It's time to solve deep learning's productivity problem


Deep learning is fueling breakthroughs in everything from consumer mobile apps to image recognition. Yet running deep learning-based AI models poses many challenges. One of the most difficult roadblocks is the time it takes to train the models. The need to crunch lots of data and the computational complexity of building deep learning-based AI models also slows down the progress in accuracy and the practicality of deploying deep learning at scale. It's the training times -- often measured in days, sometimes weeks -- that slow down implementation.

Singapore aims to drive up standards for autonomous vehicles with test centre


A new test centre has opened up in Singapore to develop standards and ensure the safe deployment of autonomous vehicles on public roads. Spanning two hectares in Jurong Innovation District, the test site was jointly developed by the country's Land Transport Authority (LTA), Nanyang Technological University of Singapore (NTU), and JTC. It also would support the Centre of Excellence for Testing & Research of AVs - NTU (CETRAN), which was launched in August last year. In a joint statement, the organisations noted the lack of international test standards or international certification bodies for autonomous vehicles (AVs). The new test site as well as efforts led by CETRAN would establish Singapore's role in driving the testing and deployment of such vehicles.

Apple's self-driving car team uses machine learning to get more out of LiDAR - SiliconANGLE


Apple Inc. has had a "will they or won't they" relationship with self-driving car development over the last few years, and unlike companies like Alphabet Inc. or Uber Technologies Inc., Apple has been fairly tight lipped about most of its work. From what little is known, Apple has been focusing more on the software side rather than on hardware, and a new research paper published Friday by the company on Cornell University's arXiv repository seems to confirm that theory. In the paper, Apple describes a new method for getting more out of a self-driving car's LiDAR sensors using machine learning. LiDAR uses pulses of laser light to create digital maps of objects using point clouds, which are a sort of 3D version of a connect the dots puzzle. Denser point clouds offer a clearer, more accurate picture of an object, but Apple's researchers say their new method, which they call VoxelNet, makes even sparse point clouds useful for object detection.

How Fintech Companies are disrupting the Capital Markets Space


The investment Banking Industry is in the state flux. Digital revolution, increased regulation, and seismic shifts, the industry is now aware of the threat that they have been trying to stay ahead. Everyone knows the era of transformation has been underway for over a decade now. Technology now serves as Value proposition in Capital Markets Industry. What is the digital disruption that is affecting banking and other financial services?

The inevitability of artificial intelligence


In its hospital complex in New York City, leading cancer center Memorial Sloane Kettering is partnering with IBM to create the medicine of the future. There, oncology specialists have been teaching Watson, a cognitive computing system probably best known for beating humans at the TV game show Jeopardy, how to interpret cancer patients' clinical information and identify personalized, evidence-based treatment options. Watson mimics the human brain, digesting terabytes of data on certain cancers. Today, it is no smarter than the cumulative knowledge of the people who feed it information or the human-produced research it absorbs. But given the exponential growth in the amount of data on cancers coming available and the machine's ability to "learn," recognize patterns, and summon information instantaneously, it may be one day.

Demand for Valuable Data to Empower Deep Learning Market


San Francisco, California, October 09, 2017 – The global market for deep learning is projected to undergo immense growth opportunities in the coming years, as reported by TMR Research. The report published by the market research company, titled, "Deep Learning Market – Global Industry Analysis, Size, Share, Trends, Analysis, Growth, and Forecast 2017 – 2025," explains how the growing utilization of deep learning in a few enterprises including automotive, marketing and medicinal services is the essential driver for the market. Notwithstanding that, thorough innovative work that are at present in progress are relied upon to develop the innovation and capacity of the market in a way that different enterprises can improve their product. Since deep learning systems can give master help, they help people to expand their capacities. These systems initially build up a deep space knowledge and give this data to the end-clients in an auspicious, normal, and usable way.

How 3 Brands Are Using AI For Enhanced Creativity - Dataconomy


This article was originally published on Every decade or so, a new, game-changing technology platform changes the way the world works. From the desktop, to mobile, and to the cloud, the landscape continues to advance. We are knee-deep in the artificial intelligence (AI) revolution--one so big that it has been compared to the invention of electricity. AI has the potential to power future innovation, especially in terms of customer experiences and the way we do our jobs.

The future of getting dressed: AI, VR and smart fabrics


Cher Horowitz's closet from the film "Clueless" had a futuristic computer system that helped her put together outfits. Back in 1995, the concept teased what it might be like to get dressed in the future. Technology has evolved a lot since then, but closets have been largely untouched by innovation. Now, that's starting to change. "If algorithms do their job well, people will spend less time thinking about what to wear," said Ranjitha Kumar, an assistant professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign.

17 Experts Tell The Most Exciting IoT Trends to Watch for in 2018 - TechJini


Needless to say, IoT is one of the most talked about technologies in 2017. According to Statista, the global IoT market is forecast to be valued at more than 1.7 trillion U.S. dollars. "What According To You Is The Most Exciting IoT Trend To Watch For In 2018?" I think the most exciting IoT trend to watch out for in 2018 is the use of Blockchain technology to accelerate transactions, ensure trust, and reduce costs. The Internet of Things, (IoT), is such and exciting yet complex ecosystem.

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.