Editorial Note: This article has been translated from Traditional Chinese
Recently, Mars exploration has become hot news, reinvigorating Beyond Limits’ AI technology origin story from NASA’s Mars Project in 2012. Using Beyond Limits Cognitive AI technology, the Curiosity Rover had the ability to approach human-like reasoning to autonomously judge and deal with unfamiliar situations, helping it successfully complete its mission. This success story boosted the market potential for Beyond Limits AI.
Pre-existing AI technology only provided single-point analytical functionality after accumulating big data and simply yielded the answer (“what”) to the user’s problem without explaining its reasoning (“why”). This describes an AI black box that feeds distrust. Because of this lack of trust, there had been some hesitation around AI adoption in high-risk industries.
Introducing Human Knowledge with One-stop Solution Capabilities
However, Beyond Limits Cognitive AI is different from previous technology. It adopts the introduction of human knowledge, encodes that expertise, and builds in human-like reasoning for model inference. Therefore, even in an environment with limited information, suitable countermeasures can be calculated in real-time because Beyond Limits AI has a comprehensive perspective. Its one-stop solution capabilities have become valued for future application potential in critical industries such as energy, healthcare, manufacturing, and more. A good example includes supermajor, bp, successfully implementing Beyond Limits AI technology to help identify problems and optimize the decision-making process. bp has also participated in Beyond Limits’ Series B and C funding rounds.
Human-like Reasoning for Enhanced AI Trust
David Liu, Executive Chairman of Beyond Limits Asia Pacific provided a vivid example of an autonomous scenario where a conventional system may detect obstacles and suggest an alternate course. Though, a cognitive system based on human-like reasoning would go further because it has the ability to consider the obstacle as well as the potential for additional obstacles that could result from the original.
Beyond Limits AI solutions’ cognitive abilities make them more all-encompassing, logical, and interpretable – advantages that allow users to better understand the reasoning behind their recommendations, thereby greatly enhancing trust in the AI. After all, no matter how good it is – if technology cannot reassure users, it has no commercial value.
Zhang Zhongyi, General Manager of Beyond Limits Taiwan, added that Beyond Limits AI is not only highly efficient with a high level of trust, but it is also an AI software platform with an open SaaS model which can be applied to different units or fields according to the needs of the client. The professional expertise and industry know-how of past experts are preserved through the technology, made accessible across an organization, and transformed into the role of an advisor to humans in the loop.
Observing that Taiwan has ample AI talent, Beyond Limits will expand its presence in Taiwan this year. In addition to planning on setting up an R&D center in Taiwan and strategic partnerships with hardware chip makers, the company will also actively cooperate with numerous industries to improve business processes and maximize value.
About Beyond Limits
Beyond Limits is an industrial and enterprise-grade artificial intelligence company built for the most demanding sectors including energy, utilities, and healthcare.
Beyond traditional artificial intelligence, Beyond Limits’ unique Cognitive AI technology combines numeric techniques like machine learning with knowledge-based reasoning to produce actionable intelligence. Customers implement Beyond Limits AI to boost operational insights, improve operating conditions, enhance performance at every level, and ultimately increase profits as a result.
Founded in 2014, Beyond Limits leverages a significant investment portfolio of advanced technology developed at Caltech’s Jet Propulsion Laboratory for NASA space missions. The company was recently honored by CB Insights on their 2020 List of Top AI 100 most innovative artificial intelligence startups and by Frost & Sullivan for their North American Technology Innovation Award.
Artificial intelligence is invaluable when it comes to its role in this transformational stage facing the utilities sector. Advanced technologies are already at the forefront of driving valuable strategies optimizing the industry across all operations. This includes facilitating missions for achieving smart/clean-city initiatives and net-zero commitments.
According to a 2018 Gartner report, it’s expected that AI will become a critical feature of 30% of smart city applications by 2020, up from just 5% a few years prior.Intentional AI implementation is rapidly becoming recognized as the not-so-secret ingredient helping major energy providers accomplish their lowest carbon footprint to date with sustainability and attractive profit margins.
AI-powered Utilities Propel Smart Cities
Components making a city “smart” involve the collection and analysis of vast amounts of data across numerous sectors, from metropolitan development and utility allocation, all the way down to manual functions like city services. Smart cities involve the construction and maintenance of arrangements of correlative sensors, equipment, and other systems designed to help create more sustainability and efficiency. According to findings from CB Insights, “The global smart cities market size is projected to be worth $1.3T.”
