Read full article here.
Machine learning is taking over the running of many industries. To some, it’s a sound of rather bad news while to other businesses, its a sign of better days ahead. We know some entrepreneurs have embraced or had experience with machine learning thus we asked them what they think will be the impact of it on business.
Meeting of more complex demands
The machine learning and big data based AI that currently pervade are powerful tools for identifying associations in large quantities of data, but don’t have much on humans in terms of working out the complex phenomena of cause and effect, or to identify modifiable factors that can engender desired outcomes. So how does AI make the leap to the next step? The first step is to enhance the big data and machine learning with another layer of AI functionality – that of cognitive intelligence. What is missing in the AI learning simply from crunching the data at hand is an AI that can reason through and incorporate missing information, reason abstractly, plan, and problem solve. Mapping out scenarios and searching for potential outcomes to weed out confounders or even fill in missing data gaps through hypothetical scenarios. In real world application, it is substantially more complicated that reasoning through an opponent’s potential moves in a complicated game and altering game play to reach a desired outcome. But the foundation is there, and the technology is certainly there as well. While machine learning and big data has dominated for years, a new breed of commercial AI has begun to emerge to meet the more complex demands of modern human machine interactions. The aim of cognitive intelligence AI platforms isn’t to supplant big data or machine learning. Rather, it’s there as a supervisor of sorts, monitoring how traditional AI process data, filling in gaps and identifying misinterpretations. Ultimately, the goal of a cognitive AI platform is to be able to complete tasks without the need for human supervision, to be able to quickly process unexpected or unfamiliar external input and adjust its response accordingly.
WomenHack is a community that aims to empower women in tech by facilitating access and transparency in the industry. WomenHack events are invite-only recruiting events focused on connecting top female software engineers, UI/UX designers, and product managers with opportunities at tech companies around the world. Beyond Limits was honored to attend and spread the word that Beyond Limits is hiring top talent, including AI engineers, data scientists, project managers, and more.
Beyond Limits is a pioneering AI company with a unique legacy from the US space program. The company transforms proven technologies from Caltech and NASA’s JPL into advanced AI solutions, hardened to industrial strength, and put to work for forward-looking companies on earth.
Like WomenHack, Beyond Limits is committed to creating a more inclusive workplace for all.
Ready to test your limits?
Head over to our careers page: https://www.beyond.ai/careers/
Kevin Price recently interviewed the CEO of Beyond Limits, AJ Abdallat. They talked about the beginnings of Beyond Limits, Cognitive Intelligence and the future of AI. https://www.beyond.ai/
By Atanu Shaw on October 11 2017 2:59 PM
Where Does Artificial Intelligence Go From Here
Studies are ongoing so that NASA’s artificial intelligence (AI) systems could eventually run spacecrafts with much higher intelligence during deep space explorations. Meanwhile, on Earth, a company based in Southern California is adapting NASA’s AI systems to advance market comprehension and benefit business technologies on Earth.
Since landing on Mars in 2012, NASA has been dramatically expanding Earth’s understanding of the Martian climate and geology through the Curiosity rover. Next year, another spacecraft, InSight, is probing deeper into Mars to investigate the red planet’s interior.
Space missions are becoming more complex as automation technologies are evolving, developing higher intelligence. The same thing is happening back on Earth. AI is going beyond mere data crunching and machine operations. The world is seeing tremendous advancements in deep learning. AI systems are paving the way for more meaningful innovations and disruptions in various industries.
NASA AI To Boost Business On Earth
For its space missions, Caltech and NASA’s Jet Propulsion Laboratory in Pasadena aims to build spacecrafts that would require less of high-level human direction, particularly in surprising situations. On Earth, a company called Beyond Limits aims to deliver automated solutions that can process big data with human-level comprehension.
Caltech has granted Beyond Limits license to improve and commercialize its AI technology for business operations. Incidentally, The Economist has found that companies in North America are truly keen about understanding how AI solutions can impact their growth.
“We are creating automated solutions with advanced intelligence so they can think more like humans,” says AJ Abdallat, CEO of Beyond Limits, based in Glendale. The company has recently secured $20 million in Series B funding from BP Ventures. It is poised to deliver game-changing industrial-grade AI solutions to manage big and emerging markets.
