- Ai - Engineering Mailing Lists

AI Seminar: Understanding the promises and limits of fine-tuning
by Abou Mrad, Christian 13 Feb '25

13 Feb '25

Dear all, Our next AI seminar is scheduled for Friday, February 14th. Talk details: AI Seminar: Understanding the promises and limits of fine-tuning Speaker: Dr. Aditi Raghunathan, Assistant Professor of Computer Science, Carnegie Mellon University Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: In recent years, foundation models—large pretrained models that can be adapted for a wide range of tasks—have achieved state-of-the-art performance on a variety of tasks. The adaptation or fine-tuning process is a crucial component that enables specialization to the task of interest, and is the de facto standard for mitigating risks such as reducing toxic and harmful generations from large language models. While the pretrained models are trained on broad data, the adaptation (or fine-tuning) process is often performed on limited well-curated data. How well does fine-tuning generalize beyond the narrow training distribution? Via theory and experiments, we show how to improve current fine-tuning approaches so that they can better leverage diverse pretraining knowledge and improve downstream performance across broader settings than the narrow fine-tuning data. On the flip side, we show that pretrained knowledge can be hard to get rid of, thereby underlining the potential perils of over reliance on fine-tuning for safety. Speaker Bio: Aditi Raghunathan is an Assistant Professor in the Computer Science Department at CMU. She received her PhD from Stanford in 2021, and Bachelor of Technology from IIT Madras in 2016. She is a recipient of the Okawa research grant, Schmidt AI2050 Early Career Fellowship, the Google Research Scholar Award, Rising Stars in EECS, Google PhD Fellowship, Open Philanthropy AI Fellowship, Stanford School of Engineering Fellowship and Google Anita Borg Memorial Fellowship. She was featured in the Forbes 30 under 30 list for her contributions to reliable machine learning. Her PhD thesis was awarded the Arthur Samuel Best Thesis Award at Stanford. Her research has also been recognized by multiple orals and spotlights at top conferences, and a Best Paper Award at Data Problems in ML Workshop at ICLR 2024. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Active Learning For Human Preference Elicitation In LLMs
by Abou Mrad, Christian 06 Feb '25

06 Feb '25

Dear all, Our next AI seminar is scheduled for Friday, February 7th. Talk details: AI Seminar: Active Learning For Human Preference Elicitation In LLMs Speaker: Branislav Kveton, Adobe Research Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Learning from human preferences has been central to recent advances in AI. Motivated by the cost of obtaining high-quality human feedback, we study active learning of large language models (LLMs) through adaptive human preference elicitation. The key idea in our work is to linearize LLMs, either the reward model or the optimized policy, and apply optimal designs, a methodology for computing optimal information-gathering policies in statistics. We design efficient algorithms, fundamentally leverage the autoregressive nature of the LLMs, and evaluate our algorithms on state-of-the-art models. Speaker Bio: Branislav (Brano) is a Principal Research Scientist at Adobe Research and leads their team on planning and reasoning with generative AI models. He proposes, analyzes, and applies algorithms that learn incrementally, run in real time, and converge to near-optimal solutions with more feedback. Brano has been an active researcher in the fields of ML and AI for more than 15 years. His works have been published at top-tier conferences in these fields and he serves on senior roles at these conferences. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Introduction To Accelerated Computing with NVDIA GPUs
by Abou Mrad, Christian 31 Jan '25

31 Jan '25

Dear all, Two AI seminars are scheduled for Friday, January 31th. This is the second talk. Talk details: AI Seminar: Introduction To Accelerated Computing with NVDIA GPUs Speaker: Zoe Ryan, Solutions Architect, NVIDIA Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: In this session we will cover the basics of the NVIDIA GPU (graphics processing unit) and how it can be used in the context of education and research. We will start with an overview of how the GPU functions compared to traditional CPU computing and will follow that with an outline of the existing hardware portfolio. Then we will transition to talk about how you can program for the GPU, and what workloads are well suited to take advantage of the parallel nature of the GPU. Finally, we will have a hands-on demonstration of cutting edge LLMs (large language models) and generative AI workloads that rely on the compute power of the GPU. Speaker Bio: Zoe Ryan is a solutions architect at NVIDIA. She's worked in embedded systems/simulations and GPU-accelerated high-performance computing, specifically targeting higher education institutions and researchers to adopt and fully utilize GPU technology. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Painful Intelligence: What AI Can Tell Us About Human Suffering
by Abou Mrad, Christian 31 Jan '25

