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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 ...
 
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.
 
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 ...
 
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 ...
 
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.
 
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 ...
 
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 ...
 
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.
 
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
 
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.
 
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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“Data engineers are like plumbers,” Edward Chenard, the Senior Director of Data Science and Analytics at Shipwell, said in this latest episode of the Data Futurology Podcast. By that, Chenard means that data scientists are excellent at analysing what’s coming through the proverbial pipes, but if the “pipes” break for even a couple of hours the cost…
 
The conversation this week is with Amelia Winger-Bearskin. Amelia innovates with artificial intelligence in ways that make a positive impact on our community and the environment. She's a Banks Family Preeminence Endowed Chair and Associate Professor of Artificial Intelligence and the Arts at the Digital Worlds Institute at the University of Florida…
 
Yibo Jiang, Victor VeitchAbstractReal-world classification problems must contend with domain shift, the (potential) mismatch between the domain where a model is deployed and the domain(s) where the training data was gathered. Methods to handle such problems must specify what structure is common between the domains and what varies. A natural assumpt…
 
This and all episodes at: https://aiandyou.net/ . We've talked a lot about artificial general intelligence (AGI) on the show, but never as much as in this interview, when we talk with Mr. AGI himself, Ben Goertzel. Ben wrote a book, Artificial General Intelligence, founded the AGI Society and SingularityNET, and wrote Ten Years to the Singularity i…
 
Dream it. Imagine it. Create it. In this podcast, If-What-If approaches and deals with the subject of Bias and how it affects data and AI. This comes after our previous podcast in AI, on Information Theory. Bias - The Achilles Heel Of AI & Data What is information bias? How does it occur? Is it a genuine problem? And if so, is there anything we can…
 
Today we wrap up our coverage of the 2022 CVPR conference joined by Aljosa Osep, a postdoc at the Technical University of Munich & Carnegie Mellon University. In our conversation with Aljosa, we explore his broader research interests in achieving robot vision, and his vision for what it will look like when that goal is achieved. The first paper we …
 
Andy and Dave discuss the latest in AI news and research, starting with the Department of Defense releasing its Responsible AI Strategy. In the UK, the Ministry of Defence publishes its Defence AI Strategy. The Federal Trade Commission warns policymakers about relying on AI to combat online problems and instead urges them to develop legal framework…
 
It’s one thing for us to talk about CPMAI and the benefits it can bring to AI and advanced data projects, but hearing directly how companies are applying the CPMAI Methodology can be incredibly valuable. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer interview Charles Mendoza, who is Sr. Continue reading AI Today Pod…
 
Includes a special emphasis on how to acquire businesses without any of your own money down or even no money down.Dr. Rollan Roberts II
 
[Audio] Podcast: Play in new window | Download Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS Steve received his PhD from Johns Hopkins University in Cognitive Science where he began his AI research and also taught Statistics at Towson State University. After receiving his PhD in 1979, AI pioneer Roger Schank invited Steve to join t…
 
Nuno Oliveira, Norberto Sousa and Isabel Pra\c{c}aAbstractElectricity is a volatile power source that requires great planning and resource management for both short and long term. More specifically, in the short-term, accurate instant energy consumption forecasting contributes greatly to improve the efficiency of buildings, opening new avenues for …
 
Jeong-Jae Kim, Yeseul Jeon, SuMin Yu, Junggu Choi, Sanghoon HanAbstractThere have been several attempts to use deep learning based on brain fMRI signals to classify cognitive impairment diseases. However, deep learning is a hidden black box model that makes it difficult to interpret the process of classification. To address this issue, we propose a…
 
Wen Guo, Yuming Du, Xi Shen, Vincent Lepetit, Xavier Alameda-Pineda, Francesc Moreno-NoguerAbstractThis paper tackles the problem of human motion prediction, consisting in forecasting future body poses from historically observed sequences. Despite of their performance, current state-of-the-art approaches rely on deep learning architectures of arbit…
 