“In some ways, the hype for conventional AI has exceeded the promise,” Abdallat explains, adding that business technologies today need automations powered by cognitive human-like reasoning that can truly comprehend the intricacies of large amounts of data.
“It is this transformative technology that will help AI accomplish the vision of bettering human lives,” the CEO adds. He further underscores the fact that Beyond Limits offers solutions that have been tested and proven in space. He further underscores the fact that Beyond Limits offers solutions that have been tested and polished in space. Standard AI and machine learning processes are simply touching the tip of a colossal iceberg.
By 2020, business analysts at Forrester Research predict insights-driven businesses will take away $1.2 trillion per annum from their competition, assuming the competition is not investing well in customer insights.
‘Extremely Light’ Solution Perfect For IoT
In both fiction and real life, talks about advanced AI systems are often met with confusion and skepticism, if not fear. For some, simplifying AI using the word automation helps in coming to terms with what it really means.
Still, not every business is eager to adapt to AI systems because of financial reasons. Existing AI stand to be extremely resource intensive. The usual AI requirements today, like a great deal of server hardware and expensive human resource for control and direction, are quite intimidating.
Some small to medium size enterprises fear AI may not be worth investing in now. However, experts are saying AI is here to stay, and small businesses can leverage it now.
Beyond Limits is also addressing the most common blocks between AI and businesses. Its technology is extremely light yet fast and profoundly intelligent. Power is not an issue; it can even run on small devices, perfect for the Internet of Things (IoT).
Consider the Curiosity Mars rover. The Jet Propulsion Lab is running it, and soon the InSight, with the most cutting-edge and adaptive AI‘brainwork’ from NASA with smart use of power at play.
The future of AI is boundless. Abdallat anticipates the application of NASA’s AI in every industry one can imagine: finance, transportation, healthcare and more. Exceptionally efficient and flexible, NASA’s AI is set to augmenthuman capability on Earth.
Beyond Limits is featured by The Tech Tribune as one of the best tech startups in Glendale.
The Tech Tribune staff has compiled the very best tech startups in Glendale, California. In doing our research, we considered several factors including but not limited to:
- Revenue potential
- Leadership team
- Brand/product traction
- Competitive landscape
Additionally, all companies must be independent (un-acquired), privately owned, at most 10 years old, and have received at least one round of funding in order to qualify.
BP Technology Outlook 2018
“Intelligence is the most powerful and precious resource in existence, but there are countless untapped opportunities for intelligence to make the world a better place. The key is actionable intelligence – which could be harnessed by our digital world where everything can potentially be connected to generate data.”
Intelligence. In its varied forms, from the mysterious brain of the octopus and the swarm intelligence of ants to Go-playing deep learning machines and driverless vehicles, intelligence is the most powerful and precious resource in existence. Beyond recent advances in Artificial Intelligence (AI) that enable it to win games and drive cars, there are countless opportunities for intelligence to help make the world a better place. One such area is energy, including the modernization of the oil and gas industry. This is a global landscape rich in opportunities for protection of the environment, more efficient discovery of energy sources, workplace safety, plus diagnostics for more informed decision-making.
We live in a digital world where everything can potentially be connected. The key is actionable intelligence – data that’s been analyzed to aid human decision-making. One important strategy is embedding intelligence so, decisions can be made at the sensor rather than “phoning home” to headquarters. Imagine an intelligence sensor on a drill bit that can manage its residual lifespan, avoiding the costly practice of pulling it up for inspection just because its Mean Time Between Failure rating (MTBF) says so.
Downstream, cognitive AI is now being applied to track tankers to determine when they leave port, where they’re going, and how much petroleum or LNG they are transporting. Predicting what is being shipped, plus refinery destination and arrival times, will help traders make smarter decisions.
Removing friction from port scheduling operations requires a rare form of machine intelligence called cognitive intelligence (or human-like reasoning). This involved the fusion of the key cognitive capabilities of multi-agent scheduling with reactive recovery, asset management, rule compliance, diagnostics, and prognostics to ensure seamless autonomous operation.
