14 October 2020
Author: STEPHEN OSTROWSKI
Originally Posted: 7 October 2020 for Built In LA

 

Built In LA recently featured Beyond Limits’ own Anupama Gunupudi in a recent insider spotlight talking about her strategy as the Senior Manager of Engineering Resource Planning. The article highlights Anupama’s focus on how important team building, talent recognition, and open cross-functional communication are to efficient project planning and effective resource allocation.

 

“I aim to drive project execution efficiently and productively for every software team that I have,” Gunupudi said. “That means understanding each team, developing their skills and talents to build them up, and ensuring that they’re successful in their role and career.”

 

Read the rest of Built In LA’s spotlight here.

 

 

29 September 2020
Los Angeles, CA

 

Does the evolution of creativity rely on support from Artificial Intelligence? Beyond Limits CEO, AJ Abdallat shares his take in a recent feature from Forbes in their piece, 15 Amazing Technologies that are Contributing to the Greater Good. AJ highlights the unique benefits of AI during this era of digital transformation and its potential for major impacts on future growth and technological evolution.
 
AI is going to create so many opportunities because it can magnify innate human talents and creativity. Look at what has happened over the last 20 years in terms of digital transformation in social networking alone: There are now thousands of social networking jobs that simply didn’t exist before. AI is going to allow humans to go after the really complex and challenging problems while achieving a higher level of creativity.”
 
 

Check out the other 14 featured technologies here.

 
 
18 September 2020
Los Angeles, CA
 
In response to a recent McKinsey & Company Article
“Reinventing upstream oil and gas operations after the COVID-19 crisis”
 
 
This year has thrust the energy industry into a complicated corner. While all industries, businesses, and companies are facing new struggles, the crisis created by this pandemic has hit oil and gas especially hard. This is the subject matter of a recent article published by McKinsey & Company in which they discuss the many supply challenges now being faced along with how “the COVID-19 pandemic has cut global demand sharply.” The article continues with a narrative centered on the future of upstream and what the industry will need to adjust in order to recover and move forward into a changing world, post Covid-19.
 
 
Beyond Limits’ key takeaways and central boiling points from the article:
 
+ There exists a critical need for advanced digitalization solutions in upstream.
+ The oil and gas industry must prioritize exploration while moving their assets from an Improve-centric approach to more of a Promote-focused strategy.
+ The key to successfully carrying out a transition is to reduce the break-even price per barrel for specific classes of assets.
 
For clarification purposes, this article describes the aforementioned assets as such:
 
+ Promote: “These are assets with low break-even prices and high potential to increase reserves. Operators will want to concentrate on developing the field, changing the asset footprint, and finding more low-cost reserves in the same basin.”
+ Improve: “This can describe two kinds of assets. The first has high break-even prices and good potential in terms of reserves. The other has low break-even prices but low potential in terms of reserves. For this group, the priorities are to improve operational efficiency and optimize production.”
 
 
Evolution in Upstream
 
The path forward for the evolution of upstream can be found in optimization and digitalization solutions that deliver greater visibility across an organization and its assets. The industry requires solutions that provide stakeholders with a more complete viewpoint from the big picture down to the smallest detail to best optimize entire operations.
 
Exhibit 4 within the McKinsey article seeks to provide a management roadmap in list form that describes what companies could do, “To reduce costs, enhance development opportunities, and reduce the carbon intensity of assets.” Two items listed in this exhibit focus on the need for data-driven production optimization to apply advanced analytics for improved maintenance purposes and more effective well and reservoir management.
 
 
 
 
A Solution in Revolutionary AI
 
Beyond Limits is already making progress in this area with a lot of experience in the oil and gas industry, offering a variety of solutions that support predictive maintenance efforts alongside asset, reservoir, and well management initiatives. Other significant proposals listed within Exhibit 4 include rationalizing/centralizing activities, simplifying workflows, and transitioning to a more agile environment.
 
All of these objectives resonate with Beyond Limits. Advanced Cognitive AI features a comprehensive and complete approach to artificial intelligence – providing a solution that has the ability to focus on a global view of large and complex operations. Cognitive AI provides optimized recommendations, driven by data and expert knowledge while still keeping humans in the loop to make decisions; explainable solutions that are managed by the oil and gas executives, managers, engineers, and operators they support.
 
Beyond Limits Cognitive AI appears an ideal match for helping upstream achieve the ambitions laid out by this McKinsey article and come out of the crisis more efficient than ever. This advanced form of artificial intelligence is already providing stakeholders with a holistic view over assets, from the big picture down to the smallest detail, ultimately elevating entire operations for the energy sector and several other high-value industries currently facing tough transitional periods.
 
 
 
17 SEPTEMBER 2020
LOS ANGELES, CA
Author: AJ Abdallat, Beyond Limits CEO 
Originally Posted on Health IT Outcomes
 
COVID-19 has ushered in a period of struggle and uncertainty for people, businesses, and industries everywhere – but it’s also forced them to seek and embrace innovative new tools and solutions that can help through the pandemic and beyond.
 
