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With the rise of artificial intelligence in use today including applications like Siri, Alexa, Tesla, Cortana, Cogito, Google Now, and even Netflix, podcasts are a great alternative to keep yourself updated. We've gathered a list of podcasts available for you about this technology where you can get the latest news and trends plus learn more about how AI works and its impact on our lives.
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Machine learning and artificial intelligence are dramatically changing the way businesses operate and people live. The TWIML AI Podcast brings the top minds and ideas from the world of ML and AI to a broad and influential community of ML/AI researchers, data scientists, engineers and tech-savvy business and IT leaders. Hosted by Sam Charrington, a sought after industry analyst, speaker, commentator and thought leader. Technologies covered include machine learning, artificial intelligence, de ...
 
Artificial intelligence is a tremendously beneficial technology that's advancing at an incredibly rapid pace. As more and more organisations adopt and implement AI we find that the main challenges are not in the technology itself but in the human side, ie: the approaches, chosen problems and what's called 'the last mile', etc. That's why Data Futurology focuses on the leadership side of AI and how to get the most value from it. Join me, Felipe Flores, a Data Science executive with almost 20 ...
 
AI with AI explores the latest breakthroughs in artificial intelligence and autonomy, and discusses the technological and military implications. Join Andy Ilachinski and David Broyles as they explain the latest developments in this rapidly evolving field. The views expressed here are those of the commentators and do not necessarily reflect the views of CNA or any of its sponsors.
 
Welcome to the Conversations on Applied AI Podcast where Justin Grammens and the team at Emerging Technologies North talk with experts in the fields of Artificial Intelligence and Deep Learning. In each episode, we cut through the hype and dive into how these technologies are being applied to real-world problems today. We hope that you find this episode educational and applicable to your industry and connect with us to learn more about our organization at AppliedAI.MN. Enjoy!
 
Dream It! Imagine It! Create It! "If What If" (IWI) is an educational, consulting, and development company where our expertise is in Artificial Intelligence (AI), Virtual Reality (VR), Virtual Worlds (VW), and the Metaverse. "If What If" are a group of Futurists, computer analysts, data scientists, and researchers who believe that Virtual Reality (VR), Augmented Reality (AR), Extended Reality (XR), and the Metaverse coupled with AI is one of the next great technological frontiers. Our podcas ...
 
Get knowledge and inspiration to apply artificial intelligence to drug development. Discover startups applying machine learning to biomedical research. Hear how biotech and pharma companies use AI to speed discovery and cut costs. Learn from academic researchers pushing boundaries in applying computation to biology. We interview leaders transforming drug development with data and algorithms. Subscribe now and never miss an episode!
 
Danilo McGarry is a prominent leader, coach and Keynote speaker in the topics of Automation (and all its related areas: Artificial Intelligence/RPA/Machine Learning/Neural Networks/Deep Learning/Transformation) - to read more about the creator of this space please visit www.danilomcgarry.com
 
Artificial intelligence technologies are undoubtedly beginning to change the face of modern warfare. AI and machine learning applications promise to enhance productivity, reduce user workload, and operate more quickly than humans. But, this doesn’t come without its challenges. The Artificial Intelligence on the Battlefield podcast dives into these issues and more, looking at just how will AI reshape the future of warfare? Created by Shephard Studio, the Artificial Intelligence on the Battlef ...
 
Talking Robots is a podcast featuring interviews with high-profile professionals in Robotics and Artificial Intelligence for an inside view on the science, technology, and business of intelligent robotics. It is managed and sponsored by the Laboratory of Intelligent Systems (LIS) at the EPFL in Lausanne, Switzerland.
 
Dr. Rollan Roberts is an advisor and resource to national governments on strong Artificial Intelligence and quantum-proof Cybersecurity and was nominated to Central Command's Department of Defense Civilian Task Force. He is the CEO of Courageous!, a superhuman AI and Cybersecurity research and product development think tank that serves advanced national security initiatives of national governments. He served as CEO of the Hoverboard company, creating the best-selling consumer product worldwi ...
 