31 Jan '25

Dear all, Two AI seminars are scheduled for Friday, January 31th. This is the first talk. Talk details: AI Seminar: Painful Intelligence: What AI Can Tell Us About Human Suffering Speaker: Dr. Aapo Hyvärinen, Professor of Computer Science, University of Helsinki Time: 10:00 AM Location: Zoom remotely only Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: This talk introduces my recent e-book with the same title, freely available on Arxiv<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cs.he…>. The book uses the modern theory of artificial intelligence (AI) to understand human suffering or mental pain. Both humans and sophisticated AI agents process information about the world in order to achieve goals and obtain rewards, which is why AI can be used as a model of the human brain and mind. The book starts with the assumption that suffering is mainly caused by frustration. Frustration means the failure of an agent (whether AI or human) to achieve a goal or a reward it wanted or expected. Frustration is inevitable because of the overwhelming complexity of the world, limited computational resources, and scarcity of good data. In particular, such limitations imply that an agent acting in the real world must cope with uncontrollability, unpredictability, and uncertainty, which all lead to frustration. Such computational theory is finally used to derive various interventions or training methods that will reduce suffering in humans. The ensuing interventions are very similar to those proposed by Buddhist and Stoic philosophy, and include mindfulness meditation. Speaker Bio: Aapo Hyvärinen studied undergraduate mathematics at the universities of Helsinki (Finland), Vienna (Austria), and Paris (France), and obtained a Ph.D. degree in Information Science at the Helsinki University of Technology in 1997. After post-doctoral work at the Helsinki University of Technology, he moved to the University of Helsinki in 2003, where he was appointed Professor in 2008, at the Department of Computer Science. From 2016 to 2019, he was Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London, UK. Aapo Hyvarinen is the main author of the books "Independent Component Analysis" (2001), "Natural Image Statistics" (2009), and "Painful Intelligence" (2022). He is Action Editor at the Journal of Machine Learning Research and Neural Computation, and has worked as Area Chair at ICML, ICLR, AISTATS, UAI, ACML and NeurIPS. He is a Fellow at the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on the probabilistic theory of machine learning and its applications in neuroscience. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Painful Intelligence: What AI Can Tell Us About Human Suffering
by Abou Mrad, Christian 28 Jan '25

28 Jan '25

Dear all, Two AI seminars are scheduled for Friday, January 31th. This is the first talk. Talk details: AI Seminar: Painful Intelligence: What AI Can Tell Us About Human Suffering Speaker: Dr. Aapo Hyvärinen, Professor of Computer Science, University of Helsinki Time: 10:00 AM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: This talk introduces my recent e-book with the same title, freely available on Arxiv<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.cs.he…>. The book uses the modern theory of artificial intelligence (AI) to understand human suffering or mental pain. Both humans and sophisticated AI agents process information about the world in order to achieve goals and obtain rewards, which is why AI can be used as a model of the human brain and mind. The book starts with the assumption that suffering is mainly caused by frustration. Frustration means the failure of an agent (whether AI or human) to achieve a goal or a reward it wanted or expected. Frustration is inevitable because of the overwhelming complexity of the world, limited computational resources, and scarcity of good data. In particular, such limitations imply that an agent acting in the real world must cope with uncontrollability, unpredictability, and uncertainty, which all lead to frustration. Such computational theory is finally used to derive various interventions or training methods that will reduce suffering in humans. The ensuing interventions are very similar to those proposed by Buddhist and Stoic philosophy, and include mindfulness meditation. Speaker Bio: Aapo Hyvärinen studied undergraduate mathematics at the universities of Helsinki (Finland), Vienna (Austria), and Paris (France), and obtained a Ph.D. degree in Information Science at the Helsinki University of Technology in 1997. After post-doctoral work at the Helsinki University of Technology, he moved to the University of Helsinki in 2003, where he was appointed Professor in 2008, at the Department of Computer Science. From 2016 to 2019, he was Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London, UK. Aapo Hyvarinen is the main author of the books "Independent Component Analysis" (2001), "Natural Image Statistics" (2009), and "Painful Intelligence" (2022). He is Action Editor at the Journal of Machine Learning Research and Neural Computation, and has worked as Area Chair at ICML, ICLR, AISTATS, UAI, ACML and NeurIPS. He is a Fellow at the European Laboratory for Learning and Intelligent Systems (ELLIS). His research focuses on the probabilistic theory of machine learning and its applications in neuroscience. If you would like to meet with the speakers one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: "Explainable AI with Guarantees" by Dr. Adnan Darwiche
by Abou Mrad, Christian 23 Jan '25

