26 FEBRUARY 2021
AI has become crucial to high-value industries, with many organizations creating entirely new departments focused on driving innovation forward and interweaving emerging technology into numerous aspects of their operations and business strategy. The AI jobs market has grown and expanded to accommodate this digital transformation, making artificial intelligence one of the most popular career fields in the world.
Beyond Limits is at the forefront of this global job market shift, hiring top-tier data scientists, AI engineers, and machine learning scientists to help better position large-scale industries for the future.
Thinking about taking the leap into the AI job market? Check out this video to learn why you should be pursuing one of the many AI-related career opportunities across numerous industries.







18 February 2021
Los Angeles, CA
Artificial intelligence isn’t just some vague, figurative ideation contributing to movie plots anymore. It is a very real, tangible technological necessity for the majority of today’s most critical industries. To remain competitive, companies, industries, governments, and entire countries are realizing the need for enterprise-grade AI that can support them in their efforts to deliver to their bottom-lines and keep up with the ever-accelerating road of technological evolution.
The Challenges to Enterprise AI Adoption
Unfortunately, potholes and roadblocks can hinder the path of progress and often present themselves in the form of adoption and implementation. In the summer of 2020, Hydrocarbon Processing hosted the International Refining & Petroleum Conference Americas. On the second day of the conference, there was a panel discussion on digitalization where Joe McMullen of AVEVA Value Chain Optimization Marketing listed off a few contributing hurdles around the adoption of artificial intelligence including:
+ Technology Adoption
Due to a lack of cultural buy-in from internal personnel, the solution’s goal is often misunderstood and thus goes unused, resulting in the inability of the technology to prove its ultimate value.
+ Challenge Identification
Unrealistic expectations exist around technology having the ability to solve a problem without that problem actually being understood before attempting to implement the technology.
+ Technology Integration
The technology is hindered from proving its ultimate value when entities seeking to implement AI don’t do their due diligence in pursuing vendors that won’t disappear after supplying the technology. Issues arise when a company is forced to move forward without access to an AI software vendor that will continue to work with the company on its digital transformation journey. 
McMullen’s astute observations serve as an outline that helps us focus on some of the core issues surrounding AI implementation such as building trust in the technology, identifying a solution advanced enough to work with limited, misleading or missing data, and empowering teams to perpetuate a digital-ready, innovation-minded company culture.
The Keys to Enterprise AI Adoption
Fortunately, a majority of the challenges reported by McMullen are made trivial when the right AI solution presents itself. When tackling the issue of adoption, the leading factor comes down to picking an enterprise-grade AI company that possesses the vital keys and features necessary to facilitate implementation including:
+ Explainable AI that lives outside a black box
Explainable AI is essential for detailing recommendations in a clear manner with transparent information, evidence, uncertainty, confidence and risk, which can be understood by people and interpreted by machines. All of this boils down to the most important factor in successful artificial intelligence adoption and implementation: trust. The value of an AI systems’ functionality may be measured in terms of usability that results in increased efficiency, decreased waste, or accelerated time-to-decision. The ultimate value lies in delivering everyday decision-makers with actionable intelligence so they make faster, more accurate decisions that pique their confidence.
Keeping humans in the loop via explainable AI is a vital key to developing a symbiotic relationship, grounded in trust, with the technology and fortifying confidence in its results. Explainable, glass box artificial intelligence solutions can be found in systems that provide human-understandable, traceable, and adaptable audit trails for their recommendations. All of this clarity and transparency leads to more inherent, cultural buy-in and utilization from relevant personnel.
+ Cognitive AI – The most advanced form of the technology currently on the market
Clean data is always ideal, yet often allusive. Cognitive AI systems can both consume and organize unstructured data, analytics, and other essential information. Moreover, this advanced technological innovation can work with limited, misleading, or missing data by combining the best of conventional numeric AI approaches and advanced symbolic AI techniques to deliver reasoning and intelligence that emulates human intuition.
Cognitive AI can codify expert knowledge, expertise, experience, and best practices – then disseminate that data across every level of an entire organization. This capability is instrumental to unlock the value in seemingly un-quantifiable data. Human-inspired knowledge bases empower the system to compare recommended courses of action against best practices developed by people, enabling the system to also become smarter over time as it continues learning from new data, inputs, and influences. This facilitation of increased and streamlined access to expert information that’s readily recognized by industry professionals sustains trust in the system.
+ An AI readiness program at the ready
A digital-ready company culture must exist with an innovation-minded team that’s empowered to implement structural transitions kicked into high gear by the adoption of AI technology. It’s vital this culture places importance on data-driven decision-making instead of defaulting to legacy approaches. This is where your AI investment will either thrive or fall flat.” AJ Abdallat, Forbes
Any great enterprise-grade AI software company will come with a readiness program to help both identify the main operation problem that needs to be solved as well as support that company along on its digital transformation journey. Selecting such an AI company that sticks around to ensure a seamless transition by working on the ground directly (in tandem) with the software’s users will help ensure correct implementation of the technology. AI engineers should be training everyday decision-makers on how to properly use the solution while simultaneously learning whether the UI/UX is practical for any user’s day-to-day purposes.
Cultivating a digital attitude by diving into innovative technology and including personnel at every level, while building on their abilities and defining an AI outlook at the outset, are important aspects. Involving every stakeholder with a clear angle on success will inspire implementation efforts.
“This is a very exciting time for Beyond Limits to gain such a valuable partner as The Carnrite Group. Through Carnrite’s vast network, we hope to provide valuable guidance and increase awareness of the benefits of AI in critical sectors, including boosting operational insights, improving operating conditions, and ultimately, increase adoption of this next generation technology.”AJ Abdallat, Beyond Limits & The Carnrite Group Press Release
The Outlook for Enterprise AI Adoption
As of now AI is almost everywhere and contributing to almost everything. From energy to utilities, natural resources, healthcare, and other evolving markets, artificial intelligence solutions are spearheading the trail when it comes to companies outlining their digital transformation strategies. Adoption and implementation may seem like the most daunting challenges but partnering with the right enterprise-grade AI company is key to lighting that path forward and beyond.
12 February 2021
Los Angeles, CA