My final prediction is about a development which I feel will become of increasing importance: embedding intelligence in silicon. While the world may think of AI running on mammoth computers, as in sci-fi movies, that approach is becoming a thing of the past. In the near future you will see the emergence of true intelligence being deployed in tiny blocks of silicon – even more disruptive than the transition from tubes to microelectronics.
Our wider vision of AI for the future of energy includes cognitive systems that intelligently and fluently interact with human experts and provide articulate explanations and answers. Across the board, you will see, and work with, systems endowed with rare and valuable intelligence.
See full article here:
Beyond Limits named by CIO Review as one of the 50 most promising companies at the forefront of providing FinTech solutions and impacting the marketplace.
I hired a car to drive from San Francisco to Monterey for GCV’s summit earlier this year. This London-based Brit enjoyed the sun, the views, singing along with the audio system, and the general Californian vibe. I enjoy driving, particularly in southern California. I hired a car to drive from San Francisco to Monterey for GCV’s summit earlier this year. This London-based Brit enjoyed the sun, the views, singing along with the audio system, and the general Californian vibe. I enjoy driving, particularly in southern California.
By way of contrast, Meghan Sharp, the San Francisco-based managing director of BP Ventures, the venturing unit of the energy major, took an Uber to the summit and did three conference calls in the two-and-a-half-hour journey. (When I say “an Uber” here and below I don’t necessarily mean the car service of that name; I simply mean a car service enabled by a smart phone).
Like many I speak to in the venture business these days, Meghan travels so much that she’s stopped driving. “For me, the opportunity cost of driving is just too high. It doesn’t make sense to be behind the wheel when I could be working,” she explains. “I also save money by not owning a car – I’ve done the math.”
Meghan is also happy to rely on Uber to transport her 83-year-old mother to the Dallas Ft. Worth airport to visit her in San Francisco. “This type of chauffeur service is a luxury that until very recently was only available to the very rich,” she says. Although she draws the line at using Uber to transport her children to school (as some San Franciscans do), she predicts that a business model that fuses child care with Uber could work. (How about ‘Kinder-Uber’? You heard it here first).
The more you travel, the less you want to drive; the less you drive; the more work you can do and the more money you save; the readiness to trust a driver you’ve never met before and sit in an ‘impersonal’ car you’ve never sat in before: as such truths dawn, they are rapidly and thoroughly disrupting travel and the several industries that depend on it, including BP’s main business, energy.
In the interview below, Meghan explains some of the ways in which BP is using venturing to participate in this disruption and find new business models which draw on and build on BP strengths. “For example, BP has all this real estate and all these gas stations. How are you going to monetise that?” she asks. “We can explore adding electric vehicle charging facilities, for example” she answers. BP is also considering the shift to autonomous vehicles (AV), partly through investing in artificial intelligence (AI). “With AV, there’s a huge opportunity to increase safety. We have to get it right and AI is going to play a huge piece.”
BP is increasing its commitment to lower carbon and digital businesses through its Alternative Energy business and across five focus areas to $500m per year. “I don’t think there’s a bubble. I think it’s a real trend,” says Meghan.
She cites two California-based venture investments that are supporting the parent company’s strategic shift to electric and autonomous mobility.
FreeWire, a manufacturer of mobile rapid charging systems for electric vehicles, received $5m earlier this year from BP, which will trial its technology at selected retail sites in the UK and Europe. “BP has the ability to help FreeWire scale,” says Meghan. “It should be a mutually beneficial relationship.” BP’s investment was part of a $13.33 million Series A1 venture funding, which was led by Stanley Ventures, the venturing subsidiary of Stanley Black & Decker, the US power tool business.
In the summer of 2017, BP was the sole investor in the $20m Series B round of Beyond Limits, an AI and cognitive computing company, which is commercialising software from NASA, the US space agency, and the US Department of Defence (software that was used in the Mars Rover exploration). “Beyond Limits is genuinely cognitive. It’s not just deep learning,” says Meghan. “It is looking at mobility with BP and other partners.”
Meghan, what do you drive?