Ruina Sun, Yuexin PangAbstractWith the development of computer technology, various models have emerged in artificial intelligence. The transformer model has been applied to the field of computer vision (CV) after its success in natural language processing (NLP). Radiologists continue to face multiple challenges in today's rapidly evolving medical f…
 
Rui Wang, Chongwei Liu, Xudong Mou, Xiaohui Guo, Kai Gao, Pin Liu, Tianyu Wo, Xudong LiuAbstractThe accumulation of time series data and the absence of labels make time-series Anomaly Detection (AD) a self-supervised deep learning task. Single-assumption-based methods may only touch on a certain aspect of the whole normality, not sufficient to dete…
 
Yinya Huang, Lemao Liu, Kun Xu, Meng Fang, Liang Lin, and Xiaodan LiangAbstractTextual logical reasoning, especially question answering (QA) tasks with logical reasoning, requires awareness of particular logical structures. The passage-level logical relations represent entailment or contradiction between propositional units (e.g., a concluding sent…
 
Yue Qin and Xiaojing LiaoAbstractCybersecurity vulnerability information is often recorded by multiple channels, including government vulnerability repositories, individual-maintained vulnerability-gathering platforms, or vulnerability-disclosure email lists and forums. Integrating vulnerability information from different channels enables comprehen…
 
Jun Rao, Liang Ding, Shuhan Qi, Meng Fang, Yang Liu, Li Shen, Dacheng TaoAbstractAlthough the vision-and-language pretraining (VLP) equipped cross-modal image-text retrieval (ITR) has achieved remarkable progress in the past two years, it suffers from a major drawback: the ever-increasing size of VLP models restricts its deployment to real-world se…
 
Gianluigi Lopardo and Damien GarreauAbstractComplex machine learning algorithms are used more and more often in critical tasks involving text data, leading to the development of interpretability methods. Among local methods, two families have emerged: those computing importance scores for each feature and those extracting simple logical rules. In t…
 
Yuki Shirai, Xuan Lin, Alexander Schperberg, Yusuke Tanaka, Hayato Kato, Varit Vichathorn, Dennis HongAbstractWhile motion planning of locomotion for legged robots has shown great success, motion planning for legged robots with dexterous multi-finger grasping is not mature yet. We present an efficient motion planning framework for simultaneously so…
 
Zhongxiang Chang and Zhongbao ZhouAbstractThe asynchronous development between the observation capability and the transition capability results in that an original image data (OID) formed by one-time observation cannot be completely transmitted in one transmit chance between the EOS and GS (named as a visible time window, VTW). It needs to segment …
 
Rub\'en Izquierdo, \'Alvaro Quintanar, David Fern\'andez Llorca, Iv\'an Garc\'ia Daza, Noelia Hern\'andez, Ignacio Parra, Miguel \'Angel SoteloAbstractThis work presents a novel method for predicting vehicle trajectories in highway scenarios using efficient bird's eye view representations and convolutional neural networks. Vehicle positions, motion…
 
Youngeun Kim, Yuhang Li, Hyoungseob Park, Yeshwanth Venkatesha, Ruokai Yin, and Priyadarshini PandaAbstractSpiking Neural Networks (SNNs) have recently emerged as a new generation of low-power deep neural networks where binary spikes convey information across multiple timesteps. Pruning for SNNs is highly important as they become deployed on a reso…
 
Eitan Kosman and Dotan Di CastroAbstractWe propose a concise representation of videos that encode perceptually meaningful features into graphs. With this representation, we aim to leverage the large amount of redundancies in videos and save computations. First, we construct superpixel-based graph representations of videos by considering superpixels…
 
Sebastian Curi, Armin Lederer, Sandra Hirche, Andreas KrauseAbstractEnsuring safety is a crucial challenge when deploying reinforcement learning (RL) to real-world systems. We develop confidence-based safety filters, a control-theoretic approach for certifying state safety constraints for nominal policies learned via standard RL techniques, based o…
 
Zhuo Chen, Yufeng Huang, Jiaoyan Chen, Yuxia Geng, Wen Zhang, Yin Fang, Jeff Z. Pan, Wenting Song, Huajun ChenAbstractZero-shot learning (ZSL) aims to predict unseen classes whose samples have never appeared during training, often utilizing additional semantic information (a.k.a. side information) to bridge the training (seen) classes and the unsee…
 
