BootstrapLabs To Speak at The SuperReturn US East Private Equity Venture Capital Conference

BootstrapLabs Co-Founder, Benjamin Levy, will be speaking at the SuperReturn US East Private Equity Venture Capital Conference in Boston, on June 11th, 2019.

The conference will bring together over 450 of the leading players in Private Equity and Venture Capital from the West Coast, for an unparalleled opportunity to meet, learn, and create new business ventures.

Ben, along with other leading industry experts, will share their strategies and discuss key issues during a session called: A.I. will radicalize VC and PE.

More about Ben Levy:

Ben Levy is the Co-Founder and Managing Partner of BootstrapLabs, a leading Venture Capital firm based in Silicon Valley and focused on Applied Artificial Intelligence. Ben is a repeat entrepreneur who launched, built, and exited two startups in the financial technology space. Praedea Solutions, a data mining and machine learning startup acquired by Mergent in 2006, and InsideVenture, an information portal for venture-backed pre-IPO companies and institutional investors, acquired by Second Market/NASDAQ in 2009.

Early in his career, Ben was an Investment Banker who advised CxOs of Fortune 500 companies. Over a period of 10 years, Ben helped his clients raise over $300M and close over $5B in M&A transactions. Ben worked at Lazard, SG Cowen, Houlihan Lokey, Wedbush Securities, and QuantumWave Capital.

Ben is a member of the AAAI (Association for the Advancement of AI), and a frequent keynote speaker on innovation, technology investing, entrepreneurship, and artificial intelligence in the US, Europe, and Asia.

 

AI, Geopolitics, and National Security:

Your Information and Your Nation

Hacking is on the world stage again this week after Julian Assange, founder of WikiLeaks, was arrested in London and accused by U.S. authorities of conspiring with former Army intelligence officer Chelsea Manning leading to what is described as “one of the largest compromises of classified information in the history of the United States.” While some see Assange’s case as one strictly about freedom of speech and others see it as a question of security, his arrest brings the reality of hacking back into the spotlight, reminds governments and citizens alike about the potential vulnerability of the information they have stored digitally.

Experts suggest that this vulnerability can be pinned on the lack of attribution models, an integrated identity, and the complexity of establishing global privacy and ethical standards within the core building blocks of the Internet. While the general public watches tensions between super-powers mount on the international stage, trade tensions escalate, and the frequency and severity of cyber attacks amplify, what most don’t know is how artificial intelligence is playing an increasing role and intensifying what is at stake. This, of course, has not been lost on those in both the private and public sector who understand that how governments and the private sector engage with AI may very well dictate their future economic strength and security posture.  And yet, while many countries are active in AI, only a few have a planned national strategy for employing the technology.

As nations continue to invest in the implementation of AI, geopolitics will change irreversibly. But how remains to be seen. Experts from the United Nations and World Economic Forum explain what plans nations are already making at this year’s annual BootstrapLabs’ Applied AI Conference.

It is a critical time for nations as AI technology is rapidly developing and has already contributed to the exacerbation of state actors, terrorist organizations, and criminals’ political and ideologically motivated use of the internet for financial gain and power grabs. And when projecting into the future, some think things will only escalate, “Eventually geopolitics will no longer be territorial…but will reside mainly in the neuro- technological complex. We need to prepare ourselves for fierce power battles… plots, power grabs, secessions, manipulations, traitors and malevolence that will make the Wannacry and Petya viruses of spring 2017 seem harmless in comparison.”

But AI can also be applied as a method to not only alleviate such threats, but also strengthen our existing digital infrastructures and create stronger platforms for the future stability, economic prosperity, and security of our society, companies, and citizens. In a fireside chat at AAI19, specialists from U.S. Department of Homeland Security, Quantum Vault Inc., Atlas Organization, and MobiledgeX join to discuss what the industry can anticipate in the next few years across the security domains that AI will impact.

To further unpack the relationship between AI and national security, panelists from the Technology for Global Security, U.S. Department of Homeland Security, and Defense Innovation Unit discuss key topics covered in the annual unclassified US National Intelligence Report and what they are doing within their respective organizations to accelerate the discovery, development, vetting, adoption, and deployment of AI and other new technologies in service of protecting American lives and interests around the world.

Want to learn more about how to become engaged, what you can do, where you should look to get involved and have a broader impact, and how the Defense Innovation Unit and Department of Homeland Security are making it easier for companies to get engaged and navigate the federal marketplace? Then join us this Thursday at BootstrapLabs Applied AI Conference.

