A couple of months ago, Vice-President J. D. Vance made an appearance in Washington at the American Dynamism summit, an annual event put on by the venture-capital firm Andreessen Horowitz. Members of Congress, startup founders, investors, and Defense Department officials sat in the audience. They gave Vance a standing ovation as he walked onstage, while Alabama's "Forty Hour Week (For a Livin')" played in the background. "You're here, I hope, because you love your country," Vance told the crowd. "You love its people, the opportunities that it's given you, and you recognize that building things--our capacity to create new innovation in the economy--cannot be a race to the bottom."

Large language models (LLMs), while promising, face criticisms for biases, hallucinations, and a lack of reasoning capability. This paper introduces SocraSynth, a multi-LLM agent reasoning platform developed to mitigate these issues. SocraSynth utilizes conditional statistics and systematic context enhancement through continuous arguments, alongside adjustable debate contentiousness levels. The platform typically involves a human moderator and two LLM agents representing opposing viewpoints on a given subject. SocraSynth operates in two main phases: knowledge generation and reasoning evaluation. In the knowledge generation phase, the moderator defines the debate topic and contentiousness level, prompting the agents to formulate supporting arguments for their respective stances. The reasoning evaluation phase then employs Socratic reasoning and formal logic principles to appraise the quality of the arguments presented. The dialogue concludes with the moderator adjusting the contentiousness from confrontational to collaborative, gathering final, conciliatory remarks to aid in human reasoning and decision-making. Through case studies in three distinct application domains, this paper showcases SocraSynth's effectiveness in fostering rigorous research, dynamic reasoning, comprehensive assessment, and enhanced collaboration. This underscores the value of multi-agent interactions in leveraging LLMs for advanced knowledge extraction and decision-making support.

With the recent releases of large-language models, such as ChatGPT, artificial intelligence (AI) capability has leapfrogged, attracting intense attention around the globe. Inspired by the success of ChatGPT, many Chinese technology companies, such as Baidu, rushed to announce their own plans for developing a Chinese version of ChatGPT. However, to everyone's surprise, the Chinese government recently banned tech companies from offering ChatGPT-like services and will potentially impose more regulations on the development of AI. Since AI has gradually evolved into a foundational part of societal infrastructure essential to national interests, China may create a new state-owned enterprise (SOE) to monopolize AI foundation in China, similar to how SOEs monopolize the energy and telecommunication sectors. Traditionally, China's SOEs have controlled industries that are deemed essential to national interest and China's economy.

The Navy is progressively phasing artificial intelligence (AI) into its ship systems, weapons, networks, and command and control infrastructure as computer automation becomes more reliable and advanced algorithms make once-impossible discernments and analyses. Previously segmented data streams on ships, drones, aircraft, and even submarines are now increasingly able to share organized data in real-time, in large measure due to breakthrough advances in AI and machine learning. AI can, for instance, enable command and control systems to identify moments of operational relevance from among hours or days or surveillance data in milliseconds, something which saves time, maximizes efficiency, and performs time-consuming procedural tasks autonomously at an exponentially faster speed. "Multiple data bytes of information will be passed around on the networks here in the near future. So as we think about big data, and how do we handle all that data and turn it into information without getting overloaded, this will be a key part of AI, then we're talking about handling decentralized systems," Nathan Husted of the Naval Surface Warfare Center, Carderock told an audience at the 2022 Sea Air Space Symposium.

What is the impact of artificial intelligence (AI) and big data on societies in the Indo-Pacific? How are countries using AI and big data to enhance their national security and advance their national interests? And what are the major regulatory issues? For a perspective on these and other matters, Jongsoo Lee interviewed Simon Chesterman, dean and provost's chair professor of the National University of Singapore Faculty of Law and senior director of AI Governance at AI Singapore. What are nations in the Indo-Pacific doing to develop their artificial intelligence (AI) and big data capabilities?

Here's What You Need to Know: AI-capable drone defenses can already gather, pool, organize and analyze an otherwise disconnected array of threat variables. What if waves of hundreds of autonomous, integrated artificial intelligence (AI)-capable mini-drones were closing in upon a forward Army unit, Air Force base or Navy ship at staggering speeds, presenting unprecedented complexity for defenders? Perhaps they are programmed with advanced algorithms such that they operate in close coordination with one another? Perhaps hundreds of them are themselves engineered as explosives to close in upon and explode on target? Simply put, what happens when computerized swarms of enemy drone attacks exceed any human capacity to respond in time?

Here's What You Need to Remember: From a tactical circumstance, given that attack submarines and nuclear-armed ballistic missile submarines are likely to conduct large amounts of clandestine patrols, it seems as though an ability to avoid having to surface would bring an extraordinary operational advantage. Could newer kinds of AI-enabled undersea drone data processing and analysis introduce new breakthrough possibilities when it comes to solving the longstanding challenge of achieving high-speed, real-time connectivity? Submarine commanders and weapons developers explain that UUV undersea functionality is dependent upon limited battery power and would therefore be further enabled by an ability to "process the data at the source of the sensor" to distinguish and transmit only the most critical information needed by human decision-makers. "That's the concept, how do you get all of that information back to a human to analyze. Maybe you don't want to do that? Maybe you want to allow the UUV to do some initial analysis and make some modifications to its behavior autonomously?"

Enemy drone attack threats are a key part of the inspiration for newer kinds of laser weapons because they can incinerate drones without generating large amounts of explosive fragmentation. Moreover, newer lasers can scale attacks to align with the target and desired combat effect and, perhaps most of all, travel at the speed of light to destroy drones quickly, ideally before they are able to strike. Attacking drone swarms may be approaching for attack so quickly that kinetic responses such as interceptor missile fire control systems may be challenged in certain respects, depending upon the extent of artificial intelligence (AI)-enabled target recognition technology and computer automation. The question of scaling lasers to optimize power input for counter-drone strikes is addressed in a recent essay from May of last year called "Testing the Efficiency of Laser Technology to Destroy Rogue Drones," in the Security & Defense Quarterly from War Studies University. The essay describes innovative experimental methods of "incorporating a laser module and groups of optical lenses to focus the power in one point to carbonize any target."

Here's What You Need to Remember: Should the application of these synthetic materials come to fruition, they could help soldiers and combat units avoid detection from enemy sensors and satellites. Robot armies on attack, self-driving tanks and massive, long-range, computer-enabled sensors and natural camouflage technology are just a few of the many dynamics expected to characterize warfare in 2035, a set of circumstances now under close and careful examination by teams of Army scientists looking to anticipate the wars of tomorrow. "Our core focus areas include AI, robotics and autonomy underpinned by network and data technologies," Col. Stephanie Ahern, Secretary of the Army Initiatives Group Chief, told reporters on October 14. The effort, called "Team Ignite," is lodged within Army Futures Command. It is a collaborative endeavor involving scientists, engineers, academics, concepts experts, and weapons requirements writers to explore the realm of the possible in terms of research, emerging technologies, maneuver formations, and new tactics, techniques, and procedures.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. The Army has been upgrading and augmenting the attack system for its Abrams tank to ensure a clearer view for gunners looking to find, engage and destroy targets. The effort involves upgrading and modifying Kongsberg's Common Remotely Operated Weapons Station, a combat-tested technology that lets soldiers control and fire a vehicle weapon from beneath the protection of armor by virtue of looking at a video screen and leveraging advanced fire-control technology. Kongsberg took 300 systems and manufactured the smaller, lower profile systems the Army wanted to change as a way to help modify the weapons system for more efficient use.