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Making artificial intelligence practical, productive, and accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, and more). The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the lates ...
 
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 ...
 
Neuroscience and artificial intelligence work better together. Brain inspired is a celebration and exploration of the ideas driving our progress to understand intelligence. I interview experts about their work at the interface of neuroscience, artificial intelligence, cognitive science, philosophy, psychology, and more: the symbiosis of these overlapping fields, how they inform each other, where they differ, what the past brought us, and what the future brings. Topics include computational n ...
 
On the Mind Matters podcast, Discovery Institute’s Walter Bradley Center for Natural and Artificial Intelligence considers the implications and misconceptions, the opportunities and limitations, and the applications and challenges presented by intelligent agents and their algorithms.
 
Welcome! We at MLST are inspired by scientists and each week we have a hard-hitting discussion with the leading thinkers in the AI space. Street Talk is ridiculously technical and we believe strongly in diversity of thought in AI, covering all the main ideas in the field, avoiding hype where possible. MLST is run by Dr. Tim Scarfe and Dr. Keith Duggar, and with regular appearances from Dr. Yannic Kilcher.
 
Eye on A.I. is a biweekly podcast, hosted by longtime New York Times correspondent Craig S. Smith. In each episode, Craig will talk to people making a difference in artificial intelligence. The podcast aims to put incremental advances into a broader context and consider the global implications of the developing technology. AI is about to change your world, so pay attention.
 
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NLP Highlights

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NLP Highlights

Allen Institute for Artificial Intelligence

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Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. The hosts are the members of the AllenNLP team at Allen Institute for AI. All views expressed belong to the hosts and guests and do not represent their employers.
 
TalkRL podcast is All Reinforcement Learning, All the Time. In-depth interviews with brilliant people at the forefront of RL research and practice. Guests from places like MILA, MIT, DeepMind, Berkeley, Amii, Oxford, Google Research, Brown, Waymo, Caltech, and Vector Institute. Hosted by Robin Ranjit Singh Chauhan. Technical content.
 
AI has been described as “Thor’s Hammer“ and “the new electricity.” But it’s also a bit of a mystery – even to those who know it best. We’ll connect with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor. This podcast is produced by NVIDIA, the AI computing company. Multiple episodes are released every month.
 
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 Data Brew by Databricks with Denny and Brooke! In this series, we explore various topics in the data and AI community and interview subject matter experts in data engineering/data science. So join us with your morning brew in hand and get ready to dive deep into data + AI! For this first season, we will be focusing on lakehouses – combining the key features of data warehouses, such as ACID transactions, with the scalability of data lakes, directly against low-cost object stores.
 
Roboism is a show mostly about robots. We are exploring how artificial intelligence, machine learning, and digital assistants are affecting our culture. Come explore the humanity behind the bots that are quickly becoming a part of every day life. Hosted by Kathy Campbell and Alex Cox.
 
The AI in Business Podcast is for non-technical business leaders who need to find AI opportunities, align AI capabilities with strategy, and deliver ROI. Each week, Emerj Artificial Intelligence Research CEO Daniel Faggella interviews top AI executives from Fortune 500 firms and unicorn startups - to uncover trends, use-cases, and best practices for practical AI adoption. Subscribe to Emerj's weekly AI newsletter by downloading our "Beginning with AI" PDF guide: https://emerj.com/beg1
 
Machine learning audio course, teaching the fundamentals of machine learning and artificial intelligence. It covers intuition, models (shallow and deep), math, languages, frameworks, etc. Where your other ML resources provide the trees, I provide the forest. Consider MLG your syllabus, with highly-curated resources for each episode's details at ocdevel.com. Audio is a great supplement during exercise, commute, chores, etc.
 
Get the inside story of how AI is being created and uncover the extraordinary ways artificial intelligence (AI) is transforming our world. In the highly-praised, award-nominated "DeepMind: The Podcast", mathematician and broadcaster Hannah Fry goes behind the scenes of world-leading research lab DeepMind to find out how AI can benefit our lives and the society we live in. The first season explores the link between neuroscience and AI, the importance of games, and building safe AI. Now in its ...
 
