Sam and Emma host Kate Crawford, Research Professor at the University of Southern California Annenberg, to discuss her recent book Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence, on our relationship with big tech, and the concept of the AI industry as a continuation of the extractive practices and power dynamics in the workplace that we have been building for centuries. We stream our live show every day at 12 PM ET. We need your help to keep providing free videos! Support the Majority Report’s video content by going to Watch the Majority Report live M–F at 12 p.m. EST at or listen via daily podcast at http://Majority.FM Download our FREE app: SUPPORT the show by becoming a member: We Have Merch!!! LIKE us on Facebook: FOLLOW us on Twitter: SUBSCRIBE to us on YouTube:
As AI chips become more common, three primary approaches are moving to the forefront. Here’s how to take advantage of repeatability, what the different flavors look like, the difference between flat and hierarchical design, and what impact black-box arrays have on programmability. Bradley Geden, director of product marketing at Synopsys, talks with Semiconductor Engineering.
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: Jacob Devlin, Google AI Language Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Director, Stanford Artificial Intelligence Laboratory (SAIL)
How you can speed up the creation of many repetitive descriptions significantly by using AX Semantics software? You will learn this in this video. AX Semantics software is intuitive and quickly able to generate all the content needed to keep pace with your business needs. AX software is 100% SaaS – everything is available from your desk via your web browser, no programming or IT departments required. Our self-service with integrated e-learning allows customers to start automating text within 48 hours – more than 500 customers have already done this successfully. We already work with some of the world’s best known brands on content generation
For more information about Stanford’s Artificial Intelligence professional and graduate programs, visit: Professor Christopher Manning, Stanford University Professor Christopher Manning Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science Director, Stanford Artificial Intelligence Laboratory (SAIL) To follow along with the course schedule and syllabus, visit:
In this Python Tutorial we build a simple chatbot using PyTorch and Deep Learning. I will also provide an introduction to some basic Natural Language Processing (NLP) techniques. 1) Theory + NLP concepts (Stemming, Tokenization, bag of words) 2) Create training data 3) PyTorch model and training 4) Save/load model and implement the chat Resource: This tutorial was inspired and adapted from the following article: “Contextual Chatbots with Tensorflow”: 🪁 Code faster with Kite, AI-powered autocomplete that integrates into VS Code: * ✅ Write cleaner code with Sourcery, instant refactoring suggestions in VS Code & PyCharm: * 📚 Get my FREE NumPy Handbook: 📓 Notebooks available on Patreon: ⭐ Join Our Discord : If you enjoyed this video, please subscribe to the channel! NLTK: You can find the code on GitHub: PyTorch Beginner Course: Please checkout my website to see all tutorials: You can find me here: Twitter: GitHub: Icons: #PyTorch #NLP #DeepLearning ———————————————————————————————————- * This is a sponsored or an affiliate link. By clicking on it you will not have any additional costs, instead you will support me and my project. Thank you so much for the support! 🙏
Parkinson’s disease (PD) is a progressive disorder with a presymptomatic interval; that is, there is a period during which the pathologic process has begun, but motor signs required for the clinical diagnosis are absent. There is considerable interest in discovering markers to diagnose this preclinical stage. Current predictive marker development stems mainly from two principles; first, that pathologic processes occur in lower brainstem regions before substantia nigra involvement and second, that redundancy and compensatory responses cause symptoms to emerge only after advanced degeneration. Decreased olfaction has recently been demonstrated to predict PD in prospective pathologic studies, although the lead time may be relatively short and the positive predictive value and specificity are low. Screening patients for depression and personality changes, autonomic symptoms, subtle motor dysfunction on quantitative testing, sleepiness and insomnia are other potential simple markers. More invasive measures such as detailed autonomic testing, cardiac MIBG-scintigraphy, transcranial ultrasound, and dopaminergic functional imaging may be especially useful in those at high risk or for further defining risk in those identified through primary screening. Despite intriguing leads, direct testing of preclinical markers has been limited, mainly because there is no reliable way to identify preclinical disease. Idiopathic RBD is characterized by loss of normal atonia with REM sleep. Approximately 50% of affected individuals will develop PD or dementia within 10 years. Dataset Link: #machinelearning #artificialintelligence #ai #datascience #python #programming #technology #deeplearning #coding #bigdata #computerscience #tech #data #pythonprogramming #programmer #developer #dataanalytics #software #datascientist #javascript #iot #java #coder #ml #innovation #robotics #linux #analytics [More]