For healthcare, it’s resulted in the increased adoption and appreciation of artificial intelligence (AI) technologies.
In many instances, lack of historical data and fragmented data sources along with rapidly changing and unexpected scenarios have made it difficult to establish reliable and timely prognoses for patients, determine the most appropriate treatment methods, maintain accurate visibility across operations, and manage the pandemic’s overall spread. Fortunately, some recent AI technologies have been designed to help providers overcome many of these problems.
 
Ai: Revolutionizing Healthcare’s Battle Against COVID-19
 
Trustworthy AI that implements human-like reasoning and applies proven medical data, established lab work, and expert human knowledge is helping to drive the most dynamic advancements within the healthcare tech industry.
As described in a 2017 Journal of Physics paper by AI researcher Jagreet Kaur and physics professor Dr. Kulwinder Singh Mann, “AI in healthcare is needed to bring real, actionable insights and individualized insights in real time for patients and doctors to support treatment decisions.” The paper goes on to emphasize “…the importance of applying AI-based predictive and prescriptive analytics techniques in the health sector. The system will be able to extract useful knowledge that helps in decision making and medical monitoring in real time through an intelligent process analysis and Big Data processing.”
 
The benefits of AI-powered predictive modeling tools have been increasingly evident throughout the pandemic. A few notable examples include Penn Medicine’s COVID-19 capacity planning tool, CHIME, Washington State’s predictive dashboard, another COVID-19 risk assessment tool, and our own Beyond Limits dynamic predictive model, which is based on the SIR model in predicting the progression of pandemics.
 
These forecasting models, created in partnership with renowned medical professionals working directly in the fight against COVID-19, analyze the impact of social mobility on infection and hospitalization rates to better inform hospitals and policymakers in their efforts to combat the pandemic. They can estimate resource allocation supply and demand, enabling medical facilities to better prepare for personal protective equipment (PPE) needs by analyzing the percentage of patients that may need ventilators and extracorporeal membrane oxygenation (ECMO) in the ICU and dialysis units.
 
These models also can factor in impacts from social distancing modifications to stay-at-home regulations through cell phone mobility data, and are designed to aid relevant leaders in calculating the effects of viruses on individuals, medical facilities, and regional recovery strategies while supporting planners in forming procedural tactics for counties, states, and nations.
 
Developing predictive models in the war against contagious diseases is challenging. The likelihood of determining outbreak occurrences, alongside unfolding infection case numbers and deaths, are multidimensional problems with high variability. The most valuable models are designed to operate with several data sources and categories simultaneously.
The data that goes into such models is heterogeneous and highly dimensional by nature, while vast volumes of relevant data are continuously being collected by various parties. Therefore, the ability to integrate a variety of sources of time-series and dynamic spatial data into models with learning capabilities – which get smarter over time – is critical for more accurate decision making.
 
To effectively utilize all this data and create dynamic models with learning capabilities that function in near real-time, most conventional data processing, classification, pattern recognition, modeling, and forecasting tasks must be automated and streamlined.
 
In addition to predictive forecasting models, other examples of AI helping in the battle against COVID-19 include chatbots and telehealth initiatives that use conversational AI, vaccine discovery tools, and medical insurance solutions that optimize claims management, fulfillment, and billing.
 
Keys To AI Acceptance, Adoption & Implementation
 
Two of the biggest challenges facing this era in healthcare are the acceptance of AI and the proper implementation of the technology.
 
A 2019 Future Healthcare Journal article by Thomas Davenport and Ravi Kalakota sets out to discuss “…both the potential that AI offers to automate aspects of care and some of the barriers to the rapid implementation of AI in healthcare.” The article concludes by stating, “It also seems increasingly clear that AI systems will not replace human clinicians on a large scale, but rather will augment their efforts to care for patients. Over time, human clinicians may move toward tasks and job designs that draw on uniquely human skills like empathy, persuasion, and big-picture integration. Perhaps the only healthcare providers who will lose their jobs over time may be those who refuse to work alongside artificial intelligence.”
 
AI must be implemented not in a way that discounts expert input, but rather to work in conjunction with medical experts to amplify their capabilities. This means leveraging explainable AI solutions that are both auditable and accountable, providing transparent recommendations that keep domain experts informed and in control. This is the key to trusted AI.
 
Hospitals and healthcare organizations can further support and successfully implement AI through close collaboration with the developers of the AI solution. AI engineers should be working in tandem with the healthcare leaders, professionals, and doctors who will be using the solutions. Regardless of how promising any one AI solution may seem, it won’t likely be adopted if the UI/UX is confusing or impractical for day-to-day purposes. At the same time, coordination between the developers and users helps to dispel mistrust among healthcare staff, ensuring personnel is properly trained to utilize their new tools to the fullest potential.
 
COVID-19 has forced rapid disruption and evolution in virtually every major industry around the globe. Healthcare in particular is bearing the brunt of this change, but the introduction of new AI models, analytics, and diagnostic solutions will be critical to overcoming the coronavirus pandemic. Consequently, as AI becomes more entrenched within our existing healthcare systems, we’ll be better prepared to combat future outbreaks.
 
