The massive, beautiful tree canopies in the Western U.S., which may grow perilously close to power lines, can quickly spark destructive wildfires. In fact, 70% of electrical outages are caused by vegetation, and this number has increased by 19% year over year from 2009-2020. The second-largest wildfire in California's history, The Dixie Fire, sparked when power lines came into contact with a fir tree. Could AI-driven solutions help prevent wildfires before they start by analyzing the tree growth that can spark them? Hitachi Energy, the Zurich, Switzerland-based global technology company, says yes. Hitachi Energy, formerly known as Hitachi ABB Power Grids (the name was changed last October) is currently focused on "powering good for a sustainable energy future."

Now, imagine an entirely different kind of computer, with head-spinning power, using mind-bending quantum mechanics to bring barely believable capabilities to life. A super super computer that can tackle calculations that the most powerful conventional machines would need decades to process – in a split second. This contraption – which resembles a baroque chandelier that could have hung at Versailles – is a quantum computer. They probably won't replace today's computers – don't expect your next laptop to be a quantum device – but they will be able to tackle certain boxed and highly complex tasks that force traditional computers to throw in the towel. If there are near-endless possible answers to a clearly defined problem, a quantum computer will find the solution much quicker than any conventional computer.

On the very first business process design project, my team was told to redesign an internal invoice process in accounts receivable. Problems involved duplicate systems and duplicate BPs that prolonged invoice processing for days. Working hand in hand with finance, we reviewed each step of the process, identifying duplicates in data and processes and eliminating them. The result was a more streamlined invoicing process that went from three days to one. I often think of that first BP redesign assignment and how straightforward it was when compared to redesigning BPs with artificial intelligence.

Tatum, Texas might not seem like the most obvious place for a revolution in artificial intelligence (AI), but in October of 2020, that's exactly what happened. That was when Wayne Brown, the operations manager at the Vistra-owned Martin Lake Power Plant, built and deployed a heat rate optimizer (HRO). Vistra Corp. is the largest competitive power producer in the United States and operates power plants in 12 states with a capacity of more than 39,000 megawatts of electricity--enough to power nearly 20 million homes. Vistra has committed to reducing emissions by 60 percent by 2030 (against a 2010 baseline) and achieving net-zero emissions by 2050. To achieve its goals, the business is increasing efficiency in all its power plants and transforming its generation fleet by retiring coal plants and investing in solar- and battery-energy storage, which includes the world's largest grid-scale battery energy-storage facility.

In the third of a series of blogs from our global offices, we provide a overview of key trends in artificial intelligence in the United Arab Emirates. What is the UAE's strategy for Artificial Intelligence? In 2017, the UAE appointed a Minister of State for Artificial Intelligence, H.E. Omar Bin Sultan Al Olama, and issued a national AI strategy seeking to become one of the world leaders in AI by 2031. To implement the national AI strategy, the UAE established an Office for Artificial Intelligence, which is responsible for enhancing government performance by investing in AI technologies and tools for application across various sectors. The UAE Council for Artificial Intelligence and Blockchain was also established to provide advice to the government on the adoption and use of AI, to design policies that promote an AI-friendly ecosystem, to advance research and to promote private–public collaboration in that space.

In this decade of 21st century, world is seeing very different challenges in the power management in Power Generation, transmission, distribution & consumption. As most of the countries are taking on challenges on sustainability goals, there is significant Energy Transition happening towards more & more GREEN energy. Lot more sources of energy like Wind, Solar are becoming more viable and being adopted. However, this has put a clear expectation on adding intelligence into the existing products & solutions to manage this transition as well as adopting new digital software-based solutions. With the rapid advancement in the IoT & Cloud infrastructure, creating this intelligence is now feasible and economically viable.

AUSTIN – The Railroad Commission has turned to artificial intelligence to optimize the time the agency's technical analysts spend on seismicity reviews to ensure residents and the environment are protected. Seismicity reviews are conducted by the Underground Injection Control (UIC) Department for injection/disposal well permits in areas susceptible to earthquakes and in certain geologic zones. UIC staff programed a machine learning algorithm to help with the large amount of information that needs to be processed and digested. Along with some other changes, tasks performed by the machine learning algorithm have enabled UIC to wipe out a backlog of seismic reviews to zero today. Like the technical analyst, the AI program weighs many factors related to the number, severity and proximity of earthquakes and uses a decision tree to assign a grade to the review.

Recent advances in vision-based navigation and exploration have shown impressive capabilities in photorealistic indoor environments. However, these methods still struggle with long-horizon tasks and require large amounts of data to generalize to unseen environments. In this work, we present a novel reinforcement learning approach for multi-object search that combines short-term and long-term reasoning in a single model while avoiding the complexities arising from hierarchical structures. In contrast to existing multi-object search methods that act in granular discrete action spaces, our approach achieves exceptional performance in continuous action spaces. We perform extensive experiments and show that it generalizes to unseen apartment environments with limited data. Furthermore, we demonstrate zero-shot transfer of the learned policies to an office environment in real world experiments.

Robotics in oil and gas production can save several lives every year by executing tasks that are too dangerous for workers. Oil and gas production involves some of the most dangerous jobs in the world. Tasks such as oil drilling, roughneck jobs and maintenance tests, among others, cause several worker deaths every year. In fact, a study found that there are several deaths in oil and gas production that are never reported. Such points and facts beg the question, what makes oil and gas production so dangerous?

AJ Abdallat is CEO of Beyond Limits, a leader in artificial intelligence and cognitive computing. Artificial intelligence (AI), machine learning (ML) and similar digitalization solutions are modifying the way the world's most influential companies and industries -- as well as entire cities -- function every day. When working in harmony with humans, AI and other automation systems have the potential to make huge impacts on economic growth across the globe, going so far as to support solving humanity's most critical roadblocks, from streamlining energy production to improving grid systems and achieving more sustainable operations for nearly every major industry on Earth. As the CEO of an AI company making advanced digitalization software products and solutions, the paradigm of enabling people and AI to work together on achieving more sustainable operations is always top of mind; its importance cannot be curbed. As we move into the future, I'm confident there will be plenty of jobs for both humans and AI so long as they are able to function in conjunction with one another.