23 Jan '25

Dear all, Our next AI seminar is scheduled for Friday, January 24th. Talk details: AI Seminar: Explainable AI with Guarantees Speaker: Dr. Adnan Darwiche, Professor of Computer Science, UCLA Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: I will discuss a theory of formal explainable AI that has emerged over the last few years, which is geared towards explaining the decisions of learned classifiers likes ones based on Bayesian Networks, random forests and some types of neural networks. The theory is based on compiling the input-output behavior of such classifiers into symbolic form and then using sophisticated machinery from symbolic logic to explain decisions. The theory employs newly-introduced, and profound, abstraction operators that distill the essence of an instance (i.e., classifier input) which causes the decision on that instance. Among the implications is an ability to identify minimal aspects of an instance that guarantee the decision, and minimal aspects that must be changed (and in what way) to change the decision. I will illustrate the theory using concrete examples and case studies and also tie these developments to more classical explanations and some widely used approximate explanations. Speaker Bio: Adnan Darwiche is a professor and former chairman of the computer science department at UCLA. He directs the Automated Reasoning Group, which focuses on symbolic reasoning, probabilistic reasoning and their applications to machine learning. Professor Darwiche is a Fellow of AAAI and ACM and recipient of the Lockheed Martin Excellence in Teaching Award. He is a former editor-in-chief of the Journal of Artificial Intelligence Research (JAIR) and author of “Modeling and Reasoning with Bayesian Networks,” by Cambridge University Press. Many of his works can be found on his YouTube Channel, https://www.youtube.com/@UCLA.Reasoning<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.youtu…>. If you would like to meet with the speakers one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu>. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Where do Ethics Belong in Artificial Intelligence?
by Abou Mrad, Christian 16 Jan '25

16 Jan '25

Dear all, Our next AI seminar is scheduled for Friday, January 17th. Talk details: AI Seminar: Where do Ethics Belong in Artificial Intelligence? Speakers: Dr. Houssam Abbas, Assistant Professor of Electrical Engineering and Computer Science & Dr. Alicia Patterson, Mary Jones and Thomas Hart Horning Assistant Professor of Applied Philosophy Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: The camera on-board a self-driving car switches to a power-saving mode and takes low-resolution images; as a result, the car hits a pedestrian. A mundane decision to save battery thus becomes a decision to value battery life over human life: all without anyone - or anything - ever explicitly making that choice. While we have long relied on software and automation, the prospect of a fully automated decision process charges many algorithmic decisions with a variety of ethical problems. Where do ethics (and the discipline of Ethics) belong in Artificial Intelligence? What occupies the minds of ethicists and computer scientists working on AI today? This talk will explore how ethicists and engineers think about ethics in Artificial Intelligence. We highlight two approaches engineers have taken to formalizing ethics, the harms these methods may leave unaddressed and analytical tools to understand them. Speakers Bio: Houssam Abbas is an Assistant Professor of Electrical Engineering and Computer Science at Oregon State University. His research interests are in the verification and control of cyber-physical systems and formal ethical theories for autonomous agents, with particular emphasis on unpiloted ground and aerial vehicles. He received the NSF CAREER award in 2022, and participated in the Frontiers of Engineering Symposium of the National Academies of Engineering in 2022. Prior to OSU, he was a postdoctoral fellow at the University of Pennsylvania, and a design automation engineer at Intel. Alicia Patterson is the Mary Jones and Thomas Hart Horning Assistant Professor of Applied Philosophy at the School of History, Philosophy, and Religion at OSU. Her research focuses on the ethics of emerging technology, with a special interest on privacy and data ethics. Prior to OSU, Patterson was a postdoctoral fellow at Ethics Lab at Georgetown University. At Georgetown, she worked on developing ethics curriculum for computer science classes as part of the Mozilla Responsible Computer Science Challenge. She holds a Ph.D. in philosophy from Cornell University. If you would like to meet with the speakers one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: "What is the road to humanoid laborers?" by Dr. Alan Fern
by Abou Mrad, Christian 10 Jan '25

10 Jan '25

Dear all, Our next AI seminar is scheduled for Friday, January 10th. Talk details: AI Seminar: What is the road to humanoid laborers? Speaker: Dr. Alan Fern, Professor of computer science, artificial intelligence, and robotics Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Cheap human physical labor has long been a critical component of large civilizations. While the demand for such labor remains virtually limitless, societal norms and ethical considerations often limit its accessibility. In contrast, humanoid robots have the potential to dramatically scale the supply of human-like labor, offering a guilt-free alternative. Although the path to realizing this vision remains uncertain, advances in humanoid robotics are accelerating. This talk will provide an overview of our research at OSU on AI for general-purpose humanoid labor and explore the key open problems and challenges that lie ahead. Speaker Bio: Alan Fern is a professor of computer science in the School of Electrical Engineering and Computer Science at Oregon State University. He received his Ph.D. (2004) in Computer Engineering from Purdue University, and his B.S. (1997) in Electrical Engineering from the University of Maine. His research interests span a variety of topics in Artificial Intelligence and Robotics with a particular emphasis on building systems that can learn from experience. He directs the Dynamic Robotics and AI Laboratory (DRAIL), which studies AI for enabling humanoid robots to perform real-world work. He is also the OSU lead PI for the AgAID AI Institute led by Washington State University. If you would like to meet with the speaker one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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לא קיבלתי תשובה למייל הקודם שלי, למה בבקשה?
by Mrs Annie Hyemin Kim 17 Dec '24

17 Dec '24

[This email originated from outside of OSU. Use caution with links and attachments.]

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לא קיבלתי תשובה למייל הקודם שלי, למה בבקשה?
by Mrs Annie Hyemin Kim 17 Dec '24

17 Dec '24

[This email originated from outside of OSU. Use caution with links and attachments.]

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