Trains, Planes, and Automobiles:

 

The Necessity of Real-Time Processing in Autonomous Vehicles

When thinking about autonomous vehicles, it’s easy to focus on driverless cars, how your commute to work will change, how your drives with the family will be filled with board games instead of “are we there yet?” The technology has been parodied in the HBO show Silicon Valley, is roaming the streets of San Francisco and Hamburg, and is the unforgettable protagonist in a vehicular accident that led to a man’s decapitation.

Whether you are trepidatious or excited, self-driving technology is inevitable. For the folks working to get the technology ready for wide-spread deployment, the trick is making sense of the road in real time, not if the driver’s seat can rotate to face backwards.

Ultimately, the concept of a driverless vehicle is simple, a vehicle that drives itself. But the mechanics of how that vehicle drives all by itself is where the challenge lies. In order to work without human intervention, driverless vehicles are “permanently surveying the road and sending relevant bits of information up to the cloud,” explains Christoph Grote, SVP of Electronics at BMW. But the trick is knowing and catching the “relevant” information. And this is not easy.

AEye, an artificial perception technology company, focuses their work specifically in the space of creating tech that is able to abstract and extract meaningful and necessary information from a car’s environment. Namely, they are creating AI-enabled sensors that enable vehicles to “think like a robot, perceive like a human” – seeing, classifying, and responding to an object, whether it is a parked car, or a child crossing the street, in real time and before it’s too late.

What AEye understood, is that in order to create technology that can perceive like a person and think like a robot they needed a rocket scientist (almost) literally. The Chief Scientist at AEye, Dr. Allan Steinhardt, serves this function. Dr. Steinhardt is an expert on radar and missile defense, including ground moving target indicator radars (so, a radar and missile scientist if you want to get nit-picky about the rocket analogy); space surveillance; and he is the former Chief Scientist for DARPA.

At this year’s BootstrapLabs Applied Artificial Intelligence Conference, Dr. Steinhardt delivers a keynote on how transportation AI is uniquely different from other applications of AI. In addition to exploring how AI is augmenting the collection and interpretation of environmental data the car must process, he will also address the very environments these autonomous vehicles will be driving in: the cities of the future.

It is easy to get fixated on the gadget. We are primed to want the newest artifact of technology, be it the newest phone, scooter-rideshare, or smart speaker. What is easily forgotten is the network that these technologies rely on. Up until now, the landscape of things needing internet connectivity has been able to rely on either WiFi or 4G. Autonomous vehicles, and the reams of data they are reliant on processing and distributing, require much more bandwidth. Christoph Grote explains that driverless cars are continuously gathering data from their environments, “generating a true, real-time map of a car that is pushed down to all the other cars…autonomous driving is not the capability of a car, it is really about swarm intelligence.” And in order to do this, autonomous vehicles will need to be able to connect to 5G.  

The cities of the future will be increasingly optimized to support automated functionality, including autonomous driving. But how, you ask? Join Dr. Allan Steinhardt’s keynote at AAI19 to find out.

Human Capital in the Age of Artificial Intelligence

Will Your Job be Taken Over by Robots?

In 1589, a British inventor introduced his invention, the Knitting Machine, to the Queen of England expecting to be granted a patent. Instead, she replied, “Consider thou what the invention could do to my poor subjects. It would assuredly bring to them ruin by depriving them of employment, thus making them beggars.”

The fear that technology will displace workers is not a new fearbut it is certainly a trending-fear, with a web app to match. Workers are not unfamiliar with skepticism about how new technology will change their job or make it obsolete. But the true fear the workforce has about new technology, especially automation, is not about losing a job, but about having an employable skill set. And from there, it is a slippery slope to worrying about becoming destitute.  

In 2013, researchers at the University of Oxford estimated that 47 percent of US employment is at “high-risk” for complete automation within two decades. Should their estimations be correct, we can expect that roughly 65 million Americans will not only be out of a job, but will have been asked to leave their jobs because their skill set had become obsolete, taken over by automation. Given that these are conservative estimates, perhaps it is time to get worried.

But not so fast.

Despite the dreaded prediction, that over 500 million people worldwide will lose their jobs in the first wave of the Fourth Industrial Revolution (4IR) to automation, experts agree that people, with their inherently human social savvy and creativity, will continue to remain the main drivers of innovation.

At this year’s BootstrapLabs Applied Artificial Intelligence Conference, experts from companies working to manage the transition to automation and insiders at companies like Facebook, Adobe, and Microsoft working internally to prepare for this upcoming shift in their workplaces, will discuss the Future of Work in the Age of AI.

