Toggle light / dark theme

A new coalition of rights-holders has called on the government to support growth in the creative and tech sectors by protecting copyright ahead of an imminent AI consultation.

The BPI, PRS For Music, PPL, MPA and UK Music are among the group of publishers, authors, artists, music businesses, specialist interest publications, unions and photographers.

Launching today, the Creative Rights In AI Coalition has published three key principles for copyright and generative AI policy and a statement supported by all member organisations. The coalition is calling on government to adopt the principles as a framework for developing AI policy.

Here’s my take: I was in the music industry for many years, so I know how it operates. People pay royalties every time an artists music is used. My friend Ayub Ogada made an ungodly amount of money from only one album that supported him all the way past death. His music still generates rotalties. Much of it was due to the smarts of Rob Bozas who ran royalties for Peter Gabriel’s Real World Records. AI companies also will have to start paying royalties to creatives whose intellectual property they use to train their AI just like royalties are paid in the music industry. Many AI companies may not be as profitable as many may think due to liabilities from use of intellectual property to train the AI, as without the content the AI could not be trained. Many lawsuits will happen in the foreseeable future.

Japan’s fledgling space defense sector is taking its cues from the US Space Development Agency, which is pursuing a novel concept based on constellations of small satellites and maximum use of existing commercial technologies. Space policy researcher Umeda Kota discusses the challenges facing Japan as it embraces the SDA’s “proliferated architecture” for military communications, missile detection and tracking, and other purposes.

IINA provides ongoing analysis of international affairs both by region—such as North America, China, and Europe—and by such topics as human security, nontraditional security threats, and cyber security. The articles on this site, written by experts at the Sasakawa Peace Foundation and guest contributors, are carefully selected for their objectivity, accuracy, timeliness, and relevance for Japan.

IINA provides ongoing analysis of international affairs both by region—such as North America, China, and Europe—and by such topics as human security, nontraditional security threats, and cyber security. The articles on this site, written by experts at the Sasakawa Peace Foundation and guest contributors, are carefully selected for their objectivity, accuracy, timeliness, and relevance for Japan.

IINA provides ongoing analysis of international affairs both by region—such as North America, China, and Europe—and by such topics as human security, nontraditional security threats, and cyber security. The articles on this site, written by experts at the Sasakawa Peace Foundation and guest contributors, are carefully selected for their objectivity, accuracy, timeliness, and relevance for Japan.

Science, Policy And Advocacy For Impactful And Sustainable Health Ecosystems — Dr. Catharine Young, Ph.D. — fmr. Assistant Director of Cancer Moonshot Policy and International Engagement, White House Office of Science and Technology Policy (OSTP)


Dr. Catharine Young, Ph.D. recently served as Assistant Director of Cancer Moonshot Policy and International Engagement at the White House Office of Science and Technology Policy (https://www.whitehouse.gov/ostp/) where she served at OSTP to advance the Cancer Moonshot (https://www.cancer.gov/research/key-i… with a mission to decrease the number of cancer deaths by 50% over the next 25 years.

Dr. Young’s varied career has spanned a variety of sectors including academia, non-profit, biotech, and foreign government, all with a focus on advancing science.

Dr. Young previously served as Executive Director of the SHEPHERD Foundation, where she championed rare cancer research and drove critical policy changes. Her work has also included fostering interdisciplinary collaborations and advancing the use of AI, data sharing, and clinical trial reform to accelerate cancer breakthroughs.

Dr. Young’s leadership in diplomacy and innovation includes roles such as Senior Director of Science Policy at the Biden Cancer Initiative and Senior Science and Innovation Policy Advisor at the British Embassy, where she facilitated international agreements to enhance research collaborations.

Convergent engagement of neural and computational sciences and technologies are reciprocally enabling rapid developments in current and near-future military and intelligence operations. In this podcast, Prof. James Giordano of Georgetown University will provide an overview of how these scientific and technological fields can be — and are being — leveraged for non-kinetic and kinetic what has become known as cognitive warfare; and will describe key issues in this rapidly evolving operational domain.

James Giordano PhD, is the Pellegrino Center Professor in the Departments of Neurology and Biochemistry; Chief of the Neuroethics Studies Program; Co-director of the Project in Brain Sciences and Global Health Law and Policy; and Chair of the Subprogram in Military Medical Ethics at Georgetown University Medical Center, Washington DC. Professor Giordano is Senior Bioethicist of the Defense Medical Ethics Center, and Adjunct Professor of Psychiatry at the Uniformed Services University of Health Sciences; Distinguished Stockdale Fellow in Science, Technology, and Ethics at the United States Naval Academy; Senior Science Advisory Fellow of the SMA Branch, Joint Staff, Pentagon; Non-resident Fellow of the Simon Center for the Military Ethic at the US Military Academy, West Point; Distinguished Visiting Professor of Biomedical Sciences, Health Promotions, and Ethics at the Coburg University of Applied Sciences, Coburg, GER; Chair Emeritus of the Neuroethics Project of the IEEE Brain Initiative; and serves as Director of the Institute for Biodefense Research, a federally funded Washington DC think tank dedicated to addressing emerging issues at the intersection of science, technology and national defense. He previously served as Donovan Group Senior Fellow, US Special Operations Command; member of the Neuroethics, Legal, and Social Issues Advisory Panel of the Defense Advanced Research Projects Agency (DARPA); and Task Leader of the Working Group on Dual-Use of the EU-Human Brain Project. Prof. Giordano is the author of over 350 peer-reviewed publications, 9 books and 50governmental reports on science, technology, and biosecurity, and is an elected member of the European Academy of Science and Arts, a Fellow of the Royal Society of Medicine (UK), and a Fulbright Professorial Fellow. A former US Naval officer, he was winged as an aerospace physiologist, and served with the US Navy and Marine Corps.

Reinforcement learning (RL) has become central to advancing Large Language Models (LLMs), empowering them with improved reasoning capabilities necessary for complex tasks. However, the research community faces considerable challenges in reproducing state-of-the-art RL techniques due to incomplete disclosure of key training details by major industry players. This opacity has limited the progress of broader scientific efforts and collaborative research.

Researchers from ByteDance, Tsinghua University, and the University of Hong Kong recently introduced DAPO (Dynamic Sampling Policy Optimization), an open-source large-scale reinforcement learning system designed for enhancing the reasoning abilities of Large Language Models. The DAPO system seeks to bridge the gap in reproducibility by openly sharing all algorithmic details, training procedures, and datasets. Built upon the verl framework, DAPO includes training codes and a thoroughly prepared dataset called DAPO-Math-17K, specifically designed for mathematical reasoning tasks.

DAPO’s technical foundation includes four core innovations aimed at resolving key challenges in reinforcement learning. The first, “Clip-Higher,” addresses the issue of entropy collapse, a situation where models prematurely settle into limited exploration patterns. By carefully managing the clipping ratio in policy updates, this technique encourages greater diversity in model outputs. “Dynamic Sampling” counters inefficiencies in training by dynamically filtering samples based on their usefulness, thus ensuring a more consistent gradient signal. The “Token-level Policy Gradient Loss” offers a refined loss calculation method, emphasizing token-level rather than sample-level adjustments to better accommodate varying lengths of reasoning sequences. Lastly, “Overlong Reward Shaping” introduces a controlled penalty for excessively long responses, gently guiding models toward concise and efficient reasoning.