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Artificial Intelligence הפודקאסטים הטובים ביותר שיכולנו למצוא
Artificial Intelligence הפודקאסטים הטובים ביותר שיכולנו למצוא
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!
 
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.
 
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 ...
 
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 ...
 
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.
 
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 ...
 
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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Not all algorithms are explainable. So does that mean that it’s ok to not provide any explanation on how your AI system got to the decision it did if you’re using one of those “black box” algorithms? The answer should obviously be no. So, what do you do then when creating Ethical and Responsible AI systems to address this issue around explainable a…
 
It’s safe to say that most people in data science want to do the right thing. However, AI ethics cannot just be an afterthought done in the service of regulatory obligations. It needs to be baked into the way the organisation looks at data, at every level. How organisations can achieve that is the focus of our latest podcast, with Natalie Rouse, Ge…
 
NOTE: I am excited to announce that all listeners of the Conversations on Applied AI Podcast are eligible to receive a 50% discount at the 2022 Applied AI Conference! Just use the discount code of "podcast" when purchasing your ticket. The conversation this week is with Younes Amar and Mohammed Sabri. Younes is the head of product at Wallaroo, an e…
 
Today we’re joined by Vidyut Naware, the director of machine learning and artificial intelligence at Paypal. As the leader of the ML/AI organization at Paypal, Vidyut is responsible for all things applied, from R&D to MLOps infrastructure. In our conversation, we explore the work being done in four major categories, hardware/compute, data, applied …
 
This and all episodes at: https://aiandyou.net/ . Don't Panic! Our returning guest, Robbie Stamp, is a friend and associate of the late Douglas Adams and was an executive producer on the 2005 movie of the HitchHiker's Guide to the Galaxy. But he is also CEO of Bioss International, a global consultancy helping clients focus on decision-making in con…
 
Andy and Dave discuss the latest in AI news and research, starting with a publication from the UK’s National Cyber Security Centre, providing a set of security principles for developers implementing machine learning models. Gartner publishes the 2022 update to its “AI Hype Cycle,” which qualitatively plots the position of various AI efforts along t…
 
Steven Banerjee: How Machine Intelligence, NLP and AI is changing Health Care [Audio] Podcast: Play in new window | Download Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS Steven Banerjee is the CEO of NExTNet Inc. NExTNet is a Silicon Valley based technology startup pioneering natural language based Explainable AI platform to accel…
 
Mingyo Seo, Ryan Gupta, Yifeng Zhu, Alexy Skoutnev, Luis Sentis and Yuke ZhuAbstractWe tackle the problem of perceptive locomotion in dynamic environments. In this problem, a quadrupedal robot must exhibit robust and agile walking behaviors in response to environmental clutter and moving obstacles. We present a hierarchical learning framework, name…
 
Like a newborn animal, a four-legged robot stumbles around during its first walking attempts. But while a foal or a giraffe needs much longer to master walking, the robot learns to move forward fluently in just one hour. A computer program acts as the artificial presentation of the animal's spinal cord, and learns to optimize the robot's movement i…
 
In order to have people use AI systems they need to feel that they can trust these systems. That includes putting measures in place around AI Auditability, Traceability, and System Control. But what exactly does that mean and how do you do this in the context of your Ethical and Responsible AI Framework? In this episode of the AI Today podcast host…
 
Healthcare is an industry that stands to benefit a great deal from data and analytics. At the same time, the sensitivity of the data in the sector is extreme and how organisations manage that data is critical. Yalchin Oytam, the Head Of Clinical Insights And Analytics at South Eastern Sydney Local Health District (SESLHD) is right in the thick of t…
 
Dingqi Zhang, Antonio Loquercio, Xiangyu Wu, Ashish Kumar, Jitendra Malik, Mark W. MuellerAbstractThis paper proposes a universal adaptive controller for quadcopters, which can be deployed zero-shot to quadcopters of very different mass, arm lengths and motor constants, and also shows rapid adaptation to unknown disturbances during runtime. The cor…
 
This and all episodes at: https://aiandyou.net/ . Don't Panic! This week's guest, Robbie Stamp, was a friend and associate of the late Douglas Adams and was an executive producer on the 2005 movie of the HitchHiker's Guide to the Galaxy. But he is also CEO of Bioss International, a global consultancy helping clients focus on decision-making in cond…
 
Today we’re back with another installment of our Data-Centric AI series, joined by Wendy Foster, a director of engineering & data science at Shopify. In our conversation with Wendy, we explore the differences between data-centric and model-centric approaches and how they manifest at Shopify, including on her team, which is responsible for utilizing…
 
Miguel Faria, Francisco S. Melo, Ana PaivaAbstractIn this paper we investigate the notion of legibility in sequential decision tasks under uncertainty. Previous works that extend legibility to scenarios beyond robot motion either focus on deterministic settings or are computationally too expensive. Our proposed approach, dubbed PoL-MDP, is able to …
 
Ziyun Li, Jona Otholt, Ben Dai, Di hu, Christoph Meinel, Haojin YangAbstractNovel class discovery (NCD) aims to infer novel categories in an unlabeled dataset leveraging prior knowledge of a labeled set comprising disjoint but related classes. Existing research focuses primarily on utilizing the labeled set at the methodological level, with less em…
 