 
 
11 September 2020
Glendale, CA
Alyssa Cotrina, Beyond Limits
 
 
Let’s talk about a question a lot of people ask themselves… What is AI? The thing about artificial intelligence is that most people don’t really know what it is. A lot of what most individuals think they know about AI technology is derived from assumptions based on the clichés found in Hollywood rhetoric and politically-motivated paradigms, often impeding AI adoption. The real story is a lot less about an inevitable war between cyborgs and humanity and much more about advanced solutions, grounded in the age of digital transformation, that will propel us forward into this next era of technological evolution.
 
 
 
 
 
The general concept behind “artificial intelligence” dates far back to the times of ancient history with traces found in Greek mythology’s Talos, a gigantic bronze mechanical robot-like heroic figure with human intelligence that served as a guardian to the island of Crete against ill-intentioned outsiders and invaders. The concept maintained its headway with early period thinkers from Descartes’ – who posited the concept that the bodies of animals are nothing more than complex machines – to early-modern legends and modern fiction like Mary’s Shelley’s “Frankenstein”.
 
 
The origination of modern artificial intelligence is considered to have transpired in the 1950s alongside the dawn of the computer age. In 1950 Alan Turing published a seminal paper titled “Computing Machinery and Intelligence” where Turing discusses the potential for a scenario where humans create a scenario in which “machines can think.” This led to the development of the earliest major proposal in artificial intelligence philosophy, the Turing Test. Currently, the Turing test serves an investigative technique to decide whether or not a software/computer/machine/etc. is capable of “thinking” like a human being. Of course, “thought” is a subjective ideology. Turing’s proposal also sought to dissect the term “think” and instead focus on the action of a machine’s performance capabilities and dexterity to create human cognitive competency.
 
 
In 1956, not long after Turing’s contributions, the term “artificial intelligence” was minted by John McCarthy as the subject matter of a Dartmouth Conference in which he presented a “Proposal for the Dartmouth Summer Research Project on Artificial Intelligence”. This was a first-of-its-kind conference focused on the issue of artificial intelligence and is widely considered the moment “AI” was officially born and defined as “the science and engineering of making intelligent machines.” It was also at this conference that the sentiment “artificial intelligence is achievable” was accepted, ultimately igniting the spark that kicked off the following few decades of research in AI.
 
 
AI Classifications – What does it all mean?
 
There are scores of categorizations when it comes to classifying factions and features of artificial intelligence. However, boiling a vast pool down to a few of the most commonly consumed terms paints a fairly holistic picture for our purposes.
 
 
Machine Learning:
It’s important to note that some do not consider machine learning to be AI, but rather solely a field of computer science. However, the term is commonly used in conjunction with artificial intelligence. In that vein, we can (more or less) consider machine learning to be a branch stemming from both computer science and artificial intelligence. Machine learning strives to educate systems, using structured and/or labeled data, on how to absorb information and perform a specific task without requiring categorical programming. It is a method of data analysis that comprises constructing and amending models that permit programs to “learn” through experience and repetition. A few examples of instances wherein machine learning is utilized include image/speech recognition, financial services such as spend tracking, spam/malware email filtering, customer service chatbots, and many more.
 
Deep Learning:
Deep learning is a division of machine learning that employs numerous “levels” of neural networks, built to function in an unsupervised learning manner that emulates a human brain with the ability to “learn” from vast quantities of data, regardless of whether or not that data is unstructured, unlabeled, missing, or otherwise. Every layer of the neural network contains deep learning algorithms that carry out computations and make forecasts in repetition to learn and progressively boost the precision of the results/recommendations as time goes on. A few examples of instances wherein deep learning is utilized include digital assistants, financial fraud detection, self-driving vehicles, and many more.
 
Neural Net[works]:
Neural networks are structures of neurons that can adjust with variable data inputs, composed of a sequence of algorithms that seek to identify core connections within a group of data in a procedure that simulates how a human brain might function in order to identify and recognize patterns. “Neural networks take input data, train themselves to recognize patterns found in the data, and then predict the output for a new set of similar data. Therefore, a neural network can be thought of as the functional unit of deep learning, which mimics the behavior of the human brain to solve complex data-driven problems,” stated Pratik Shukla and Roberto Iriondo for Towards AI, a Medium publication.
 
Symbolic AI:
Symbolic artificial intelligence is the practice of directly infusing human knowledge and expertise into a solution/system/machine/etc. by employing symbols, intelligible by humans, which characterize real-world notions and rationale to construct ‘rules’ that can then direct those symbols. This AI technique promotes a human-readable, rule-based technique, to produce transparent recommendations that are more easily understood by the people utilizing the solution. One example of an instance wherein a more symbolic-based AI approach is utilized includes conversational chatbots that use Natural Language Processing (NPL). “Natural Language Processing or NLP is a field of Artificial Intelligence that gives the machines the ability to read, understand and derive meaning from human languages,” stated Diego Lopez Yse for Towards Data Science, a Medium publication.
 
