Artificial Intelligence

Đây là phần thứ tư và cũng là phần cuối cùng trong loạt phim bốn phần của Nhóm Human AI Labs ( Hu.man.ai ), trước đây là Luther.ai. Các bài báo trước đã khám phá Trí nhớ con người qua ba lăng kính riêng biệt: Khoa học, Công nghệ và Thiết kế. Bài viết thứ tư qua lăng kính doanh nhân của Suman Kanuganti, Giám đốc điều hành và Đồng sáng lập của Human AI Labs.Lưu ý : Văn bản in … [Read more...] about Hu.man.ai đóng vòng hạt giống 3,2 triệu đô la để tạo một phần mở rộng AI của Trí nhớ con người

Finding the category of the question asked, i.e., the type of answer to be given.Photo by Mike Mirandi on DribbbleTo answer a question, we need to understand the question and also the type of answer required. Different questions require different formats of answers. Categorizing questions based on answer formats help in addressing the questions better.For example, a question … [Read more...] about Question classification — on cAInvas

One of many lack-luster posters for DEMON SEEDSpecial-needs tutor Susan Harris (played by British bombshell Julie Christie, Doctor Zhivago) is frustrated with her husband Alex Harris (Fritz Weaver, “The Martian Chronicles” [1980, TV Movie]). He’s away from home for months at a time and even takes his work home to a remote home terminal, one of many factors which contributed to … [Read more...] about MOVIE REVIEW: Demon Seed (1977)

Visualizing High-Dimensional Data in Low-Dimensional Spacet-SNE on MNIST Data set (From Google TechTalk by the First Author, Laurens van der Maaten, https://www.youtube.com/watch?v=RJVL80Gg3lA)In this story, Visualizing Data using t-SNE, t-SNE, by Tilburg University, and University of Toronto, is briefly reviewed. It is a very famous paper by Prof. Hinton. In this paper:t-SNE … [Read more...] about Review — t-SNE: Visualizing Data using t-SNE (Data Visualization)

https://nlp.pw/Steps:IntroductionTrain our own word embedding (code)Phrases(bigrams)t-SNE visualizations in 2DRetrain Glove Vectors on top of my own dataIntroduction:Word embedding is one of the most popular representations of document vocabulary. It is capable of capturing the context of a word in a document, semantic and syntactic similarity, relation with other words, … [Read more...] about Creating Custom-word-embedding with t-SNE 2D-dimension visualizations and retrain Glove Vectors on…

I previously pontificated about the difficulties of making a neural network robust in the adversarial model and a general approach to overcoming them. In this post I’ll flesh out the specifics of the construction a bit more.What we want to do is make a neural network whose overall structure naturally gives it adversary resistance, so we can simply train it as well as we can and … [Read more...] about How to make an adversary resistant neural network

There are many ways to classify ML algorithms. Here, we’ll use one of them, the types of learning:Supervised LearningUnsupervised LearningReinforcement LearningThe following bubble chart shows some commons fields of applications for each paradigm.Source: mactoresIn this category, the models have as input a set of labeled data. When the labels are discrete, we say that is a … [Read more...] about Where does the knowledge is storage inside machine learning algorithms?

What is a Smartphone-Connected Pacemaker? Can they be Hacked?According to the Circulation Journal, 3 million people around the world have electronic pacemaker implants, with almost 600,000 new pacemakers being implanted each year. These small, yet powerful electronic devices work by normalizing irregular heartbeats for patients of arrhythmia, a heart disorder that affects the … [Read more...] about Can a Smartphone Enabled Pacemaker be Hacked?

Meredith Broussard works as an associate professor at the Arthur L. Carter Journalism Institute of New York University (MeredithBroussard.com). With foundational studies in computer science, Broussard has a passion for researching artificial intelligence, with an emphasis in how it affects us socially. After reading chapter one of her book “Artificial Unintelligence: How … [Read more...] about “Artificial Unintelligence” Chapter One

Ok, not exactly. But COVID did significantly impact some AI based applications. For example, models used to detect fraud in air travel used to see the purchase of a one-way ticket as a strong sign of fraud. Clearly no longer the case. The type of items bought online has shifted rapidly, rendering previous recommender models less relevant.The cause is something called concept … [Read more...] about How COVID Broke AI