Memory-Based Learning

It's impossible to talk about artificial intelligence without mentioning IBM's Watson. A pioneer in cognitive computing, the American computer giant has found multiple health applications for Watson. Pascal Sempé, senior sales consultant for Watson Health Solutions in France, explained how Watson functions and what's at stake. ME e-mag: Could Watson ever replace doctors? Pascal Sempé: Watson is a tool that helps the doctor, certainly not one that tells the doctor what to do.

We study finite sample expressivity, i.e., memorization power of ReLU networks. Recent results require $N$ hidden nodes to memorize/interpolate arbitrary $N$ data points. In contrast, by exploiting depth, we show that 3-layer ReLU networks with $\Omega(\sqrt{N})$ hidden nodes can perfectly memorize most datasets with $N$ points. We also prove that width $\Theta(\sqrt{N})$ is necessary and sufficient for memorizing $N$ data points, proving tight bounds on memorization capacity. The sufficiency result can be extended to deeper networks; we show that an $L$-layer network with $W$ parameters in the hidden layers can memorize $N$ data points if $W \Omega(N)$.

We present the Bayesian Case Model (BCM), a general framework for Bayesian case-based reasoning (CBR) and prototype classification and clustering. BCM brings the intuitive power of CBR to a Bayesian generative framework. The BCM learns prototypes, the quintessential observations that best represent clusters in a dataset, by performing joint inference on cluster labels, prototypes and important features. Simultaneously, BCM pursues sparsity by learning subspaces, the sets of features that play important roles in the characterization of the prototypes. The prototype and subspace representation provides quantitative benefits in interpretability while preserving classification accuracy.

In my previous blog post, I outlined the challenges faced by local authorities across the country to consistently deliver resident services amidst increasingly stringent budgetary cuts. In this post, I will propose some suggestions. Whilst it certainly will not undo the financial tight spot authorities find themselves in, I believe it will help alleviate funding pressures and, over time, bring costs down to a manageable level. Firstly, it is imperative to understand not just current resident needs, but future needs. Secondly, authorities collect data in abundance, and it is time to start using this data smartly.

In my previous blog post, I outlined the challenges faced by local authorities across the country to consistently deliver resident services amidst increasingly stringent budgetary cuts. In this post, I will propose some suggestions. Whilst it certainly will not undo the financial tight spot authorities find themselves in, I believe it will help alleviate funding pressures and, over time, bring costs down to a manageable level. Firstly, it is imperative to understand not just current resident needs, but future needs. Secondly, authorities collect data in abundance, and it is time to start using this data smartly.

Wong's Mandarin class meets four times a week. On Mondays and Fridays, he attends a class in a traditional classroom with Helen Zhou, Associate Professor at the RPI. There he learns new vocabulary and gets an introduction to phrases and grammatical structures. On Tuesdays and Thursdays, the class meets in the CIR, where students conduct conversations with virtual agents. In a restaurant environment, Wong said students can go through the entire process of sitting down in the restaurant, looking at a menu, ordering food, speaking with a waiter on how the food is prepared, and paying the bill.

We do not want to write another technical AI book as the bottleneck of this technology is actually implementing it into our business and life rather than keep researching it in the labs. More and more people need to aware of how this technology work like how people realised how internet could have changed our lives and adopt it. I really hope the book can not only be a tool for me to explain my idea in a classroom but also to express my view of two points, that this technology is going to change our live like the internet did to us, and we must embrace it while considering all the social aspects of how it would change us.

The IBM Developer NYC team will be hosting a Holiday Tech Showcase & Party! Please join us & the community for a fun-filled night of food & drinks, networking, IBM's BIG IDEAS for 2020, exclusive project demos using IBM technologies, & a special holiday gift from IBM Developer as a token of appreciation. Sign up for IBM Cloud (here: http://ibm.biz/IBMHolidayParty) to receive a special IBM holiday gift. Pooja, Roger, Grant, Nigel, Jenna, & Mofi Special Message: The IBM Developer NYC team would like to thank you ALL for being the best part of our events this year! This year, IBM Developer New York has grown over 70%! Thank you for showing up, participating & being excited to learn with us!

Assist AI doesn't need data scientists to train or refine models for maintenance work.