Cognitive AI:
Cognitive AI is feasibly the most advanced form of artificial intelligence to date. It is a hybrid of conventional numeric AI (machine learning, neural networks, and deep learning), used in conjunction with symbolic AI to enable a system to produce transparent recommendations. Cognitive AI is an intelligent system that comprehends large quantities of variable data while applying situational awareness and codified expert human knowledge, expertise, and best practices to identify problems and recommend solutions to real-world challenges. “This unique hybrid AI combines the best of numerical/statistical approaches with the best of symbolic/logical techniques to become greater than the sum of its parts,” stated VentureBeat and Beyond Limits in a 2019 VBLab article – Beyond Conventional AI: More Intelligent, More Explainable AI.
 
 
In contrast to the “black box” issue concerning conventional AI approaches, Cognitive AI systems equate to Explainable AI solutions that can disclose the reasoning behind their recommendations. Cognitive AI systems have the ability to show human-users detailed information regarding the substantiations, contingencies, confidence-levels, and ambiguities behind their decision-making process through intelligible audit trails. The key to a successful Cognitive AI tool is to build a primary set of models and propose hypothetical extensions, resulting in systems that sustain distinctive competencies to utilize encoded human expert knowledge in conjunction with historical and other external data. This results in systems with the ability to model hypothetical paths that predict problematic scenarios then recommend remediation plans, regardless of whether or not data inputs are unstructured, unlabeled, missing, or otherwise.
 
 
Advanced AI Applications – How can they help solve real challenges in the real world?
 
More advanced, enterprise AI software and cognitive solutions, have been proving their value and making a permanent mark on this world from industrial AI to power and natural resources and renewable initiatives. “Enterprises are increasingly deploying AI systems to monitor IoT devices in far-flung environments where humans are not always present, and internet connectivity is spotty at best; think highway cams, drones that survey farmlands, or an oil rig infrastructure in the middle of the ocean,” said Beyond Limits’ CEO AJ Abdallat in an insideBIGDATA article – AI Hype: Why the Reality Often Falls Short of Expectations. “One-quarter of organizations with established IoT strategies are also investing in AI.”
 
 
Enterprise-level AI has been substantiating its power to transform businesses for the better by supporting leaders in extracting more value from their data and production processes by streamlining their entire operation at every level of the organization. Industries and businesses have been realizing more than just a return on AI investments; they are experiencing actual revenue from artificial intelligence investments (RAI).
 
 
In a recent Forbes Tech Council Article, AJ Abdallat explained how “AI is generating major revenue in major industries.” In the article Abdallat referenced a 2019 report by Morgan Stanley to illustrate that fact and spotlighted the following examples:
 
“-Machine learning is analyzing wind farms to make power predictions 36 hours in advance, enabling providers to make supply commitments to power grids a full day before delivery and increase the value of wind energy output by 20%.
-In Australia, mining companies are using autonomous trucks and drilling technology to cut mining costs, improve worker safety and boost productivity by 20%.
If U.S. utility companies used AI-powered asset management software, costs could be cut by $23 billion annually, reducing outage frequency, overall footprints, installation times and copper cabling usage.
-A European automaker built a “fully digitized” factory and significantly reduced manufacturing time while boosting productivity by 10%.”
 
 
 
 
Outside of purely business-centric purposes, powerful AI solutions have the potential to help solve some of Earth’s most complex challenges. For example, the healthcare industry has also been discovering AI solutions fueled by historical medical data, lab work, literature, and expert human knowledge. Recently, powerhouse AI has been designed to aid doctors, nurses, and other leading industry professionals by reducing risk and improving patient outcomes at the point-of-care.
 
 
Lately, forecasting models such as Beyond Limits’ Coronavirus Dynamic Predictive Model have been designed to help provide some relief in humanity’s fight against the unexpected introduction of the COVID-19 pandemic. “This moment in time has uncovered just how crucial AI solutions are for the future of healthcare. Rapid changes have made it difficult to manage the pandemic’s spread and determine what the industry will look like after coming through the other side,” said AJ Abdallat in a recent Forbes Tech Council article. “Regardless of complications, it’s still the responsibility of leadership teams to use every tool at their disposal to manage the pandemic and be better prepared for the future. It matters that legitimate attempts are made by all – for the good of all – to pursue pioneering solutions in the face of this global challenge.
 
 
Another example of AI being used for good includes the exploration of applications designed to aid in the fight against climate change; generating hope for a more sustainable, renewable future with the aim to create a scenario in which humanity’s carbon footprint looks a lot less discouraging. “The suggested use-cases are varied, ranging from using AI and satellite imagery to better monitor deforestation, to developing new materials that can replace steel and cement (the production of which accounts for nine percent of global green house gas emissions),” wrote James Vincent in a 2019 article for The Verge on AI and climate change.
 