I rarely drive. I use Uber or Lyft. And it’s changed my life, professionally and personally. My working days starts on the phone in an Uber. At BP we have a strict policy that you can’t be on the phone while driving. But there’s no way I’m going to spend an hour driving to work in the morning. I need to catch up with Europe and the East Coast, which means I’m on the phone. So, I get an Uber every day. (And by the way, this is at my own expense). On the personal side, we’ve been able to use curb-side check in at the airport, and Uber and competing services to very conveniently, safely and inexpensively transport my mother to come and see us in San Francisco. She lives in a different city and there’s no way this would be possible without the innovation in travel we’ve seen in recent years.
So, there’s a personal as well as a professional commitment to venturing in new mobility technologies?
Yes. I’ve embraced the new model of transport. Or maybe it’s embraced me. Sometimes there is wifi in the cars I’m in. This is going to become increasingly the norm – the car is going to be very similar to the office environment in terms of the amenities it offers. This means that the car is going to be competing more with the plane, and many of us will choose to be driven rather than to fly. For example, to get to LA from San Francisco is an 8-hour drive. Sure, it’s longer than a two-hour flight, but if you factor in the ride to and from the airport, the security clearance and the hassle, the 8-hour car journey is increasingly attractive, particularly as we switch to autonomous vehicles, which will increase safety.
Where and when do electric vehicles feature in this picture? Most of the cars you get in today are still powered by the internal combustion engine.
Yes, they are. But I was picked up by a Tesla last week and I expect to be sitting in more EVs in the very near future.
Don’t you worry that there is a lot of hype around EVs and AVs? Is there a danger we’re in a bubble?
I don’t think there’s a bubble. These are real trends that are underpinned by societal demand. BP is an oil and gas major. The internal combustion engine is a big part of its history and we believe it will still be a big part of its future. However, our perspective is that the EV market is real and emerging, and we want to create a disruptive, distinctive and differentiated offer looking at supporting that market.
How? What are you prioritising? What type of venture investments are you looking for?
Over the next 12 months a big focus for us will be on what we do with BP’s forecourts. BP has all this real estate and all these gas stations. How is it going to monetise that? What are the gas stations going to be in the future? BP isn’t betting that they are going to remain just gas stations. They are going to introduce more electric vehicle charging facilities at them. That’s why we’re really interested in fast charging. We are also very focused on the material technology that enables this.
Let’s hear about your most recent investment in charging technology, FreeWire Technologies.
FreeWire is a great example of the type of investment we want to make. It’s the market leader in mobile fast charging for electric vehicles. It’s going to be trialled on our forecourts. We’ll learn a lot. FreeWire will learn a lot. BP has the ability to scale FreeWire. It should be a mutually beneficial relationship. If all we can offer a venture investment is dollars, it’s not the right relationship for both parties. The strategic relationship has to go both ways.
Why should the EV owner charge his vehicle at a BP gas station? What can BP provide that you can’t get elsewhere?
It turns out that lots of people don’t have garages they can charge their vehicles in. Around 50% of people simply can’t charge at home. Charging on a BP forecourt will be a winning proposition if you can charge in about ten minutes and drive for about 300 miles. If you re-charge at home, you don’t care how long it takes to re-charge. But with recharging elsewhere, speed is a big issue. So, we’re very interested in fast-charging deals.
Turning now to autonomy, what’s your most recent investment here?
We were the sole investor in Beyond Limits, a cognitive AI business whose team came out of Jet Propulsion Labs [part of NASA]. To date, most of the work we’ve done with Beyond Limits is to find what relief they can provide to our pain points in the upstream, but we know there will be applications also for the downstream. Beyond Limits is looking at mobility with BP and other partners. We will get proof of concept on its applications before going into deployment. It’s really exciting. We know that Beyond Limits is genuinely cognitive. It’s not just deep learning. With AV, there’s a huge safety issue. We have to get it right and AI is going to play a huge piece.
With EV and AV, how big a pond are you fishing in? What types of deals are you after? How early stage do you go?