Unlock the business value of AI in financial services with in-depth interviews on trends, use-cases, and cutting-edge best practices. In each episode, Emerj Founder Daniel Faggella interviews leaders at firms like HSBC, Citigroup, and Visa - as well as AI innovators from Silicon Valley and around the world. Subscribe to Emerj's weekly AI newsletter by downloading our "AI in Financial Services Cheat Sheet" PDF guide: https://emerj.com/fin1
 
In each episode of The Robot Brains podcast, renowned artificial intelligence researcher, professor and entrepreneur Pieter Abbeel meets the brilliant minds attempting to build robots with brains. Pieter is joined by leading experts in AI Robotics from all over the world as he explores how far humanity has come in its mission to create conscious computers, mindful machines and rational robots. Host: Pieter Abbeel | Executive Producers: Alice Patel & Henry Tobias Jones | Audio Production: Kie ...
 
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.
 
Hosted by Rajeev Kanth to Build your skills on Data Science, Artificial intelligence, Machine Learning, Deep Learning e.t.c. from our podcasts. Listen to best podcasts like machine learning algorithms, data science projects, data science resume building tips, data science algorithms, data science job life, machine learning applications, machine learning implementations, big data e.t.c. from this top podcasts in the industry. Listen now in iTunes, buzzsprout, Spotify, anchor FM e.t.c. Learn D ...
 
Al: Innovation or Destruction? In this sci-fi podcast based on the groundbreaking interactive series Artificial, our hosts delve into the world of Sophie, an artificial intelligence being on a journey to become human, in attempts to illuminate the dangers and benefits of AI while looking at how to ethically treat and develop our new sentient friends. We invite you to join the conversation and weigh in on the ultimate question: Will Al prove to be good for the world... or will it lead to our ...
 
The team at MMC go 'Beyond the Hype' with the world’s leading AI technologists, entrepreneurs and corporate executives that are transforming today's industries. This podcast is produced by MMC Ventures, the research-led venture capital firm investing in early-stage technology companies. Visit mmc.vc for more details or find us on Twitter @MMC_Ventures.
 
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Learning Machines 101

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Learning Machines 101

Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

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Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions that wil ...
 
BRIDGEi2i’s signature podcast “AI to Impact” covers everything about Digital and AI. Featuring some remarkable thought leadership, expert points of view, and commentaries from a gamut of industry leaders, this is a definitive guide for Making AI Real. Put on your headphones and join us on this insightful journey of AI-powered Transformation.You can also listen to our podcast on below channels-Spotify link: https://spoti.fi/2TiJLRfApple link: https://apple.co/3cI0pkUGoogle link: https://bit.l ...
 
Hello World, it's Siraj! I conduct educational discussions about AI technology, Science, Engineering, and Mathematics with humans I admire. The goal is to give you inspiration & education so that you can gain financial freedom by helping create technology that empowers humans. Support this podcast: https://anchor.fm/sirajraval/support
 
Welcome to YOU, a podcast about the intersection of technology, humanity, and identity, brought to you by Okta. Each episode, host Claire L. Evans speaks with renowned experts in the fields of science, technology, art, philosophy, and design about how tech is changing the way we see ourselves, each other, and the world. Together, we’ll explore the many facets of identity: how we quantify ourselves, find love and belonging, engage as citizens, and so much more.
 
