Rep. Rob Wittman, R-Va., joins'Fox News Live' to react to the United States Air Force's unveiling of its new B-21 raider stealth bomber, named'The Raider' for Jimmy Doolittle's famous bombing raid on Japan in WW2. With the launch of the Air Force's hypersonic missile off the coast of California earlier this month, the Navy's development of water-based drones over the summer and the recent unveiling of the B-21 Raiders, the U.S. military has made major technological advancements over the past year. The military unveiled the U.S. Air Force B-21 Raider in Palmdale, California. The B-21 Raider is the first new American bomber aircraft in more than three decades. In an email to Fox News Digital, a spokesperson confirmed the Air Force would transition its three-bomber fleet to a two-bomber fleet of B-21s and modernized B-52s.

We introduce a new open information extraction (OIE) benchmark for pre-trained language models (LM). Recent studies have demonstrated that pre-trained LMs, such as BERT and GPT, may store linguistic and relational knowledge. In particular, LMs are able to answer ``fill-in-the-blank'' questions when given a pre-defined relation category. Instead of focusing on pre-defined relations, we create an OIE benchmark aiming to fully examine the open relational information present in the pre-trained LMs. We accomplish this by turning pre-trained LMs into zero-shot OIE systems. Surprisingly, pre-trained LMs are able to obtain competitive performance on both standard OIE datasets (CaRB and Re-OIE2016) and two new large-scale factual OIE datasets (TAC KBP-OIE and Wikidata-OIE) that we establish via distant supervision. For instance, the zero-shot pre-trained LMs outperform the F1 score of the state-of-the-art supervised OIE methods on our factual OIE datasets without needing to use any training sets. Our code and datasets are available at https://github.com/cgraywang/IELM

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The U.S. Army test-fired Javelin anti-tank missiles at a recent exhibition in Fort Hood, Texas to demonstrate technological advancement in its fighting capabilities. During a series of weapons drills and exercises, soldiers fired Javelins and .50-caliber A Javelin missile fired by soldiers with the 2nd Stryker Brigade Combat Team, separate from the exhibition in Texas.

The Army's plans for robotic wingmen in vehicle formations, a drone on every soldier and robotic mules carrying gear all aim to take the load off the fighter. But how will the two communicate, robot and human? Voice commands like automated assistants on smartphones are great, but not when the threat of incoming fire means the robot battle buddy needs to decipher a range of priorities that humans might take for granted. The next test will come in late 2021 and involve a company-sized maneuver at Fort Hood, Texas. Think more C3PO or R2D2 in the "Star Wars" movies than Hal in "2001: A Space Odyssey" --or better yet, a friendly cyborg from "Terminator" might be the best way to see your robot combatant squad mate of the distant future.

This paper shows how to construct knowledge graphs (KGs) from pre-trained language models (e.g., BERT, GPT-2/3), without human supervision. Popular KGs (e.g, Wikidata, NELL) are built in either a supervised or semi-supervised manner, requiring humans to create knowledge. Recent deep language models automatically acquire knowledge from large-scale corpora via pre-training. The stored knowledge has enabled the language models to improve downstream NLP tasks, e.g., answering questions, and writing code and articles. In this paper, we propose an unsupervised method to cast the knowledge contained within language models into KGs. We show that KGs are constructed with a single forward pass of the pre-trained language models (without fine-tuning) over the corpora. We demonstrate the quality of the constructed KGs by comparing to two KGs (Wikidata, TAC KBP) created by humans. Our KGs also provide open factual knowledge that is new in the existing KGs. Our code and KGs will be made publicly available.

File photo - FORT HOOD, Tx--A Sabot round is fired from an M1A2 Abrams tank during 3rd Armored Brigade, 1st Cavalry Division gunnery qualification. Such a scenario, however likely, incorporates some of the complexities now informing current Army thinking. How much can current platforms, such as the 1980s-era Abrams tank, be upgraded and maintained such that they can provide the requisite force, protection and firepower to meet such a contingency? To what extent would the Army's emerging fleet of Next-Generation Combat Vehicles be better equipped to respond? The Army's most pressing priority, senior leaders explain, is to be ready for war "now" -- "today" -- and in the immediate future.

A convoy of US Army autonomous trucks is due to cruise along a stretch of public highway in Michigan this month as part of a trial of driverless military vehicles. Although the vehicles to be used in the trial will be flatbed military trucks, the technology could also be rolled out for tanks and armoured vehicles. The US Army said its future goal is to send unmanned trucks into dangerous scenarios that could put the lives of soldiers at risk. Called the Unmanned Mission Module, the technology used in the Fort Hood tests included a high performance LIDAR sensor - or laser radar. This remote sensing technology is capable of scanning the road ahead and measuring distances by illuminating a target with a laser, and analysing the light that is reflected.

COLUMBUS, OHIO – A Somali-born student who carried out a car-and-knife attack at Ohio State University might have been inspired by the Islamic State group and a former al-Qaida leader, investigators said Wednesday. Law enforcement officials said that it's too soon to say the rampage that hurt 11 people on Monday was terrorism. They said they aren't aware of any direct contact between the Islamic State group and the attacker, Ohio State student Abdul Razak Ali Artan. "We only believe he may have been inspired" by the group, said Angela Byers, the top FBI agent overseeing federal investigations in the southern half of Ohio. Artan also might have been influenced by Anwar al-Awlaki, a U.S.-born cleric who took a leadership role in al-Qaida before being killed in a 2011 U.S. drone strike in Yemen, Byers said.

NEW YORK – Five years after Anwar al-Awlaki was killed by an American drone strike, he keeps inspiring acts of terror. Investigators say a bomb that rocked New York a week ago, injuring more than two dozen people, was the latest in a long line of incidents in which the attackers were inspired by al-Awlaki, an American imam who became an al-Qaida propagandist. Federal terrorism charges against the bombing suspect, Ahmad Khan Rahami, say a bloodstained notebook -- found on him after he engaged in a shootout with police in New Jersey and was arrested -- included passages praising al-Awlaki. And Rahami's father has said he went to the FBI two years ago in part because he was concerned about his son's admiration for al-Awlaki and the time he spent watching his videos advocating jihad, or holy war. Terror experts say al-Awlaki remains a dangerous inciter of homegrown terror.

They are already promising to make the journey to work more bearable for commuters, but self-driving vehicles could also soon transform the way the US armed forces operate in dangerous areas. A convoy of US Army autonomous trucks is due to cruise along a stretch of public highway in Michigan in June as part of a trial of driverless military vehicles. Although the vehicles to be used in the trial will be flatbed military trucks, the technology could also be rolled out for tanks and armoured vehicles. Due to current road laws, each vehicle in the test will have someone sitting behind the wheel, but the autonomous technology will use sensors to help it stay on the road. Each truck will use adaptive cruise control and lane keeping assistance to stay within the convoy.