cunning artificial intelligence algorithm will presumably have to obey the laws of silicon. Its capabilities will be constrained by the hardware that it's running on. Some researchers are exploring ways to exploit that connection to limit the potential of AI systems to cause harm. The idea is to encode rules governing the training and deployment of advanced algorithms directly into the computer chips needed to run them. In theory--the sphere where much debate about dangerously powerful AI currently resides--this might provide a powerful new way to prevent rogue nations or irresponsible companies from secretly developing dangerous AI.

International watchdog Human Rights Watch (HRW) on Thursday accused the Burkina Faso army of killing at least 60 civilians in drone strikes which the government said targeted armed groups. The deaths occurred in three military drone strikes since August, two at crowded markets and another at a funeral, the rights group said in a new report. Since becoming head of state after a 2022 coup, Captain Ibrahim Traore has focused on a strong security response in reclaiming swathes of territory controlled by armed groups affiliated with al-Qaeda and the ISIS (ISIL) group. But those efforts have often been criticised as heavy-handed, with the HRW report being the latest instance of that criticism. HRW said it interviewed dozens of witnesses between September and November 2023 and analysed photographs, videos and satellite images.

Concerns about AI interfering with the 2024 elections are well-founded, yet not unprecedented in recent history. In 1975, the Asilomar Conference on Recombinant DNA foreshadowed today's AI concerns. Asilomar set the precedent on how to respond to changes in scientific knowledge. According to conference organizers, biochemist Paul Berg and molecular biologist Maxine Singer, the proper response to new scientific knowledge was to develop guidelines that governed how to regulate it. They were as wrong as those asking for AI regulation.

This story was produced with support from the Pulitzer Center's AI Accountability Network. Rohtak and New Delhi, India: Dhuli Chand was 102 years old on September 8, 2022, when he led a wedding procession in Rohtak, a district town in the north Indian state of Haryana. As is customary in north Indian weddings, he sat on a chariot in his wedding finery, wearing garlands of Indian rupee notes, while a band played celebratory music and family members and villagers accompanied him. But instead of a bride, Chand was on his way to meet government officials. Chand resorted to the antic to prove to officials that he was not only alive but also lively.

Some investors are already gaming out how the U.S. 2024 presidential election could impact markets, as former U.S. President Donald Trump's victory in the New Hampshire Republican primary brings him closer to a rematch with Democratic President Joe Biden Any calculation of how stocks, bonds and currencies could react to the results of the November vote comes with caveats -- especially since it's early in the year and betting markets are split on which candidate will prevail. Most investors also believe drivers such as Federal Reserve policy, the economic cycle and corporate earnings will ultimately matter more for markets over the long term. Nevertheless, expectations for politically fueled moves in asset prices around the 2024 vote are high among some strategists, with Goldman Sachs saying the election could be a "major market event."

Fine-grained few-shot entity extraction in the chemical domain faces two unique challenges. First, compared with entity extraction tasks in the general domain, sentences from chemical papers usually contain more entities. Moreover, entity extraction models usually have difficulty extracting entities of long-tailed types. In this paper, we propose Chem-FINESE, a novel sequence-to-sequence (seq2seq) based few-shot entity extraction approach, to address these two challenges. Our Chem-FINESE has two components: a seq2seq entity extractor to extract named entities from the input sentence and a seq2seq self-validation module to reconstruct the original input sentence from extracted entities. Inspired by the fact that a good entity extraction system needs to extract entities faithfully, our new self-validation module leverages entity extraction results to reconstruct the original input sentence. Besides, we design a new contrastive loss to reduce excessive copying during the extraction process. Finally, we release ChemNER+, a new fine-grained chemical entity extraction dataset that is annotated by domain experts with the ChemNER schema. Experiments in few-shot settings with both ChemNER+ and CHEMET datasets show that our newly proposed framework has contributed up to 8.26% and 6.84% absolute F1-score gains respectively.

This paper introduces a novel approach called "friendly attack" aimed at enhancing the performance of error correction channel codes. Inspired by the concept of adversarial attacks, our method leverages the idea of introducing slight perturbations to the neural network input, resulting in a substantial impact on the network's performance. By introducing small perturbations to fixed-point modulated codewords before transmission, we effectively improve the decoder's performance without violating the input power constraint. The perturbation design is accomplished by a modified iterative fast gradient method. This study investigates various decoder architectures suitable for computing gradients to obtain the desired perturbations. Specifically, we consider belief propagation (BP) for LDPC codes; the error correcting code transformer, BP and neural BP (NBP) for polar codes, and neural BCJR for convolutional codes. We demonstrate that the proposed friendly attack method can improve the reliability across different channels, modulations, codes, and decoders. This method allows us to increase the reliability of communication with a legacy receiver by simply modifying the transmitted codeword appropriately.