Optimizing a municipality’s strategy behind the entirety of its utility operations is one of the major keys to creating a “smarter city” and a more sustainable environment overall. AI solutions are already making major strides where this initiative is concerned. As the CEO of an AI company making software for the utilities sector, the impact advanced solutions are already having on the industry is something I’m very excited about.
A real-world example of how AI is being utilized to construct smart cities includes infrastructure advancement undertakings such as geospatial analysis company Picterra’s initiative, providing technology that supports better analysis to best optimize road maintenance costs in the city of Kokomo, Indiana. According to the company, the project is designed to “allow the city council to manage road maintenance costs preemptively, optimally map public fund utilization priorities for renovation or construction and provide a methodology for all future public infrastructure maintenance efforts.”
Another good example of a company making moves on the smart city front includes NVIDIA’s Metropolis platform that employs AI at the edge in the form of intelligent video analytics to elevate public services and logistics. The solution is designed to enhance sustainability while maintaining infrastructure and improving community services. The company collects vast amounts of data from sensors and other IoT devices across a city to provide actionable insights, leading to improvements in areas like disaster response, asset protection, supply forecasting, traffic management and more.
My organization is working with Xcell Security House and Finance S.A. to build the world’s first power plant guided by cognitive AI, driving utility development in West Africa. As the earliest implementation of an AI-powered plant from the ground up, the endeavor will employ advanced sensor placement technology and techniques that encode then embed knowledge and expertise into every part of the facility’s processes. Stakeholders will have streamlined access to facility-scale insights, creating a plant environment with greater risk mitigation, as well as maximized efficiency and productivity, resulting in more environmentally conscious, sustainable operations.
These are only a few project mentions. When applying AI, the sector also stands to achieve greater cost and operational efficiencies in several key areas such as predictive maintenance, load forecasting/optimization, grid reliability, energy theft prevention and renewable resource optimization.
Enterprise-grade AI for the Job
When discussing the efficiency of power generation, many factors play into the overall picture, including the impacts of environmental circumstances as commonplace as temperature and humidity levels. Historically, experienced human operators were best equipped to handle necessary, efficiency-boosting adjustments. Cognitive AI is already making moves to encode that human knowledge and expertise across providers’ entire operations, delivering auditable, explainable recommendations at a moment’s notice.
Advanced systems, with the ability to monitor and support large-scale industrial plant operations that encompass complex facilities, have been proving themselves valuable. Retaining holistic coordination across intersecting processes and functionalities is no easy task. Explainable AI creates the trust necessary for operators, engineers and stakeholders to solve acute issues quickly. The system’s situational awareness can help detect, foresee and solve problems, even when circumstances are in constant flux — scenarios as critical as an entire city’s water and power supply.
AI is already playing a principal role in supporting the move toward smarter cities by helping entire sectors get closer to efficiency and net-zero objectives. Achieving a lower carbon future commands more resourceful processes that boost efficiency and reduce waste. AI for utilities can work toward this with systems built to elevate productivity, yielding more acute consideration around resource consumption thus hastening renewable, decarbonization and carbon-friendly strategies on a global scale.
According to a report from the IDC, smart city technology spending across the globe, “reached $80 billion in 2016, and is expected to grow to $135 billion by 2021.” Important considerations to contemplate for companies, industries and other entities looking to participate in this important stage of digital transformation include seeking out industrial-grade AI with software that provides holistic, organization/sector/city-wide insights through sensor placement technology and data collection techniques.
Public and private organizations, plus governments at every level, are moving toward facilitating technological implementation and digital transformation. Private and public partnerships have become a major method for cities to adopt technology that makes them smarter. The best course of action is to embrace AI that blends knowledge-based reasoning with advanced digitalization techniques helping stakeholders distinguish unanticipated scenarios and make tough choices.
Applying AI in these dynamic ways to transform utility sectors contributing to the development of smart cities could result in indelible process improvements, like streamlined operational capacities where all facilities function more efficiently in harmony, reducing waste and carbon footprints. Enhanced communication, strengthened collaboration, increased fuel savings and decreased waste means companies also increase probabilities for propagating profits, predominantly in high-value industries.
WANT TO GET EVEN MORE INFORMATION ON BEYOND LIMITS’ OFFERINGS FOR THE UTILITIES INDUSTRY? CHECK IT ALL OUT HERE.
Forbes recently featured Beyond Limits and also quoted our own Steve Kwan, Director Product Management for Power Generation/Grid Management, in not one but two articles focusing on the power generation sector.