Here is a compilation of best thought provoking quotes on Artificial Intelligence. #Alan Kay #Alan Perlis #Eliezer Yudkowsky #Elon Musk #Gray Scott #Klaus Schwab #Larry Page #Ray Kurzweil #Stephen Hawking #Tom Chatfield #AI #aiquotes #technology
First Order Logic in Artificial Intelligence, that is FOL is explained fully here. We will also see examples to convert English sentences into FOL in AI in this video of CSE concepts with Parinita. #FirstOrderLogic #FOL #ai #ArtificialIntelligence #cse #cseconceptwithparinita For the people asking me for the equipments I use…. you can buy them from the below links: MOBILE: LAPTOP: TRIPOD: MIC: CAMERA: HEADPHONES: POWER BANK: EARPLUGS: WHITE BOARD: If you like my video contents, please LIKE, COMMENT, SUBSCRIBE and SHARE with your friends. You can always connect with me at: Facebook: Instagram: Whatsapp: Mail: Compiler design tutorials: Theory of computation (TOC) tutorials: Cryptography techniques tutorials: Artificial Intelligence tutorials: GATE previous year important questions: Data Compression tutorials: Computer networks tutorials: Technical job updates: Database management system tutorials: Data structures and Algorithms tutorials: Programming questions: Digital image processing: Digital electronics: Motivational videos: Keep learning, keep supporting 🤝✨💯
The influence of AI is on the rise today, as this technology holds the potential to transform the country’s economic potential. According to Prime Minister Narendra Modi the day is pretty close when humanity will completely depend on AI. Modi remarks, “Artificial intelligence will drive human race. It will be debated whether there will be any jobs left or not. However, experts say that there is huge possibility of job creation through AI.” Get in touch with us: Website: Contact: Facebook: Twitter: Linkedin:
SASTRA Day 1, Session 01 ATAL AICTE FDP on AI,ML u0026DL 2020 09 13 at 20 51 GMT 7 Workshop topics – Introduction to Artificial Intelligence – Introduction to Python – Introduction to Internet of Things(IoT) – Problem Formulations & Representations – Uninformed and Informed Search Algorithms – Knowledge Representation and different types of Knowledge Representation – Ontology Engineering – Fuzzy and Temporal Logic Systems – Natural Language Processing – Machine Learning and Deep Learning – Reinforcement Learning – Application and current trends of AI – Sample Problems – Case Studies & hands-on Coding using Python for the above topics Full playlist:
Part II of Session 4 of CMPS 403 Artificial Intelligence, Fall 2020 course at Qatar University by Dr. Tamer Elsayed ( Slides are available at: The entire set of lectures are available at: This course is mostly following Berkeley’s “CS188” course.
Watch this video completely to know more about the course which helped more than three hundred people to find their dream job within just three years time. For More Info and Free Videos. Register Here – Contact Us: USA: +1-314-827-5272 India: 91-837-432-3742 Email: Social links: FaceBook – Twitter – Linkedin – Add Connection OR Join our Professional Network on… Google+ – Add to Circles on
Session Chair: Federica Sarro Perf-AL: Performance Prediction for Configurable Software through Adversarial Learning – (Technical Paper) Yangyang Shu, Yulei Sui, Hongyu Zhang and Guandong Xu Presenter: Yangyang Shu Learning Features that Predict Developer Responses for iOS App Store Reviews – (Technical Paper) Kamonphop Srisopha, Daniel Link, Devendra Swami and Barry Boehm Presenter: Kamonphop Srisopha Automatic Identification of Code Smell Discussions on Stack Overflow: A Preliminary Investigation – (Emerging Result and Vision Paper) Sergei Shcherban, Peng Liang, Amjed Tahir and Xueying Li Presenter: Peng Liang GASSER: Genetic Algorithm for teSt Suite Reduction – (Emerging Result and Vision Paper) Carmen Coviello, Simone Romano, Giuseppe Scanniello and Giuliano Antoniol Presenter: Carmen Coviello
📌 Session #4 – SSD: Single Shot MultiBox Detector 📌 Paper Reading & Discussion About: MLT __init__ is a monthly event led by Jayson Cunanan and J. Miguel Valverde where a paper is first presented by a volunteer and then discussed among all attendees. Our goal is to give participants good initializations to study Deep Learning effectively. We also hope to promote collaboration between participants. We will try to achieve this by: * Discussing fundamental papers whose key ideas apply to state-of-the-art models. * Providing the audience with summaries, codes, and visualizations to help understand the critical parts of a research paper. 📌 SPEAKER BIO Charles Melby-Thompson is an AI Researcher at AI Inside. He obtained a Ph.D. in Physics from UC Berkeley, MSc Mathematics and Comp. Science from the University of Oxford and A.B. Physics from Princeton University. He has multiple research experiences from several countries including Japan. Related links: 📌ORGANIZERS’ BIO * J. Miguel Valverde is a Ph.D. student at the University of Eastern Finland working on Rodent MRI Segmentation with Deep Learning. He has multiple research experiences across Europe and Japan. In his free time, he enjoys nature, learning languages, programming, and making food. * Jayson Cunanan is an AI Researcher/Engineer at AI inside. He obtained a Ph.D. in Mathematics at Nagoya University and was awarded the JSPS Postdoctoral Fellowship 2018. In his free time, he loves playing the guitar. ========================= MLT (Machine Learning Tokyo) site: github: slack: discuss: [More]
Just wait til 1:15… David tries to imitate his human family by pretending to eat and drink, but see what happens after that..