Xueyan Yin, Feifan Li, Yanming Shen, Heng Qi, and Baocai YinAbstractRecently, deep learning methods have made great progress in traffic prediction, but their performance depends on a large amount of historical data. In reality, we may face the data scarcity issue. In this case, deep learning models fail to obtain satisfactory performance. Transfer …
 
Shivansh Beohar, Fabian Heinrich, Rahul Kala, Helge Ritter and Andrew MelnikAbstractLearn-to-Race Autonomous Racing Virtual Challenge hosted on www.aicrowd.com platform consisted of two tracks: Single and Multi Camera. Our UniTeam team was among the final winners in the Single Camera track. The agent is required to pass the previously unknown F1-st…
 
Zhongxiang Chang and Abraham P. Punnen and Zhongbao ZhouAbstractActive-imaging agile earth observation satellite (AI-AEOS) is a new generation agile earth observation satellite (AEOS). With renewed capabilities in observation and active im-aging, AI-AEOS improves upon the observation capabilities of AEOS and provide additional ways to observe groun…
 
Emad Shihab and Stefan Wagner and Marco A. Gerosa and Mairieli Wessel and Jordi CabotAbstractWe are witnessing a massive adoption of software engineering bots, applications that react to events triggered by tools and messages posted by users and run automated tasks in response, in a variety of domains. This thematic issues describes experiences and…
 
Zijian Hu, Xiaoguang Gao, Kaifang Wan, Qianglong Wang, Yiwei ZhaiAbstractUnmanned aerial vehicles (UAVs) have been widely used in military warfare. In this paper, we formulate the autonomous motion control (AMC) problem as a Markov decision process (MDP) and propose an advanced deep reinforcement learning (DRL) method that allows UAVs to execute co…
 
Zhongxiang Chang and Zhongbao ZhouAbstractObservation scheduling problem for agile earth observation satellites (OSPFAS) plays a critical role in management of agile earth observation satellites (AEOSs). Active imaging enriches the extension of OSPFAS, we call the novel problem as observation scheduling problem for AEOS with variable image duration…
 
Zhongxiang Chang and Yuning Chen and Zhongbao ZhouAbstractA novel problem called satellite downlink scheduling problem (SDSP) under breakpoint resume mode (SDSP-BRM) is studied in our paper. Compared to the traditional SDSP where an imaging data has to be completely downloaded at one time, SDSP-BRM allows the data of an imaging data be broken into …
 
Vishnu Raj, Tianyu Cui, Markus Heinonen and Pekka MarttinenAbstractBayesian deep learning offers a principled approach to train neural networks that accounts for both aleatoric and epistemic uncertainty. In variational inference, priors are often specified over the weight parameters, but they do not capture the true prior knowledge in large and com…
 
Oshri Naparstek, Ophir Azulai, Daniel Rotman, Yevgeny Burshtein, Peter Staar, Udi BarzelayAbstractFor digitizing or indexing physical documents, Optical Character Recognition (OCR), the process of extracting textual information from scanned documents, is a vital technology. When a document is visually damaged or contains non-textual elements, exist…
 
Haoren Guo, Haiyue Zhu, Jiahui Wang, Vadakkepat Prahlad, Weng Khuen Ho, Tong Heng LeeAbstractPrediction of Remaining Useful Lifetime(RUL) in the modern manufacturing and automation workplace for machines and tools is essential in Industry 4.0. This is clearly evident as continuous tool wear, or worse, sudden machine breakdown will lead to various m…
 
Jiahui Wang, Haiyue Zhu, Haoren Guo, Abdullah Al Mamun, Vadakkepat Prahlad, Tong Heng LeeAbstract3D part segmentation is an essential step in advanced CAM/CAD workflow. Precise 3D segmentation contributes to lower defective rate of work-pieces produced by the manufacturing equipment (such as computer controlled CNCs), thereby improving work efficie…
 