Artificial Intelligence Could Have Helped Alleviate Suffering from Texas Blackouts Is an article that features the repercussions Texas faced after an unexpectedly devastating snowstorm hit, leading to an almost total breakdown of the state’s power grid, leaving many in the dark and without power for weeks on end. Artificial intelligence (AI) is pointed to as one of the principal solutions that could’ve been an important key for preventing such a disaster to have occurred in the first place, had such transformational software been adopted beforehand.
“Another way in which AI could have helped alleviate the problems seen on the Texas grid in February would have been in providing improved long-term weather forecasts. This could have enabled the grid’s operators to determine in advance which units would have to go offline in order to protect the grid’s integrity, which in turn would have allowed electricity consumers more time to prepare for planned outages. Artificial Intelligence technology could also help match up power supply with power demand, down to a minute-by-minute basis, which would have been especially helpful to the ERCOT regulators during the crisis. Texas is in a unique situation because ERCOT isn’t connected to the western and eastern grid so there are fewer opportunities to make up for a shortfall.”
“Taking into account consumer behavior to ensure that supply matches demand as much as possible is a very large puzzle. This is a perfect application of artificial intelligence, because you can take into account many variables and be able to provide a recommendation in a very timely manner to support the changing needs of the consumer on a 15-minute basis. Using traditional physics-based modeling is inefficient or too slow.”
Forbes recently featured Beyond Limits in not one but two articles focusing on the energy/oil and gas sector.
Oil Industry Turns to AI to Help Confront Daunting Challenges Is an article discussing obstacles the industry is currently facing in this era of evolution and digital transformation. Artificial intelligence (AI) technologies are framed as hopeful solutions that address a growing list of concerns including complications posed by the COVID-19 pandemic, carbon-neutral and renewable transition expectations, maintenance issues, and more.
“Upstream oil companies are also using AI to optimize the storage of CO₂ for enhanced oil recovery. Beyond Limits, a Los Angeles-based industrial AI software company, has created an oilfield optimization application, in which captured CO₂ is pumped down a well bore to force more oil to the surface while ensuring the unwanted CO₂ remains trapped in the subsurface environment.”
Built-In-LA recently featured Beyond Limits, and our very own Leigh Yeh in a recent feature, How 3 Local Tech Leaders Use Machine Learning to Drive Innovation. The article spotlights three team members from local leading artificial intelligence/technology companies with a focus on how they are leveraging machine learning to elevate solutions, supporting customers to streamline entire processes and optimize operations at every level of their organization.
“At the end of the day, it’s great to see our products being used by customers and know that we’ve made their processes faster, more reliable and more interpretable,” said Yeh. “It’s so rewarding to build products with the power to make a difference.”
POWERGRID International recently featured an article by our own Stephen Kwan, Director of Product Management for Power Generation/Grid, Energizing the Future of Power with Artificial Intelligence, focusing on the question: As experienced power plant operators retire and the industry become more decentralized, could AI help fill in the knowledge gaps?
The article discusses how advanced artificial intelligence has the potential to transform the health of the industry’s most valuable assets while helping to manage and streamline processes of crucial large-scale plants. There is also a noteworthy spotlight on the technology’s role in helping the sector more seamlessly transition to decentralized power generation systems while facilitating the digitization and distribution of domain expert knowledge across operations.
“Indeed, AI has the potential to revolutionize the power generation domain, combining historical and real-time operational datasets with embedded deep subject matter expertise to result in explainable, trusted recommendations. Such accessibility is designed to maximize the efficiency and reliability of operations while simultaneously minimizing risk, meeting power generation demands, and achieving financial objectives.”
READ THE FULL ARTICLE TO GET MORE OF STEPHEN’S EXPERT INSIGHTS HERE.
POWER magazine recently featured our own Stephen Kwan, Director of Product Management for Power Generation/Grid, in a Q&A interview-style spotlight.
The POWER Interview: AI, Big Data, and Efficiency is an in-depth feature that endeavors to get a glimpse into Stephen’s expert perspectives on artificial intelligence and machine learning as they apply to the electricity sector, with insights into what the future holds as the power generation landscape continues transforming. POWER magazine also took the opportunity to highlight some of the advanced, differentiating technologies offered by Beyond Limits.
“Integration and adoption of machine learning and other artificial intelligence solutions are already increasing exponentially,” said Stephen Kwan. “At this pace, the outlook for advanced technologies points toward AI approaches becoming the gold standard for the future growth of the power generation/utilities industry.”
How can the trend of decentralized power generation benefit from AI?