Dive into the world of Artificial Intelligence with your host Anna-Regina Entus - founder and president of the AI in Management Association and fellow of the AI Research Center at emlyon business school in Paris. Together with guest speakers from around the globe, I am helping you make sense of AI and share insights on the latest innovations in the world of Artificial Intelligence. Episodes 1-6: Hosted by Anna-Regina Entus and Victoria Rugli from Episode 7: Hosted by Anna-Regina Entus
 
Artificial intelligence is already controlling washing machines and translation assistants and helping doctors reach a diagnosis. It is changing our working lives and our leisure time. AI is making our lives easier and, ideally, even better! AI raises expectations, fears and hopes. And it involves risks. It’s all about personal autonomy and freedom, about security as well as sustainability and even global equity. AI between a promising future and a brave new world. Leading AI experts talk ab ...
 
An introduction to machine learning to assist business leaders to understand what it can and can't do. In the three episodes, you will get a sense of the potential impact, the nature and types of models available and case studies that may apply to your industry. Allan Kent is the Head of Digital at Primedia Broadcasting and is the host of this series.
 
David Yakobovitch explores AI for consumers through fireside conversations with industry thought leaders on HumAIn. From Chief Data Scientists and AI Advisors, to Leaders who advance AI for All, the HumAIn Podcast is the channel to release new AI products, to learn about industry trends, and to bridge the gap between humans and machines in the Fourth Industrial Revolution.
 
TOPBOTS educates business leaders on high-impact applications of modern machine learning and AI techniques and helps leading organizations adopt and implement emerging technologies. We run the largest publication and community for enterprise AI professionals to learn about the latest machine learning and automation solutions and exchange insights with each other. Through education and community, we inspire you to think creatively about how AI can be used to improve lives, revolutionize indus ...
 
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Organizations are increasingly making use of AI systems to power their operations and enable a wide range of applications from the trivial to the mission-critical. As a result it’s more important than ever to understand the many complex issues related to AI and Data fairness and bias. In this Ethical and Responsible AI Series hosts Kathleen Walch a…
 
Graph databases are powerful tools in analytics, but they are an often-misunderstood innovation. As they hold the relationships between data as a priority, they are an invaluable tool for modern, heavily inter-connected datasets. In this episode of Data Futurology, we explore graph databases with Peter Kokinakos (pk), the COO of MIP. They have been…
 
Louis AnnabiAbstractDespite the recent progress in deep learning and reinforcement learning, transfer and generalization of skills learned on specific tasks is very limited compared to human (or animal) intelligence. The lifelong, incremental building of common sense knowledge might be a necessary component on the way to achieve more general intell…
 
This and all episodes at: https://aiandyou.net/ . Cansu Canca is founder and director of the AI Ethics Lab, providing ethics analysis and guidance to researchers and practitioners. Prior to that, she was on the full-time faculty at the University of Hong Kong, and an ethics researcher at Harvard. She was listed among the “30 Influential Women Advan…
 
Today we close out our ICML 2022 coverage joined by Sharad Goel, a professor of public policy at Harvard University. In our conversation with Sharad, we discuss his Outstanding Paper award winner Causal Conceptions of Fairness and their Consequences, which seeks to understand what it means to apply causality to the idea of fairness in ML. We explor…
 
The conversation this week is with Gian Marco. Gian is a tech lead in the machine learning group at ARM and the author of the TinyML Cookbook published in April of 2022. At ARM Gian looks after the ML performance optimizations for the arm compute library, which he co-created in 2017 to get the best performance on ARM Cortex-A CPUs. ARM Compute Libr…
 
Dr. Anya Fink from CNA’s Russia Studies program joins the podcast to discuss the impacts of global sanctions on Russia’s technology and AI sector. Report CNA: A Technological Divorce: The impact of sanctions and the end of cooperation on Russia’s technology and AI sector.
 
