Goto

Collaborating Authors


Making data meaningless so AI can map its meaning

#artificialintelligence

AI Outside In is a column by PAIR's writer-in-residence, David Weinberger, who offers his outsider perspective on key ideas in machine learning. His opinions are his own and do not necessarily reflect those of Google. Suppose you want a machine learning system to suggest paint names based on any color you specify. This has been done hilariously by Janelle Shane -- "burf pink," "navel tan" -- but let's say we want to do it more seriously (and without any reference to how Shane actually did it). Machine learning, at least of the common sort called "supervised learning", learns from the data you give it, so you first want to gather a large set of colors to which humans have applied various labels.


Activation Functions in Deep Learning: From Softmax to Sparsemax -- Math Proof

#artificialintelligence

The objective of this post is three-fold. The first part discusses the motivation behind sparsemax and its relation to softmax, summary of the original research paper in which this activation function was first introduced, and an overview of advantages from using sparsemax. Part two and three are dedicated to the mathematical derivations, concretely finding a closed-form solution as well as an appropriate loss function. In the paper "From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification", Martins et al. propose a new alternative to the widely known softmax activation function by introducing Sparsemax. While softmax is an appropriate choice for multi-class classification that outputs a normalized probability distribution over K probabilities, in many tasks, we want to obtain an output that is more sparse.


Don't Be Overwhelmed by NLP

#artificialintelligence

With enormous amount go textual datasets available; giants like Google, Microsoft, Facebook etc have diverted their focus towards NLP. Let's these Tweets put things into perspective: This is barely the tip of the iceberg. So while you were trying to understand and implement a model, a bunch of new lighter and faster models were already available. I read them all to realize most of the research is re-iteration of similar concepts. Learn to use what's available, efficiently, before jumping on to what else can be used In practice, these models are a small part of a much bigger pipeline.


ESA's Φ-Week: Digital Twin Earth, Quantum Computing and AI Take Center Stage

#artificialintelligence

Digital Twin Earth will help visualize, monitor, and forecast natural and human activity on the planet. The model will be able to monitor the health of the planet, perform simulations of Earth's interconnected system with human behavior, and support the field of sustainable development, therefore, reinforcing Europe's efforts for a better environment in order to respond to the urgent challenges and targets addressed by the Green Deal. ESA's 2020 Φ-week event kicked off this morning with a series of stimulating speeches on Digital Twin Earth, updates on Φ-sat-1, which was successfully launched into orbit earlier this month, and an exciting new initiative involving quantum computing. The third edition of the Φ-week event, which is entirely virtual, focuses on how Earth observation can contribute to the concept of Digital Twin Earth – a dynamic, digital replica of our planet which accurately mimics Earth's behavior. Constantly fed with Earth observation data, combined with in situ measurements and artificial intelligence, the Digital Twin Earth provides an accurate representation of the past, present, and future changes of our world.


Artificial Intelligence In Healthcare -- Everything Artificial Intelligence + Robotics + IoT +

#artificialintelligence

Artificial intelligence (AI), Machine learning, NLP, Robotics, and Automation are increasingly prevalent in all aspects and are being applied to healthcare as well. These technologies have the potential to transform all aspects of health care from patient care to the development and production of new experimental drugs that can have a faster roll-out date than traditional methods. There are numerous research studies suggesting that AI can outperform humans at key healthcare tasks, such as diagnosing ailments. Here is a great example, AI'outperforms' doctors diagnosing breast cancer¹. Artificial intelligence is a collection of technologies that come together form artificial intelligence. Tech firms and startups are also working assiduously on the same issues.


Coursera

#artificialintelligence

Learn online and earn valuable credentials from top universities like Yale, Michigan, Stanford, and leading companies like Google and IBM. Join Coursera for free and transform your career with degrees, certificates, Specializations, & MOOCs in data science, computer science, business, and dozens of other topics.


The Journey of AI & Machine Learning

#artificialintelligence

Imtiaz Adam, Twitter @Deeplearn007 Updated a few sections in Sep 2020 Artificial Intelligence (AI) is increasingly affecting the world around us. It is increasingly making an impact in retail, financial services, along with other sectors of the economy.


Large Scale Machine Learning Via SQL On Google BigQuery w/ BQML

#artificialintelligence

The health & safety of our attendees & speakers is our primary concern. While this currently proves to be a tricky time for public gatherings, Dataiku is still committed to providing great tech content & facilitating discussions in the data science space. As such, weve decided to pivot towards online webinars via our partner platform, BrightTalk. Google 2:45pm: Q&A Talk Abstract: In this talk, Sanjay will discuss how to perform machine learning using SQL for a variety of model types & the flexibility of using BQML to import & export models. Speaker bio: Sanjay Agravat is a Machine Learning Specialist for Google Cloud based out of Atlanta, GA.


2 Megatrends Dominate the Gartner Hype Cycle for Artificial Intelligence, 2020

#artificialintelligence

Despite the global impact of COVID-19, 47% of artificial intelligence (AI) investments were unchanged since the start of the pandemic and 30% of organizations actually planned to increase such investments, according to a Gartner poll. Only 16% had temporarily suspended AI investments, and just 7% had decreased them. During the pandemic, for example, AI came to the rescue. Chatbots helped answer the flood of pandemic-related questions, computer vision helped maintain social distancing and machine learning (ML) models were indispensable for modeling the effects of reopening economies. "If AI as a general concept was positioned on this year's Gartner Hype Cycle, it would be rolling off the Peak of Inflated Expectations. By that we mean that AI is starting to deliver on its potential and its benefits for businesses are becoming a reality," says Svetlana Sicular, VP Analyst, Gartner.


The Rise of Chatbots

#artificialintelligence

Good customer service is an integral element to the success of any business. With the rise in mobile devices over the last decade, chatbots are increasingly becoming a popular option to interact with users. The popularity of chatbots and their adoption is rapidly increasing as they enable businesses to provide real-time customer service in many e-commerce settings. Let us explore the rise of Artificial Intelligence (AI), Natural Language Processing (NLP), and chatbots for customer service. A chatbot is an AI-based software that interacts with a user through either text or audio.