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Today’s guest is Arun Iyengar, CEO at Untether AI. Untether is a semiconductor firm based in Toronto, but with employees all over North America, including Silicon Valley. Arun previously worked with AMD, another major hardware and software firm in the Bay Area, before stepping into his current CEO role at Untether AI. In this episode, Arun shares s…
 
Far too often, agencies, organizations, and consulting firms are running data and AI projects without taking the right steps to ensure their success. Agile and iterative approaches have become adopted best practices for application development projects, but why don’t we have something similar when it comes to advanced analytics, big data, and AI pr…
 
Chenyang Si, Weihao Yu, Pan Zhou, Yichen Zhou, Xinchao Wang, Shuicheng YanAbstractRecent studies show that Transformer has strong capability of building long-range dependencies, yet is incompetent in capturing high frequencies that predominantly convey local information. To tackle this issue, we present a novel and general-purpose Inception Transfo…
 
This week, we continue our conversations around the topic of Data-Centric AI joined by a friend of the show Adrien Gaidon, the head of ML research at the Toyota Research Institute (TRI). In our chat, Adrien expresses a fourth, somewhat contrarian, viewpoint to the three prominent schools of thought that organizations tend to fall into, as well as a…
 
[Audio] Podcast: Play in new window | Download Subscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSS Gianluca Mauro is the CEO of AI Academy, which he founded with the mission of helping people understand what artificial intelligence is and its place in their organizations and their career. Gianluca is the author of the book "Zero to AI - …
 
Andy and Dave discuss the latest in AI news and research, starting with the European Parliament adopting the final recommendations of the Special Committee on AI in a Digital Age (AIDA), finding that the EU should not always regulate AI as a technology, but use intervention proportionate to the type of risk, among other recommendations [1:31]. Sync…
 
Early in his career, IEEE fellow and retired National Science Foundation program director Paul Werbos developed the neural network training algorithm known as error backpropagation, which has been foundational to the vast majority of today’s advances in artificial intelligence. Listen in as he discusses his work in this area and other topics, inclu…
 
Mathieu Lauri\`ere, Sarah Perrin, Matthieu Geist, Olivier PietquinAbstractNon-cooperative and cooperative games with a very large number of players have many applications but remain generally intractable when the number of players increases. Introduced by Lasry and Lions, and Huang, Caines and Malham\'e, Mean Field Games (MFGs) rely on a mean-field…
 
Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin ChoiAbstractTheorem proving in natural mathematical language - the mixture of symbolic and natural language used by humans - plays a central role in mathematical advances and education, and tests aspects of reasoning that are core to intelligence. Yet it has remained underexplored wi…
 
Dmitrii Medvedev, Rand Muhtaseb, Ahmed Al MahrooqiAbstractGlaucoma is one of the most severe eye diseases, characterized by rapid progression and leading to irreversible blindness. It is often the case that pathology diagnostics is carried out when the one's sight has already significantly degraded due to the lack of noticeable symptoms at early st…
 
Haitian Sun, William W. Cohen, Ruslan SalakhutdinovAbstractSome questions have multiple answers that are not equally correct, i.e. answers are different under different conditions. Conditions are used to distinguish answers as well as to provide additional information to support them. In this paper, we study a more challenging task where answers ar…
 
Zangir Iklassov, Dmitrii MedvedevAbstractLogistics optimization nowadays is becoming one of the hottest areas in the AI community. In the past year, significant advancements in the domain were achieved by representing the problem in a form of graph. Another promising area of research was to apply reinforcement learning algorithms to the above task.…
 
Xin Sun, Xuan Wang, Jialin Gao, Qiong Liu, Xi ZhouAbstractMoment retrieval in videos is a challenging task that aims to retrieve the most relevant video moment in an untrimmed video given a sentence description. Previous methods tend to perform self-modal learning and cross-modal interaction in a coarse manner, which neglect fine-grained clues cont…
 
Ho Long Fung, Victor-Alexandru Darvariu, Stephen Hailes, Mirco MusolesiAbstractAn often neglected issue in multi-agent reinforcement learning (MARL) is the potential presence of unreliable agents in the environment whose deviations from expected behavior can prevent a system from accomplishing its intended tasks. In particular, consensus is a funda…
 
Liyan Tang, Tanya Goyal, Alexander R. Fabbri, Philippe Laban, Jiacheng Xu, Semih Yahvuz, Wojciech Kry\'sci\'nski, Justin F. Rousseau, Greg DurrettAbstractThe propensity of abstractive summarization systems to make factual errors has been the subject of significant study, including work on models to detect factual errors and annotation of errors in …
 
