Oceania
Asia Pacific youth expect Artificial Intelligence to have biggest impact on their future: Microsoft survey - Asia News Center
SINGAPORE, 22 February 2017 -- In our increasingly digital world, new and emerging innovations are set to disrupt the way people live, work and play. According to youth across the Asia Pacific region, the most exciting technologies expected to have the largest impact on their future lives will be artificial intelligence (AI), virtual/mixed/augmented reality (VR/MR/AR), and Internet of Things (IoT), based on survey findings released today by Microsoft. In the Microsoft Asia Digital Future Survey, 1,400 youth were polled across 14 markets across the Asia Pacific region, comprising Australia, China, Hong Kong, India, Indonesia, Japan, Korea, Malaysia, New Zealand, Philippines, Singapore, Taiwan, Thailand and Vietnam. Artificial intelligence (AI) is ranked as the top technology that youth expect to have the biggest impact on their lives. In recent years, the confluence of power devices, cloud and data has enabled bold visions on how AI can be an integrated part of our digital future.
Born Again Neural Networks
Furlanello, Tommaso, Lipton, Zachary C., Tschannen, Michael, Itti, Laurent, Anandkumar, Anima
Knowledge distillation (KD) consists of transferring knowledge from one machine learning model (the teacher}) to another (the student). Commonly, the teacher is a high-capacity model with formidable performance, while the student is more compact. By transferring knowledge, one hopes to benefit from the student's compactness. %we desire a compact model with performance close to the teacher's. We study KD from a new perspective: rather than compressing models, we train students parameterized identically to their teachers. Surprisingly, these {Born-Again Networks (BANs), outperform their teachers significantly, both on computer vision and language modeling tasks. Our experiments with BANs based on DenseNets demonstrate state-of-the-art performance on the CIFAR-10 (3.5%) and CIFAR-100 (15.5%) datasets, by validation error. Additional experiments explore two distillation objectives: (i) Confidence-Weighted by Teacher Max (CWTM) and (ii) Dark Knowledge with Permuted Predictions (DKPP). Both methods elucidate the essential components of KD, demonstrating a role of the teacher outputs on both predicted and non-predicted classes. We present experiments with students of various capacities, focusing on the under-explored case where students overpower teachers. Our experiments show significant advantages from transferring knowledge between DenseNets and ResNets in either direction.
How Advanced Analytics Is Changing B2B Selling
From targeted online advertising to more precise recommendation engines, consumer markets are bursting with innovation around machine learning and advanced analytics. While there's less buzz around business-to-business markets, these innovations are changing the game in B2B as well, even in old-line industries selling what might be considered commodity products. A growing number of B2B companies are using data and analytics to add services that bring new elements of value to customers, and in some cases new sources of revenue. These elements are fundamental attributes of a company's offering in their most essential and discrete forms โ things like product quality, flexibility, and associated expertise; they lift value propositions above commodity status and benefit customers in particular ways. Consider recent moves by Australia-based Orica, which provides packaged explosives materials to mining companies worldwide.
Budget 2018: National AI ethics framework on the way
As artificial intelligence continues to creep into everyday life, the Australian government has pledged $29.9 million over four years to enhance local AI capabilities. Treasurer Scott Morrison announced in Tuesday night's budget that "research in artificial intelligence" was to be included as part of the Government's $2.4 billion investment into Australia's science and technology capacity. The Department of Industry, Innovation and Science will receive the bulk of the funding ($26 million), alongside the CSIRO ($2.3 million) and the Department of Education and Training ($1.5 million). "This measure will support Cooperative Research Centre projects, PhD scholarships and school-related learning to increase knowledge and develop the skills needed for AI and machine learning," the budget papers state. Professor of Artificial Intelligence at the University of New South Wales and ACS AI Ethics Committee Member, Professor Toby Walsh, welcomed the funding, but questioned whether it was enough to poise Australia as a global leader in the field.
Reciprocal Attention Fusion for Visual Question Answering
Farazi, Moshiur R, Khan, Salman
Existing attention mechanisms either attend to local image grid or object level features for Visual Question Answering (VQA). Motivated by the observation that questions can relate to both object instances and their parts, we propose a novel attention mechanism that jointly considers reciprocal relationships between the two levels of visual details. The bottom-up attention thus generated is further coalesced with the top-down information to only focus on the scene elements that are most relevant to a given question. Our design hierarchically fuses multi-modal information i.e., language, object- and gird-level features, through an efficient tensor decomposition scheme. The proposed model improves the state-of-the-art single model performances from 67.9% to 68.2% on VQAv1 and from 65.3% to 67.4% on VQAv2, demonstrating a significant boost.
Artificial intelligence: The advantages and disadvantages of AI
Australia and other countries around the world are seeing an increased use of artificial intelligence (AI). This week, Google unveiled a new feature called Duplex that uses artificial technology to generate a realistic-sounding voice assistant. The Australian government also announced in Tuesday's federal budget it would invest more than $2.4 billion in technology and science, including leading research in artificial intelligence. RMIT Senior Lecturer Dr Andy Song believes the definition has been debated for quite a long time. "There is no premise definition," Dr Song said.
A new machine learning tool could flag dangerous bacteria before they cause an outbreak
A new machine learning tool that can detect whether emerging strains of the bacterium, Salmonella are more likely to cause dangerous bloodstream infections rather than food poisoning has been developed. The tool, created by a scientist at the Wellcome Sanger Institute and her collaborators at the University of Otago, New Zealand and the Helmholtz Institute for RNA-based Infection Research, a site of the Helmholtz Centre for Infection Research, Germany, greatly speeds up the process for identifying the genetic changes underlying new invasive types of Salmonella that are of public health concern. Reported today (8 May) in PLOS Genetics, the machine learning tool could be useful for flagging dangerous bacteria before they cause an outbreak, from hospital wards to a global scale. As the cost of genomic sequencing falls, scientists around the world are using genetics to better understand the bacteria causing infections, how diseases spread, how bacteria gain resistance to drugs, and which strains of bacteria may cause outbreaks. However, current methods to identify the genetic adaptations in emerging strains of bacteria behind an outbreak are time-consuming and often involve manually comparing the new strain to an older reference collection.
Oracle AI enables Polo concierge - Enterprise Times
Oracle has announced that it is leveraging its AI capabilities to deliver a better consumer experience to attendees of Heineken Urban Polo. Heineken Urban Polo is a series of events in New Zealand cities that combines polo, fine cuisine and music. The Oracle Intelligent Bot will answer questions about the event through a Facebook interface. It enables attendees to ask questions about how to get there, where the bar is, what times the matches start, when the pony parade is on, rules of the game, details of players, which DJs are playing and when. As more people interact with the bot it will apply machine learning to improve its answers about the various subjects.