After a viral blog post by Andrej Karpathy demonstrated that recurrent neural networks are capable of producing very realistic looking (but fake) text, C source code, and even LaTex, there has been considerable interested in this technology. This video demonstrates the use of LSTM, in Keras/TensorFlow, to generate text based on a sample corpus. Code for This Video: Course Homepage: Follow Me/Subscribe: Support Me on Patreon:
Julia Computing delivers JuliaSim as an answer to accelerating simulations through digital-twin (or surrogate) modeling. By blending classical, physical modeling with advanced scientific machine learning (SciML) techniques, JuliaSim provides a next-generation platform for building, accelerating, and analyzing models. 00:00 Julia Computing introduction 00:46 How JuliaSim solves industrial modeling challenges 03:59 Real-world success with JuliaSim 04:51 Example model 05:37 Launching JuliaSim’s FMU Accelerator 06:29 Surrogatizing the example model 08:46 Analyzing the surrogate model via diagnostic dashboard 15:25 Workflow integration review 15:53 JuliaSim as a fully-featured simulation platform 16:09 Cost versus Benefit For more information, contact #sciml #machinelearning #ai #modeling #simulation
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
Today we’re joined Richard Socher, Chief Scientist and Executive VP at Salesforce. Richard, who has been at the forefront of Salesforce’s AI Research since they acquired his startup Metamind in 2016, and his team have been publishing a ton of great projects as of late, including CTRL: A Conditional Transformer Language Model for Controllable Generation, and ProGen, an AI Protein Generator, both of which we cover in-depth in this conversation. We explore the balancing act between investments, product requirement research and otherwise at a large product-focused company like Salesforce, the evolution of his language modeling research since being acquired, and how it ties in with Protein Generation. The complete show notes for this episode can be found at
NTA UGC NET 2020 (Paper-1) | Information & Communication Technology (ICT) by Aditi Ma’am | Generation of Programming Computer Go through this video for Generation of Programming Computer in Hindi by Aditi Ma’am. In this video, we have compiled for you the most important Information & Communication Technology (ICT) Questions that have maximum chances of coming this year in the UGC NET June 2020 Exam. So start practicing these questions to ace the UGC NET Exam this year. For clearing UGC NET June 2020 Exam, candidates must practice the most frequently appearing questions of different sections of the exam. Information and communications technology or (ICT) is an extensional term for information technology (IT) that stresses the role of unified communications and the integration of telecommunications (telephone lines and wireless signals), computers as well as necessary enterprise software, middleware, storage, and audio-visual systems, which enable users to access, store, transmit and manipulate information. So, in this video, we have compiled the most important Information & Communication Technology (ICT) Questions that have maximum chances to come this year in UGC NET June 2020 Exam. Welcome to Unacademy UGC NET, your one-stop solution for cracking NTA UGC NET Examination. India’s top educators will be teaching you daily on this channel. We will cover the entire syllabus, strategy, updates, and notifications which will help you to crack NTA UGC NET examination with flying colors. Unacademy platform has the best educators from all over the country, who take live classes every day. === Live Classes [More]
An overview of the gpt-3 machine learning model, why everyone should understand it, and why some (including its creator, open AI) think it’s dangerous. Like if you learned something && subscribe for more machine learning (we can learn together) ==== Links ==== gpt-3 paper the open AI API gpt-2 open source repository 👨‍💻 Join Freemote, the Freelance Developer Bootcamp 🍿 Learn the “Zero to Freelance Developer” Strategy (free) 📸 Social media #io #ai #ml
Robotics and AI are the future of many or most industries, but the barrier of entry is still difficult to surmount for many startups. Speakers will discuss the challenges of serving robotics startups and companies that require robotics labor, from bootstrapped startups to large scale enterprises. TechCrunch is a leading technology media property, dedicated to obsessively profiling startups, reviewing new Internet products, and breaking tech news. Subscribe to TechCrunch today:
Educator and entrepreneur Sebastian Thrun wants us to use AI to free humanity of repetitive work and unleash our creativity. In an inspiring, informative conversation with TED Curator Chris Anderson, Thrun discusses the progress of deep learning, why we shouldn’t fear runaway AI and how society will be better off if dull, tedious work is done with the help of machines. “Only one percent of interesting things have been invented yet,” Thrun says. “I believe all of us are insanely creative … [AI] will empower us to turn creativity into action.”
What is natural language generation, what should clients be doing with it, and what is its future? Get answers from Deloitte’s interview with Kris Hammond, chief scientist at Narrative Science.