Xiangri LuAbstractThe confrontation of modern intelligence is to some extent a non-complete information confrontation, where neither side has access to sufficient information to detect the deployment status of the adversary, and then it is necessary for the intelligence to complete information retrieval adaptively and develop confrontation strategi…
 
S\'ebastien Ollivier, Sheng Li, Yue Tang, Chayanika Chaudhuri, Peipei Zhou, Xulong Tang, Jingtong Hu, and Alex K. Jones (University of Pittsburgh)AbstractEdge computing is a popular target for accelerating machine learning algorithms supporting mobile devices without requiring the communication latencies to handle them in the cloud. Edge deployment…
 
Shunyu Yao, Howard Chen, John Yang, Karthik NarasimhanAbstractExisting benchmarks for grounding language in interactive environments either lack real-world linguistic elements, or prove difficult to scale up due to substantial human involvement in the collection of data or feedback signals. To bridge this gap, we develop WebShop -- a simulated e-co…
 
Jiashu WuAbstractOver the past decades, researchers had put lots of effort investigating ranking techniques used to rank query results retrieved during information retrieval, or to rank the recommended products in recommender systems. In this project, we aim to investigate searching, ranking, as well as recommendation techniques to help to realize …
 
Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, Jian LiAbstractMultivariate time series forecasting has seen widely ranging applications in various domains, including finance, traffic, energy, and healthcare. To capture the sophisticated temporal patterns, plenty of research studies designed complex neural network archite…
 
Mingyuan Meng, Lei Bi, Michael Fulham, David Dagan Feng, and Jinman KimAbstractDeformable image registration is fundamental for many medical image analyses. A key obstacle for accurate image registration lies in image appearance variations such as the variations in texture, intensities, and noise. These variations are readily apparent in medical im…
 
Alessandra Carneiro and Lorena Nascimento and Mauricio Noernberg and Carmem Hara and Aurora PozoAbstractPortuguese man-of-war (PMW) is a gelatinous organism with long tentacles capable of causing severe burns, thus leading to negative impacts on human activities, such as tourism and fishing. There is a lack of information about the spatio-temporal …
 
Zhibo Yang, Sounak Mondal, Seoyoung Ahn, Gregory Zelinsky, Minh Hoai, Dimitris SamarasAbstractThe prediction of human gaze behavior is important for building human-computer interactive systems that can anticipate a user's attention. Computer vision models have been developed to predict the fixations made by people as they search for target objects.…
 
Di Zhang, Qiang Niu, Youzhou ZhouAbstractVolatility clustering is a common phenomenon in financial time series. Typically, linear models are used to describe the temporal autocorrelation of the (logarithmic) variance of returns. Considering the difficulty in estimation of this model, we construct a Dynamic Bayesian Network, which utilizes the conju…
 
Eleanor Loh, Jalaj Khandelwal, Brian Regan, Duncan A. LittleAbstractManaging discount promotional events ("markdown") is a significant part of running an e-commerce business, and inefficiencies here can significantly hamper a retailer's profitability. Traditional approaches for tackling this problem rely heavily on price elasticity modelling. Howev…
 
Liam Schramm, Yunfu Deng, Edgar Granados, Abdeslam BoulariasAbstractDealing with sparse rewards is a long-standing challenge in reinforcement learning (RL). Hindsight Experience Replay (HER) addresses this problem by reusing failed trajectories for one goal as successful trajectories for another. This allows for both a minimum density of reward and…
 
Vahid Reza Khazaie and Anthony Wong and Yalda MohsenzadehAbstractAnomaly detection is to recognize samples that differ in some respect from the training observations. These samples which do not conform to the distribution of normal data are called outliers or anomalies. In real-world anomaly detection problems, the outliers are absent, not well def…
 
Vahid Reza Khazaie and Anthony Wong and John Taylor Jewell and Yalda MohsenzadehAbstractAnomaly detection is to identify samples that do not conform to the distribution of the normal data. Due to the unavailability of anomalous data, training a supervised deep neural network is a cumbersome task. As such, unsupervised methods are preferred as a com…
 
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