If there’s one thing we know about artificial intelligence it’s this: AI is a disruptive innovation that has the power to make the world a better place. As cliché as it sounds, decision-makers around the world are already realizing the value of AI for resolving global issues. AI has come to mean more than just a competitive advantage for companies, but an important solution providing better healthcare for those in need, improving the state of the global climate change crisis, yielding power in underserved communities, and numerous other examples.
However, uncertainty around AI implementation remains one of the biggest obstacles the world is facing when it comes to embracing these transformative technological solutions. Some regions do exhibit higher levels of AI maturity while others exhibit different priorities when it comes to AI implementation. This is where decision-makers must recognize that AI is not a one-time magic wand but part of a continual improvement process – one that can be evolved by gaining insights from those around the world who are paving pioneering roads for successful AI solutions.
AI Around the Globe
+ Europe
According to the 2020 Government AI Readiness Index from Oxford Insights, the UK, Finland, Germany, and Sweden are leading Europe’s AI market. On the global scale, however, insights from The Carnegie Endowment for International Peace suggest that Europe as a whole still has much to accomplish compared to the United States, China, and Israel. Despite their position compared to their global counterparts, with their extensive resources in education and research as well as the European Commission’s efforts to elevate AI Research and Design (R&D) investment, Europe is set to focus coordinated efforts toward addressing the digital skills gap and building a framework for increasing trust in AI adoption.
+ North Africa & Middle East
On a different note, The United Arab Emirates (UAE) and Israel are leading the charge in the Middle East, with the UAE specifically demonstrating massive potential in terms of AI readiness. This is, in large part, thanks to a proactive government that has prioritized AI implementation through the UAE Strategy for AI and the National Program for Artificial Intelligence created in 2017.
Despite progress made in local AI applications like natural language processing and machine learning-based systems, many countries in the Middle East and North Africa region face challenges due to poor datasets and political instability in some areas. Inhibitors to AI adoption range from uncertainty around the economic implications of AI applications to security and ethical concerns related to representation. Countries in this region must focus on implementing proper policy, data, and knowledge infrastructures to better set the foundation for AI development.
+ Asia Pacific
Singapore, South Korea, Japan, and China are the four countries that top the scale for AI readiness in this region. According to a Deloitte study on how countries are pursuing AI, China’s government has stated its desire to be the world’s leader in AI innovation by 2030, demonstrating its commitment to competitive digital innovation. They have poured billions worth of US dollars toward AI applications and are leading the world in annual government R&D spending at around $59 billion. AI governance is a top priority for both Singapore and China alike, with both countries going as far as establishing advisory councils to determine how to best implement responsible AI tactics, mitigate concerns, and build consumer trust.
On the other hand, South Korea and Japan are equipped with their own advantages including data availability and representativeness. With a staggering percentage of their population being internet users, not to mention widespread 5G deployment in South Korea, these two countries are poised to lead innovations in areas like autonomous vehicles, smart manufacturing, and gaming.
+ North America
In this region, both the United States and Canada are considered the top innovators – with the United States leading the world in AI readiness. Both regions have strong strategic methods for implementing AI and both have the means to do so considering the advanced technology and data infrastructure they possess. The US government has led many initiatives to implement national standards and priorities for AI development as well as regulations for how to manage the technology. Canada was also one of the first countries to release a national approach for AI when it launched the Pan-Canadian Artificial Intelligence Strategy with CIFAR in 2017.
Overall, the US and Canada foster an incredible amount of dedication towards technological advancement demonstrated through increased R&D spending and international cooperation in AI research. However, even for these unwaveringly dedicated tech giants, some challenges have yet to be faced. Canada will need to address its impeding concerns for making wrong AI-backed decisions, while the US must continue to address the pressing skill-gap and, more importantly, data security concerns in light of the Covid-19 health crisis.

