Blogs or Expert Columns
Computer, respond to this email.
Computer, respond to this email. Posted by Greg Corrado*, Senior Research Scientist Machine Intelligence for You What I love about working at Google is the opportunity to harness cutting-edge machine intelligence for users’ benefit. Two recent Research Blog posts talked about how we’ve used machine learning in the form of deep neural networks to improve voice search and YouTube thumbnails. Today we can share something even wilder -- Smart Reply, a deep neural network that writes email. I get a lot of email, and I often peek at it on the go with my phone. But replying to email on mobile is a real [...]
MRNet: Deep-learning-assisted diagnosis for knee magnetic resonance imaging
MRNet: Deep-learning-assisted diagnosis for knee magnetic resonance imaging Nicholas Bien *, Pranav Rajpurkar *, Robyn L. Ball, Jeremy Irvin, Allison Park, Erik Jones, Michael Bereket, Bhavik N. Patel, Kristen W. Yeom, Katie Shpanskaya, Safwan Halabi, Evan Zucker, Gary Fanton, Derek F. Amanatullah, Christopher F. Beaulieu, Geoffrey M. Riley, Russell J. Stewart, Francis G. Blankenberg, David B. Larson, Ricky H. Jones, Curtis P. Langlotz, Andrew Y. Ng†, Matthew P. Lungren† We developed an algorithm to predict abnormalities in knee MRI exams, and measured the clinical utility of providing the algorithm’s predictions to radiologists and surgeons during interpretation. Magnetic resonance (MR) [...]
Stacking models for improved predictions: A case study for housing prices
If you have ever competed in a Kaggle competition, you are probably familiar with the use of combining different predictive models for improved accuracy which will creep your score up in the leader board. While it is widely used, there are only a few resources that I am aware of where a clear description is available (One that I know of is here, and there is also a caret package extension for it). Therefore, I will try to workout a simple example here to illustrate how different models can be combined. The example I have chosen is the House Prices competition from Kaggle. This is [...]
Discovery of independently controllable features through autonomous goal setting
Discovery of independently controllable features through autonomous goal setting This blog post is accompanied with a colab notebook 34 Despite recent breakthroughs in artificial intelligence, machine learning agents remain limited to tasks predefined by human engineers. The autonomous and simultaneous discovery and learning of many-tasks in an open world remains very challenging for reinforcement learning algorithms. In this blog post we explore recent advances in developmental learning to tackle the problems of autonomous exploration and learning. Consider a robot like the one depicted on the first picture. In this environment it can do many things: it can move its arms around, [...]
Artificial intelligence tracks biological age at every level and rewinds the aging clock
Artificial intelligence tracks biological age at every level and rewinds the aging clock Insilico Medicine publishes a new paper presenting the latest advances in artificial intelligence for aging research INSILICO MEDICINE, INC. Monday, December 3, Rockville, MD - Insilico Medicine, one of the leaders in artificial intelligence for drug discovery, biomarker development, digital medicine, and aging research announced today the publication of its recent paper titled "Artificial Intelligence for Aging and Longevity Research: Recent Advances and Perspectives" in Ageing Research Reviews, one of the highest-impact journals in the field. The paper introduces recent advances in deep learning for aging research and [...]
BI EVOLUTION: INCREMENTAL DATA REFRESH
BI EVOLUTION: INCREMENTAL DATA REFRESH Posted on December 27, 2018 by Josh Caplan As Power BI grows to become a superset of Analysis Services functionality, a lot of that functionality will evolve as it becomes available. Incremental data refresh is a great example of how Power BI is modernizing/simplifying complex BI implementations. Incremental data refresh is the process of incrementally loading new or changed data to a BI model without needing to reload the full set of data. This can have the following benefits: Refreshes are faster since you don’t need to load all the data every time and more can be done [...]
A new era of computing is coming. How can we make sure it is sustainable?
A new era of computing is coming. How can we make sure it is sustainable? Sustaining the growth predicted by Moore's Law has required vast spending, investment and collaboration Image: REUTERS/Mike Blake Eighty years ago, Alan Turing laid down the mathematical basis of computation. Just a decade later, John von Neumann made computing practical. Advances in information technology since then have been fundamental to global economic growth, fuelled by a collection of critical core technologies for which we have been able to engineer exponentially increasing performance at exponentially decreasing costs. A memory chip in a modern cellphone has a [...]
Lawyer-Bots Are Shaking Up Jobs
Lawyer-Bots Are Shaking Up Jobs AI is augmenting and automating the tasks currently performed by hundreds of thousands of people in the U.S. alone. by Erin Winick December 12, 2017 Meticulous research, deep study of case law, and intricate argument-building—lawyers have used similar methods to ply their trade for hundreds of years. But they’d better watch out, because artificial intelligence is moving in on the field. As of 2016, there were over 1,300,000 licensed lawyers and 200,000 paralegals in the U.S. Consultancy group McKinsey estimates that 22 percent of a lawyer’s job and 35 percent of a law clerk’s job [...]