We’re happy to do all stages including very early. BP is making a lot more capital available for advanced mobility opportunities and other core focus areas so we are not constrained. We recently funded and sponsored a smart mobility competition for entrepreneurs at the NYU Tandon School of Engineering as well as partnering with TechX, an oil and gas incubator in the UK. But we’re also interested in technologies that are closer to commercialisation as well as in growth capital opportunities.
Other than fast charging, what else are you prioritising in mobility?
We’re taking a very close look across the value chains and how it all fits together. We’re keen to see venture opportunities that disrupt the value chain at any point. We are continuing to explore opportunities in smart and advanced mobility. As BP’s recent Energy Outlook found, the interaction of fully-autonomous cars with shared mobility has the potential to substantially boost the intensity with which electric cars are driven. BP has a new business unit, the Advanced Mobility Unit, which is focused on exploring various mobility options, and which will help inform our venturing. This is mission critical work, which can have a huge impact on not only BP’s overall business, but wider society as well.
CB Insights – March 8th, 2018
BP Ventures has invested in artificial intelligence company Beyond Limits. Beyond Limits was previously trialed in deep space exploration. At the time of its investment, BP stated that it planned to use Beyond Limits’ technology for upstream exploration, which involves searching for oil reserves.
Starting a business is a big achievement for many entrepreneurs, but maintaining one is the larger challenge. There are many standard challenges that face every business whether they are large or small. It is not easy running a company, especially in a fast-paced, ever-changing business world. Technology advances, new hiring strategies, and now, political changes coming with the new administration, all add to the existing business challenges that entrepreneurs, business owners, and executives have to deal with.
Maximizing profits, minimizing expenses and finding talented staff to keep things moving seem to be top challenges for both SMBs and large corporations. We have been interviewing companies from around the world to discover what challenges they are facing in their businesses. We also asked each company to share business advice they would give to a younger version of themselves.
Below is our interview with AJ Abdallat, CEO at Beyond Limits:
What does your company do?
Beyond Limits is a pioneering AI company with a unique legacy from the NASA space program, notably AI technology developed at the Jet Propulsion Laboratory (JPL). Beyond Limits drives new innovations and IP on our mission to bring advanced AI technology to solve commercial applications here on Earth. We enhance software systems developed for NASA/JPL, giving them additional capabilities and hardening them to industrial strength. We are an AI leader with breakthrough cognitive technology that goes beyond conventional AI, blending deep learning and machine learning tools together with symbolic AIs that emulate human intuition. This is what we call cognitive intelligence. Beyond Limits’ cognitive agents are trained and deployed to solve complex industrial and enterprise problems, bringing cognitive advantages to help energy, fin-tech, healthcare, and logistics companies stay competitive or transform their business for the future. The company was founded in 2014.
What is your role? What do you enjoy most about your role?
Starting in 1998, I worked with Caltech/JPL to commercialize technologies developed at JPL, including smart sensors and artificial intelligence projects. Since then, I have founded several companies to bring innovative Caltech/JPL space technology to market, the latest of which is Beyond Limits.
Beyond Limits is the only AI company in the world attempting to bring advanced intelligence systems proven in extreme environments 150 million miles away in space, to extreme conditions 15,000 thousand feet underground for oil and gas production. Our technology has been to places where no other AI company could go, under conditions too extreme for others to master. I am extremely proud of the fact that we have been able to advance AI beyond conventional AI, applying our pioneering inventions and proven technologies from the space program to solve complex mission-critical business, industrial, and medical problems for companies here on earth.
What are the biggest challenges in your business right now?
I see AI as a profoundly transformative capability that is going to have a
major impact on us as a society and on our business environment. Sundar
Pichai, Google CEO, stated recently that “AI is probably the most important
thing humanity has ever worked on. I think of it as something more profound
than electricity or fire.” I agree with Sundar. The biggest challenge in our
business is making sure that some of the overinflated hype about the
potential of AI (that unfortunately some companies are creating) doesn’t
turn off businesses and consumers. By contrast, we aim to be plain-spoken
and rational about the practical problems AI is best-suited to solve. Our
customers keep us grounded in the reality of their business needs.
If you could go back in time, what business advice would you give to a younger version of yourself?
I feel very fortunate with my career as an entrepreneur. However, my advice to younger version of myself would be to enjoy the journey and have a more balanced business and personal life.
