Oceania
Tealium CEO: AI, IoT and the ongoing customer data integration challenge
Ask any marketer what's on their to-do list in 2017, and they'll tell you they have a project underway to achieve a 360-degree view of the customer, Tealium's global CEO, Jeff Lunsford, says. "Any marketer is going to be looking to pull in data about that customer or a prospect from the myriad points where data is available in this new world," he says. "This could be IoT, mobile devices, or customer care. "Every marketer will nod yes, they want to leverage all the data they possibly can. So there's vision sync across the industry, the question is, how to do that." Tealium is one of a growing number of vendors looking to provide that answer with its Universal Data Hub, a software solution aimed at addressing data fragmentation for marketers across online and offline channels. The platform brings together the vendor's AudienceStream and DataAccess solutions with its iQ foundational technology. Since launching six years ago, Tealium has spent several years integrating its offering with more than 1000 applications across the marketing ecosystem, and recently raised another US$35m in capital, off the back of increased investment earlier in 2016, bringing total funding to $112.9m. Tealium now has 750 enterprise customers globally, from small digital-first companies to the largest, mature organisations. Australian clients include Cronulla Sharks, Nude by Nature, Greenstone Financial, and Melbourne University, while Asia-Pacific clients include Cathy Pacific. Speaking to CMO during a visit to Australia this week, Lunsford described Tealium as the "neutral layer down the stack of the marketing cloud", and the common management component organisations need in order to be able to exchange data across multiple best-of-breed systems in real time. Rather than competing with the large marketing cloud providers, he sees Tealium's role as being a complementary component. Not surprisingly, Lunsford sees technology as providing the foundational layer marketers need across customer touchpoints to pull that 360-degree vision off. "Companies use multiple software applications to create the customer experience, each has its own idea of the customer, and most don't talk to each other," he says. "The average Tealium customer has 26 software applications that contribute to the customer experience.
Artificial intelligence has arrived, but Australian businesses are not ready for it
A survey of business leaders has found Australian companies are the worst prepared for the arrival of artificial intelligence (AI) technologies among selected major economies, despite spending the second-largest amount of money on automation. Independent research agency Vanson Bourne was commissioned by IT company Infosys (which as a seller of an AI platform has a vested interest in promoting such technology) to poll 1,600 business leaders of companies with more than 1,000 staff and at least US$500m in annual revenue across Australia, China, the United States, Germany, France, India and the UK. According to the survey, released at the World Economic Forum last week, major Australian businesses invested an average of $7.9m last year in AI, behind only the US, but placed last in both the skills required for AI takeup and in plans to integrate AI. The Infosys Australia regional head, Andrew Groth, told the Guardian the survey demonstrates that Australia risks becoming uncompetitive. "The challenge is the skills situation," he said.
Artificial intelligence has arrived, but Australian businesses don't know how to use it
A survey of business leaders has found Australian companies are the worst prepared for the arrival of artificial intelligence (AI) technologies among selected major economies, despite spending the second-largest amount of money on automation. Independent research agency Vanson Bourne was commissioned by IT company Infosys (which as a seller of an AI platform has a vested interest in promoting such technology) to poll 1,600 business leaders of companies with more than 1,000 staff and at least US$500m in annual revenue across Australia, China, the United States, Germany, France, India and the UK. According to the survey, released at the World Economic Forum last week, major Australian businesses invested an average of $7.9m last year in AI, behind only the US, but placed last in both the skills required for AI takeup and in plans to integrate AI. The Infosys Australia regional head, Andrew Groth, told the Guardian the survey demonstrates that Australia risks becoming uncompetitive. "The challenge is the skills situation," he said.