Industry thought leaders, like Oliver Brdiczka who is building Adobe’s AI assistant and Noelle LaCharite who is working to educate developers for Microsoft about AI, are dedicated to making AI understand and respond to human behavior. Rather than sacrificing human intelligence to the might of AI, as science fiction might have us believe is our inevitable future, they are focused on harnessing human intelligence. This new wave of AI, called Contextual and Conversational AI, trusts that artificial intelligence is hardly intelligent without human intelligence, cementing the future for human capital. In fact, valuing human intelligence aids in securing human capital’s place as the most valuable resource of any company.

And yet, even if human intelligence dominates work culture, the working landscape is still destined to change in the face of artificial intelligence and machine learning technology in the workplace. And it’s going to change fast. In fact, it is the industries that are most increasingly reliant on automated work, that will need to most-quickly consider how to adapt in stride with the developments of AI and how to rethink frameworks for sound management in a world of work supported by automation, lest failure. That’s where Dinkar Jain, Head of Machine Learning for Facebook Ads, is focusing his attention: the future of management and business practices in the Age of AI.

Despite the centuries-old hesitations of the labor force surrounding the adoption of new technology, historical data shows that technology has actually created more jobs than it has displaced or made obsolete.

But the big question in a time where artificial intelligence and machine learning are leading rapid developments in automation is: will it be different this time?

Find out from the experts, and learn how to prepare and transition today’s human capital into their roles of tomorrow at AAI19.  

 

Get your tickets today, For a limited time, get 50% off on registration using promo code: AAI1950Percent

BootstrapLabs AAI18 Keynote and Fireside Chat – SoftBank Robotics AI Vision 2020

Don’t miss this year’s Applied AI Conference 2019

on April 18th in San Francisco

Join thought leaders leveraging AI applications to build the future of enterprise, corporations, governments, and society as we know it.

For a limited time, get 50% off on registration using promo code AAI1950Percent

 

 

In the meantime, please enjoy some of our favorite sessions from 2018:

Speakers:

  • Steve Carlin, Chief Strategy Officer, SoftBank Robotics
  • Ben Levy, Co-Founder, BootstrapLabs
  • Doug Aley, Chief Revenue Officer, Ever AI

During this session, the speakers discussed AI in robotics, and where SoftBank sees the future going in the next few years, some of the key challenges in hospitality and how companies can partner with SoftBank and the 2020 Vision.

Some of the key takeaways from the session are:

  • Contextualizing data is going to be a key differentiator in AI technologies moving forward like conversational UX and deciphering customer intent.
  • Robotics has the capability to disrupt the key revenue-driving experience for over 20 trillion dollar industry.
  • Be hyper focused in the use cases your technology will be able to solve instead of covering a wide range.

About Steve Carlin:
Steve Carlin leads SoftBank Robotics America and is the global Chief Strategy Officer. In this role, he acts as the General Manager for the Americas region and oversees global marketing, product and strategy. Carlin most recently came from Facebook where he held the role of Global Head of Strategy – Gaming. Prior to Facebook, Carlin was the Senior Director of Marketing and Insights for Ubisoft. He also held a series of roles in sales, shopper marketing, brand management, and strategy at Energizer and Procter & Gamble. He holds a BA in Geology from Miami University in Oxford, Ohio, and an MBA in Marketing and International Business from Goizueta Business School. He has also studied at Cornell, HEC business school in Paris and the UIBE business school in Beijing.

About Ben Levy:
Ben is a Co-founder and Partner at BootstrapLabs, a leading Venture Capital firm based in Silicon Valley and focused on Applied Artificial Intelligence. Prior to BootstrapLabs, Ben was repeat entrepreneur who launched, built, and exited two startups in the financial technology space, Praedea Solution and InsideVenture. He also was a Technology, Media, and Telecom Investment Banker who advised startup founders and CxOs of Fortune 500 companies on corporate strategy, financing, and M&A. Over a period of 10 years, Ben helped his clients raise over $300M from institutional investors and close over $5B in M&A transactions. Ben is a frequent keynote and panel speaker on innovation, technology investing, entrepreneurship, artificial intelligence, and globalization in the US, Europe, and Asia.

About Doug Aley:
Doug Aley has spent his career helping to found, lead, and scale startups. He is currently Ever AI’s CRO and a principal at Atomic Ventures. Prior to Ever AI, he held positions early in his career at Amazon, was VP of Marketing, Product, and Business development at Jott Networks, helped Zulily scale from $100M to $700M as VP of Product and Corporate Development, held the same role at Room77, and started and led Minted’s digital growth team. Mr. Aley holds a BA from Stanford University and an MBA from Harvard Business School, and lives in Greenbrae, CA with his wife, Susan, and their two boys.