Aaron M. Roth, Jing Liang, Ram Sriram, Elham Tabassi, and Dinesh ManochaAbstractWe present Multiple Scenario Verifiable Reinforcement Learning via Policy Extraction (MSVIPER), a new method for policy distillation to decision trees for improved robot navigation. MSVIPER learns an "expert" policy using any Reinforcement Learning (RL) technique involv…
 
Richard Comploi-Taupe and Gerhard Friedrich and Konstantin Schekotihin and Antonius WeinzierlAbstractDomain-specific heuristics are an essential technique for solving combinatorial problems efficiently. Current approaches to integrate domain-specific heuristics with Answer Set Programming (ASP) are unsatisfactory when dealing with heuristics that a…
 
Katherine Avery, Jack Kenney, Pracheta Amaranath, Erica Cai, David JensenAbstractRecent work in reinforcement learning has focused on several characteristics of learned policies that go beyond maximizing reward. These properties include fairness, explainability, generalization, and robustness. In this paper, we define interventional robustness (IR)…
 
Mateo Espinosa Zarlenga, Pietro Barbiero, Gabriele Ciravegna, Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Zohreh Shams, Frederic Precioso, Stefano Melacci, Adrian Weller, Pietro Lio, Mateja JamnikAbstractDeploying AI-powered systems requires trustworthy models supporting effective human interactions, going beyond raw prediction accu…
 
Kai North, Marcos Zampieri, Tharindu RanasingheAbstractLexical simplification (LS) is the task of automatically replacing complex words for easier ones making texts more accessible to various target populations (e.g. individuals with low literacy, individuals with learning disabilities, second language learners). To train and test models, LS system…
 
Orel Lavie, Asaf Shabtai, Gilad KatzAbstractMany challenging real-world problems require the deployment of ensembles multiple complementary learning models to reach acceptable performance levels. While effective, applying the entire ensemble to every sample is costly and often unnecessary. Deep Reinforcement Learning (DRL) offers a cost-effective a…
 
Peter Mlakar, Tapio Nummi, Polona Oblak, and Jana Faganeli PucerAbstractWe investigate a novel non-parametric regression-based clustering algorithm for longitudinal data analysis. Combining natural cubic splines with Gaussian mixture models (GMM), the algorithm can produce smooth cluster means that describe the underlying data well. However, there …
 
Jingguang Tian, Xinhui Hu, Xinkang XuAbstractIn this technical report, we describe the Royalflush submissions for the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). Our submissions contain track 1, which is for supervised speaker verification and track 3, which is for semi-supervised speaker verification. For track 1, we develop a powerfu…
 
Arhum Ishtiaq, Maheen Anees, Sara Mahmood, Neha JafryAbstractAutonomous driving vehicles have been of keen interest ever since automation of various tasks started. Humans are prone to exhaustion and have a slow response time on the road, and on top of that driving is already quite a dangerous task with around 1.35 million road traffic incident deat…
 
Alberta Longhini, Marco Moletta, Alfredo Reichlin, Michael C. Welle, David Held, Zackory Erickson, and Danica KragicAbstractWe study the problem of learning graph dynamics of deformable objects which generalize to unknown physical properties. In particular, we leverage a latent representation of elastic physical properties of cloth-like deformable …
 
Michiel van der Meer, Myrthe Reuver, Urja Khurana, Lea Krause, Selene B\'aez Santamar\'iaAbstractThis paper describes our contributions to the Shared Task of the 9th Workshop on Argument Mining (2022). Our approach uses Large Language Models for the task of Argument Quality Prediction. We perform prompt engineering using GPT-3, and also investigate…
 
Erick Rosete-Beas, Oier Mees, Gabriel Kalweit, Joschka Boedecker, Wolfram BurgardAbstractEveryday tasks of long-horizon and comprising a sequence of multiple implicit subtasks still impose a major challenge in offline robot control. While a number of prior methods aimed to address this setting with variants of imitation and offline reinforcement le…
 
Xianfu Chen and Zhifeng Zhao and Shiwen Mao and Celimuge Wu and Honggang Zhang and Mehdi BennisAbstractThe age of information metric fails to correctly describe the intrinsic semantics of a status update. In an intelligent reflecting surface-aided cooperative relay communication system, we propose the age of semantics (AoS) for measuring semantics …
 
Janne Alatalo, Joni Korpihalkola, Tuomo Sipola, Tero KokkonenAbstractOne-pixel attack is a curious way of deceiving neural network classifier by changing only one pixel in the input image. The full potential and boundaries of this attack method are not yet fully understood. In this research, the successful and unsuccessful attacks are studied in mo…
 
Qiong Nan, Danding Wang, Yongchun Zhu, Qiang Sheng, Yuhui Shi, Juan Cao, Jintao LiAbstractBoth real and fake news in various domains, such as politics, health, and entertainment are spread via online social media every day, necessitating fake news detection for multiple domains. Among them, fake news in specific domains like politics and health has…
 