How can AI be used in power trading, with regard to forecasts, etc.?
Are there specific challenges for power plant operators that AI and ML can help solve?
FIND OUT THESE ANSWERS AND READ THE FULL ARTICLE HERE.
Tech Republic featured our own CEO AJ Abdallat in an interview-style feature that discusses his perspectives on the valuable role AI is playing to help increase operational efficiency in the oil and gas, energy, manufacturing, and healthcare fields. The interview also sheds light on the importance of adopting more advanced AI solutions that are explainable so these critical industries have a clearer path to implementation.
“AI is playing a critical role in operational efficiency across the energy value chain to optimize resource production, democratize domain expert knowledge, and increase value while reducing environmental risk. In the oil and gas sector, AI is enabling companies to optimize their production and improve asset maintenance in many ways, such as pinpointing drilling opportunities, inspecting pipes for problems with self-navigating robots, and predicting equipment wear and tear.”
RIGZONE recently featured our own Michael Krause, Data Scientist, in not one but two articles on the news portion of their company website.
What Were the Top Oil and Gas Trends in 2020? Is a feature that was published on the final day of 2020 in which RIGZONE sought the insights of “informed industry-watchers” regarding their considerations on the topic of recapping the sector’s year. Michael’s observations were highlighted among top 5 trends with a focus on the pandemic’s impact on accelerating the adoption of Cognitive AI and other advanced digital transformation solutions in upstream oil and gas.
“COVID-19 jump-started the long-awaited digital transformation and AI adoption in many upstream oil and gas organizations. Many domain experts, engineers and operators have had to learn new skill sets and built trust in AI and other modern technologies in a very short period of time.”
What Looms for Oil and Gas in 2021? Is a follow-up feature that was published in the first week of the new year in which RIGZONE built on the previous article’s focus and took a closer look into the insights of “informed market-watchers” regarding their considerations on what is to come for the industry. Michael’s observations were selected once again and highlighted among top 5 trends with a focus on the shifting roles of oil and gas domain experts as AI technologies help to supplement some of the traditional aspects of those jobs.
“So far, AI has had the biggest impact on the industry through data cleanup and analysis – the critical next step will be using advanced AI to figure out what all that data means and the reasoning around the meaning of the results, and oil and gas companies will increasingly try to recruit to meet those needs accordingly. This will help domain experts like geoscientists free up their time from tedious analysis work to better leverage their expertise to understand the reasoning behind the results and interpret that to solve larger, more complex industry challenges.”
Smart Industry featured an article by our own CEO AJ Abdallat that touches on Cognitive AI’s flourishing impact on the utilities industry. The article highlights challenges the industry is currently facing and how advanced technologies, like Beyond Limits’ pioneering solutions, are helping to pave the way for transformational digitalization efforts designed to facilitate waning access to expert knowledge, increase efficiency, and streamline entire operations.
“The capabilities of AI in the utilities space have only scratched the surface of the technology’s potential impact. So much more can be possible if/when utilities companies are willing to make investments in their technological advancement; these investments will help amplify decades of existing industry-operator intelligence and intuition.”
Unite.AI featured Beyond Limits in an article, written by Antoine Tardif, featuring some of our experts’ perspectives on artificial intelligence trends in 2021. Our own Kim Gilbert, Ph.D., Manager Technical Commercial Engineering & Michael Krause, Ph.D., Data Scientist, weighed in with their predictions on the significant impact advanced, enterprise-grade AI will have on improving the efficiency and capabilities of industries across the globe over the coming new year.
“When traditional AI and machine learning solutions are no longer enough, utilities operators will turn to new technologies like Cognitive AI, which is able to provide operators with a global perspective of the plant and plan to make informed decisions when considering numerous tradeoffs, goals, and constraints at the same time.”
AJ Abdallat is CEO of Beyond Limits, the leader in artificial intelligence and cognitive computing.
Our world has reached a point where society recognizes the planet is under stress, with energy and technology sectors at the forefront of this reckoning. Microsoft, in association with PwC, revealed the urgency of the challenges currently facing our planet, reporting that 91% of people don’t live in standard air quality-controlled areas, 60% of biodiversity has been lost since 1970, and greenhouse gases are at their highest levels in 3 million years.
To get ahead of these challenges, we must reduce carbon footprints. AI will play a crucial role in supporting the energy industry’s goals of achieving a more efficient, connected and sustainable future.
