HC30-T2: Architectures for Accelerating Deep Neural Nets
Tutorial 2, Hot Chips 30 (2018), Sunday, August 19, 2018. Organizers: Kurt Keutzer, UC Berkeley, Geoffrey Burr, IBM, Bill Dally, Nvidia, and Ralph Wittig, Xilinx ...
hotchipsvideos
Lecture 1.2: Gabriel Kreiman - Computational Roles of Neural Feedback
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Gabriel ...
MIT OpenCourseWare
Andrew Ng: Artificial Intelligence is the New Electricity
On Wednesday, January 25, 2017, Baidu chief scientist, Coursera co-founder, and Stanford adjunct professor Andrew Ng spoke at the Stanford MSx Future ...
Stanford Graduate School of Business
【NTT IR DAY 2019】Quantum Neural Network
NTT IR DAY held on Thursday, September 26, 2019.
NTT official channel
Time Series Forecasting Using Recurrent Neural Network and Vector Autoregressive Model: When and How
The General Data Protection Regulation (GDPR), which came into effect on May 25, 2018, establishes strict guidelines for managing personal and sensitive data ...
Databricks
Computing in the 2020s
Future computing predictions from futurist Christopher Barnatt -- including the rise of AI and attentive computing, shrinking desktop PCs, mainstream NPUs, and ...
ExplainingComputers
Advanced Machine Learning Day 3: Neural Program Synthesis
How do you learn programs? View presentation slides and more at ...
Microsoft Research
Advanced Machine Learning Day 3: Neural Architecture Search
How do you search over architectures? View presentation slides and more at ...
Microsoft Research
AI in 2020
Almost exactly 4 years ago I decided to dedicate my life to helping educate the world on Artificial Intelligence. There were hardly any resources designed for ...
Siraj Raval
Keynote: The Neural Aesthetic - Gene Kogan
PyData Warsaw 2018 Over the past several years, two trends in machine learning have converged to pique the curiosity of artists working with code: the ...
PyData
The Future of Computing
As computing's underpinning technologies reach a tipping point 70 years in the making, a new innovation curve is ready to break out. Join Kirk Bresniker, Fellow ...
World Economic Forum
DataXDay - How to scale Neural Network Architecture Search with RabbitMQ and Kubernetes
Automated neural network architecture search (NAS) is a computation intensive task. Tools like Cloud AutoML have lower the technical barrier for adoption but ...
Publicis Sapient Engineering
"Student's Insights": #1 Introduction Neural Networks - from Max and Julian
Julian and Max provide you an intuitive and comprehensive Introduction on Artificial Neural Networks. They also provide insights in how to use that neural ...
Computational Risk and Asset Management Research Group of the KIT
Lecture 8 | Deep Learning Software
In Lecture 8 we discuss the use of different software packages for deep learning, focusing on TensorFlow and PyTorch. We also discuss some differences ...
Stanford University School of Engineering
MIT 6.S191 (2018): Sequence Modeling with Neural Networks
MIT Introduction to Deep Learning 6.S191: Lecture 2 Sequence Modeling with Neural Networks Lecturer: Harini Suresh January 2018 Lecture 1 - Introduction to ...
Alexander Amini
Xavier Bresson: "Convolutional Neural Networks on Graphs"
New Deep Learning Techniques 2018 "Convolutional Neural Networks on Graphs" Xavier Bresson, Nanyang Technological University, Singapore Abstract: ...
Institute for Pure & Applied Mathematics (IPAM)
Tutorial: Large-Scale Distributed Systems for Training Neural Networks
Over the past few years, we have built large-scale computer systems for training neural networks, and then applied these systems to a wide variety of problems ...
Microsoft Research
Lecture 3 | Loss Functions and Optimization
Lecture 3 continues our discussion of linear classifiers. We introduce the idea of a loss function to quantify our unhappiness with a model's predictions, and ...
Stanford University School of Engineering
Neural Networks Tutorial | Artificial Neural Network | Perceptron in AI | Intellipaat
Intellipaat Artificial Intelligence Course:- https://intellipaat.com/ai-deep-learning-course-with-tensorflow/ This Artificial Neural Network video is an introduction to ...
Intellipaat
Recurrent Neural Networks for Recommendations and Personalization with Nick Pentreath (IBM)
In the last few years, RNNs have achieved significant success in modeling time series and sequence data, in particular within the speech, language, and text ...
Databricks
Finding the right architectures for neural networks in the Bonseyes project
What's the right computer architecture for neural networks? In this video, Valentin Radu (University of Edinburgh) explains how the Bonseyes project is working ...
HiPEAC
The Political Mind | George Lakoff | Talks at Google
The Authors@Google program was pleased to welcome author and professor George Lakoff to Google's New York office to discuss his new book, "The Political ...