Fei-Fei Li, director of Stanford Artificial Intelligence Laboratory, and Lei Zhang, chairman and CIO of Hillhouse Capital Management, discuss with Paul Oyer, an economics professor at the Graduate School of Business, the current research and development in the field of artificial intelligence, as well as future implementations into daily life, at the Stanford China Economic Forum in Beijing, on September 8, 2018.
Talk given on 2021/06/20. Andrej is the Senior Director of AI at Tesla, where he leads the team responsible for all neural networks on the Autopilot. Previously, Andrej was a Research Scientist at OpenAI working onDeep Learning in Computer Vision, Generative Modeling and Reinforcement Learning. Andrej received his PhD from Stanford, where he worked with Fei-Fei Li on Convolutional/Recurrent Neural Network architectures and their applications in Computer Vision, Natural Language Processing and their intersection. Over the course of his PhD, Andrej squeezed in two internships at Google where he worked on large-scale feature learning over YouTube videos, and in 2015 he interned at DeepMind and worked on Deep Reinforcement Learning. Together with Fei-Fei, Andrej designed and taught a new Stanford class on Convolutional Neural Networks for Visual Recognition (CS231n). The class was the first Deep Learning course offering at Stanford and has grown from 150 enrolled in 2015 to 330 students in 2016, and 750 students in 2017.
✅ Instagram: You are on the PRO Robotics channel and in this episode we will talk about what science has already achieved in the field of artificial intelligence and what we can expect in the future. Conscious and super-intelligent AI, variants of artificial intelligence development, whether the singularity is possible and why Elon Musk is afraid of artificial intelligence and creates his own chip in the brain. Watch the video to the end and write in the comments what you think about the future of artificial intelligence? Time Codes: 00:00 Intro 00:38 Artificial intelligence today 1:10 Machine learning and deep learning 1:43 Narrow artificial intelligence 3:14 Conscious artificial intelligence 4:22 Supersmartt artificial intelligence 5:11 Why is Elon Musk afraid of artificial intelligence 6:11 Can robots have desires 7:09 Why do we need a chip in Elon Musk’s brain 8:24 Will we become cyborgs 9:02 The future with artificial intelligence #prorobots #artificialintelligence #supersmartt #elonmusk #technology #technologynews #sciencenews More interesting and useful content: ✅ Elon Musk Innovation ✅Future Technologies Reviews ✅ Technology news #prorobots #technology #roboticsnews PRO Robots is not just a channel about robots and future technologies, we are interested in science, technology, new technologies and robotics in all its manifestations, science news, technology news today, science and technology news 2020, so that in the future it will be possible to expand future release topics. Today, our vlog just talks about complex things, follows the tech news, makes reviews of exhibitions, conferences and events, where the main [More]
Artificial intelligence is changing how we interact with everything: food, healthcare, travel – and also religion. Experts say major global faiths are discussing their relationship with AI, and some are starting to incorporate this technology into their worship. Robot priests can recite prayers, perform funerals, and even comfort those experiencing a spiritual crisis. Is it just a gimmick, or will it transform how people experience faith? Please subscribe HERE #BBCNews
Elon Musk Says AI Will Take Over in 5 Years – How Neuralink Will Change Humanity Musk has consistently warned us of the existential threat posed by advanced artificial intelligence in recent years. Despite this, he still feels that the issue is not properly understood.  Many widely regarded scientist, like Steven Hawking, Steve Wozniak and Bill Gates, have already expressed their concerns that super-intelligent AI could escape our control and move against us. Musk lays out a number of possible scenarios for us to survive the rise of AI, if at all. One of them is his neuroscience start-up, Neuralink. The company aims to implant wireless brain-computer interfaces that will link human brains directly to computers. For Musk, brain computer interfaces are the only way the human race will survive the dangers of AI. ⏱️ TIMESTAMPS 00:00 – Intro 01:28 – Why AI is Dangerous 06:30 – The Singularity and Self-Designed Evolution 08:25 – Neuralink 10:35 – Concerns About AI Companies – DeepMind ►► Tech Flake explores the big questions with an open mind. Subscribe for more: ►►