Why Every Data Scientist Needs A Data Engineer
This article was written by Lauren Brunk. The data scientist was deemed the “sexiest job of the 21st century.” The Harvard Business Review reasons that this “hybrid of data hacker, analyst, communicator and trusted adviser” is a rare combination of skills, worth a high paycheck. Too good to be true? Yes, according to Forbes. Turns out, data scientists spend most of their time (up to 79%!) on the part of their job they hate most. The Demand for Data Scientists: Thousands of companies across a myriad of industries are hiring data scientists, likened to the "quants" of Wall Street in the 1980s [...]
Best NLP Model Ever? Google BERT Sets New Standards in 11 Language Tasks
Best NLP Model Ever? Google BERT Sets New Standards in 11 Language Tasks The new Google AI paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding is receiving accolades from across the machine learning community. Google researchers present a deep bidirectional Transformer model that redefines the state of the art for 11 natural language processing tasks, even surpassing human performance in the challenging area of question answering. Some highlights from the paper: NLP researchers are exploiting today’s large amount of available language data and maturing transfer learning techniques to develop novel pre-training approaches. They first train a model architecture on one [...]
Taking a practical approach to BigQuery cost monitoring
Taking a practical approach to BigQuery cost monitoring Marco Tranquillin Cloud Consultant, Professional Services Google BigQuery is a serverless enterprise data warehouse tool that’s designed for scalability. We built BigQuery to be highly scalable and let you focus on data analysis without having to take care of the underlying infrastructure. We know BigQuery users like its capability to query petabyte-scale datasets without the need to provision anything. You just upload the data and start playing with it. BigQuery comes with two different pricing models: The on-demand model, where users are charged for the amount of TB of data to be processed [...]
Kroger, Microsoft Create Futuristic Grocery Store. Amazon, Take Note
Kroger, Microsoft Create Futuristic Grocery Store. Amazon, Take Note The supermarket chain and technology giant are using the cloud to make it faster to navigate the grocery aisles and pick up online orders. Kroger Co. and Microsoft Corp. are joining forces to bring the ease of online shopping to brick-and-mortar grocery stores. Kroger, America’s biggest supermarket chain, has remodeled two stores to test out the new features, which include “digital shelves” that can show ads and change prices on the fly along with a network of sensors that keep track of products and help speed shoppers through the aisles. Kroger could eventually roll out the [...]
Data Science and the Art of Persuasion
Data Science and the Art of Persuasion Data science is growing up fast. Over the past five years companies have invested billions to get the most-talented data scientists to set up shop, amass zettabytes of material, and run it through their deduction machines to find signals in the unfathomable volume of noise. It’s working—to a point. Data has begun to change our relationship to fields as varied as language translation, retail, health care, and basketball. But despite the success stories, many companies aren’t getting the value they could from data science. Even well-run operations that generate strong analysis fail to capitalize on their insights. [...]
Recurrent Neural Networks cheatsheet
Recurrent Neural Networks cheatsheet By Afshine Amidi and Shervine Amidi Overview Architecture of a traditional RNN ― Recurrent neural networks, also known as RNNs, are a class of neural networks that allow previous outputs to be used as inputs while having hidden states. They are typically as follows: For each timestep tt, the activation a<t>a<t> and the output y<t>y<t> are expressed as follows: a<t>=g1(Waaa<t−1>+Waxx<t>+ba)andy<t>=g2(Wyaa<t>+by)a<t>=g1(Waaa<t−1>+Waxx<t>+ba)andy<t>=g2(Wyaa<t>+by) where Wax,Waa,Wya,ba,byWax,Waa,Wya,ba,by are coefficients that are shared temporally and g1,g2g1,g2 activation functions. The pros and cons of a typical RNN architecture are summed up in the table below: Advantages Drawbacks • Possibility of processing input of any length • Model size not increasing with size of input • [...]
The Cold Start Problem: How to Build Your Machine Learning Portfolio
This post outlines what makes a good machine leaning portfolio, with useful examples to help you begin to understand the type of project that gets noticed by big companies. By Edouard Harris, Founder @SharpestMindsAI (YC W18). I’m a physicist who works at a YC startup. Our job is to help new grads get hired into their first machine learning jobs. Some time ago, I wrote about the things you should do to get hired into your first machine learning job. I said in that post that one thing you should do is build a portfolio of your personal machine learning projects. But I [...]
No-code Machine Learning in Power BI
Can Microsoft democratise AI? The new code-free Power BI integrations with Azure Cognitive Services and Azure Machine Learning are a big step along that road. Modern businesses run on information, but we're drowning in data from line-of-business systems, company databases, the data generated by industrial IoT systems, and all manner of external data. So how can we stay on top of the data we have, in order to get the business insights we need, when good data scientists are rare and expensive to employ? Modern data analysis tools like Tableau and Power BI go a long way to solving some of these problems, [...]
