Center for AI Safety Director Dan Hendrycks explains concerns about how the rapid growth of artificial intelligence could impact society. Judges are likely to take concerns over artificial intelligence into their own hands and create their own rules for the tech in courtrooms, experts say. U.S. District Judge Brantley Starr of the Northern District of Texas may have been a pioneer last week when he required lawyers who appear in his courtroom to certify they did not use artificial intelligence programs, such as ChatGPT, to draft their filings without a human checking for accuracy. "We're at least putting lawyers on notice, who might not otherwise be on notice, that they can't just trust those databases," Starr, a Trump appointed judge, told Reuters. "They've got to actually verify it themselves through a traditional database."

LGBTQ advocate Heather Hester scolded Target's "rainbow capitalism" after the retailer dialed back Pride displays (Reuters) Subscribe now to get Fox News First in your email. And here's what you need to know to start your day ... EYE ON THE TARGET - Retailer's $15B loss in'stunning collapse' should serve as warning to CEOs, 'Shark Tank' star says. 'UNDENIABLE FACTS': - Tim Scott earns praise after leaving liberal'View' host'speechless.' TARMAC TROUBLE - Deputies remove handcuff and remove unruly passenger from Southwest plane before takeoff. SCIENTOLOGY SPOTLIGHT - Danny Masterson, Tom Cruise and Leah Remini illuminate Hollywood church drama.

Kyiv, Ukraine – The enemy "turns border districts into a dead zone", a war correspondent covering the Russia-Ukraine war wrote on his Telegram channel on Saturday. But retired colonel Yuri Kotyonok, who reported from almost every war zone in the former Soviet Union and whose Telegram channel has 420,000 subscribers, was not talking about Ukraine. The districts belong to the western Russian region of Belgorod that borders Ukraine. In recent months, it has been shelled and attacked by drones hundreds of times – 130 in May alone, Russian officials say. As a result, 32 people were killed and 157 wounded, regional governor Vyacheslav Gladkov said in late April.

In April and May, surgeons at West Virginia University placed thin strips of a cellophane-like material on the brains of three patients. Made by New York-based startup Precision Neuroscience, the thumbnail-sized strips are designed to conform to the surface of the brain without damaging its delicate tissue. During the 15 minutes the devices were in place, the implants were able to read, record, and map electrical activity in part of the patients' temporal lobes, which helps process sensory input. The patients were already in the hospital to have brain tumors removed, and doctors used Precision's devices alongside standard electrodes to determine the location of their tumors. Although just a small pilot study, it puts Precision one step closer to building a brain-computer interface, or BCI--a system that provides a direct communication link between the brain and an external device.

Last week, a group of tech company leaders and AI experts pushed out another open letter, declaring that mitigating the risk of human extinction due to AI should be as much of a global priority as preventing pandemics and nuclear war. So how do companies themselves propose we avoid AI ruin? One suggestion comes from a new paper by researchers from Oxford, Cambridge, the University of Toronto, the University of Montreal, Google DeepMind, OpenAI, Anthropic, several AI research nonprofits, and Turing Prize winner Yoshua Bengio. They suggest that AI developers should evaluate a model's potential to cause "extreme" risks at the very early stages of development, even before starting any training. These risks include the potential for AI models to manipulate and deceive humans, gain access to weapons, or find cybersecurity vulnerabilities to exploit.

On Tuesday, June 6 at 19:30 GMT: The role of artificial intelligence has long been debated in military communities. But as recent leapfrog advancements in technology have garnered headlines about the effects on how we live, work and create, consideration of the role of AI in warfare has also gained urgency with some declaring this the era of the AI arms race. From autonomous weapons and AI-driven strategic decision making to generative misinformation, experts warn that the advancements could completely transform how wars are fought. Russian President Vladimir Putin once declared that "whoever becomes the leader in this sphere will become the ruler of the world." As the technology continues to improve at a rapid pace, global leaders are beginning to push for consensus on what Responsible AI (RAI) means in the context of militaries. In this episode of The Stream, we'll look at how artificial intelligence is revolutionising contemporary warfare and discuss what efforts are underway to keep it in check.

Harvey Castro talks about how AI cold be used in cold cases and the symbiotic relationship between AI and a detective. A new bill introduced in the House of Representatives on Monday is aimed at making sure American consumers know the difference between fantasy and reality online by cracking down on generative artificial intelligence technology. Rep. Ritchie Torres, D-N.Y., is leading the effort on the AI Disclosure Act of 2023, which would force AI-generated content to include the disclaimer, "Disclaimer: this output has been generated by artificial intelligence." In a statement announcing the bill, Torres predicted that "regulatory framework for managing the existential risks of AI will be one of the central challenges confronting Congress in the years and decades to come." He noted risks in going too far with policing AI as well as not regulating it enough.

Naftali Bennett spoke exclusively with Fox News Digital about the benefits of AI and the need to set parameters for its use now. The new drone swarm test conducted by the U.S. and its allies last week shows some of the wider applications of artificial intelligence (AI) in military settings while also raising some potential issues about how multiple militaries will be able to cooperate. "Just like coordination is needed to conduct classic, joint and coalition maneuvers and military operations, similar clear definitions of boundaries, tasks, responsibility and authority are needed to control and de-conflict drone swarms," retired Brig. Gen. Uri Engelhard, AI and cyber expert, member of the Israel Defense and Security Forum, told Fox News Digital. "If planned and conducted properly, the deployment of drone swarms should not be more challenging than other military activities."

Relation extraction (RE) involves identifying the relations between entities from unstructured texts. RE serves as the foundation for many natural language processing (NLP) applications, such as knowledge graph completion, question answering, and information retrieval. In recent years, deep neural networks have dominated the field of RE and made noticeable progress. Subsequently, the large pre-trained language models (PLMs) have taken the state-of-the-art of RE to a new level. This survey provides a comprehensive review of existing deep learning techniques for RE. First, we introduce RE resources, including RE datasets and evaluation metrics. Second, we propose a new taxonomy to categorize existing works from three perspectives (text representation, context encoding, and triplet prediction). Third, we discuss several important challenges faced by RE and summarize potential techniques to tackle these challenges. Finally, we outline some promising future directions and prospects in this field. This survey is expected to facilitate researchers' collaborative efforts to tackle the challenges of real-life RE systems.

This paper surveys machine-learning-based super-resolution reconstruction for vortical flows. Super resolution aims to find the high-resolution flow fields from low-resolution data and is generally an approach used in image reconstruction. In addition to surveying a variety of recent super-resolution applications, we provide case studies of super-resolution analysis for an example of two-dimensional decaying isotropic turbulence. We demonstrate that physics-inspired model designs enable successful reconstruction of vortical flows from spatially limited measurements. We also discuss the challenges and outlooks of machine-learning-based super-resolution analysis for fluid flow applications. The insights gained from this study can be leveraged for super-resolution analysis of numerical and experimental flow data.