AI Policy, artificial intelligence

BootstrapLabs AAI18 Panel – AI Policymakers: the Need for Public/Private Partnership

Over the next several weeks we’ll be releasing the videos from the sessions from the BootstrapLabs Applied AI Conference 2018. The yearly conference organized by BootstrapLabs, a leading Venture Capital firm focused on Applied AI, that brings together over 800 members of the Artificial Intelligence community for a day of incredible speakers and exciting conversations.

Join the Applied AI Conference 2019, on April 18, in San Francisco

Join thought leaders leveraging AI applications to build the future of enterprise, corporations, governments, and society as we know it.

A limited number of tickets are currently on sale at the Early Bird price ($1040 off) ENDING MARCH 15TH!

 

Moderator: Jane Macfarlane, CEO, Seurat Labs / Director – Smart Cities, UC Berkeley

Speakers:

  • Kay Firth-Butterfield, Head  of AI and Machine Learning, World Economic Forum
  • Norma Krayem, Sr. Policy Advisor and Co-Chair – Cybersecurity and Privacy, Holland & Knight
  • Raj Minhas,VP – Interaction and Analytics Lab, PARC

During this session, the panelists discussed AI in the context of regulation, the role of government in fostering and leveraging emerging technologies and the reasons why we need better public/private collaboration.

Some of the key takeaways from the session are:

  • Fostering and creating explainable models is going to be crucial to get government support and foster collaboration in the AI space.
  • Standards, certification, protocols, partnerships and process or outcomes based scalable laws are some of the avenues we need to explore to “regulate” AI.
  • Open, honest conversations are necessary between technology companies and regulators, it’s important to educate them on how the technology works and the real risks with integrating to different systems.

About Jane Macfarlane:
Jane Macfarlane is the CEO of Seurat Labs and is also the Director of Smart Cities and Sustainable Mobility at the University of California at Berkeley. Dr. Macfarlane has over 30 years of experience in high performance computing, data analytics and geospatial mapping. She has held various roles responsible for directing industry research groups including: Chief Scientist and Head of Research for HERE, VP of Process Engineering at Imara, and Director of Advanced Technology Planning for OnStar at General Motors. She has authored 26 patents, primarily in geospatial data analytics. She holds a Ph.D. in Mechanical Engineering from the University of Minnesota. Currently she is leading a DOE National Laboratory effort focused on the use of High Performance Computing to address Big Data Issues in transportation systems.

About Kay Firth-Butterfield:
Kay Firth-Butterfield is the Head of AI & ML at the World Economic Forum and is a Barrister-at-Law and former part-time Judge in the UK. She is an Associate Fellow of the Centre for the Future of Intelligence at Cambridge and Fellow of the Robert E. Strauss Center on international Security and Law at the University of Texas. She is Vice-Chair of the IEEE Initiative on Ethical Considerations in AI and Autonomous Systems. She is one of Robohub’s top 25 Women in Robotics and co-founded AI-Austin, AI-Global and the Consortium for Law and Policy of AI and Robotics.

About Norma Krayem:
Norma Krayem is a Senior Policy Advisor and Co-Chair of the Holland & Knight Global Cybersecurity and Privacy Team. She brings more than 20 years of experience within the global policy-making arena including executive-level positions in the U.S. Departments of State, Commerce and Transportation, and as a consultant at the Federal Emergency Management Agency (FEMA). She works on a daily basis with the White House, Executive Branch and Congress on a host of matters, including Homeland Security, Commerce, Defense, Treasury, Transportation among others. She is a member of The Chatham House and served on the prestigious CSIS Cybersecurity Task Force from 2015-2017.

About Raj Minhas:
Raj Minhas is Vice President and Director of the Interactions and Analytics Lab (IAL) at PARC. Research in IAL focuses on people and their behaviors. Raj joined PARC in September 2013 as the Program Manager for Prognostics and Health Management and was responsible for the strategy and execution for the commercialization of the related technologies. Prior to PARC, he was the Director of Xerox Research Center India where he led its growth, development, and outreach for two years. Raj earned his Ph.D. and M.S. in Electrical and Computer Engineering from University of Toronto and B.E. from Delhi University. He has eight patents and six pending patent applications.

BootstrapLabs Applied AI Workshop: AI and Human Capital

 

Date and Time: Wednesday, January 23, 2019

Location: San Francisco

Registration: This event is INVITE ONLY. You can request more information at events@bootstraplabs.com

Come join us to learn more about how Artificial Intelligence will revolutionize the enterprise of tomorrow, and how Applied AI solutions can help executives and leaders around the world better manage, attract and engage their employees and customers.

As the Fourth Industrial Revolution unfolds, companies are seeking to harness new and emerging technologies to reach higher levels of efficiency and compete on a global scale for innovation, customers, and talent.