How Cognitive AI Can Help
Artificial intelligence is a big part of an evolving technological improvement process and innovators are progressing to find new ways to accelerate its use in the world’s most high-stake industries like energy and healthcare. As such, global decision-makers must understand the impact that an AI system can bring to global value chains in the following industries to derive the most ROI from its implementation.
+ Energy & Utilities
The global energy value chain stands to gain a lot from employing Cognitive AI, as can be seen with Beyond Limits’ contract order through Xcell to provide the world’s first cognitive power plant in West Africa. As many as 8.7 million people in this region are currently without access to electricity, with spotty service throughout the day at best. Cognitive AI can address this pressing issue by enabling inexperienced power plant operators to make strategic decisions based on recommendations from a cognitive system that possesses and makes accessible essential knowledge.
+ Healthcare
AI has been a driving force in this industry. In fact, it has played a pivotal role in helping to address the Covid-19 pandemic. A great example of this is shown through Beyond Limits’ partnership with medical professionals to tackle some issues created by the global pandemic by developing a dynamic predictive model that allows for more accurate prognostic analysis, resource allocation, and decision making. AI can also deliver advanced solutions for patient monitoring to allow for real-time analysis of their vitals. Not to mention, it can also support in mitigating the risk of inadequate healthcare in developing countries that lack basic resources, ultimately resulting in a higher standard of care.
+ Manufacturing & Industrial Internet of Things (IIoT)
AI and IIoT are key components to achieving the coveted smart factory for manufacturers as well as logistics and supply chain managers alike. In fact, over 50% of respondents in an MHI Annual Industry Report declare artificial intelligence and IIoT as potentially disruptive technologies with the ability to give companies a significant competitive advantage. Organizations in the sector can leverage cyber-physical systems and AI to reduce hazardous manual labor tasks, utilize predictive maintenance analytics, and increase supply chain automation as well as optimize facility integrations.
+ Financial Services & Banking
Quality and risk assessment are some of the biggest benefits of implementing AI in financing and banking. Specifically, AI can increase visibility for bankers and credit lenders through AI algorithms to make underwriting decisions with more accuracy as well as enhance monitoring capabilities for quality and risk in credit portfolios. Through machine learning capabilities, financial institutions are better able to create more accurate predictions by pinpointing trends and analyzing data in greater depth.
+ Smart City Projects
By leveraging current technologies and policies, cities have the potential to reduce their carbon emissions by 90% by 2050. Specifically, smart city projects such as those bp are undertaking in Houston and Aberdeen have the potential to make serious headway toward mitigating carbon emissions through decarbonized transport, low carbon energy and gas, and smart buildings. As a result, this paves the way for a higher quality of life via optimized costs and a cleaner industry.
Overcoming Barriers to AI Adoption
As is the case when pursuing new and uncharted opportunities, challenges will inevitably follow. According to insights from the aforementioned Deloitte study, we can identify a few major factors that inhibit many countries from fully embracing AI adoption:
+ Maturity- how advanced a country’s AI infrastructure is, as well as the ability to achieve and scale impact from AI implementation
+ Urgency- how rapidly countries are adopting and implementing AI strategies
+ Overall challenges- technical skills gap, cybersecurity vulnerabilities, distrust, etc.
Only 21% of overall global respondents from Deloitte’s study declared they were “seasoned” AI early adopters with the United States exhibiting the highest level of AI maturity. Additionally, 43% declared themselves as “skilled” while 36% stated they were “starters,” not yet having developed proficiency in AI strategies or implementation.
Despite varying levels of maturity, a significant percentage of respondents (63%) state that AI is critical to their company’s success and are seeking ways to advance their maturity level. Additionally, many global respondents are more likely to use AI to create a competitive advantage rather than to catch up with fellow key players, further demonstrating their intent to instigate rapid change on their AI journeys.
It’s a fact that global companies recognize the value of AI adoption. The AI infrastructure market is even expected to see a compound annual growth rate of 21% from 2021 through 2026 according to Mordor Intelligence. However, companies are still met with challenges that inhibit this adoption process.
The technical skills gap is one such challenge that many countries face. In a SnapLogic survey conducted with 300 IT leaders across the US and UK, a lack of skilled talent was cited as the number one barrier to progressing their AI initiatives. Others like Germany are concerned with AI ethics and how it can manipulate information or create falsehoods. The US and China, in particular, are concerned with cybersecurity vulnerabilities and how to combat these risks.
Artificial intelligence is constantly evolving and adapting to humans’ most critical needs in the world’s most heavyweight industries. Because of the weight and complexity in these industries, global decision-makers need an AI technology they can trust if they wish to overcome their hesitancy around adoption. Such trust is more easily built through an AI solution they can actually understand. This is where Cognitive AI comes into play. By implementing explainable systems that can emulate human reasoning to understand and resolve problems, decision-makers are better able to derive meaning from these solutions and make pivotal decisions more strategically.
AI proliferation across the globe has never been more prominent – with countries demonstrating outstanding capabilities in terms of data governance, technical advantages, investment, and building the necessary infrastructure to support AI solutions. As AI continues to grow more advanced and the application of solutions more extensive, the more that global decision-makers must partner with leading AI innovators to overcome challenges and pursue better opportunities.
As one of many pioneers in AI innovation, we’ve come to realize the need for AI and collaborative partnerships to more adequately sustain our current industries. As part of our ongoing effort to develop these partnerships, we’ve expanded our reach across the globe into APAC and MEA regions to deliver AI solutions where they’re needed most. By taking a collaborative approach to AI innovation, and working with other pioneers in the space, global decision-makers will be better prepared to incorporate these advanced solutions into their business operations and ultimately drive impact toward a transformative future.
10 February 2021
Los Angeles, CA