Akshat GuptaAbstractSpoken dialog systems are slowly becoming and integral part of the human experience due to their various advantages over textual interfaces. Spoken language understanding (SLU) systems are fundamental building blocks of spoken dialog systems. But creating SLU systems for low resourced languages is still a challenge. In a large n…
 
Miroslav Bl\v{s}t\'ak and Viera Rozinajov\'aAbstractAutomatic question generation is one of the most challenging tasks of Natural Language Processing. It requires "bidirectional" language processing: firstly, the system has to understand the input text (Natural Language Understanding) and it then has to generate questions also in the form of text (…
 
Stephen Kotkin is a historian specializing in Stalin and Soviet history. Please support this podcast by checking out our sponsors: – Lambda: https://lambdalabs.com/lex – Scale: https://scale.com/lex – Athletic Greens: https://athleticgreens.com/lex and use code LEX to get 1 month of fish oil – ExpressVPN: https://expressvpn.com/lexpod and use code …
 
Bei Zhou and S{\o}ren RiisAbstractThe AlphaZero algorithm and its successor MuZero have revolutionised several competitive strategy games, including chess, Go, and shogi and video games like Atari, by learning to play these games better than any human and any specialised computer program. Aside from knowing the rules, AlphaZero had no prior knowled…
 
Shuyu Yin, Tao Luo, Peilin Liu, Zhi-Qin John XuAbstractGradient descent or its variants are popular in training neural networks. However, in deep Q-learning with neural network approximation, a type of reinforcement learning, gradient descent (also known as Residual Gradient (RG)) is barely used to solve Bellman residual minimization problem. On th…
 
Andrea Gesmundo and Jeff DeanAbstractMultitask learning assumes that models capable of learning from multiple tasks can achieve better quality and efficiency via knowledge transfer, a key feature of human learning. Though, state of the art ML models rely on high customization for each task and leverage size and data scale rather than scaling the nu…
 
Xiaonan Gao, Sen Wu, Wenjun ZhouAbstractWe propose NECA, a deep representation learning method for categorical data. Built upon the foundations of network embedding and deep unsupervised representation learning, NECA deeply embeds the intrinsic relationship among attribute values and explicitly expresses data objects with numeric vector representat…
 
Sascha Saralajew and Ammar Shaker and Zhao Xu and Kiril Gashteovski and Bhushan Kotnis and Wiem Ben-Rim and J\"urgen Quittek and Carolin LawrenceAbstractWith the rise of AI systems in real-world applications comes the need for reliable and trustworthy AI. An important aspect for this are explainable AI systems. However, there is no agreed standard …
 
Zhora GevorgyanAbstractThe effectiveness of Object Detection, one of the central problems in computer vision tasks, highly depends on the definition of the loss function - a measure of how accurately your ML model can predict the expected outcome. Conventional object detection loss functions depend on aggregation of metrics of bounding box regressi…
 
Daniel Cunnington, Mark Law, Jorge Lobo, Alessandra RussoAbstractOne of the ultimate goals of Artificial Intelligence is to learn generalised and human-interpretable knowledge from raw data. Neuro-symbolic reasoning approaches partly tackle this problem by improving the training of a neural network using a manually engineered symbolic knowledge bas…
 
Clara Na, Sanket Vaibhav Mehta, Emma StrubellAbstractModel compression by way of parameter pruning, quantization, or distillation has recently gained popularity as an approach for reducing the computational requirements of modern deep neural network models for NLP. Pruning unnecessary parameters has emerged as a simple and effective method for comp…
 
Monica Agrawal, Stefan Hegselmann, Hunter Lang, Yoon Kim, David SontagAbstractWe show that large language models, such as GPT-3, perform well at zero-shot information extraction from clinical text despite not being trained specifically for the clinical domain. We present several examples showing how to use these models as tools for the diverse task…
 