 
A 2019 article written by Simon Greenman for Towards Data Science, a Medium publication, also discusses the capacity for AI to, “Improve manufacturing efficiency by digitising, connecting and analysing end to end manufacturing processes. For example many global manufactures are using predictive AI modelling to make turbine combustion more efficient, reduce errors and energy wastage on the production line, and improve production efficiency with advanced robotics.”
 
 
The potential use cases for artificial intelligence solutions are seemingly endless. While AI may seem like nebulous ideation from an outsider’s perspective, and whether or not we are actively aware of the fact, it is ever-present throughout our surroundings and day-in-day-out lives. What used to be perceived as merely an intriguing plot-point for sci-fi narratives is now an inevitable, necessary, and welcomed reality. If you’re still asking yourself, “What is AI?” It may not be far-flung to boil it down to this statement: artificial intelligence is humanity’s focal point in their next stage of digital transformation and technological evolution.
 
 
References
http://www.maicar.com/GML/Talos1.html
https://www.csee.umbc.edu/courses/471/papers/turing.pdf
http://www-formal.stanford.edu/jmc/history/dartmouth/dartmouth.html
https://medium.com/towards-artificial-intelligence/building-neural-networks-from-scratch-with-python-code-and-math-in-detail-i-536fae5d7bbf
https://towardsdatascience.com/your-guide-to-natural-language-processing-nlp-48ea2511f6e1
http://stories.venturebeat.com/beyond-conventional-ai-more-intelligent-more-explainable-ai/
https://insidebigdata.com/2020/02/07/ai-hype-why-the-reality-often-falls-short-of-expectations/
https://www.beyond.ai/news/beyond-limits-builds-dynamic-forecasting-model-to-help-in-fight-against-covid-19/
https://www.theverge.com/2019/6/25/18744034/ai-artificial-intelligence-ml-climate-change-fight-tackle
https://towardsdatascience.com/how-can-technology-and-artificial-intelligence-help-tackle-climate-change-b97db0ff4c95
 
 
 
26 May 2020
Glendale, CA
Malene M. Therkelsen

 

With employers currently encouraging workers to telecommute, alongside the closure of schools and daycares, many parents are finding themselves in new territory: working from home (often full-time) with children but without access to babysitters, playdates, or even help from grandparents. All those supportive outlets that we normally rely on aren’t accessible when they are needed most.    

 

Attempting to keep up with your workload while simultaneously taking care of children can be challenging. But don’t panic just yet! We’ve gathered 6 tips on how to navigate life at the intersection of working from home and parenting that have helped our team and made our new situation a little easier.

 

Be upfront with your employer

Communication is an essential part of any job. When working remotely while parenting, make sure you continue to proactively communicate with your boss and coworkers that you will require flexibility to address the needs of your children. “If you clearly communicate your needs, you not only help to make your own life less stressful during this time, but you also open the door for your coworkers to have this conversation as well,” says Kaila Kea, Career Coach at themuse.com. “They may also be struggling with balancing work and family life, just like you, but don’t know how to address it.”

 

Communicate with your coworkers

No matter how well you try to plan out the day, your children will most likely interrupt your work at some point. They might make loud noises during your conference calls or photobomb your video meetings. Your coworkers will be more understanding about interruptions if you communicate and warn them ahead of time. “If you have a conference call and know there might be some unavoidable noises in the background, call attention to it at the beginning of the conversation,” suggests Alissa Carpenter, Author of How to Listen and How to Be Heard: Inclusive Conversations at Work. “This way if/when it happens, people are a little more prepared and not as thrown off by the distraction.”

 

Create a schedule and be creative with it

While working from home full-time as a parent, you might need to make adjustments to your work schedule in order to watch your children. Consider how many hours you need to work that day, when you will return calls, and what you can accomplish while your child is playing in the next room. It can be challenging to finish all of your work during regular business hours if you’re also on 24/7 kid-patrol. Depending on your flexibility and your partner’s flexibility, you might consider switching to shift work,” suggests Sara Sutton, CEO & Founder of FlexJobs. “Maybe you work for four hours (uninterrupted) in the morning while your partner watches the kids, then you switch. You watch the kids in the afternoon while your partner works. Then, when the kids are in bed, you both get a little more work done.”

 

 

Establish boundaries with your children

It’s important to establish boundaries with your children while working from home. “Have a family meeting and explain how work works. Let your kids know that you have certain tasks that you must accomplish, and you can’t take frequent breaks to help them,” says Sutton. Use visual cues to minimize interruptions such as a “do not disturb” sign on the door and let your children know that when the sign is hanging there they either 1. can’t come in or 2. need to be in “quite-mode” if they do. Sutton suggests that you explain to your children “once you’re done with whatever it is you’re doing, you’ll come out and check on them. But until that happens, they need to either wait for you or solve the problem themselves.”

 

Schedule breaks with your children – as well as some “alone time” downtime

Parents temporarily working from home may benefit from scheduling breaks with their children throughout the day. During these breaks, you can play with them, help them with schoolwork, or go outside to burn off some energy. Consider reading, board games, drawing, dancing, scavenger hunts, etc. “If you give the kids your full attention during breaks, they can look forward to them, and it might just be easier for them to get through your working blocks too,” says Teresa Douglas, Co-Author of Working Remotely: Secrets to Success for Employees on Distributed Teams. 