Accelerating Digitization in Downstream Oil & Gas with AI
In the past year, COVID-19 has jumpstarted digital transformation and AI adoption in the Oil & Gas industry, most notably in the downstream sector, where AI-led efficiency has proven critical to combat low-price markets.
This webinar, presented by Beyond Limits digital transformation experts, explains how operational efficiency is achieved in refining using AI and how explainable AI technologies are allowing operators to build trust in these cutting-edge systems.
Check out this video to learn:
26 January 2021
Los Angeles, CA


Data Den is a thought-leadership alcove within the world of Beyond Limits where we provide an opportunity to dive into the minds of our gifted data scientists to get a better understanding of their domain. Keep reading to catch a glimpse of their essential expertise; without it, artificial intelligence wouldn’t be possible.
Let’s talk a little about a project you worked on recently. What were the biggest challenges you faced as a data scientist working on that project?
I’ve been working on a well management project for an oil and gas supermajor for a while now that involves the kind of tech that “technical people” get really excited about. Tech-centric professionals get excited about the technical challenges at the interface of science and machine learning. Though, the real challenges emerge when you try to put all the relevant pieces together to create a coherent system that intuitively executes a complicated workflow.
All data scientists have their own specific, individual tasks they’re working on; it can become really easy to fall prey to the minute details of any one of those tasks. Though, at the end of the day, everyone is creating a lot of moving pieces that need to be able to work together. It’s always fun to dig into the tech, just don’t get bogged down in it because the process isn’t just about data science. The ability to carry out effective evaluation is also about working with databases, the software team, and perhaps internet-based API’s (if the project calls for it). There are a lot of moving pieces that all need to be in sync and talking with each other in order to truly be something.
Steering into the topic of the data itself. How do you handle missing data? What techniques do you recommend? Is there a specific project, as an example, that comes to mind?
There are a lot of different methods for dealing with missing data that range from very simplistic statistical and interpolation approaches to advanced machine learning neural network techniques. With machine learning, you can utilize neural networks or autoencoders to essentially learn behavior from a group and infill those missing data sets as much as possible. You can also make use of the other analog data to which you do have access in order to try and predict what might make up the missing parts. Those are some fairly commonly implemented techniques – but everything depends on each particular application and determining the appropriate method to successfully carry out a particular project.
One thing that’s different about the projects I’ve worked on (while we do use those methods a lot) is that, at Beyond Limits, we tend to handle bulk discrepancies using knowledge-based data. So, in the attempt to supplement missing data, we tease out the models for certain behaviors and feed those to a knowledge base that then interprets them. If I don’t have a direct measurement because I don’t have enough measurement locations in a system, or I don’t know the system-state to make a model, this comes in very handy. For example, an expert with twenty years of experience can tell me – based on the signals they do have – exactly what is happening underneath, which we then embed into a knowledge base that essentially interprets other signals in the context of that knowledge to provide a more meaningful interpretation.
Can you talk a little about codifying domain expert knowledge into an AI system?
There are several different avenues we have taken in the past to go about this. Our most commonly traversed path would probably be the same we took to create one of our geological modeling solutions. Essentially, in most situations, we gather an expert’s (or a set of experts’) expertise, along with common industry knowledge captured from research papers, textbooks, etc. If the gathered information is in a nice clean state, we are able to more easily ingest it. However, that is a fairly rare occurrence. In most cases, we want to understand the problem and how existing knowledge relates to that problem. Once we can grasp that understanding we can codify the information into our proprietary IP format.
For example, with the aforementioned solution, the idea is to have the ability to model a geological environment based on a number of measurements. We would utilize high resolution one-dimensional measurements of the asset in question along with large scale low resolution, three-dimensional seismic measurements that portray the inside of the earth. Then we correlate these measurements to some hard data samples that may exist pointwise throughout some three-dimensional space. However, we may not have sufficient data to understand the kind of system we are dealing with or to determine what the actual environment looks like.