Artificial Intelligence is here to stay, and will drastically change the way we do business and live. The economic and social impact of artificial intelligence technologies will ultimately depend on how quickly organizations and institutions are able to learn, adapt, control, and ultimately wield these powerful technologies for the greater good.

Over the last 30 years, the allocation of market capitalization value for corporations has shifted from 80% being assigned to tangible assets (machinery, plants, buildings, etc), to 80% being assigned to their intangible assets (brands, intellectual properties, trade secrets, business processes, and talent).

They are many opportunities and challenges ahead, and as a Venture Capital firm focused on Applied AI technologies, BootstrapLabs believes that the success of any business today, more so than any other time before, will ultimately be determinate by their ability to not only adopt AI solutions across their entire business but also, and maybe most critically, apply AI to known critical factors such as attracting, retaining, developing and managing their pool of Human Capital as well as delighting their customers.

Agenda:

  • 5:00pm – 5:25pm: Registration & Networking
  • 5:25pm – 5:30pm: Greetings and Introduction by BootstrapLabs
  • 5:30pm – 5:45pm: “Applied AI and Human Capital Investment Trends”, Ben Levy, Co-Founder & Managing Partner, BootstrapLabs
  • 5:45pm – 6:00pm: “Bringing AI in the Enterprise – Legal Considerations”, Natalie A. Pierce, Partner, Littler
  • 6:00pm – 6:20pm: “Scaling your Enterprise Conversational Knowledge”, Jonathan Eisenzopf, CEO, Discourse.ai
  • 6:20pm – 6:40pm: “Corporate Culture 2.0”, Sabrina Atienza, Co-Founder & CEO, Stealth Mode Startup
  • 6:40pm – 7:30pm: “Applied AI and Human Capital Panel + Q&A”, moderated by Debi Hirshlag, Advisor and former VP, HR at Workday, Flex, Trimble & Ariba
  • 7:15pm – 8:00pm: Networking Reception

Speakers:

Ben Levy, Co-Founder & Managing Partner, BootstrapLabs

Jonathan Eisenzopf, CEO, Discourse.ai

Natalie A. Pierce, Partner, Littler

 

Sabrina Atienza, Co-Founder & CEO, Stealth Mode Startup

Debi Hirshlag, Advisor and former VP, HR at Workday, Flex, Trimble & Ariba

Thank You To Our Host

Image result for littler mendelson logo

b.telligent and BootstrapLabs partner to accelerate the adoption of AI technology among German and Swiss Corporations

SAN FRANCISCO, CALIFORNIA, US and MUNICH, GERMANY, Dec. 20th, 2018 /PRNewswire/ – b.telligent, a Munich and Zurich based premier data science and business intelligence management consulting company, and BootstrapLabs, a Silicon Valley based venture capital firm focused on Applied Artificial Intelligence, today announced the formation of a strategic partnership to accelerate the deployment of AI technology among b.telligent’s existing and future corporate customers.

Accenture estimates that AI has the potential to boost rates of profitability by an average of 38% and could lead to an economic boost of US$14 trillion by 2035 globally. With so much at stake, and a possible reallocation of wealth from traditional players to digital first players, Germany and Switzerland are among the countries with the most to lose if their multinational corporations fall behind during the AI revolution.

“We are excited to partner with b.telligent,” said Nicolai Wadstrom, Founder, CEO, and Managing Partner of BootstrapLabs. “Klaus and Sebastian have assembled a great pool of talent with deep domain knowledge expertise in data warehousing, data management, data science, and data strategy that helps their clients successfully transition into the new data driven world. As such, they represent an ideal partner to roll out some of our portfolio companies’ products across their client base of over 300 companies, and in doing so, accelerate the adoption of innovative AI solutions for Germany and Switzerland, and some of their leading multinational corporations.”

For the past 3 years, BootstrapLabs has been exclusively investing in Applied AI technologies and has assembled an exciting portfolio of 22 companies, each looking to solve hard and meaningful problems in multibillion dollar industries.

“Startups often waste time and capital figuring out which of the several large corporations they are talking to today i) can quickly and fairly evaluate their solution, ii) has the budget to purchase their solution in the next 3-6 months, and iii) is ready to scale that solution across their entire organization,” said Benjamin Levy, Co-Founder and Managing Partner of BootstrapLabs.

“b.telligent is in an incredible position to accelerate BootstrapLabs’ portfolio companies’ revenue generation, as we not only have our customers’ trust (such as Telefónica, Car2Go, Puma or BSH), but we have an intimate understanding of their readiness level as well as often act as an extension of their team, managing the very data that is required for these AI solutions to become valuable to our clients,” said Sebastian Amtage, Managing Director of b.telligent.