This is the second installment of a two-part Q&A series on artificial intelligence (AI) with AJ Abdallat. It covers AI’s potential significance to computing; how AI affects jobs; the employee specializations needed to fuel AI; big data; and cultural challenges in the enterprise. Be sure to check out Part 1 as well.
AJ Abdallat is a serial entrepreneur who, from 1998 to 2011, worked with NASA’s Jet Propulsion Labs (JPL) and Caltech on a series of tech incubation startups. The goal was to commercialize NASA technologies, many of which were artificial intelligence-related.
In 2014, Abdallat co-founded and became CEO of Beyond Limits, a startup that secured licenses to NASA AI technologies for use in commercial applications. Beyond Limits currently holds exclusive licenses to 42 blocks of sophisticated intellectual property developed through NASA R&D investment, a $150 million AI technology head start under the aegis of Caltech’s Office of Technology Transfer and Corporate Partnerships program. Abdallat’s company is a leader in cognitive technology, which goes beyond conventional AI, binding deep learning and machine learning tools with symbolic AIs to emulate human intuition.
We interviewed Abdallat while researching the story, “AI Delivering on the Business Analytics Promise.” With AI poised to potentially revolutionize business, Abdallat’s career, which blends AI science and commercialization of the technology, makes his insights fascinating.
DevOps.com: How does the advent of AI as used by enterprises compare to earlier significant computing milestones like networking, the internet, or cloud computing?
Abdallat: Part of me wants to quash as much artificial intelligence speculation as possible. The hyperbole. But frankly, I think AI is potentially more transformative than the other things you mentioned, which are just infrastructure. AI is starting to help us pose the questions that we ultimately want to answer. What’s unique about AI is that it’s an introspective exercise. Every new success for AI is giving us some insight about how we work.
AJ Abdallat is co-founder and CEO, Beyond Limits, an artificial intelligence firm. He’s an engineer and entrepreneur.
As we integrate AI, the trend may not be that transformative initially. Improvements will likely be focused on doing it faster, bigger with lower downtime and more efficiency. But what comes next is thinking about all the humans involved in that process, and what they touch and how they work. I think once AI starts to integrate with that activity, and act at that level within the enterprise, this will truly change how we think about what a business is meant to do. I’m a little biased in this, but you might go so far as to say we are entering the era of the cognitive corporation, where man and machine at all levels of the enterprise will operate in a synergistic fashion to solve problems, each learning from the other.
If you think about most business processes and most problems that humans find interesting to solve, they are heterogeneous. They move through a pipeline of different specialists that look at separate pieces or provide specific oversight to balance specialized objectives. If I can couple my engineering and sales activities at the enterprise level, and use AI to mediate the trade-offs of both of those objectives, and I have these people processes synchronized with machine processes, it gives me the ability to learn how these two potentially juxtaposed business ends are coupled, where they’re divergent, and what kind of switches I can flick or knobs I can turn to make the net positive of these two forces all the greater.
DevOps.com: Is artificial intelligence intended to replace humans or help them do their jobs?
Abdallat: In some places, as with any kind of automation, you will see some jobs go away. But the labor that was there before finds a new role working with AI, and I think those new roles, especially at the level of knowledge work, will be very interesting.
As good as artificial intelligence systems are, they’re not going to set our objectives. They can move toward them, and think outside the box, which is one of things that we work hard to do at Beyond Limits. But being able to deal with the nuances of problems is still something that humans excel at. So, finding the things that are worth teaching to AI, to learn and to figure out, that’ll still always be a job in the hands of humans. I imagine that’s also when it gets kind of cyclical. I’m going to learn something, the machine’s going to discover a new pattern, we’ll optimize an approach that I didn’t think could be optimized to such a degree. That’s going to give me new questions, which makes me give it new training data, and the process continues like that.
DevOps.com: What types of software engineers are now or soon will be in demand to support AI, machine learning and this new industry?