 

On the other hand, planning “me-time” downtime is just as important. Working from home while taking care of children can take a toll on your energy levels and patience. “In a house with multiple adults you can trade off—and try to discuss when and how you’ll each take your downtime in advance to avoid arguments,” Douglas suggests. “Solo parents might need to wait until the weekend to use an early morning or late evening for alone time.” During your alone downtime, you should prioritize things that make you feel good and relaxed such as reading a book, working on a craft, getting a workout in, etc.

 

Suddenly juggling a full-time remote work schedule with at-home childcare creates new, unanticipated challenges. Since many parents might be unexpectedly at home for weeks, we encourage using these tips to establish an effective work-from-home strategy for you and your kids. With some planning, clear communication and an adaptable attitude, you may be better equipped to successfully manage your workload while raising your children during this difficult time.

 

Cite references for expert quotes & recommendations below:

https://www.themuse.com/advice/work-from-home-kids-coronavirus

https://www.fastcompany.com/90478087/got-kids-try-these-tips-for-working-from-home-while-theyre-with-you

 

 

31 March 2020
Glendale, CA
Alyssa Cotrina, Beyond Limits

 

When discussing AI investment with business leaders one of their biggest concerns centers around the uncertainty of exactly how to calculate their return on this growing area of technological investment – which then brings into question whether the practice is even worth doing in the first place. It’s time to reconsider what you think you know about AI and the bottom-line.

 

Why the hesitation?

 

Lack of direct historical experience with the technology (and subsequent comfort levels), among other factors, have made it challenging for some business leaders to generate a comprehensive method of calculating ROI for AI, planting apprehension in the minds of some businesses. A 2017 McKinsey report surveyed over 3,000 firms and found, “41 percent reported that one of the biggest barriers preventing them from further adoption of AI was the uncertain return on investment, while 26 percent reported a lack of relevant AI products on the market.”

 

Another survey by TechRepublic reinforced that from a slightly different angle, “Organizations recognize the value of AI/ML projects, however, they lack confidence in their team’s readiness for implementation and management of such projects.” While businesses do acknowledge the inevitable value of investing in AI for their projects, a mind-shift must take hold because inertia toward AI investment initiatives will come at a steep cost down the line. Predictably, rivals will capitalize on the potential of AI capabilities – whether or not you choose to take that step as well.

 

AI’s role in the future of technology

 

The next revolution for technology depends on the continued evolution of artificial intelligence, and it matters that we recognize AI as the future of tech. Businesses that don’t shift their tentative attitude toward investing in AI will be left in the dust as this disruptive technology continues to ramp-up and accelerate. All the truly innovative enterprises won’t hesitate to actualize this investment; they will be the ones left standing. They’ll be able to boost production efficiency thus increasing product margins and grow existing revenue as a consequence of the competencies provided by established and cutting-edge AI solutions. When that happens, how can late-in-the-game skeptics possibly compete within their respective marketplaces? At that stage, forget about even being a challenger, it’ll become less of a competition and more of a race to not be left behind.

 

How Beyond Limits Cognitive AI solutions maximize RAI within this era of progress

 

Beyond Limits is growing in authority throughout entire value chains in heavyweight industries like Energy, Power/Natural Resources, and Manufacturing for implementing a hybrid of conventional techniques with symbolic approaches to power Cognitive AI solutions that explain the reasoning behind their recommendations (XAI) via observable (and interactive) audit trails. This transparent artificial intelligence system builds trust, enabling numerous industries to confidently leverage solutions that solve their most complex problems.

 

For example, highlighted in a recent announcement, Beyond Limits has partnered with XCELL to build the world’s first power plant guided by Cognitive AI. Beyond Limits Founder & CEO, AJ Abdallat said, “Beyond Limits is committed to improving efficiencies across the energy value chain. If we can help a power plant operate more efficiently, a refinery more economically, or an exploration rig more accurately, it helps the environment and the economy – and the resulting revenue from AI quickly adds up to millions per year.”

 

Examples of Revenue from Artificial Intelligence:

 

+ An oil rig that operates more productively because Beyond Limits’ Cognitive AI for Field Management supports operators in staying ahead of maintenance and efficiency issues with expert guidance on every platform, significantly accelerates data integration and analysis that pinpoints drilling prospects and evaluates opportunity vs risk. Competencies at this scale could deliver a few thousand barrels more per day and expedite time-to-decisions, which could then yield an extra $30-40MM and $100MM per year, respectively.

+ Beyond Limits Cognitive AI for Refinery provides a comprehensive picture of what is happening in a facility from the big picture to the smallest detail, identifying trends and determining whether operations are headed in an undesirable direction. This solution is designed to decrease operational cost and increase refinery efficiency by up to 10%, improving overall margin performance.