“We believe that Artificial Intelligence poses a large threat, as well as unprecedented opportunity for every company, and we look forward to working closely with BootstrapLabs, their portfolio companies, and their large community of AI experts to support our customers on their journey to apply Artificial Intelligence,” said Klaus Blaschek, Co-Founder and Managing Director of b.telligent.

 

Media Contact

 

BootstrapLabs

press@bootstraplabs.com

 

b.telligent GmbH & Co. KG

pr@btelligent.com

Greta Wenske

 

About BootstrapLabs

Founded in 2008, BootstrapLabs is a leading Venture Capital firm based in Silicon Valley and focused on Applied Artificial Intelligence. We invest in founders that dream big and are solving today’s hardest problems by applying artificial intelligence to shape a better future for all.

BootstrapLabs works closely with some the world’s most prominent families and their multinational corporations to actively invest in artificial intelligence (AI) and machine learning (ML) startups targeting large global markets including Industrial Manufacturing, Transportation, Logistics, FinTech, Enterprise Productivity, Cybersecurity, and Healthcare.

BootstrapLabs is often the first institutional money and acts as a lead investor in the early stages, with follow-on capital at the growth stages.

Select portfolio companies include AEye, Mendel, Qurious, Vidora, Sibly, Myia Labs, Indus.ai, iUNU, SmartEar, Nodle.io, Roger, Prezi, Pryon, Trusted Insight, and AngelList.

BootstrapLabs leverages its large community of over 40,000 Applied AI experts, entrepreneurs, and developers to support its portfolio companies and investment strategies.

For more information visit: https://bootstraplabs.com

 

About b.telligent

b.telligent is considered one of the market leaders in Germany for business intelligence consulting projects. The main objective of b.telligent is to enable clients to tackle the challenges of the present and upcoming digital transformation. In order to meet those challenges, it is important for b.telligent to support its clients in the deployment of some of the most advanced data science techniques such as artificial intelligence and machine learning while at the same time ensuring these ventures are based on solid data fundamentals.

Additionally, b.telligent continuously strives to optimize clients business processes by applying knowledge gained through consolidation and analysis of business information all resulting in increased margins, lowered cost and improved risk management.

Our customers are leaders in their sectors, such as telecommunications, financial services, trade, and the industry. Since 2004, over 300 clients have benefited from our “data-first” approach. With over 160 employees spread across six offices, we are passionate about joining our clients in establishing and advancing their data-driven business models.

For more information visit: https://btelligent.com

BootstrapLabs AAI18 Keynote and Fireside Chat – Death of Moore’s Law

Over the next several weeks we’ll be releasing the videos from the sessions from the BootstrapLabs Applied AI Conference 2018. The yearly conference organized by BootstrapLabs, a leading Venture Capital firm focused on Applied AI, that brings together over 800 members of the Artificial Intelligence community for a day of incredible speakers and exciting conversations.

Speakers:

  • Tom Campbell, Founder & President, FutureGrasp, LLC
  • Madhav Thattai, Chief Operating Officer, Rigetti Computing
  • Sateesh Kumar, Founder, Pathtronic

During this session, the speakers discussed the future of computing in the age of AI, Neuromorphic and Quantum computing and edge use cases and applications.

Some of the key takeaways from the session are:

  • The death of Moore’s Law as originally define has given birth to a variety of them depending on the technology leveraged: neuromorphic, quantum, among others.
  • There’s a shift in the industry from bigger companies to focus on creating their own use-case-specific chip architecture.
  • We need to bring more power to edge computing to really provide AI solutions that work and leverage insights in real time.

About Tom Campbell:
Thomas A. Campbell, Ph.D.is the founder and president of FutureGrasp, which advises organizations on trends and impact of emerging technologies, and a special advisor to BootstrapLabs. Prior to this, Tom was the first National Intelligence Officer for Technology with the National Intelligence Council. Tom holds a Ph.D. in Aerospace Engineering Sciences from the University of Colorado at Boulder, and a B.E. in Mechanical Engineering from Vanderbilt University.

About Madhav Thattai:
Madhav Thattai is the COO of Rigetti Computing, a full-stack quantum computing company based in Berkeley, California. Prior to joining Rigetti in 2015, Madhav worked at Dell Computing for eight years in a variety of roles, most recently as Director of Product Operations. Madhav holds a Master’s degree in management from Stanford University, a Master’s degree in industrial engineering from the University of Michigan, and a Bachelor’s degree in mechanical engineering from Birla Institute of Technology and Science in India.