Junyeob Kim, Hyuhng Joon Kim, Hyunsoo Cho, Hwiyeol Jo, Sang-Woo Lee, Sang-goo Lee, Kang Min Yoo, Taeuk KimAbstractDespite recent explosion in research interests, in-context learning and the precise impact of the quality of demonstrations remain elusive. While, based on current literature, it is expected that in-context learning shares a similar mec…
 
Terufumi Morishita, Gaku Morio, Shota Horiguchi, Hiroaki Ozaki, Nobuo NukagaAbstractWe propose a fundamental theory on ensemble learning that evaluates a given ensemble system by a well-grounded set of metrics. Previous studies used a variant of Fano's inequality of information theory and derived a lower bound of the classification error rate on th…
 
Saad Abbasi, Alexander Wong, Mohammad Javad ShafieeAbstractDeep neural network (DNN) latency characterization is a time-consuming process and adds significant cost to Neural Architecture Search (NAS) processes when searching for efficient convolutional neural networks for embedded vision applications. DNN Latency is a hardware dependent metric and …
 
Sungryull Sohn, Hyunjae Woo, Jongwook Choi, lyubing qiang, Izzeddin Gur, Aleksandra Faust, Honglak LeeAbstractWe tackle real-world problems with complex structures beyond the pixel-based game or simulator. We formulate it as a few-shot reinforcement learning problem where a task is characterized by a subtask graph that defines a set of subtasks and…
 
Yimin Ou, Rui Yang, Lufan Ma, Yong Liu, Jiangpeng Yan, Shang Xu, Chengjie Wang, Xiu LiAbstractExisting instance segmentation methods have achieved impressive performance but still suffer from a common dilemma: redundant representations (e.g., multiple boxes, grids, and anchor points) are inferred for one instance, which leads to multiple duplicated…
 
Jie Huang, Hanyin Shao, Kevin Chen-Chuan ChangAbstractLarge Pre-Trained Language Models (PLMs) have facilitated and dominated many NLP tasks in recent years. However, despite the great success of PLMs, there are also privacy concerns brought with PLMs. For example, recent studies show that PLMs memorize a lot of training data, including sensitive i…
 
Jingnong Qu, Liunian Harold Li, Jieyu Zhao, Sunipa Dev, Kai-Wei ChangAbstractDisinformation has become a serious problem on social media. In particular, given their short format, visual attraction, and humorous nature, memes have a significant advantage in dissemination among online communities, making them an effective vehicle for the spread of di…
 
Yuhuai Wu, Albert Q. Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian SzegedyAbstractAutoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could advance the fields of formal verification, program synthesis, a…
 
Rebecca Qian, Candace Ross, Jude Fernandes, Eric Smith, Douwe Kiela, Adina WilliamsAbstractUnwanted and often harmful social biases are becoming ever more salient in NLP research, affecting both models and datasets. In this work, we ask: does training on demographically perturbed data lead to more fair language models? We collect a large dataset of…
 
I-Hung Hsu, Kuan-Hao Huang, Shuning Zhang, Wenxin Cheng, Premkumar Natarajan, Kai-Wei Chang, Nanyun PengAbstractRelational structure extraction covers a wide range of tasks and plays an important role in natural language processing. Recently, many approaches tend to design sophisticated graphical models to capture the complex relations between obje…
 
Ross Greer and Mohan TrivediAbstractIn this work, we contribute an EM algorithm for estimation of corner points and linear crossing segments for both marked and unmarked pedestrian crosswalks using the detections of pedestrians from processed LiDAR point clouds or camera images. We demonstrate the algorithmic performance by analyzing three real-wor…
 
Jiaxin Wei, Lige Liu, Ran Cheng, Wenqing Jiang, Minghao Xu, Xinyu Jiang, Tao Sun, Soren Schwertfeger, Laurent KneipAbstractRecent years have witnessed the surge of learned representations that directly build upon point clouds. Though becoming increasingly expressive, most existing representations still struggle to generate ordered point sets. Inspi…
 
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