+ A power plant guided by Beyond Limits Cognitive AI is designed to improve insights into the entire facility – maximizing efficiency and productivity, reducing CO2 emissions, saving fuel, and improving quality plus stabilization of raw materials supply. The enhanced ability to control cost, boost production, and provide support for operators with entire system monitoring can help them better manage production for peak efficiency, generate superior maintenance planning, and further extend long-term lifespans.

 

Moreover, a recent Forbes Technical Council Article by Beyond Limits Founder & CEO Founder AJ Abdallat, called-out numerous additional industry examples of how AI solutions have more than proven their value as well.

 

It’s time to reconsider what you think you know about AI and the bottom-line. Pioneering solutions, like Beyond Limits’ Cognitive AI, are already etching a path of proof that artificial intelligence investments can (and do) move beyond the point of just discussing ROI, into the realm of revenue from AI (RAI). You’ll never experience RAI unless you take that first plunge into the transformative business-driver known as artificial intelligence.

 

03 March 2020
Glendale, CA

 

Beyond Limits honored for achievements in groundbreaking Cognitive AI solutions revolutionizing heavy industries

 

CB Insights today named Beyond Limits to the fourth annual AI 100 ranking, showcasing the 100 most promising private artificial intelligence companies in the world.

“It’s been remarkable to see the success of the companies named to the Artificial Intelligence 100 over the last four years. The 2019 AI 100 saw 48 companies go on to raise $4.9B of additional financing and nine got acquired,” said CB Insights CEO Anand Sanwal. “It has been gratifying to see that CB Insights’ data-driven approach to identifying the top AI companies using patents, customer traction, investor quality, market sizing and more has become so effective at picking the AI winners of tomorrow. We look forward to seeing what the 2020 AI 100 companies will accomplish over the course of this year and beyond.”

In addition to disrupting core sectors including healthcare, retail, and finance, the 2020 AI 100 companies are revamping the broader enterprise tech stack. These companies span the globe, from the US, UK, China, Chile, and South Africa, and are supported by more than 600 investors.

“Beyond Limits is very excited to be acknowledged by CB Insights,” said Beyond Limits CEO AJ Abdallat. “It is especially meaningful to us that the recognition has come at this point in our growth; 2020 is going to be big year for Beyond Limits as we make significant strides toward global expansion to serve the energy industry and a variety of other sectors. We believe Beyond Limits’ innovative and unique AI technologies are going to be a key component in reimagining and modernizing the energy industry – through advanced digitization we can create more intelligent, more efficient operations for a lower carbon future.”

 

 

Through an evidence-based approach, the CB Insights research team selected the AI 100 from nearly 5,000 companies based on several factors including patent activity, investor quality, news sentiment analysis, proprietary Mosaic scores, market potential, partnerships, competitive landscape, team strength, and tech novelty. The Mosaic Score, based on CB Insights’ algorithm, measures the overall health and growth potential of private companies to help predict a company’s momentum.

Beyond Limits serves industrial customers with Cognitive AI systems designed to apply human-like expertise and reasoning to solve complex problems and provide cognitive and analytical horsepower that accelerates executive and operator decision-making. For example, in the energy sector, Beyond Limits is deploying new products for refinery optimization, managing upstream wells, assisting petroleum engineers in formulating lubricants products, and advising reservoir engineers on optimized well locations and in-fill well production rate prediction.

Beyond Limits’ systems utilize a hybrid approach that combines conventional machine learning and deep learning approaches with knowledge-based reasoning. The company has developed powerful Cognitive AI engines that leverage encoded expert knowledge and experience to provide clear, understandable solutions to important challenges facing heavy industries today. Unlike most “black box” AI techniques, Beyond Limits has pioneered “glass box” Explainable AI that yields recommendations that can be understood by people and interpreted by machines.

 

Quick facts on the 2020 AI 100:

 

  1. As of the end of February 2020, these 100 emerging private companies have raised over $7.4B in funding across 300+ deals from 600+ unique investors.
  2. There are 10 unicorns (companies valued over $1B) in this year’s AI 100 cohort.
  3. The list spans across various industries, including healthcare, retail & warehouse, and finance & insurance.
  4. 13 countries, such as China, Sweden, and Japan, are represented on the ranking. The majority of startups (65%) are based in the United States.

 

The AI 100 Companies:

 

About CB Insights

CB Insights helps the world’s leading companies accelerate their digital strategy and transformation efforts with data, not opinion. Our Emerging Tech Insights Platform provides companies with actionable insights and tools to discover and manage their response to emerging technology and startups. To learn more, please visit www.cbinsights.com.

 

Contact:

CB Insights

awards@cbinsights.com

 

About Beyond Limits

Beyond Limits is a pioneering Artificial Intelligence engineering company creating advanced software systems that go beyond conventional AI. Founded in 2014, Beyond Limits is helping companies solve tough, complex, mission-critical problems and transform their business. The company applies a unique hybrid approach to AI, combining numeric AI techniques like machine learning with knowledge-based reasoning to produce actionable intelligence. The end result is faster, better decisions that reduce risk, decrease waste, and increase efficiency. For more information, please visit www.beyond.ai.