To complete the analysis we can supplement this data using scientific knowledge, like a particular physical process that’s taken place over a long period of time – we can look at systems and know that those processes occurred in a certain order, as well as their relationship to one another. How we interpret such indirect measurements is different based on the type of system we are looking at but the principles of how we incorporate knowledge to supplement the interpretation remain the same. We can build such knowledge and relationships into our knowledge base with interpretations of those indirect measurements that are consistent with the actual physical processes and theories about such a system. So, what we are essentially left with is the ability to build in the true physical relationships of a geological system while using machine learning to automatically understand and build a 3D representation of that system. We’re not just using neural networks to train; we’re actually using the expert knowledge and common principles of science to do so.
Dr. Michael Krause is Senior Manager of AI Solutions at Beyond Limits, a pioneering artificial intelligence engineering company creating advanced software solutions that go beyond conventional AI. Michael specializes in subsurface machine learning with experience spanning major initiatives at supermajors to next-generation digital transformations at small independents. Prior to joining Beyond Limits, Michael was Director of Analytics at Tiandi Energy in Beijing, China, and later at Energective in Houston, Texas. Michael holds a Ph.D. in Energy Resources Engineering from Stanford University.
22 December 2020
Los Angeles, CA
2020 has been a year of change and growth for Beyond Limits as we navigated the COVID-19 pandemic and came together to find ways to adapt to the new world around us. With so many in our community impacted by current events, our Corporate Social Responsibility (CSR) team worked harder than ever to enact positive change with programs that had meaningful impacts on relevant causes.
We are honored to recognize our employees and the wonderful organizations we’ve partnered with to support initiatives ranging from philanthropic causes and community support to environmental responsibility.
People Assisting the Homeless (PATH) is an organization working to end homelessness for individuals, families, and communities throughout California by building affordable housing and providing support services. PATH Los Angeles was founded to provide a variety of services including employment, outreach, homelessness prevention, housing navigation, interim housing, rapid rehousing, and permanent supportive housing. An outlet to connect with PATH can be found here.
“Earlier during the year, we partnered with PATH for the second time and assembled 90 care kits,” said CSR member Tim Guerrero, Beyond Limits Senior Accountant. “These care kits – which included travel-sized hygiene items and non-perishable snacks – enable PATH to build relationships with our neighbors experiencing homelessness, which may help lead them to find affordable housing and/or land a job opportunity. With record highs of homelessness in our Greater LA community, it was really incredible to see our Beyond Limits team support this PATH initiative. It takes one act of kindness and generosity to make a lasting and positive impact on someone’s life, and we accomplished that together.”
Another important initiative involved Adventist Health Glendale, an integral part of the community where Beyond Limits is headquartered. Glendale is also the city many of our employees call home. To say the least, Adventist Health’s frontline workers have worked tirelessly this year to provide essential care for the community. We recently had the opportunity to partner with Tavern on Brand, a favorite local restaurant of our employees, to show our support during stay-at-home measures and provide meals to our local Adventist Health frontline workers.
“Our CSR team knew it was more important than ever to give back to the community that always provides us with so much,” said CSR member Evan Jennings, Beyond Limits HR Business Partner. “We were so excited to plan an event that allowed us to not only give thanks to our local health care first responders but also support one of our favorite local restaurants.”
The CSR team also made moves this holiday season to work with Hillsides, a premier provider dedicated to healing children and young adults, strengthening families, and transforming Pasadena, Glendale, and Burbank communities through quality comprehensive services and advocacy. This year Beyond Limits took part in the Hillsides adopt-a-family program which was established to provide a brighter holiday and bring cheer during the season to families experiencing financial hardships. An outlet to connect with Hillsides can be found here.
“The holidays can be a difficult time for many families, let alone during this pandemic,” said CSR member Stephanie Datu, Beyond Limits Technical Project Manager. “We have all been so fortunate to be safe at home and healthy this year, which is why it was important to give back to our neighbors who haven’t been as lucky. This year, with the support of company leadership and employee volunteers, we were able to give at least two families everything on their holiday wish lists! It’s been so uplifting to work with the CSR Committee and make a difference in our community!”
As we move into 2021, Beyond Limits’ CSR Committee looks forward to continuing to uphold its mission to promote awareness and accountability of philanthropic and environmental responsibility within the company, community, and beyond.
17 December 2020
Los Angeles, CA