Talks at Google
Efficient Computing for Deep Learning, Robotics, and AI (Vivienne Sze) | MIT Deep Learning Series
Lecture by Vivienne Sze in January 2020, part of the MIT Deep Learning Lecture Series. Website: https://deeplearning.mit.edu Slides: http://bit.ly/2Rm7Gi1 ...
Lex Fridman
Stanford Seminar - Current Status of tinyML and the Enormous Opportunities Ahead (panel discussion)
Dr. Evgeni Gousev Qualcomm Research Pete Warden Google October 31, 2019 Dr. Evgeni Gousev is a Senior Director of Engineering in Qualcomm Research.
stanfordonline
Building the Software 2 0 Stack (Andrej Karpathy)
A lot of our code is in the process of being transitioned from Software 1.0 (code written by humans) to Software 2.0 (code written by an optimization, commonly in ...
Databricks
Artificial Intelligence & the Future - Rise of AI (Elon Musk, Bill Gates, Sundar Pichai)|Simplilearn
Artificial Intelligence (AI) is currently the hottest buzzword in tech. Here is a video on the role of Artificial Intelligence and its scope in the future. We have put ...
Simplilearn
SDC2020: Analog Memory-based Techniques for Accelerating Deep Neural Networks
Deep neural networks (DNNs) are the fundamental building blocks that allowed explosive growth in machine learning sub-fields, such as computer vision and ...
SNIAVideo
ML Conference 2018 - Livestream: Cracking Open the Black Box of Neural Networks - Xander Steenbrugge
Secure your 10% discount for the ML Con Spring 2019: https://mlconference.ai/youtube-special/ Through my own YouTube channel on Machine Learning ...
Machine Learning Conference
Tableau BI Trends 2019 - 1-Rise of Explainable AI
At Tableau, we believe that everyone should be able to explore their data to find insights that drive action. And in today's data-driven world, it's important for ...
Tableau Software
Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches |
For slides and more information on the paper, visit https://aisc.ai.science/events/2020-03-25 Discussion lead: Maurizio Ferrari Dacrema Discussion facilitator(s): ...
ML Explained - A.I. Socratic Circles - AISC
The incredible inventions of intuitive AI | Maurice Conti
What do you get when you give a design tool a digital nervous system? Computers that improve our ability to think and imagine, and robotic systems that come ...
TED
Lecture 1.1: Nancy Kanwisher - Human Cognitive Neuroscience
MIT RES.9-003 Brains, Minds and Machines Summer Course, Summer 2015 View the complete course: https://ocw.mit.edu/RES-9-003SU15 Instructor: Nancy ...
MIT OpenCourseWare
Lecture 15 | Efficient Methods and Hardware for Deep Learning
In Lecture 15, guest lecturer Song Han discusses algorithms and specialized hardware that can be used to accelerate training and inference of deep learning ...
Stanford University School of Engineering
NIPS 2015 Workshop (Smolensky) 15592 Cognitive Computation: Integrating neural and symbolic app...
While early work on knowledge representation and inference was primarily symbolic, the corresponding approaches subsequently fell out of favor, and were ...
NIPS
The Neural Basis of Perceiving Human Visual Social Perception
Leyla Isik, a post-doctoral researcher at MIT, studies how the human brain recognizes objects and social interactions, using MEG, fMRI, and computational ...
MITCBMM
Hyperbolic geometry and symmetry breaking in neural circuits
This special ICTP QLS Colloquium will be given by Prof. Tatyana Sharpee. The talk on Hyperbolic geometry and symmetry breaking in neural circuits will take ...
Int'l Centre for Theoretical Physics
Lecture 4: Cell Types and Computing in the Retina
The retina has 60 different types of neurons. What are their functions? Dr. Christof Koch explores the definition of cell types and their functions in the mammalian ...
Allen Institute
Understanding Artificial Intelligence and Its Future | Neil Nie | TEDxDeerfield
Neil Nie demonstrates how artificial intelligence--and particularly, object recognition--works... and how it will effect the future. Neil Nie is a computer science ...
TEDx Talks
CNS*2020: Keynote 4: Computational Models of Neural Development
CNS*2020: Keynote 4: Computational Models of Neural Development Speaker(s): Geoffery Goodhill https://sched.co/cm0n.
OCNS
Neural Network using Matlab - Real-world Example
In this lesson, we will implement a restaurant rating system using a single layer neural network.
Nuruzzaman Faruqui
Boltzmann Machines and Spiking Neural Networks using Probabilistic Spin Logic
Full information posted at: http://cal.ucf.edu/ * This work was supported by the Center for Probabilistic Spin Logic for Low-Energy Boolean and Non-Boolean ...
Ronald DeMara
New rules in the age of AI | Karim R. Lakhani
Harvard Business School Professor Karim R. Lakhani shares transformation opportunities and challenges in the digital world, drawing from insights presented in ...
HBS Digital Initiative