Abdallat: One of the things we’re starting to see is a change in job definition. You probably hear about data scientists and machine learning scientists. What we’re going to see more of is taking that science and flipping it with engineer. There’s a ton of stuff in the laboratory that works and is great. And scientists can write papers and come up with nice coefficients for polynomials that solve problems. But at the end of the day, there’s an infrastructure that makes all this work. So, we will probably begin to see new job titles emerge, like data engineer. A data engineer is maybe the bridge between the work that the data scientist does and the infrastructure in which his data lives. He or she is much more of a software engineer but has some knowledge of the data science workflow and algorithms germane to data and AI work.
Data engineers are becoming more important, and we’re finding they fit somewhere between IT and the business. I think that’s important. It’s the same with machine learning people. For example, the actuary of the future will simply be a data scientist who works in insurance. Systems analysts will gradually become systems data scientists. Of course, to make all this stuff work securely, we’ll probably see a ballooning of the specialized security people to support the work that goes into the systems engineering. Unfortunately, the world is more adversarial than we would like.
DevOps.com: Does AI present a cultural challenge to enterprises?
Abdallat: Earlier big data solutions and the fact that AI looks promising for big data have paved the way. AI asks for similar machineries, although it can be used in smaller footprints when available. Culturally, some IT organizations are more progressive than others. Some like to play with new toys and would be stoked to get this down, assuming they have the budget, and AI may be enough to motivate them to allocate budget.
In other cases, there may be entrenched opposition to change. But it’s such an exciting field that whenever you start talking about artificial intelligence, you’re going to get buy-in. Some healthy skepticism is a good thing too. You can try to channel it into constructive ways of alleviating the concerns that people bring up, and assess whether they’re just nay-saying the next new thing or they’re aware of a valid institutional or physical barrier to success.
AJ Abdallat is a serial entrepreneur who worked on artificial intelligence (AI) projects and commercializing smart sensors at the NASA Jet Propulsion Laboratory at California Institute of Technology (Caltech) from 1998 until 2011. Later he founded, launched and ran several spinoff companies from Caltech/JPL, doing AI work in support of the space program and various defense agencies. NASA, for one, has used AI in its deep space missions and on the Mars Rover for more than 10 years.
In 2014, Abdallat cofounded Beyond Limits, which secured licenses to NASA AI technology with the goal of commercializing the technologies. Beyond Limits owns exclusive licenses to 42 blocks of sophisticated intellectual property (IP) developed through NASA R&D investment, a $150 million AI-technology head start under the aegis of Caltech’s Office of Technology Transfer and Corporate Partnerships program.
Beyond Limits enhances the AI IP developed for NASA/JPL, and drives new IP and innovations through its mission to bring advanced AI technology to commercial applications. The company is an AI leader in cognitive technology that goes beyond conventional AI, binding deep learning and machine learning tools together with symbolic AIs to emulate human intuition.
We interviewed Abdallat, who is CEO of Beyond Limits, while researching the story, “AI Delivering on the Business Analytics Promise.” He offered a lot of interesting commentary that just didn’t fit that earlier story. With AI poised to potentially revolutionize business, the fact that Abdallat’s career has bridged the gap of advanced AI science and commercializing it makes his insights fascinating on topics including digital transformation, IoT, big data and what AI can and can’t do.
Note: This is Part 1 of a two-part series.
DevOps.com: What three key things about AI should every C-suite member know?
Abdallat: No. 1 is understanding the transformative power of AI. Most of the AI out there today is not going to replace a human. There is a balance needed between understanding the promise of AI and not being unduly fearful of losing their jobs due to the much-publicized peril. AI is going to advance a lot of progress that’s already in place, not necessarily upend everything. So yes, there are transformative solutions in AI, but I think there are lots of places for it to plug in with what you’re already doing today, in ways that can considerably augment what is done, and free up time for individuals in your organization to turn their minds to the harder problems that AI hasn’t even cracked the shell of yet.
N0. 2 is business practicality. For every AI algorithm, there are 100 articles telling you that it’s a good thing or a bad thing. It either doesn’t matter or it’s going to change your life. I think one of the things that’s important to realize is that AI needs to start with a problem to solve. So, being cognizant of which of your business problems have the biggest potential payoff in their resolution is how you should think about applying AI, as opposed to what AI would be good at solving. The chances are, if you have a problem, AI can shed some light on it. Prioritizing how you describe that problem will be more important than selecting the right AI hammer to swing at a particular nail. Understanding what your problem really is helps artificial intelligence experts devise solutions for you.