Amir Ziaee, Erion \c{C}anoAbstractThis study introduces a new normalization layer termed Batch Layer Normalization (BLN) to reduce the problem of internal covariate shift in deep neural network layers. As a combined version of batch and layer normalization, BLN adaptively puts appropriate weight on mini-batch and feature normalization based on the …
 
Lukas Struppek, Dominik Hintersdorf, Kristian KerstingAbstractText-guided image generation models, such as DALL-E 2 and Stable Diffusion, have recently received much attention from academia and the general public. Provided with textual descriptions, these models are capable of generating high-quality images depicting various concepts and styles. Ho…
 
Ankitha Nandipura Prasanna, Priscila Grecov, Angela Dieyu Weng, Christoph BergmeirAbstractThe electricity industry is heavily implementing smart grid technologies to improve reliability, availability, security, and efficiency. This implementation needs technological advancements, the development of standards and regulations, as well as testing and …
 
Haotong Yang, Zhouchen Lin, Muhan ZhangAbstractMost knowledge graphs (KGs) are incomplete, which motivates one important research topic on automatically complementing knowledge graphs. However, evaluation of knowledge graph completion (KGC) models often ignores the incompleteness -- facts in the test set are ranked against all unknown triplets whic…
 
Dangxing ChenAbstractThe use of neural networks has been very successful in a wide variety of applications. However, it has recently been observed that it is difficult to generalize the performance of neural networks under the condition of distributional shift. Several efforts have been made to identify potential out-of-distribution inputs. Althoug…
 
Mingqi Yuan, Bo Li, Xin Jin, Wenjun ZengAbstractExploration is critical for deep reinforcement learning in complex environments with high-dimensional observations and sparse rewards. To address this problem, recent approaches proposed to leverage intrinsic rewards to improve exploration, such as novelty-based exploration and prediction-based explor…
 
Yiru Chen and Ryan Li and Austin Mac and Tianbao Xie and Tao Yu and Eugene WuAbstractWe develop NL2INTERFACE to explore the potential of generating usable interactive multi-visualization interfaces from natural language queries. With NL2INTERFACE, users can directly write natural language queries to automatically generate a fully interactive multi-…
 
Yaohua Liu, Wei Liang and Jinqiang CuiAbstractThis paper presents a lightweight, efficient calibration neural network model for denoising low-cost microelectromechanical system (MEMS) gyroscope and estimating the attitude of a robot in real-time. The key idea is extracting local and global features from the time window of inertial measurement units…
 
Jiaying Wu, Bryan HooiAbstractAs social media becomes a hotbed for the spread of misinformation, the crucial task of rumor detection has witnessed promising advances fostered by open-source benchmark datasets. Despite being widely used, we find that these datasets suffer from spurious correlations, which are ignored by existing studies and lead to …
 
Zezhong Xu, Wen Zhang, Peng Ye, Hui Chen, Huajun ChenAbstractAnswering complex queries over knowledge graphs (KG) is an important yet challenging task because of the KG incompleteness issue and cascading errors during reasoning. Recent query embedding (QE) approaches to embed the entities and relations in a KG and the first-order logic (FOL) querie…
 
Dichucheng Li, Yulun Wu, Qinyu Li, Jiahao Zhao, Yi Yu, Fan Xia, Wei LiAbstractThe Guzheng is a kind of traditional Chinese instruments with diverse playing techniques. Instrument playing techniques (IPT) play an important role in musical performance. However, most of the existing works for IPT detection show low efficiency for variable-length audio…
 
Jingxi Xu, Han Lin, Shuran Song, Matei CiocarlieAbstractTactile recognition of 3D objects remains a challenging task. Compared to 2D shapes, the complex geometry of 3D surfaces requires richer tactile signals, more dexterous actions, and more advanced encoding techniques. In this work, we propose TANDEM3D, a method that applies a co-training framew…
 
Saurav ManchandaAbstractKnowledge graph (KG) embedding techniques use structured relationships between entities to learn low-dimensional representations of entities and relations. The traditional KG embedding techniques (such as TransE and DistMult) estimate these embeddings via simple models developed over observed KG triplets. These approaches di…
 
Roshni G. Iyer, Yunsheng Bai, Wei Wang, Yizhou SunAbstractTwo-view knowledge graphs (KGs) jointly represent two components: an ontology view for abstract and commonsense concepts, and an instance view for specific entities that are instantiated from ontological concepts. As such, these KGs contain heterogeneous structures that are hierarchical, fro…
 
Vishwa Shah, Aditya Sharma, Gautam Shroff, Lovekesh Vig, Tirtharaj Dash, Ashwin SrinivasanAbstractAnalogical Reasoning problems challenge both connectionist and symbolic AI systems as these entail a combination of background knowledge, reasoning and pattern recognition. While symbolic systems ingest explicit domain knowledge and perform deductive r…
 
Yiping Lu, Wenlong Ji, Zachary Izzo, Lexing YingAbstractAlthough overparameterized models have shown their success on many machine learning tasks, the accuracy could drop on the testing distribution that is different from the training one. This accuracy drop still limits applying machine learning in the wild. At the same time, importance weighting,…
 
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