A lot of progress has been made over the years with the advancement of artificial intelligence technology in real-world applications. With the rise of this technology solving complex problems, we are also seeing industries adopt, adapt, and evolve through automation and digital transformation. But in order for humans to make better decisions, we need to be able to work with technology to gain actionable insights, solve problems, and drive value.
Conventional machine learning and deep learning have evolved, but in high-risk industries like healthcare, energy, and finance, there is a need for a more intelligent, more explainable AI. The core foundations of conventional AI are found in machine learning, deep learning, and neural networks. These approaches, on their own, give us the “what” but not the “why” humans need in order to gain more actionable insights for making better decisions. Cognitive AI bridges the gap between solely conventional and symbolic AI techniques to deliver a more intelligent solution known as Cognitive AI. This advanced technology is designed to mimic human cognition by incorporating conventional AI, machine learning, deep learning, and the cognitive capabilities of symbolic AI.
What is Cognitive AI and Why is it Important?
Cognitive AI is a hybrid of AI technologies like conventional numeric AI and symbolic AI. Cognitive computing technology is important because it combines structured data with natural language processing to derive meaning from human languages. By combining these two types of AI technologies, we are better able to identify complex problems before they happen and recommend solutions in high-risk industries such as manufacturing, healthcare, energy, and natural resource operations.
The ability to derive meaning from Cognitive AI is important because it empowers humans to interact in real-time and makes their jobs more functional by improving communications across multiple team silos, reducing risks, and evolving operations to become more proactive.
The Role of Explainable AI in Industrial Process Automation
For AI systems to be trusted by humans during the critical decision-making process in high-risk situations they need to understand the “why” – not just the “what.” Cognitive AI goes beyond simply providing system alerts; the technology also provides operators with drilled-down reasoning traces through audit trails that detail evidence, probability, and risk. This capability turns on the light in an otherwise black box of information. By taking out the mystery of solely conventional methods, explainable AI provides stakeholders at every level the critical details they need to trust their artificial intelligence solutions.
Cognitive AI is Smarter Artificial Intelligence
Cognitive AI technology moves beyond conventional AI toward a more human-like ability to perceive, understand, correlate, learn, teach, reason, and solve problems faster than other AI solutions. Cognitive systems utilize a unique hybrid procedure, combining the best of conventional numeric AI approaches and advanced symbolic AI techniques to deliver reasoning and intelligence that emulates human intuition.
Pioneering AI Technology with an Advanced Approach
Using a hybrid approach to incorporate numeric AI foundations and symbolic AI enables systems to empower operators, who work alongside the technology, to make faster and more confident decisions that boost their company’s bottom line. Being proactive and pivoting quickly to avoid disruption ensures business continuity and creates cost savings by minimizing system failures.
Cognitive AI solutions delivering transparent audit trails that explain the reasoning behind their recommendations and show all evidence, risk, confidence, and uncertainty are designed to be understood by people and interpretable by machines. These advanced systems are built to think like industry experts and produce operational efficiencies at scale, resulting in new revenue and increased profits.
15 December 2020
Los Angeles, CA
Author: Jesus Bouzada, Beyond Limits Product Manager – Refinery