About Sateesh Kumar:
Sateesh is the Founder and CEO of Pathtronic Inc, a silicon valley start-up company focused on building revolutionary AI Processing Unit. Sateesh is a visionary and seasoned entrepreneurial executive and innovator with broad technology background. He has been advisor to multiple corporations, start-ups, incubators, and universities in the area of AI, Autonomous Vehicles and Drones, and more. As a former innovation and incubation executive at Cisco, he pioneered and led various initiatives in the area of IOT, Automotive and Connected Vehicles, Industrial Switching and Automation, Smart Cities, Mobile and Wireless, Fog Computing, Big Data and Machine Learning and more. Prior to Cisco, he founded and led multiple Silicon Valley venture funded start-ups. He has published extensively in international journals including IEEE/ACM and holds dozens of granted patents.

Banish the Darkness with Artificial Intelligence

The Need

Most everything we do in life requires electricity. Transportation, farming, homes, businesses, computing—they all necessitate the efficient movement of electrons from a power production source to an energy use site¹. Unfortunately, since Thomas Alva Edison first illuminated a Menlo Park street in 1879 – thus banishing the darkness 2 – the  demands humanity has placed upon energy utilities have skyrocketed and consequently at least parts of our energy grid have become brittle and prone to failure. Moreover, the complexity of operating local, regional and national systems that are susceptible to cyber-attacks has made electricity a critical topic for national security.

World population has quintupled since the first sustained artificial light in the late 1800s. With more than 7.6 billion people now teeming on our planet and all of us needing increasing amounts of energy 4, we cannot rely anymore on simple dynamo generators creating electricity and sending it straight to the desired location. On the contrary, our electricity grids are highly complex with numerous power sources (coal, gas, oil, nuclear, and renewables—biomass, solar, wind); switching and amplifying stations; transformers; above and below ground wiring; and storage batteries. Unsurprisingly, even considering conservative trends, our energy use is growing rapidly:

“In the New Policies Scenario, global energy needs rise more slowly than in the past but still expand by 30% between today and 2040. This is the equivalent of adding another China and India to today’s global demand.” 5

Moreover, our already highly electrified society will become even more dependent on charged electrons with new technologies. The Internet of Things (IoT), which requires cloud and edge computing at massive scale, is forecasted to exceed 75 billion devices connected to the internet by 2025 (up from 23 billion presently).6 Research into autonomous vehicles is rapidly approaching deployment stages. Testing underway in Phoenix, AZ and Pittsburgh, PA may be halted temporarily because of bad algorithms causing accidents or irregular policies, but other countries are not waiting around for the United States to perfect driverless cars. China is building cities specifically designed for autonomous vehicles.The Hyperloop – Elon Musk’s dream of accelerating people and cargo in a vacuum tube to near the speed of sound – is being tested in the United States and Europe.8

Population growth is also spurring construction of whole cities from scratch; examples abound in Asia. China plans on constructing a new city the size of Chicago (2.7 million people) with the latest technologies, and thus high energy demands.5 With support from Singapore, the Indian state Andhra Pradesh is building a new capital. “It will be a stupendous 7,235 square kilometres, 10 times the size of Singapore’s own 716 square kilometres.”9

The Risks

With so much riding on our need for energy, we must avoid costly failures. For example, when one author [TAC] worked in the semiconductor industry, the great Northeast Blackout of 2003 was tripped only a few miles from the production facility where he worked. The source of the power failure was overgrown tree branches that had fallen on a transformer. Normally, this would have remained a local issue, but the lead utility failed to react quickly enough to disengage the switches to other grids, thus causing a cascading, multi-grid failure for 50 million people from Ohio to New York to southeast Canada. People were trapped in subway cars and elevators for hours; cell phone service was disrupted for millions. 10 11

Perhaps even more dangerous than a lack of sensors on the grid and failed switches is the looming possibility of a cyber-attack targeting fragile points in the electrical system. Industry is spending billions in its attempts to strengthen cybersecurity of the brittle grid.12 “U.S. utilities will spend a cumulative $7.25 billion in security from now until 2020, with distribution automation assets as the core focus.”13 Grid security is a major issue within the US Government; simulations of cyber-attacks are routinely done by groups such as DOE and DHS.14 15

While a completely failure-proof grid may be impossible with the moving demand target caused by new technologies online and rapidly growing electricity demands, companies and government agencies must nevertheless do their best to anticipate and to prevent both accidental and nefarious situations before they happen. This presents a unique opportunity to engage newly accelerated capabilities of computers, especially artificial intelligence (AI).

The Opportunities

A core challenge with global electrical grids is their growing complexity. Growing exabytes of data from billions of IoT sensors, coupled with too-fast-for-humans reaction speeds required by increasing power demands, make a purely human-controlled electrical grid impossible. To sustain our growing needs, we must resort to a more digitalized approach.