Join Black Women In Artificial Intelligence -Beyond The Lab podcast as we speak with Ovetta Sampson Vice President - Head of Design and Machine Learning and Responsible A.I. at Capital One, discussing her journey to Artificial Intelligence. A true masterclass.بقلم Black Women In A I
 
A Short Analysis of Sentiment Analysis & Emotion Recognition in AI In this introductory podcast, on the topic of sentiment analysis and emotion recognition, we are going to present a well-known textual statement, allowing the listener to understand the problems Artificial Intelligence faces when having to deal with and interpret emotion and sentime…
 
Ali Atghaei, Ehsan Rahnama, Kiavash azimiAbstractFinding the conceptual difference between the two images in an industrial environment has been especially important for HSE purposes and there is still no reliable and conformable method to find the major differences to alert the related controllers. Due to the abundance and variety of objects in dif…
 
Hiroyasu Tsukamoto, Soon-Jo Chung, Benjamin Donitz, Michel Ingham, Declan Mages, Yashwanth Kumar NakkaAbstractInterstellar objects (ISOs), astronomical objects not gravitationally bound to the Sun, are likely representatives of primitive materials invaluable in understanding exoplanetary star systems. Due to their poorly constrained orbits with gen…
 
Soo Ling Lim, Randall S. Peterson, Peter J. Bentley, Xiaoran Hu, JoEllyn Prouty McLarenAbstractTeams are central to human accomplishment. Over the past half-century, psychologists have identified the Big-Five cross-culturally valid personality variables: Neuroticism, Extraversion, Openness, Conscientiousness, and Agreeableness. The first four have …
 
Cecilia Latotzke, Tim Ciesielski, and Tobias GemmekeAbstractConvolutional Neural Networks (CNNs) reach high accuracies in various application domains, but require large amounts of computation and incur costly data movements. One method to decrease these costs while trading accuracy is weight and/or activation word-length reduction. Thereby, layer-w…
 
Junseok Park, Inwoo Hwang, Min Whoo Lee, Hyunseok Oh, Minsu Lee, Youngki Lee, Byoung-Tak ZhangAbstractThe initial years of an infant's life are known as the critical period, during which the overall development of learning performance is significantly impacted due to neural plasticity. In recent studies, an AI agent, with a deep neural network mimi…
 
Fabian Spaeh, Sven KosubAbstractWe transfer distances on clusterings to the building process of decision trees, and as a consequence extend the classical ID3 algorithm to perform modifications based on the global distance of the tree to the ground truth--instead of considering single leaves. Next, we evaluate this idea in comparison with the origin…
 
Po-Hsiang Chiu and Manfred HuberAbstractLearning a control policy that involves time-varying and evolving system dynamics often poses a great challenge to mainstream reinforcement learning algorithms. In most standard methods, actions are often assumed to be a rigid, fixed set of choices that are sequentially applied to the state space in a predefi…
 
Angelos Christos Anadiotis and Ioana Manolescu and Madhulika MohantyAbstractGraph data management and querying has many practical applications. When graphs are very heterogeneous and/or users are unfamiliar with their structure, they may need to find how two or more groups of nodes are connected in a graph, even when users are not able to describe …
 
Daniel Scheliga and Patrick M\"ader and Marco SeelandAbstractExploiting gradient leakage to reconstruct supposedly private training data, gradient inversion attacks are an ubiquitous threat in collaborative learning of neural networks. To prevent gradient leakage without suffering from severe loss in model performance, recent work proposed a PRivac…
 
Long Dai, Jiarong Mao, Xuefeng Fan, Xiaoyi ZhouAbstractWith the rapid development of natural language processing (NLP) technology, NLP models have shown great economic value in business. However, the owner's models are vulnerable to the threat of pirated redistribution, which breaks the symmetry relationship between model owners and consumers. Ther…
 
Sana KarimianAbstractNear the entire university faculty directors must select some qualified professors for respected courses in each academic semester. In this sense, factors such as teaching experience, academic training, competition, etc. are considered. This work is usually done by experts, such as faculty directors, which is time consuming. Up…
 
Oliver BuchholzAbstractExplainable artificial intelligence (XAI) seeks to produce explanations for those machine learning methods which are deemed opaque. However, there is considerable disagreement about what this means and how to achieve it. Authors disagree on what should be explained (topic), to whom something should be explained (stakeholder),…
 
Dennis Vetter, Jesmin Jahan Tithi, Magnus Westerlund, Roberto V. Zicari, Gemma RoigAbstractAssessing the trustworthiness of artificial intelligence systems requires knowledge from many different disciplines. These disciplines do not necessarily share concepts between them and might use words with different meanings, or even use the same words diffe…
 