This panel recap and review was contributed by Jesus Bouzada, Beyond Limits Product Manager, Refinery, from his own expertise, perspective, and point-of-view.


Last September, Hydrocarbon Processing hosted the IRPC Americas conference. On the second day of the conference, there was a panel discussion on digitalization. The purpose of this review is to assess the state of digitalization in the energy industry, covering the panelists’ observations and my own views, as Beyond Limits’ Refinery Product Manager, on some of the topics. Throughout the review, you will learn how Beyond Limits can help you in your digitalization journey.

Lee Nichols, Hydrocarbon Processing Editor-in-Chief, facilitated the panel. Panelists included Ron Beck, Aspen Technology Market Strategy Director, Joe McMullen, AVEVA Value Chain Optimization Marketing, and Marty Gonzalez, bp Discipline Leader – Intelligent Operations. I have the pleasure of working with Marty on regular basis as part of the implementation of Beyond Limits technology in bp. I regard Marty as a true innovation leader in the energy industry. So, I am really pleased to write about this topic.


Why Digitalization

First and foremost, let us agree on what digitalization means in this context. Digitalization is a loaded word that has been used with different meanings. Gartner describes it well for the purpose of this panel: “Digitalization is the use of digital technologies to change a business model and provide new revenue and value-producing opportunities.”

During the panel, the impact that the current environment is having on the industry, with COVID-19 and its consequences on the economy, was discussed at different times. Joe also warned of other challenges the industry will undoubtedly face going forward including another pandemic, regulations, disruptive innovation, and renewable energies.

Joe quoted Leon Megginson, a 20th-century economist. Mr. Megginson wrote that “It’s not the strongest of the species that survives but the most adaptable.” Panelists agreed that the ability to be agile will set apart the companies that survive.

In Joe’s opinion, improving collaboration leads to agility. He said that what’s important to a successful digital transformation is understanding where your silos are and where you can improve collaboration. I agree that collaboration is critical, and I would add transparency as another important factor. However, I believe that agile is a mindset (based on agile principles). It is a different way to do business, so organizations that want to become agile need to go through a culture shift.

