If you liked the concept of ONvocal's OV Bluetooth headset, but skipped it because you didn't like the combination of in-ear headphones and a neckband, you'll want to check out 66 Audio's Pro Voice cans. These on-ear headphones host only Amazon's Alexa (the OV supported Alexa, Google Assistant, and Siri), but they're simpler to operate, far more comfortable to wear, and--most importantly--they sound better.
In this talk we will present the various optimization problems encountered in smart grids from the production, transmission and distribution of energy as well as the demand side management in smart homes and the pricing of energy. The optimization opportunities are highlighted for metaheuristics, multi-objective optimization, optimization under uncertainty, optimization-simulation, optimization-machine learning and multi-level optimization.
If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. There's no doubt that technology advances faster than we can even keep up these days, and the smart home sector is one of the fastest-growing. At CES 2018, hundreds of companies showed off new smart home solutions and gadgets, from the useful and innovative to the repetitive and uneventful. As we toured the showrooms, we noticed a few different trends coming to the table for smart home enthusiasts this year.
The potential of artificial intelligence (AI) is exciting and vast, with researchers just starting to understand all the potential applications. However, one solution which users can tap into now, to experience how AI can make their lives more convenient and easier, is Samsung Electronics' HomeCare Wizard. The unique AI-based service solution, available on Samsung's 2018 smart home appliances, essentially enables devices to diagnose themselves for not only system errors, but to enhance efficiency and to help users use their appliances better.
Consider, for a moment, some of the most pernicious challenges facing humanity today: the increasing prevalence of natural disasters; the systemic overfishing of the world's oceans; the clear-cutting of primeval forests; the maddening persistence of poverty; and above all, the accelerating effects of global climate change.
This nascent AI technique – which requires no input data, substantially less computing power, and in which the evolutionary-like AI learns from itself – could soon evolve to enable its application to real-world problems in the natural sciences. Collaboration with Earth scientists to identify the systems – from climate science, materials science, biology, and other areas – which can be codified to apply reinforcement learning for scientific progress and discovery is vital. For example, DeepMind co-founder, Demis Hassabis, has suggested that in materials science, a descendant of AlphaGo Zero could be used to search for a room temperature superconductor – a hypothetical substance that allows for incredibly efficient energy systems.