Empathy: The Killer App for Artificial Intelligence
Artificial intelligence that reads and responds to our emotions is the killer app of the digital economy. It will make customers and employees happier--as long as it learns to respect our boundaries. When psychologist Dr. Paul Ekman visited the Fore tribe in the highlands of Papua New Guinea in 1967, he probably didn't imagine that his work would become the foundation for some of the latest developments in artificial intelligence (AI). After studying the tribe, which was still living in the preliterate state it had been in since the Stone Age, Ekman believed he had found the blueprint for a set of universal human emotions and related expressions that crossed cultures and were present in all humans. A decade later he created the Facial Action Coding System, a comprehensive tool for objectively measuring facial movement.
iTWire - Machine learning is the 2017 megatrend
"The industry will continue to focus on refining systems, applications, software, security and network infrastructure to meet their needs. Machine learning is the megatrend: its application and influence, particularly on our mobiles, will be improving all parts of our lives in 2017," he said. So begins Deloitte's annual global TMT (Technology, Media, and Telecommunications) report, that since its inception in 2001 has reached an 87% prediction accuracy rate. The report is long but makes for interesting reading. Deloitte Australia forecasts a year that will see further significant breakthroughs in machine learning, indoor GPS navigation, safer travel in motor cars, more cyber mischief and a growing use of biometric security.
Passports replaced with WHAT?
If you're the type of traveler that can never remember which pocket you put your passport in when asked to produce it by airport officials, then Australia's plan for a major overhaul of its checking systems is likely to appeal. The nation's Department of Immigration and Border Protection is aiming to do away with the need for passports at its international airports by introducing systems for biometric recognition of the face, iris and/or fingerprints, the Sydney Morning Herald (SMH) reported. International arrivals could speed through airside without ever interacting with a human official as the new technology -- part of the government's high-tech Seamless Traveler initiative aimed at transforming the border experience -- will eradicate the need for passport checks and passenger cards. Besides making the arrival experience more efficient, officials also believe the system will be better at identifying passengers on watch lists. While a number of airports have for several years been using so-called smart gates that prompt travelers to scan their passports upon arrival, the new system, which the government wants in place within the next three years, goes much further.
New Insight Into How Bees See Could Improve Artificial Intelligence Systems
Dr Dyer is one of Australia's leading bee experts and his latest research shows that honeybees can learn to recognise human faces even when seen from different viewpoints. Dr Dyer said the research could be applied in the areas of new technology, particularly the development of imaging systems. "What we have shown is that the bee brain, which contains less than 1 million neurons, is actually very good at learning to master complex tasks. Computer and imaging technology programmers who are working on solving complex visual recognition tasks using minimal hardware resources will find this research useful," Dr Dyer said. "Most current artificial intelligence (AI) recognition systems perform poorly at reliably recognising faces from different viewpoints. However the bees have shown they can recognise novel views of rotated faces using a mechanism of interpolating or image averaging previously learnt views."
Facial recognition will replace passports in Australia
Australia has started implementing biometric facial, iris and fingerprint recognition in airports, allowing passengers to go through without showing a passport or even talking to anyone. The "Seamless Traveler" project is aimed at creating a "fast, seamless self-processing experience for up to 90 percent of travelers," so that border control can focus on high-risk passengers. The handy, but invasive-sounding plan would allow international travelers to "literally just walk out like at a domestic airport," security analyst John Coyne told Australia's Sidney Morning Herald. The system would replace passport-scanning SmartGates, which were implemented in the nation just ten years ago. The government's plan to implement biometrics might be a touch ambitious, however.
How to Reframe Your Time Series Forecasting Problem - Machine Learning Mastery
You do not have to model your time series forecast problem as-is. There are many ways to reframe your forecast problem that can both simplify the prediction problem and potentially expose more or different information to be modeled. A reframing can ultimately result in better and/or more robust forecasts. In this tutorial, you will discover how to reframe your time series forecast problem with Python. How to Reframe Your Time Series Forecasting Problem Photo by Sean MacEntee, some rights reserved.
How to Reframe Your Time Series Forecasting Problem
You do not have to model your time series forecast problem as-is. There are many ways to reframe your forecast problem that can both simplify the prediction problem and potentially expose more or different information to be modeled. A reframing can ultimately result in better and/or more robust forecasts. In this tutorial, you will discover how to reframe your time series forecast problem with Python. How to Reframe Your Time Series Forecasting Problem Photo by Sean MacEntee, some rights reserved.