Two studies tested the hypothesis that a Large Language Model (LLM) can be used to model psychological change following exposure to influential input. The first study tested a generic mode of influence - the Illusory Truth Effect (ITE) - where earlier exposure to a statement (through, for example, rating its interest) boosts a later truthfulness test rating. Data was collected from 1000 human participants using an online experiment, and 1000 simulated participants using engineered prompts and LLM completion. 64 ratings per participant were collected, using all exposure-test combinations of the attributes: truth, interest, sentiment and importance. The results for human participants reconfirmed the ITE, and demonstrated an absence of effect for attributes other than truth, and when the same attribute is used for exposure and test. The same pattern of effects was found for LLM-simulated participants. The second study concerns a specific mode of influence - populist framing of news to increase its persuasion and political mobilization. Data from LLM-simulated participants was collected and compared to previously published data from a 15-country experiment on 7286 human participants. Several effects previously demonstrated from the human study were replicated by the simulated study, including effects that surprised the authors of the human study by contradicting their theoretical expectations (anti-immigrant framing of news decreases its persuasion and mobilization); but some significant relationships found in human data (modulation of the effectiveness of populist framing according to relative deprivation of the participant) were not present in the LLM data. Together the two studies support the view that LLMs have potential to act as models of the effect of influence.

Lt. Gen. Keith Kellogg says China is an adversary, not a competitor, amid growing concerns over rising threats on "Your World." The U.S. Treasury Department announced new sanctions Thursday on a China-based network that sells aerospace components to Iran for manufacturing drones. The Iran Aircraft Manufacturing Industrial Company manufactures the Shahed-136 drones and exports them to Russia, which has increasingly used them to bombard Ukraine in recent months. "Iran is directly implicated in the Ukrainian civilian casualties that result from Russia's use of Iranian UAVs (unmanned aerial vehicle), in Ukraine," said Brian Nelson, the Treasury Department's undersecretary for Terrorism and Financial Intelligence, in a statement on Thursday. "The United States will continue to target global Iranian procurement networks that supply Russia with deadly UAVs for use in its illegal war in Ukraine."

Stuart Russell is a Professor of Computer Science at the University of California at Berkeley, holder of the Smith-Zadeh Chair in Engineering, and Director of the Center for Human-Compatible AI. He is an Honorary Fellow of Wadham College, Oxford, an Andrew Carnegie Fellow, and a Fellow of the American Association for Artificial Intelligence, the Association for Computing Machinery, and the American Association for the Advancement of Science. His book, Artificial Intelligence: A Modern Approach, co-authored with Peter Norvig, is the standard text in AI, used in 1500 universities in 135 countries. Russell is also the author of Human Compatible: Artificial Intelligence and the Problem of Control. His research covers a wide range of topics in artificial intelligence, with a current emphasis on the long-term future of artificial intelligence and its relation to humanity.

The central factor that distinguishes autonomous weapons from remotely controlled weapons is human control. Lethal weapon systems in which target selection and the manner of target engagement are not subject to human control but are left to artificial intelligence (AI) are problematic from both ethical and legal perspectives. Elon Musk, 160 research and business organizations, and experts from the Stop Killer Robots campaign called against building autonomous weapons systems in 2018. In doing so, they raised awareness of the threat of autonomous weapons for the first time. In principle, most objects can become weapons (Bendel, 2019, page 321). Examples include bicycle chains, screwdrivers, or scissors.

These patterns can then be used to develop models that can detect new instances of malware. This can help security teams stay ahead of attackers and take proactive measures to prevent attacks. Hawaiian Telcom's trusted partner Elastic has incorporated machine learning algorithms into its security solutions to help organizations identify and respond to threats more quickly and effectively. Together they invite you to join a free virtual event where they'll talk about Elastic's journey from Search to Security, the role of Security Information and Event Management (SIEM) in modern security programs, and the addition of technology like machine learning to help secure your network.

This article is part of a series. Check out the full series: Part I, Part II, Part III. Over the past few days, we've been building a complete Python IDE inside Jupyter. In this article, we will add the final touches and package everything in a Docker image to create a portable working environment for data scientists and Machine Learning engineers. It's not even an IPython UI, as many may think.

An artificial intelligence boom is taking over Silicon Valley, with hi-tech firms racing to develop everything from self-driving cars to chatbots capable of writing poetry. Yet AI could also spread conspiracy theories and lies even more quickly than the internet already does – fueling political polarization, hate, violence and mental illness in young people. It could undermine national security with deepfakes. In recent weeks, members of Congress have sounded the alarm over the dangers of AI but no bill has been proposed to protect individuals or stop the development of AI's most threatening aspects. Most lawmakers don't even know what AI is, according to Representative Jay Obernolte, the only member of Congress with a master's degree in artificial intelligence.

Accenture Federal Services delivers a range of innovative, tech-enabled services for the U.S. Federal Government to address the complex, sensitive challenges of national security and intelligence missions. Refer a qualified candidate and earn up to $20K. Accenture Federal Services is seeking a Data Engineer to assist with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors including but not limited to the specific office location, role, skill set and level of experience.

Accenture Federal Services delivers a range of innovative, tech-enabled services for the U.S. Federal Government to address the complex, sensitive challenges of national security and intelligence missions. Refer a qualified candidate and earn up to $20K. Accenture Federal Services is seeking a Data Engineer to assist with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. If that sounds appealing to you - we'd love to chat.

Accenture Federal Services delivers a range of innovative, tech-enabled services for the U.S. Federal Government to address the complex, sensitive challenges of national security and intelligence missions. Refer a qualified candidate and earn up to $20K. Accenture Federal Services is seeking a Junior Data Engineer to assist with the data platform blueprint and design, encompassing the relevant data platform components. Collaborates with the Integration Architects and Data Architects to ensure cohesive integration between systems and data models. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors including but not limited to the specific office location, role, skill set and level of experience.