It was clear to the University of New South Wales (UNSW) that at the end of 2018, when it was developing its data strategy, it needed to improve the turnaround time it took to get information into the hands of decision makers. But to do that, the university had to set up a cloud-based data warehouse, which it opted to host in Microsoft Azure. The cloud-based warehouse now operates alongside the university's legacy data warehouse, which is currently hosted in Amazon Web Service's (AWS) EC2. "Our legacy data warehouse has been around for 10 to 15 years. But we started looking at what platforms can let us do everything that we do now, but also allows us to move seamlessly into new things like machine learning and AI," UNSW chief data and insights officer and senior lecture at the School of Computer Science and Engineering, Kate Carruthers said, speaking to ZDNet.
In order to create effective machine learning and deep learning models, you need copious amounts of data, a way to clean the data and perform feature engineering on it, and a way to train models on your data in a reasonable amount of time. Then you need a way to deploy your models, monitor them for drift over time, and retrain them as needed. You can do all of that on-premises if you have invested in compute resources and accelerators such as GPUs, but you may find that if your resources are adequate, they are also idle much of the time. On the other hand, it can sometimes be more cost-effective to run the entire pipeline in the cloud, using large amounts of compute resources and accelerators as needed, and then releasing them. The major cloud providers -- and a number of minor clouds too -- have put significant effort into building out their machine learning platforms to support the complete machine learning lifecycle, from planning a project to maintaining a model in production.
Artificial intelligence is right up there with robots taking over our jobs. This is the first in a series on how big tech like Facebook uses AI to manipulate you. The number of AI applications has increased rapidly. We speculate and marvel about what AIs will be able to do in the future. But what we don't realise is that AI has already had a huge impact on the goods and services we use every day.
The more online customers the more eCommerce sales that bring the competitive environment that becomes most challenging especially for the marketers. To be on the competitive edge one should need to find the eCommerce trends by traveling all around the digital marketing world where your products or services promotion can take off effectively. The AI Chatbots helps in replacing human activity and give great customer experience via a live chat interface. Moreover, the retailers can find in-depth business insights with the involvement of Artificial Intelligence that gives accurate results and they can target millions of customers. The video popularity increasing and the brands are showing interest in creating the video content much more.
Dr. Oren Etzioni has served as the Chief Executive Officer of the Allen Institute for AI (AI2) since its inception in 2014. He has been a Professor at the University of Washington's Computer Science department since 1991, and a Venture Partner at the Madrona Venture Group since 2000. He has been the founder or co-founder of several companies, including Farecast (sold to Microsoft in 2008) and Decide (sold to eBay in 2013). He helped to pioneer meta-search (1994), online comparison shopping (1996), machine reading (2006), and Open Information Extraction (2007). He has authored over 100 technical papers that have garnered over 2,000 highly influential citations on Semantic Scholar.
In 2018, the smart sensor market was valued at $30.82 billion and is expected to reach $85.93 billion by the end of 2024, registering an increase of 18.82% per year during the forecast period 2019-2024. With the growing roles that IoT applications, vehicle automation, and smart wearable systems play in the world's economies and infrastructures, MEMS sensors are now perceived as fundamental components for various applications, responding to the growing demand for performance and efficiency. Connected MEMS devices have found applications in nearly every part of our modern economy, including in our cities, vehicles, homes, and a wide range of other "intelligent" systems. As the volume of data produced by smart sensors rapidly increases, it threatens to outstrip the capabilities of cloud-based artificial intelligence (AI) applications, as well as the networks that connect the edge and the cloud. In this article, we will explore how on-edge processing resources can be used to offload cloud applications by filtering, analyzing, and providing insights that improve the intelligence and capabilities of many applications.
For movie buffs, the work that the factory machines do in Charlie Chaplin's 1936 classic, Modern Times, may have seemed too futuristic for its time. Fast forward eight decades, and the colossal changes that Artificial Intelligence is catalyzing around us will most likely give the same impression to our future generations. There is one crucial difference though: while those advancements were in movies, what we are seeing today are real. A question that seems to be on everyone's mind is, What is Artificial Intelligence? The pace at which AI is moving, as well as the breadth and scope of the areas it encompasses, ensure that it is going to change our lives beyond the normal.
NTT Ltd. delivers superior assistance to enterprises in making digital transformation that will improve both efficiency and productivity Based on its recent analysis of the Thai enterprise systems integration market, Frost & Sullivan recognizes NTT Ltd. with the 2020 Thailand Enterprise Systems Integrator of the Year Award. NTT Ltd. has earned a unique position in the market as the only company to offer an end-to-end suite of solutions comprising Intelligent Infrastructure, Intelligent Cybersecurity, Intelligent Business, and Intelligent Workplace. NTT Ltd. collaborates with major service providers and vendors globally to shape and deliver business outcomes through these digital, connected, data-driven, and secure solutions. "NTT Ltd. brings together the unrivaled capabilities of its group of companies spanning technology services to delivery. The depth and breadth of its portfolio, backed by proven expertise, makes it the preferred partner for enterprise and government clients in Thailand that are embarking on digital transformation," said Krishna Baidya, Director, ICT.
Technology companies are poster children for diversity problems in the workforce. Although they far surpass the national average when hiring Asian Americans, Brookings found African Americans and Latinos were employed in tech at half the rate as they were in all other professions. There is no shortage of theories as to why these gaps persist, but no solution to date has made a significant dent in the industries' problem. Is it time to look at artificial intelligence to eradicate bias from our hiring process? First, we have to deal with the elephant in the room.
The enterprise has been talking about Digital Transformation and Industry 4.0 for years. We have seen transformation accelerate and the adoption of artificial intelligence, connected devices, and even virtual reality speed-up over the last few months due to the pandemic. As enterprise digitization continues to be top of mind and data becomes even more critical in this process, we need to look at how all the data created can be better visualized to generate better business outcomes. The Internet of Things (IoT) allows devices to talk to each other through connected sensors - producing real-time data. Companies had to learn how to process large amounts of data from IoT devices.