University


Nao robots could soon help children with autism

Daily Mail

It works by scanning children with an autism spectrum disorder (ASD) for their facial expressions and body movements in certain scenarios. Developed by a French robotic firm, the machine will also function as a diagnostic tool by collecting data in the future. The robot works by scanning children with an autism spectrum disorder (ASD) for their facial expressions and body movements in certain scenarios. Developed by a French robotic firm, the machine will also function as a diagnostic tool by collecting clinical data during therapy.


Hate speech detection with machine learning -- a guest post from Futurice

#artificialintelligence

In addition we chose to test Support Vector Machine (SVM) and Random Forest (RF), because they tend to perform very well in the most challenging tasks. We tested Bag-of-Words (BOW) and FastText (FT) (Word embeddings) feature extraction methods and Gaussian Naive Bayes (GNB), Random Forest (RF) and Support Vector Machines (SVM) machine learning methods. Based on the experiment, we chose a feature extraction and machine learning method to train a model for hate speech detection. At first, we downloaded social media messages from a previous day, then predicted hate speech (scored each message) and stored the result in a CSV file.


How artificial intelligence will impact the future of healthcare

#artificialintelligence

"IBM's Watson read 25 million scientific papers in a week." Quartz Magazine reported on an AI called AtomNet that promises to develop new drug treatments for dangerous diseases like Ebola and multiple sclerosis. Computer-assisted coding isn't exactly a form of artificial intelligence, but some in the industry promised that it would improve coder productivity and efficiency using a spell checker-like system called NLP. By auditing all charts prior to billing, eValuator acts as a highly skilled AI auditor, flagging any charts that are likely to have mistakes.


7 Real-Life Use Cases for Google DeepMind's Machine Learning Systems

#artificialintelligence

Tom studied English Literature and History at Sussex University before gaining a Masters in Newspaper Journalism from City University. He's particularly interested in the public sector and the ethical implications of emerging technologies.


Y Combinator Has Gone Supernova

WIRED

I am thinking that sounds crazy--a response that might actually make Sam Altman happy. "I think we'll fund ten thousand companies next year," he says. More than 50 companies that went through the program are worth more than $100 million each and, of course, there are the multi-billion dollar valuations of YC's big three: Dropbox, Airbnb, and Stripe. Within the organization, there's a single talking point to describe YC's evolution: YC started as a family business but now it's more like a university.


jupyter/jupyter

@machinelearnbot

Exploratory Computing with Python, a set of 15 Notebooks that cover exploratory computing, data analysis, and visualization. Code Katas in Python, a collection of algorithmic and data structure exercises covering search and sorting algorithms, stacks, queues, linked lists, graphs, backtracking and greedy problems. Data Science Notebooks, a frequently updated collection of notebooks on statistical inference, data analysis, visualization and machine learning, by Donne Martin. Learning Population Genetics in an RNA world is an interactive notebook that explains basic population genetics tools and techniques by building an in silico evolutionary model of RNA molecules.


Carnegie Mellon Solidifies Leadership Role in Artificial Intelligence

@machinelearnbot

Carnegie Mellon University's School of Computer Science (SCS) has launched a new initiative, CMU AI, that marshals the school's work in artificial intelligence (AI) across departments and disciplines, creating one of the largest and most experienced AI research groups in the world. Moore is directing the initiative with Jaime Carbonell, the Newell University Professor of Computer Science and director of the Language Technologies Institute; Martial Hebert, director of the Robotics Institute; Computer Science Professor Tuomas Sandholm; and Manuela Veloso, the Herbert A. Simon University Professor of Computer Science and head of the Machine Learning Department. It created the first and only machine learning department, studying how software can make discoveries and learn with experience. That expertise, spread across several departments, has enabled CMU to develop such technologies as self-driving cars; question-answering systems, including components of IBM's Jeopardy-playing Watson; world-champion robot soccer players; 3-D sports replay technology; and even an AI smart enough to beat four of the world's top poker players.


How AI can be a force for good

#artificialintelligence

Research and development also tends to focus on the flashiest and most consumer-facing initiatives -- self-driving cars, chatbots, and virtual assistants -- leaving little work dedicated to solutions for health, clean energy, education, and more. AI researchers are all working towards solving the fundamental problems with machine learning: how to recognize and process raw text, speech, and images; predict behavior and events; and navigate uncertainty when an algorithm can't make a high-confidence decision. It is here that IBM Watson's researchers can grab coffee with engineers from 3D design software company Autodesk, where machine learning researchers from the University of Toronto can work with companies like Deep Genomics to turn their ideas into reality, and where socially impactful technologies are being built every day. We must begin fostering the growth of AI in more productive ways by incentivizing large corporations to be less secretive, building naturally open and collaborative spaces, and recognizing and investing in the positive social impact that technology companies can create.


Carnegie Mellon Launches Artificial Intelligence Initiative

#artificialintelligence

Carnegie Mellon University's School of Computer Science (SCS) has launched a new initiative, CMU AI, that marshals the school's work in artificial intelligence (AI) across departments and disciplines, creating one of the largest and most experienced AI research groups in the world. Moore is directing the initiative with Jaime Carbonell, the Newell University Professor of Computer Science and director of the Language Technologies Institute;Martial Hebert, director of the Robotics Institute; Computer Science Professor Tuomas Sandholm; and Manuela Veloso, the Herbert A. Simon University Professor of Computer Science and head of the Machine Learning Department. It created the first and only Machine Learning Department, studying how software can make discoveries and learn with experience. That expertise, spread across several departments, has enabled CMU to develop such technologies as self-driving cars; question-answering systems, including components of IBM's Jeopardy-playing Watson; world-champion robot soccer players; 3-D sports replay technology; and even an AI smart enough to beat four of the world's top poker players.


How information overload helps spread fake news

Christian Science Monitor

A new study reveals the mathematics underlying this phenomenon, modeling how information overload can erode an individual's ability to distinguish high-quality information from its opposite, causing falsehoods to propagate. "It was the first paper I've seen in this area that quantifies what many people thought was happening, and that's basically with limited attention we're unable to see the full range of potential arguments or sides of the story," says Dr. Uzzi, who has studied how social media users isolate themselves into echo chambers. The researchers suggest that social networks could curb information overload by aggressively limiting content shared by so-called bot accounts, software agents that flood social networks with low-quality information. The research reveals some of the math that drives what psychologists have long known: Information overload makes it harder to make decisions.