As a research scientist at Google, Margaret Mitchell helps develop computers that can communicate about what they see and understand. She tells a cautionary tale about the gaps, blind spots and biases we subconsciously encode into AI — and asks us to consider what the technology we create today will mean for tomorrow. “All that we see now is a snapshot in the evolution of artificial intelligence,” Mitchell says. “If we want AI to evolve in a way that helps humans, then we need to define the goals and strategies that enable that path now.” Check out more TED Talks: The TED Talks channel features the best talks and performances from the TED Conference, where the world’s leading thinkers and doers give the talk of their lives in 18 minutes (or less). Look for talks on Technology, Entertainment and Design — plus science, business, global issues, the arts and more. Follow TED on Twitter: Like TED on Facebook: Subscribe to our channel:
Want to join the debate? Check out the Intelligence Squared website to hear about future live events and podcasts: __________________________ ** PLEASE NOTE: This video is owned by the BBC and as such is unavailable in some countries. We apologise for any inconvenience this may cause. However, the event is available as an episode of our podcast here: ** Filmed at the Emmanuel Centre in London on 2nd March 2015. They are coming to an office near you: job-gobbling robots that can do your work better and more cheaply than you can. One in three jobs could be taken over by a computer or a robot in the next 20 years. Most at risk are less skilled workers such as machine operators, postmen, care workers and professional drivers. The CEO of Uber, the ride-sharing company, recently said that his goal is to replace all the firm’s drivers with autonomous cars. But it’s not just blue-collar workers who are under threat. The relentless drive to replace expensive humans with artificial intelligence poses a threat to better paid jobs too. People whose work requires uniquely human skills, such as teachers, priests, and social workers, are likely to be safe. But already in law firms, junior lawyers are being replaced by software that can scan reams of documents in search of evidence; and in hospitals the role of pharmacists is being taken over by drug-dispensing robots. What’s worse, the people gaining from all this disruption are those already rich enough to [More]
Martin Ford There’s Going To Be Less Need For Human Workers (Techno Talk) Rise of the Robots: Technology and the Threat of a Jobless Future is a 2015 book by American futurist Martin Ford. Rise discusses the impact accelerating change and artificial intelligence will have on the labor market. His thesis is that there will be great social and economic disruption, as educated workers will no longer be able to find employment; unlike in previous technological revolutions, very few new jobs will be created in the course of the ongoing disruption.[1] While technological advances in the previous century mainly displaced more uneducated laborers, the 21st century is seeing technology increasingly threatening skilled workers’ jobs as well. Lawyers, radiologists and software designers have seen their work outsourced to the developing world. Ford believes that unlike previous centuries, the current emerging technologies will fail to generate new forms of employment; he predicts that new industries will “rarely, if ever, be highly labor-intensive”. Companies like YouTube and Instagram are based on “tiny workforces and huge valuations and revenues”.[2] Ford downplays the benefits of expanding education (“The problem is that the skills ladder is not really a ladder at all: it is a pyramid, and there is only so much room at the top”), and argues for a “dramatic policy response” such as a guaranteed basic income.[3] Many economists disagree with Ford’s thesis that the IT revolution is fundamentally different from previous technological revolutions.[4] Libertarian economist Robin Hanson argues that the recent ominous labor [More]
Felix Zuniga, Manuel Franco and Curt Hahn will join Armando F Sanchez on a panel to discuss the principle ideas of Martin Ford’s book Rise of the Robots.