In this work, we design a machine learning based method, online adaptive primal support vector regression (SVR), to model the implied volatility surface. The algorithm proposed is the first derivation and implementation of an online primal kernel SVR. It features enhancements that allow online adaptive learning by embedding the idea of local fitness and budget maintenance. To accelerate our algorithm, we implement its most computationally intensive parts in a Field Programmable Gate Arrays hardware. Using intraday tick data from the E-mini S&P 500 options market, we show that our algorithm outperforms two competing methods and the Gaussian kernel is a better choice than the linear kernel. Sensitivity analysis is also presented to demonstrate how hyper parameters affect the error rates and the number of support vectors in our models.

Chemical space is so large that brute force searches for new interesting molecules are infeasible. High-throughput virtual screening via computer cluster simulations can speed up the discovery process by collecting very large amounts of data in parallel, e.g., up to hundreds or thousands of parallel measurements. Bayesian optimization (BO) can produce additional acceleration by sequentially identifying the most useful simulations or experiments to be performed next. However, current BO methods cannot scale to the large numbers of parallel measurements and the massive libraries of molecules currently used in high-throughput screening. Here, we propose a scalable solution based on a parallel and distributed implementation of Thompson sampling (PDTS). We show that, in small scale problems, PDTS performs similarly as parallel expected improvement (EI), a batch version of the most widely used BO heuristic. Additionally, in settings where parallel EI does not scale, PDTS outperforms other scalable baselines such as a greedy search, $\epsilon$-greedy approaches and a random search method. These results show that PDTS is a successful solution for large-scale parallel BO.

On Monday, Apple will show off its latest software and hardware, including Macs and iPads, at its annual conference for developers. The most anticipated item is a new voice-controlled speaker that would compete with the Amazon Echo and Google Home devices. Fans of Warren E. Buffett -- at least those with deep pockets -- have another chance to buy the billionaire lunch. An auction for a meal with Mr. Buffett, the chief executive of Berkshire Hathaway, at Smith & Wollensky in New York City began Sunday evening and runs through Friday, with bids starting at $25,000. The entire bid will support Glide, a nonprofit group that runs antipoverty programs in San Francisco.

For those tired of the never-ending task of weeding, one set of engineers has the answer: a robot that autonomously clears up your lawn. The machine roams the garden and uses sensors to detect weeds sprouting from the soil, which it then cuts down using a small string trimmer. The robot, called Tertill, is solar powered and water-proof so can be left outside in the rain and does not need to be plugged in to charge. Experts have developed a machine that automatically roams the garden and uses sensors to detect weeds sprouting from the soil, which it then cuts down. As well as the ability to pair with smartphones through Bluetooth, the Tertill also has a USB port for charging during cloudy weeks.

Data is most valuable when it's in the hands of business users. Challenged to stay ahead of the massive changes that are disrupting the marketplace, businesses are turning the vast amounts of data distributed across their enterprise into insights and outcomes to drive material return on investment (ROI). Bengaluru-based Teknoleum Solutions is one such firm that highlights the strategic utility of data to gain real-time insights and boost efficiencies in an increasingly data-driven oil and gas sector. It has developed an innovative cloud-based Internet of Things solution for connected solar farms, called PV2, which leverages the power of SAP HANA to increase solar photovoltaic plant output and decrease operations and maintenance costs. "We are a team of SAP product development experts. Our solution is an IoT app for photo voltaic plant management that monitors solar plant performance patterns to estimate soiling losses," said Shashidhar Peddi, delivery head, Teknoleum Solutions.

Our extensive market knowledge and innovative worldwide network of candidates ensures connectivity to the right talent and increase our client's competitive advantage. We work with various type of organizations from local businesses to International / Multinational companies finding the right fit from any part of the world.

Green Technology: One of the most important ingredient for solutions being proposed, we cannot overlook the climate change which is affecting our environment. We as humans, evolved to an extent where we are dependent on the resources Earth provides us, resulting in their depletion. We invite pioneers in innovating newer techniques which would be in light of renewable energy resources. Safety: Safety for the Vehicle and for the Passenger is an important aspect of the Transportation solutions which would reduce accidents, make communications secure between vehicles and infrastructure. Machines could take over critical areas where human error may affect safety adversely.

Artificial Intelligence (AI) does more than make our technology smarter, it also protects the planet. Consider the work of researchers in the field of'Computational Sustainability' – a field of AI research making us better stewards of life on Earth. Despite being a relatively new research field, Computational Sustainability has already helped fight wildlife poaching, reduce greenhouse gas emissions, understand poverty, manage wildlife populations, and protect biodiversity. Each of these contributions address one of the United Nations Sustainable Development Goals (SDGs). The collected progress of AI is addressing all SDGs, but I will highlight three specific cases.

The AI company is in the early stages of partnering with the UK's National Grid DeepMind is in talks with the UK's National Grid to boost energy efficiency using artificial intelligence. The AI company, acquired by Google for £400 million in 2014, has developed algorithms that can anticipate energy demand and supply. These algorithms are already being used within Google's own data centres, allowing the tech giant to cut energy by 40%, but they are now in talks with the National Grid, which owns and operates energy infrastructure across the UK. DeepMind is offering AI-powered solutions that could help balance energy supply and demand across the nation. "We're early stages talking to National Grid and other big providers about how we could look at the sorts of problems they have," Demis Hassabis, DeepMind's co-founder and CEO, told the Financial Times.

There's only so much you can do with two arms and hands. But what if you could add extras without the need for ethically shady surgery or trading your apartment for a hovel in the shadow of a nuclear power plant? That's what researchers from Keio University and the University of Tokyo hope to achieve with their "Metalimbs" project. As the name suggests, Metalimbs are a pair of metal, robotic arms that doubles the amount of torso-extremities and worn with a backpack of sorts. And unlike thought-powered prosthetics we've seen recently, these are controlled not with your brain, but your existing limbs.