 

CONTACT:  

Len Fernandes

Firecracker PR

len@firecrackerpr.com

1-888-317-4687 ext. 702

Efficiency of power generation from natural gas through cognitive artificial intelligence first of its kind to drive development in West Africa

25 July 2019
Author: Beyond Limits

 

GLENDALE, Calif.July 24, 2019 /PRNewswire/ — Beyond Limits, an artificial intelligence software engineering company, has been awarded a $25MM contract initial order with follow on orders by Xcell Security House and Finance S.A (Xcell), the Swiss-based global financial and minerals development company, to build the world’s first cognitive power plant. With technology originated for NASA space missions, Beyond Limits is a pioneer in advanced cognitive AI solutions for heavy industry installations. The contract covers development of the Beyond Limits Cognitive Power Generation Advisor. The first cognitive power plant will be installed as part of a large-scale infrastructure program to drive core industrial capacity and power economic development in West Africa.

Beyond Limits CEO, AJ Abdallat states that Beyond Limits is committed to improving efficiencies across the energy value chain. “If we can help a power plant operate more efficiently, a refinery more economically, or an exploration rig more accurately, it helps the environment and the economy. And the resulting revenue from AI quickly adds up to millions per year.”

This will be the first implementation of a cognitive AI power plant built from the ground up that embeds intelligence and awareness into all of its operations. This will provide operators with facility-scale insight, making the plant safer, maximizing its efficiency and productivity, and making it more environmentally friendly.

“One of the keys to power operations is handling variations in supply and demand,” says Lynnwood Farr, CEO of Xcell. “We feel that Beyond Limits artificial intelligence in the Xcell cognitive power plant will give us the upper hand to control costs and maintain efficient, dependable power generation for our customers.”

 

Improving Efficiency with Explainable AI

The efficiency of power generation from natural gas can be affected by environmental conditions such as temperature and humidity. Human operators can make adjustments to improve efficiency, but their effectiveness is experienced-based. Expert level human knowledge can be encoded into the Beyond Limits knowledge base to validate recommendations generated by Beyond Limits cognitive reasoners.

With most power plants, power is generated as needed. Since there is currently no viable capacity for large-scale electric storage, excess production results in wasted natural gas. Conversely, under-production represents lost revenue. Changing from low production to higher production takes time due to ramp up time of expensive turbines. Likewise, reducing the power generation adds additional strain. The cognitive AI system is designed to monitor powerful gas turbines and the entire system to help operators manage production for peak efficiency, maintenance planning, and longer-term lifespan.

Beyond Limits has developed advanced AI systems to monitor and help control large-scale industrial plants that produce millions of units of product worth tens of millions of dollars per day. Manufacturing operations, such as a power plant or refinery, encompass hundreds of people and acres of equipment working 24 hours per day 365 days per year. Maintaining coordination across tightly interconnected production units, even under the best conditions, is not trivial. In novel, never-seen-before conditions, it’s an extraordinary challenge. Now, process engineers can solve problems faster with the assistance of cognitive process manufacturing advisors from Beyond Limits. These AI advisors have acute situational awareness to sense, anticipate, and resolve problems even under constantly changing conditions. All Beyond Limits cognitive AI systems explain their reasoning and recommendations to human operators in clear, evidence-rich audit trails (also known as XAI).

 

ABOUT XCELL

Xcell Security House and Finance S.A (Xcell) is a Swiss company in the form of a «Societe Anonyme » S.A. The purpose of Xcell is to offer financial commercial advice, including but not limited to: Precious Metals and Precious Stones Trade, Monetization of Assets for their Clients, Business Planning Financial Advice, Forex, Safekeeping of Assets, and other related services. Xcell operates within the norms of Financial Regulations of Switzerland. In recent years, Xcell Finance have become active in Western Africa for Power Generation, Mining, Infrastructure Projects, and Special Artisanal Gold Mining Programs with Government Central Banks and the United Nations. Xcell holds its own Swiss Precious Metal Hallmark.

For more information, visit https://www.xcellfinance.com

 

ABOUT BEYOND LIMITS

Beyond Limits is a full-stack Artificial Intelligence engineering company creating advanced software solutions that go beyond conventional AI. Founded in 2014, Beyond Limits is transforming proven technologies from Caltech and NASA’s Jet Propulsion Laboratory into advanced AI solutions, hardened to industrial strength, and put to work for forward-looking companies on earth. Beyond Limits leverages this unparalleled innovation portfolio, along with proprietary cognitive technologies, to help companies solve tough, complex, mission-critical problems and transform their business. We apply a unique hybrid approach to AI, combining numeric AI techniques like machine learning with higher order symbolic AI and expert human knowledge to deliver intuitive cognitive reasoning and information. The result is faster, better decisions that reduce risk and increase revenue. For more information, please visit www.beyond.ai.

 

Media Contact:

Len Fernandes

Firecracker PR

(888) 317-4687, ext. 702

218741@email4pr.com

SOURCE Beyond Limits

Related Links

https://www.beyond.ai