The Net Zero Agenda
Many entities have recently announced plans to shrink their carbon footprints to “net zero” over the next few decades, commonly with a target year between 2030 and 2050. According to myclimate, “Net zero emission means that all man-made greenhouse gas emissions must be removed from the atmosphere through reduction measures, thus reducing the Earth’s net climate balance, after removal via natural and artificial sink, to zero. This way humankind would be carbon neutral and global temperature would stabilize.”
Strategies around this initiative have been paramount to the energy industry’s present and future operational plans. Some major oil and gas companies have even revealed ambitious blueprints, budgets and organizational transitions to do their part in reducing emissions and turning the climate change tide.
One example of a company making strides toward this aim is bp. The company aims to become net-zero by 2050 and hopes to help the rest of the world achieve that goal, too. The major energy company also highlighted near-term goals. According to MarketScreener, “By the end of the decade, it aims to have developed around 50 gigawatts of net renewable generating capacity — a 20-fold increase on what it has previously developed, increased annual low carbon investment 10-fold to around $5 billion, and cut oil and gas production by 40%.”
The company says all of this is aimed at “performing while transforming — operating safely and reliably as well as delivering on the promises we’ve made to shareholders.” Shell, Spain’s Repsol, and Norway’s Equinor have also set their net zero targets for 2050.
Advanced AI At The Ready
As the CEO of an AI company making software for energy, I understand the importance of a worldwide movement toward a lower-carbon future. Our company plans to continue supporting client needs while tackling the cleaner energy challenge together, playing a part in the complex global challenge of transitioning to a future of less carbon while still meeting the energy needs facing our world today.
AI will play a key role in helping companies and industries achieve net zero ambitions. Accomplishing a low carbon future will require more efficient operations that help increase productivity and reduce waste. AI for energy can work toward this with technology designed to optimize efficiency, yielding more economical utilization of resources to accelerate renewable, decarbonization and carbon-negative initiatives across the globe.
Industrial-Strength AI: Modern Solutions For Global Evolution
Digitizing downstream operations has shown promising results, with plant efficiency increasing by 8%-12%. Amplifying the potential for AI to make its mark on this movement means leveraging the most advanced forms of technology. Explainable, cognitive AI systems are already in place to meet that need. These systems can ingest and recognize sizeable quantities of data that exist in large industrial facilities like refineries and leverage codified human expertise to make recommendations at company-wide levels.
Examples can be found in solutions supporting downstream operations for facilities today like bp’s Whiting refinery project. “As the largest refinery within bp, we need to embrace the dual challenge — a world that is demanding lower-carbon energy, while at the same time demanding more energy overall,” refinery manager Don Porter said. “We are positioning ourselves to thrive in this evolving context.”
A blend of knowledge-based reasoning and digitization is designed to help decision-makers detect unforeseen prospects and make tough choices. The subsequent improvements in processes could lead to streamlined operational capacity where facilities function more efficiently and reduce waste. Improved communication, strengthened collaboration, increased fuel savings and decreased waste means companies may also increase the potential to grow revenue, particularly in high-value industries.
Cognitive AI is excellent at understanding complicated problems where industrial practices are comprised of a perpetual influx of data like that found in energy, utilities and industrial IoT — where processes require constant, transparent oversight. Cognitive AI delivers this clarity through human-readable audit trails, allowing an entire organization to track how they may optimize processes to extract more value and decrease waste, ultimately lowering carbon footprints and moving closer to net zero.
A Realistic Outlook
Transitioning the energy industry from primarily oil and gas to more renewable sources won’t happen overnight. Global communities will require energy during this phase of fluctuation. Solutions that make processes more efficient and decrease waste will be essential to this transitional stage.
Humans still require legacy energy sources, alongside transportation and refinement of high-value assets. Our fossil fuel portfolio cannot disappear overnight. We should instead determine how to better manage it as we shift toward a more renewable future with less waste, greater efficiency, more productivity, and a lower carbon footprint. Solutions designed to help decrease carbon intensity per barrel of oil can help lead us toward a more carbon-friendly outlook while ensuring the energy needs of the world are met as we move forward into a net zero-focused future.
For all industries eager to follow this path forward toward embracing carbon-reducing AI solutions, here are two tips for choosing a solution provider:
+Partner with an industrial-grade AI software company with tech that has capabilities to provide holistic, organization-wide outlooks and strategies.
+Select an artificial intelligence company that has an AI-readiness program to seamlessly transition entire enterprises into their digitization strategy right from the get-go.
AI companies with both of those elements could be key for anyone taking steps to realize net zero objectives.
Check out the article on Forbes Technology Council here.