Ruichu Cai, Weilin Chen, Zeqin Yang, Shu Wan, Chen Zheng, Xiaoqing Yang, Jiecheng GuoAbstractEstimating long-term causal effects based on short-term surrogates is a significant but challenging problem in many real-world applications, e.g., marketing and medicine. Despite its success in certain domains, most existing methods estimate causal effects …
 
Yiheng Lu, Maoguo Gong, Wei Zhao, Kaiyuan Feng, and Hao LiAbstractPruning techniques are used comprehensively to compress convolutional neural networks (CNNs) on image classification. However, the majority of pruning methods require a well pre-trained model to provide useful supporting parameters, such as C1-norm, BatchNorm value and gradient infor…
 
Zixun Lan, Binjie Hong, Ye Ma, Fei MaAbstractGraph similarity measurement, which computes the distance/similarity between two graphs, arises in various graph-related tasks. Recent learning-based methods lack interpretability, as they directly transform interaction information between two graphs into one hidden vector and then map it to similarity. …
 
Manuel A. FokamAbstractAfrican languages have recently been the subject of several studies in Natural Language Processing (NLP) and, this has caused a significant increase in their representation in the field. However, most studies tend to focus more on the models than the quality of the datasets when assessing the models' performance in tasks such…
 
Qihua Zhang, Junning Liu, Yuzhuo Dai, Yiyan Qi, Yifan Yuan, Kunlun Zheng, Fan Huang, Xianfeng TanAbstractRecommender System (RS) is an important online application that affects billions of users every day. The mainstream RS ranking framework is composed of two parts: a Multi-Task Learning model (MTL) that predicts various user feedback, i.e., click…
 
Wei-Jer Chang, Yeping Hu, Chenran Li, Wei Zhan, and Masayoshi TomizukaAbstractSimulation has played an important role in efficiently evaluating self-driving vehicles in terms of scalability. Existing methods mostly rely on heuristic-based simulation, where traffic participants follow certain human-encoded rules that fail to generate complex human b…
 
Choonghan Kim and Gary Geunbae LeeAbstractData-to-text (D2T) generation is the task of generating texts from structured inputs. We observed that when the same target sentence was repeated twice, Transformer (T5) based model generates an output made up of asymmetric sentences from structured inputs. In other words, these sentences were different in …
 
Shiyu Duan, Spencer Chang, and Jose C. PrincipeAbstractIn supervised learning, obtaining a large set of fully-labeled training data is expensive. We show that we do not always need full label information on every single training example to train a competent classifier. Specifically, inspired by the principle of sufficiency in statistics, we present…
 
Xin Huang, Xiaoyu Tian, Junru Gu, Qiao Sun, Hang ZhaoAbstractPredicting future behaviors of road agents is a key task in autonomous driving. While existing models have demonstrated great success in predicting marginal agent future behaviors, it remains a challenge to efficiently predict consistent joint behaviors of multiple agents. Recently, the o…
 
Manoosh Samiei and Ruofeng LiAbstractObject localization has been a crucial task in computer vision field. Methods of localizing objects in an image have been proposed based on the features of the attended pixels. Recently researchers have proposed methods to formulate object localization as a dynamic decision process, which can be solved by a rein…
 
Minsu Kim, Hyunjun Kim, Yong Man RoAbstractLip reading aims to predict speech based on lip movements alone. As it focuses on visual information to model the speech, its performance is inherently sensitive to personal lip appearances and movements. This makes the lip reading models show degraded performance when they are applied to unseen speakers d…
 
Thanh Tran, Sebastian Bader, Jan LundgrenAbstractDenoising is the process of removing noise from sound signals while improving the quality and adequacy of the sound signals. Denoising sound has many applications in speech processing, sound events classification, and machine failure detection systems. This paper describes a method for creating an au…
 
Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph JacobAbstractThis paper concerns pseudo labelling in segmentation. Our contribution is fourfold. Firstly, we present a new formulation of pseudo-labelling as an Expectation-Maximization (EM) algorithm for clear statistical interpretation. Sec…
 
Sophia Knight and Pavel NaumovAbstractThe paper studies the interplay between modalities representing four different types of multistep strategies in the imperfect information setting. It introduces a new "truth set algebra'' technique for proving undefinability, which is significantly different from the existing techniques based on bisimulation. T…
 
