We propose a new polar code construction framework (i.e., selecting the frozen bit positions) for the additive white Gaussian noise (AWGN) channel, tailored to a given decoding algorithm, rather than based on the (not necessarily optimal) assumption of successive cancellation (SC) decoding. The proposed framework is based on the Genetic Algorithm (GenAlg), where populations (i.e., collections) of information sets evolve successively via evolutionary transformations based on their individual error-rate performance. These populations converge towards an information set that fits the decoding behavior. Using our proposed algorithm, we construct a polar code of length 2048 with code rate 0.5, without the CRC-aid, tailored to plain successive cancellation list (SCL) decoding, achieving the same error-rate performance as the CRC-aided SCL decoding, and leading to a coding gain of 1 dB at BER of $10^{-6}$. Further, a belief propagation (BP)-tailored polar code approaches the SCL error-rate performance without any modifications in the decoding algorithm itself.

Surrogate modeling and uncertainty quantification tasks for PDE systems are most often considered as supervised learning problems where input and output data pairs are used for training. The construction of such emulators is by definition a small data problem which poses challenges to deep learning approaches that have been developed to operate in the big data regime. Even in cases where such models have been shown to have good predictive capability in high dimensions, they fail to address constraints in the data implied by the PDE model. This paper provides a methodology that incorporates the governing equations of the physical model in the loss/likelihood functions. The resulting physics-constrained, deep learning models are trained without any labeled data (e.g. employing only input data) and provide comparable predictive responses with data-driven models while obeying the constraints of the problem at hand. This work employs a convolutional encoder-decoder neural network approach as well as a conditional flow-based generative model for the solution of PDEs, surrogate model construction, and uncertainty quantification tasks. The methodology is posed as a minimization problem of the reverse Kullback-Leibler (KL) divergence between the model predictive density and the reference conditional density, where the later is defined as the Boltzmann-Gibbs distribution at a given inverse temperature with the underlying potential relating to the PDE system of interest. The generalization capability of these models to out-of-distribution input is considered. Quantification and interpretation of the predictive uncertainty is provided for a number of problems.

Today marks the launch of a world-first technology platform which aims to transform the oil trading industry through the application of artificial intelligence – OilX. Established in 2018, OilX is a new cargo and flow tracking platform which provides users with a real-time view of the supply-demand balance globally. A joint venture between the well-established maritime services organisation The Signal Group and OilX, the platform aims to provide real-time and accurate oil analytics to empower traders and analysts to make better commercial decisions. In contrast with current, resource-heavy oil analysis which is based on disparate and historical data, OilX aims to revolutionise oil analytics by harnessing artificial intelligence to provide companies with a more accurate and timely view of market fluctuations – ultimately allowing companies to do much more in far less time. "There is a significant amount of resource currently devoted to oil analytics. However, the flow, timeliness and speed of delivery of information falls far below what is needed for impactful commercial decision making," commented Florian Thaler, oil strategist and CEO of OilX.

With over 7.5 billion people on the planet, finding energy sources is always at the forefront of the scientific community. Electric-powered cars are a perfect example. With technology like this, businesses and consumers can both save money on fuel costs while doing the environment a favor. Solar power is already saving people a lot of money on energy bills, and the technology will continue to get even better in the future. Efficiency is key for any business to save money.

An amphibious supercar design that would allow its mega rich owners to look stylish and beat city traffic by travelling through water at high speed has been unveiled. According to its creators, the electric powered Amphi-X would reach speeds of more than 260 mph (418 km/h) on land and an average speed of over 90 mph (145 km/h) in water, the same as a modern speed boat. The car has been designed for the world's super rich to avoid congested roads of big cities, but comes with a hefty £2.5 million price tag. An amphibious supercar design that would allow its mega rich owners to look stylish and beat city traffic by travelling through water at high speed has been unveiled. The car has been designed for the world's super rich to avoid congested roads of big cities, but comes with a hefty £2.5 million price tag.

Last year, the US Department of Energy announced that the SunShot Initiative successfully met its 2020 utility-scale solar cost target of $0.06 per kilowatt hour three years earlier than expected. This milestone marks a huge step forward for the industry as it moves toward a greener future that's less reliant on fossil fuels. While 6 cents may sound cheap, it's far from the bottom. The SunShot Initiative is now working towards another lofty goal for 2030: $0.03 per KwH. This benchmark would make solar energy one of the least expensive options for new power generation, and help drive mass adoption on a national scale.

Few folks are aware of how much electricity their household consumes on a daily basis, according to the U.S. Energy Information Administration's Residential Energy Consumption Survey. Among smart meter owners in 2016, only 8 percent reported knowing that they had access to hourly or daily data, and just 4 percent said they'd viewed that data. That's all the more discouraging when you consider that always-on devices like DVRs and game consoles account for 23 percent of home energy usage -- a total of $40 billion annually nationwide. Boston-area startup Sense, which uses machine learning to provide real-time insights on electrical usage, is on a mission to effect change. It today revealed that energy management solutions firm Landis Gyr has joined Schneider Electric, Energy Impact Partners, Shell Ventures, Prelude Ventures, Capricorn Investment Group, and iRobot in bringing its series B round funding to $20 million.

Artificial intelligence, energy diversification and the transformation of the workforce will be amongst the major talking points at SPE Offshore Europe 2019. Senior international industry figures will co-chair the keynote sessions which also includes late life and decommissioning, underwater innovation, transformative technologies to lower the carbon footprint, digital security, integrated technologies, digitalisation, standardisation and finance. The event will take place from 3-6 September at the new £333million The Event Complex Aberdeen (TECA), under the theme: 'Breakthrough to Excellence – Our license to operate'. Michael Borrell, SPE Offshore Europe 2019 Conference Chair & Senior Vice President, North Sea and Russia at Total said: "Our committee is full of international oil and gas industry leaders and they have developed an excellent programme which gets to the heart of the main opportunities and challenges facing the region. "Offshore Europe 2019 is a great opportunity for us to challenge ourselves in the North Sea basin.

In an attempt to skill Indian youths in Artificial Intelligence, Microsoft India has taken an initiative to train five lakh youths. The company aims to train five lakh youths in AI across the country and would set up AI labs in 10 universities. Additionally, the company plans to upskill 10,000 developers in emerging technology areas like AI, IoT, etc. Microsoft also started Intelligent Cloud Hub Program to equip research and higher education institutions with AI infrastructure, build curriculum and help both faculty and students to build their skills and expertise in cloud computing, data sciences, AI and IoT. Anant Maheshwari, President, Microsoft India shares, "We believe AI will enable Indian businesses and more for India's progress, especially in education, skilling, healthcare, and agriculture. Microsoft also believes that it is imperative to build higher awareness and capabilities on security, privacy, trust, and accountability. The power of AI is just beginning to be realized and can be a game-changer for India."

NASA's InSight lander is leaning in for a better listen of Mars' underground tremors. The robotic explorer placed its seismometer on the surface at the end of last month, and is now getting even closer'for a better connection with Mars.' This will help its instruments pick up fainter signals that may otherwise have been missed. NASA's InSight lander is leaning in for a better listen of Mars' underground tremors. The robotic explorer placed its seismometer on the surface at the end of last month, and is now getting even closer'for a better connection with Mars.' Before and after images show its instrument at its lowest position yet Days prior, InSight leveled out its seismometer and adjusted the internal sensors ahead of lowering everything down toward the ground.