Learn about the limitations of RNNs, how LSTMs work, and Gated Recurrent Units (GRUs). Github repo: See all classes: Weights & Biases:
In this video, we will learn about Automatic text generation using Tensorflow, Keras, and LSTM. Automatic text generation is the generation of natural language texts by computer. It has applications in automatic documentation systems, automatic letter writing, automatic report generation, etc. In this project, we are going to generate words given a set of input words. We are going to train the LSTM model using William Shakespeare’s writings. Long Short-Term Memory (LSTM) networks are a modified version of recurrent neural networks, which makes it easier to remember past data in memory. Generally, LSTM is composed of a cell (the memory part of the LSTM unit) and three “regulators”, usually called gates, of the flow of information inside the LSTM unit: an input gate, an output gate and a forget gate. Intuitively, the cell is responsible for keeping track of the dependencies between the elements in the input sequence. The input gate controls the extent to which a new value flows into the cell, the forget gate controls the extent to which a value remains in the cell and the output gate controls the extent to which the value in the cell is used to compute the output activation of the LSTM unit. The activation function of the LSTM gates is often the logistic sigmoid function. There are connections into and out of the LSTM gates, a few of which are recurrent. The weights of these connections, which need to be learned during training, determine how the gates operate. 🔊 Watch [More]
You might be familiar with NLP (especially if you are a subscriber of my channel). But do you know what is NLG? In today’s video, I’ll explain the meaning of Natural Language Generation, and its relation with NLP. NLG and NLP are closely related, since Speech Recognition is a subfield of NLP, or to be more precise, it is a subfield of computational linguistics. So if you are interested in this topic, in AI and/or machine learning, watch it right now! Also, don’t forget to leave your impressions about it and recommendations in the comments. Link to the video What is NLP * Link to the video What is Speech Recognition * #ConsumerCentric #NLG #NaturalLanguageGeneration ======================================================= Subscribe to my channel here * Visit our company website * You can also find me on LinkedIn * Get in touch *
Learn more advanced front-end and full-stack development at: A Markov Chain is a system that transitions between states using a random, memoryless process. Markov Chains are a great tool for simulating real-world phenomena and environments with computers. In this video, we’ll give a specific example of how to use Markov Chains in Natural Language Generation. Watch this video to learn: – What is a Markov Chain – How are Markov Chains being used – The reasons they’re useful for Natural Language Generation
In this segment, you will learn the basics of Natural Language Generation and the Integration between TIBCO Spotfire and Automated Insights’s Natural Language Generation Software Wordsmith.
Presentation by Catherine Henry (2017 Clearwater DevCon). When teaching a subject through text it can be beneficial to evaluate the reader’s understanding; however, the creation of relevant questions and answers can be time-consuming and tedious. I will walk through how the implementation of NLP libraries and algorithms can assist in, and potentially remove altogether, the current necessity of an individual manually formulating these tests.
This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines. – Natural Language Processing (Part 1): Introduction to NLP & Data Science – Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python – Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python – Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python – Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python – Natural Language Processing (Part 6): Text Generation with Markov Chains in Python All of the supporting Python code can be found here:
Previous Robot Video: Subscribe here: Become a Patron!: CF Bitcoin address: 13SjyCXPB9o3iN4LitYQ2wYKeqYTShPub8 Hi, welcome to ColdFusion (formerly known as ColdfusTion). Experience the cutting edge of the world around us in a fun relaxed atmosphere. Sources: They did surgery on a grape //Soundtrack// 0:00 HESK & NADUS // You Bout it 0:30 Tangerine Dream – Love On A Real Train 2:15 Kinobe – A Small Island 4:15 Deccies – Subtle 5:43 Mono Suono – Home 6:34 Kidnap Kid – Moments (feat. Leo Stannard) 7:22 Bon Iver – Wash (OMN Remix)’ 8:52 Mike Newman – I Don’t Wanna 10:00 Till Death – Forever 11:16 Number One Fan – Sorry » Google + | » Facebook | » My music | or » » » Collection of music used in videos: Producer: Dagogo Altraide » Twitter | @ColdFusion_TV
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Markov chains are used for keyboard suggestions, search engines, and a boatload of other cool things. In this video, I discuss the basic ideas behind Markov chains and show how to use them to generate random text. My code to generate text: My code to generate line drawings:
Nabil Hassein demonstrates how to train an “LSTM” neural network to generate text in the style of a particular author using Spell and ml5.js. This stream is sponsored by Spell. Sign up here: “As creators of machine learning projects for art or otherwise, we have to take responsibility for what our programs produce and the impact that output has on people who interact with our creations. Given how common bias and oppression is in the world generally, many if not most datasets (including song lyrics) reflect that reality, and without countermeasures we as programmers are very likely to reproduce those harms. It is also worth explicitly noting that authorship and context matter, and identical words (or images, etc.) can assume completely different significance depending on who says them and when. I encourage everyone to take seriously the ethical aspects of the ml5.js documentation along with the technical material, and to consider your responsibility as a technologist to acknowledge and address the harm that the field of computing has too often caused for marginalized groups” Nabil Hassein is a freelance technologist and educator based in Brooklyn, NY. He has previously worked as an infrastructure engineer at Khan Academy and a couple of startups, taught math and programming in both public schools and private settings, and occasionally writes and speaks. His website is 🎥 Workflow: Python and Virtualenv: 🎥 Introduction to Spell: 🔗 ml5.js: 🔗 Generative-DOOM: 🔗 The Unreasonable Effectiveness of Recurrent Neural Networks: 🔗 [More]
How to reduce the drop-off ratio in an online insurance process? Our products help reduce the number of customers who abandon the insurance application form without completing it, and thereby improve the effectiveness of your on-line insurance process. Get those Agents from
Professor Christopher Manning & PhD Candidate Abigail See, 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: To get the latest news on Stanford’s upcoming professional programs in Artificial Intelligence, visit: To view all online courses and programs offered by Stanford, visit:
Winter Intelligence Oxford – Organized by the Future of Humanity Institute – AGI12 – ==The Next Generation of the MicroPsi Framework== Joscha Bach, Humboldt University of Berlin, Germany