Babak Hemmatian, Lav R. VarshneyAbstractRecent work demonstrates a bias in the GPT-3 model towards generating violent text completions when prompted about Muslims, compared with Christians and Hindus. Two pre-registered replication attempts, one exact and one approximate, found only the weakest bias in the more recent Instruct Series version of GPT…
 
Ayush Kumar, Parth Nagarkar, Prabhav Nalhe, and Sanjeev VijayakumarAbstractWith the future striving toward data-centric decision-making, seamless access to databases is of utmost importance. There is extensive research on creating an efficient text-to-sql (TEXT2SQL) model to access data from the database. Using a Natural language is one of the best…
 
Shumpei Kubosawa, Takashi Onishi, Yoshimasa TsuruokaAbstractDuring the operation of a chemical plant, product quality must be consistently maintained, and the production of off-specification products should be minimized. Accordingly, process variables related to the product quality, such as the temperature and composition of materials at various pa…
 
Yukio Ohsawa, Kaira Sekiguchi, Tomohide Maekawa, Hiroki Yamaguchi, Son Yeon Hyuk, Sae KondoAbstractA method for representing the digest information of each dataset is proposed, oriented to the aid of innovative thoughts and the communication of data users who attempt to create valuable products, services, and business models using or combining data…
 
Sarmad N. Mohammed and Semra G\"und\"u\c{c}AbstractRecent advances in complex network analysis opened a wide range of possibilities for applications in diverse fields. The power of the network analysis depends on the node features. The topology-based node features are realizations of local and global spatial relations and node connectivity structur…
 
Kaifeng Yang, Guozhi Dong, Michael AffenzellerAbstractBayesian global optimization (BGO) is an efficient surrogate-assisted technique for problems involving expensive evaluations. A parallel technique can be used to parallelly evaluate the true-expensive objective functions in one iteration to boost the execution time. An effective and straightforw…
 
Zhongzhan Huang, Senwei Liang, Hong Zhang, Haizhao Yang and Liang LinAbstractEnsemble-based large-scale simulation of dynamical systems is essential to a wide range of science and engineering problems. Conventional numerical solvers used in the simulation are significantly limited by the step size for time integration, which hampers efficiency and …
 
Tongyi Luo, Jia Xiao, Chuncao Zhang, Siheng Chen, Yuan Tian, Guangjun Yu, Kang Dang, Xiaowei DingAbstractTo make the earlier medical intervention of infants' cerebral palsy (CP), early diagnosis of brain damage is critical. Although general movements assessment(GMA) has shown promising results in early CP detection, it is laborious. Most existing w…
 
Yongjun Chen, Jia Li, Zhiwei Liu, Nitish Shirish Keskar, Huan Wang, Julian McAuley, Caiming XiongAbstractTo make Sequential Recommendation (SR) successful, recent works focus on designing effective sequential encoders, fusing side information, and mining extra positive self-supervision signals. The strategy of sampling negative items at each time s…
 
Athena Psalta, Vasileios Tsironis and Konstantinos KarantzalosAbstractData association is a crucial component for any multiple object tracking (MOT) method that follows the tracking-by-detection paradigm. To generate complete trajectories such methods employ a data association process to establish assignments between detections and existing targets…
 
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas PapernotAbstractProof-of-learning (PoL) proposes a model owner use machine learning training checkpoints to establish a proof of having expended the necessary compute for training. The authors of PoL forego crypto…
 
Qiaomu Miao, Sinhwa Kang, Stacy Marsella, Steve DiPaola, Chao Wang, Ari ShapiroAbstractThere is strong interest in the generation of synthetic video imagery of people talking for various purposes, including entertainment, communication, training, and advertisement. With the development of deep fake generation models, synthetic video imagery will so…
 
Dharanidhar Dang, Amitash Nanda, Bill Lin and Debashis SahooAbstractWith Moore's law saturating and Dennard scaling hitting its wall, traditional Von Neuman systems cannot offer the GFlops/watt for compute-intensive algorithms such as CNN. Recent trends in unconventional computing approaches give us hope to design highly energy-efficient computing …
 
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