These Portraits Were Made by AI: None of These People Exist
These Portraits Were Made by AI: None of These People Exist Check out these rather ordinary looking portraits. They’re all fake. Not in the sense that they were Photoshopped, but rather they were completely generated by artificial intelligence. That’s right: none of these people actually exist. NVIDIA researchers have published a new paper on easily customizing the style of realistic faces created by a generative adversarial network (GAN). The Verge points out that GAN has only existed for about four years. In 2014, a landmark paperintroduced the concept, and this is what the AI-generated results looked like at the time: In less than half a [...]
Artificial Intelligence System Learns To Diagnose, Classify Intracranial Hemorrhage
Artificial Intelligence System Learns To Diagnose, Classify Intracranial Hemorrhage Mass.-General-developed system able to ‘explain’ reasons behind decisions based on CT scan images Credit: Hyunkwang Lee, Harvard School of Engineering and Applied Sciences, and Sehyo Yune, MD, Massachusetts General Hospital Department of Radiology A team of investigators from the Massachusetts General Hospital (MGH) Department of Radiology has developed a system using artificial intelligence to quickly diagnose and classify brain hemorrhages and to provide the basis of its decisions from relatively small image datasets. Such a system could become an indispensable tool for hospital emergency departments evaluating patients with symptoms of [...]
Tokenization in a Nutshell
Tokenization in a Nutshell What is tokenization and a token? Tokenization is the process of transformation of infrastructure to manage asset ownership rights. A token is a digitized ownership right for an asset. Tokenization in context There are four levels on which we can view tokenization: user, business, IT infrastructure, technical details. From a legal perspective, tokenization doesn’t change the reality (whether it is paper registry or a database). From a responsibility perspective, tokenization implies that the registry of ownership is no longer controlled by a single party. The terms “a tokenized title to an asset” and “a tokenized asset” are interchangeable. Token is [...]
Build Your Own Natural Language Models on AWS (no ML experience required)
Build Your Own Natural Language Models on AWS (no ML experience required) by Dr. Matt Wood | on 19 NOV 2018 | in Amazon Comprehend, Artificial Intelligence At AWS re:Invent last year we announced Amazon Comprehend, a natural language processing service which extracts key phrases, places, peoples’ names, brands, events, and sentiment from unstructured text. Comprehend – which is powered by sophisticated deep learning models trained by AWS – allows any developer to add natural language processing to their applications without requiring any machine learning skills. Today we are excited to bring new customization features to Comprehend, which allow developers to extend Comprehend to identify [...]
Michelangelo PyML: Introducing Uber’s Platform for Rapid Python ML Model Development
Michelangelo PyML: Introducing Uber’s Platform for Rapid Python ML Model Development By Kevin Stumpf, Stepan Bedratiuk, and Olcay Cirit As a company heavily invested in AI, Uber aims to leverage machine learning (ML) in product development and the day-to-day management of our business. In pursuit of this goal, our data scientists spend considerable amounts of time prototyping and validating powerful new types of ML models to solve Uber’s most challenging problems (e.g., NLP based smart reply systems, ticket assistance systems, fraud detection, and financial and marketplace forecasting). Once a model type is empirically validated to be best for the task, engineers work closely with data science [...]
Google open-sources BERT, a state-of-the-art pretraining technique for natural language processing
Google open-sources BERT, a state-of-the-art pretraining technique for natural language processing Above: Google AI logo on screen at Google Event Center in Sunnyvale, California Image Credit: Khari Johnson / VentureBeat Natural language processing (NLP) — the subcategory of artificial intelligence (AI) that spans language translation, sentiment analysis, semantic search, and dozens of other linguistic tasks — is easier said than done. Procuring diverse datasets large enough to train text-parsing AI systems is an ongoing challenge for researchers; modern deep learning models, which mimic the behavior of neurons in the human brain, improve when trained on millions, or even billions, [...]
The Visual Python Debugger for Jupyter Notebooks You’ve Always Wanted
The Visual Python Debugger for Jupyter Notebooks You’ve Always Wanted Introducing PixieDebugger David TaiebFollow Mar 10 I’ve been using Jupyter Notebooks with great delight for many years now, mostly with Python, and it’s validating to see that their popularity keeps growing, both in academia and the industry. I do have a pet peeve though, which is the lack of a first-class visual debugger similar to these available in other IDEs like Eclipse, IntelliJ, or Visual Studio Code. Some would rightfully point out that Jupyter already supports pdb for simple debugging, where you can manually and sequentially enter commands to do things like [...]
Microsoft Open Sources Trill to Deliver Insights on A Trillion Events A Day
Microsoft Open Sources Trill to Deliver Insights on A Trillion Events A Day Posted on December 17, 2018 James Terwilliger Principal Software Engineer, Microsoft Azure In today’s high-speed environment, being able to process massive amounts of data each millisecond is becoming a common business requirement. We are excited to be announcing that an internal Microsoft project known as Trill for processing “a trillion events per day” is now being open sourced to address this growing trend. Here are just a few of the reasons why developers love Trill: As a single-node engine library, any .NET application, service, or platform can [...]