Whether we want it or not, things are changing. The key to agility is to embrace change. This takes us back to the definition of digitalization: “… the use of digital technologies to change… “ Digitalization is not about technology, but about how technology enables change in the business. Digitalization is a transformational tool for agile organizations, especially during a rapidly changing, ambiguous, turbulent environment like the one we live in today.

Tech is part of our everyday lives, and the new generations coming into the workforce have been raised surrounded by technologies. Embracing technology becomes not only a matter of running a more profitable business, but it becomes a matter of tapping into the talent pool of the new generations and, in essence, staying in business.


Challenges to Digitalization

In other disciplines such as software development, which I know very well, or even car manufacturing, embracing change is in their DNA.

As an example, Toyota paved the way for the car manufacturing industry with its Toyota Way mindset. Other car manufacturers followed suit and the Lean movement was born. Lean heavily influenced the Agile methodologies of today that are widely spread when it comes to software development.

Many other industries, including Oil and Gas, have tried to embrace the Lean way of thinking. However, the way of thinking “if ain’t broke, don’t fix it” is ingrained in more risk-averse industries like Oil and Gas. Nevertheless, things are changing. The recent crises, first the 2015 downturn, and now COVID-19, have served as a wake-up call. Crises can also be seen as opportunities.


10 December 2020
Los Angeles, CA


In addition to pioneering advanced artificial intelligence solutions, Beyond Limits also strives to be a leader in developing the next generation of talent in the field of AI. Each year, we recruit students to the Beyonders internship program – offering the chance to gain insight, knowledge, and experience in an immersive two-month program. But, what happens when an internship is suddenly forced to take place under remote conditions, and in-office aspects of an interactive program are eliminated?

Beyond Limits was ready to face these unexpected circumstances in 2020. 19 students joined us this past summer to experience a brand new virtual Beyonders internship program that fostered opportunities for students across the globe to work in various business categories, from Accounting to Software Engineering.

While we didn’t have the opportunity to meet our Beyonders in-person, we aimed to make them feel like they were genuinely a part of the company through a variety of initiatives, workshops, and many more virtual events. From professional development Lunch & Learns with CEO AJ Abdallat to a weekly Game Lunch. Beyonders had unique avenues to fully integrate into Beyond Limits’ culture.

Take a peek into the highlights of this year’s exceptional Beyonders program:

Meet some of our Beyonders in our Spotlight Series
Curious about how we made our internship program virtual? Learn more in this blog post.
Interested in joining our next Beyonders Internship program? Check out our open positions here.
9 December 2020
Los Angeles, CA
The Beyond Limits Cognitive Formulation Advisor is an AI-driven, web-based software solution for developing and optimizing lubricant blends. The advisor uses historical blend data and applies advanced AI methods with encoded domain knowledge to provide a fast, reliable, and unified process across the entire organization. This technology has been adopted by major energy companies who are already experiencing significant material and program cost reduction and faster time-to-market.
Check out this video to see how the Cognitive Formulation Advisor can accelerate product development, increase efficiency, and improve profitability.
8 December 2020
Los Angeles, CA
The Beyond Limits Refinery Operations Advisor is a web-based software system that empowers refinery operations teams to plan, operate and improve process manufacturing performance by improving how the workforce makes complex decisions.
The system is designed to “think” like an engineer, and is configured from the ground up by site teams, providing expert guidance and resolving problems across systems, including process units and sub-systems. The advisor goes beyond conventional asset-only focused approaches to ensure system-wide processes and objectives are met or exceeded.
Check out this video to see how the Refinery Operations Advisor can improve operating consistency across plan cycles & shifts, up-skill operations teams in real-time, and increase efficiency.

The Process Manufacturing industry contends with critical challenges that can impede financial performance, often facing market disruptions and inadequate factory operations due to suboptimal conditions, inefficient decision-making, and processes that are often carried out in silos.


The path toward driving value in process manufacturing can be discovered with Beyond Limits AI through: 


Check out this video to see how advanced artificial intelligence solutions can help manage operations, increasing access to valuable data, holistically optimizing processes, enhancing decision-making, and boosting revenue.



Click here to learn more on digitalizing business models in the process manufacturing industry with Beyond Limits AI.