AJ Abdallat is co-founder and CEO, Beyond Limits. He’s an AI engineer and entrepreneur.
The third thing the C-suite should know about AI is timing. The time to start thinking about this is not now, it was yesterday. Companies that started experimenting with AI a few years ago are reaping the rewards today. One large, recent study shows that 75 percent of surveyed executives say that AI will be “actively implemented” in their companies within the next three years. So, it’s happening right now.
A lot of people reading the news can’t help but wonder maybe today should be the day to act, because every day I read about something new. In fact, the sooner you can modernize your digital infrastructure, the sooner you can bring AI to address your business issues. You need to level the playing field with potential competitors. Today is the day to upgrade your networks to get more digital, get more instrumentation. The benefit is it will optimize a lot of what you’re doing today, even without AI, but it also makes the AI integration possible. AI can’t work if it can’t see the data.
DevOps.com: Does AI just pave the cow path or create a whole new business model?
Abdallat: It depends on your perspective. AI can help to automate a lot of things, and that would be paving the cow path. But in general, AI can help humans see problems in new ways. Let’s say I have a bunch of data and I don’t know what’s important in it. This is the kind of thing where we used to have pre-formed opinions, where we would have a group of statisticians help us answer. Now, with an afternoon and an algorithm I can get you a hypothesis of what’s important in your data. Is that automation? I don’t know, it’s automation of ideation, which is certainly more esoteric, and that’s where we’re headed. But I think there’s probably room for both. AI will achieve new business models, but we’re also trying to get AI to do things we’ve been doing forever. It’s really a function of how. That’s what AI changes: how we do things, not so much why. Why you should change things is ultimately something the C-suite should determine.
DevOps.com: CEOs make decisions about the future. Could artificial intelligence help?
Abdallat: Forty-six percent of executives are fearful that their business may get disrupted by an AI-powered startup, rather than a direct competitor. So, it’s a competitive necessity. Today, big companies are using AI for analytical, predictive, diagnostic and industrial control purposes. Some AI touches ordinary people through services, but they probably aren’t aware. What we’re looking at more and more is: How do I stay aware of a big stream of data and change my hypotheses as that stream comes online? There are companies looking at this, like Beyond Limits. It will become more common, but it’s going to be less about data at rest and more about data in motion. How can I quickly translate the data that I find for my search into some kind of action? That is the next big step for big data, analytics and artificial intelligence.
DevOps.com: People say lack of data and missing data are issues. Is that true?
Abdallat: Yes. One of the things we bump up against is, What happens when I don’t have all the data, or we missed some of it? A lot of machine learning approaches are bumping into this problem as well, and what they need is human intuition or expertise to guide them over those initial stumbling blocks. That’s when the unconventional comes into play.
IoT is an excellent example of missing data and so on. The internet of things (IoT) brings us new orders of magnitude of data that we need to analyze at higher frequency time scales than we’ve been asked to do before. IoT also forces us to do it out at the edge, away from the super computer that lives in the cloud that can help us answer a bunch of questions efficiently. It’s challenging to make decisions quickly enough at the edge without the ability to go back to the cloud. Because here, the speed of light without exaggeration is a factor. You’re not going to be able to get inside that decision loop if you’re waiting for light to travel back to the server farm and out to the edge again with the information needed to make your decision. You will have to bind some of the intelligence to the edge to be inside the control loop, so to speak.
IoT also relies a good deal on sensor data that has far less redundancy. That means you’re going to get data drop out. On a single installation, some of the sensors just turn off. Others might be generating data that we know, with some prior knowledge, is out of spec; we know not to believe it. These are the kinds of problems you’re going to have when you interface with industrial machinery and lightweight distributed sensors at scale. The challenge is how to deal not only with the new stream of data, but also the inconsistency in its delivery.
Watch for Part 2 of this series, which will cover big data/unstructured data, business process issues, human factors, and where AI is headed.