There has been much talk recently about the so-called “smart grid,” defined as an electricity supply network that uses digital communications technology to detect and react to local changes in usage. 16 A smart grid has three major facets: data from sensors, computational power and optimized algorithms. Let us discuss the third point in detail.

Algorithm development has progressed in concert with Moore’s Law – the doubling of the number of transistors on a given semiconductor chip roughly every two years. In the early days of computers, there were a limited number of programming languages – Basic, Fortran, C/C++, Cobol, etc. Nowadays, companies such as Google develop their own proprietary operating systems as a routine course of smart business action. Increasingly, those algorithms are leveraging the power of AI.

While there are many definitions for AI, it can be defined simply as the ability of a machine to perform tasks commonly executed by a human. 17 AI is presently the hottest ICT 18 market sector. PwC estimates that global GDP will increase $15.7 trillion (a +14% boost compared to today) by 2030 as a result of AI. 19 20 Such a huge economic contribution cannot be understated, and organizations are investing aggressively accordingly. Venture capital funding pumped almost $5 billion into AI startups in 2017 alone. 21 AI has become a top corporate spending priority, with many hundreds of billions of dollars devoted to nabbing top talent and to securing algorithmic leadership. 22 There is a global race among governments to capture the title of AI world leader.  23

The reason for this flood of venture capital, corporate and government funding is that AI can solve problems far faster than humans, and in some cases solve problems that no human can. While we humans are smarter than any other living being on Earth, we are still rather dumb when it comes to absorbing and processing quickly vast amounts of data. The human mind is limited also to mostly working on a single task; despite some claims, we are generally horrible at multitasking. 24 Computers don’t have those limitations.

How might AI help the energy sector? We suggest there are two primary means by which advanced AI algorithms can improve efficiency, enhance safety, and improve the bottom line for energy utilities: grid optimization and cybersecurity.

Grid Optimization. To reap the benefits of the smart grid, AI will be a true necessity. “AI will be the brain of this future smart grid. The technology will continuously collect and synthesize overwhelming amounts of data from millions of smart sensors nationwide to make timely decisions on how to best allocate energy resources. Additionally, the advances made from ‘deep learning’ algorithms, a system where machines learn on their own from spotting patterns and anomalies in large data sets, will revolutionize both the demand and supply side of the energy economy.” 25

A challenge for utilities is maintaining consistent power. When there is a sudden increase in demand, the go-to reaction for utilities is to power-up ‘peaker plants’ that run on fossil fuels, generally natural gas. 26 Able to be turned-on within minutes of the detection of a demand spike – for example, due to increased air conditioning or heating requirements from a weather front moving through an area – peaker plants are unfortunately terribly inefficient and polluting. AI might assist in diminishing the use of peaker plants by leveraging advanced forecasting capabilities – for example, considering weather forecasts, regional demand cycles, and smart meter sensors in a single holistic package. The solution of such multidimensional problems is a strength of AI over humans. Such efforts could save utilities significant funds that they could funnel into further grid improvements.

One recent success story in using AI for energy optimization is that of Google’s deployment of algorithms to reduce electricity consumption in their server farms. Google has thousands of data centers worldwide to run search, store and process emails, etc. Those countless banks of GPUs 27 and memory storage systems consume tremendous amounts of electricity and tend to overheat. Because of their increasing presence and inherent inefficiencies, it is estimated that 2% of the world’s energy is consumed by data centers. 28 Both to save costs and to show-off its earlier purchase of the British AI startup DeepMind, Google decided to test AI in improving the cooling efficiency of their computer banks. “The autonomous AI control system initially led to a 12 percent improvement, which over nine months of operation increased to around a 30 percent improvement, with further improvements expected over time as its decisions are improved by having more training data. Google said in the long term that there is potential to apply the technology in other industrial settings.”29

Finally, AI can assist in converting incoming power to be acceptable to a grid. Every energy utility has a mix of power sources that it taps to provide its customer base their electricity. That mix is optimized based on price and, more recently, social perception for use of renewables. A challenge with multiple power sources – natural gas, oil, coal, nuclear, renewables – is to seamlessly integrate them all into the single grid. For example, wind and solar power sources require special converters to enable them to plug into the grid. “The high penetration of renewable energy systems is calling for new more stringent grid requirements. As a consequence, the grid converters should be able to exhibit advanced functions like dynamic control of active and reactive power, operation within a wide range of voltage and frequency, voltage ride-through capability, reactive current injection during faults, and grid services support.”30 AI could assist with energy conversion from renewables by leveraging deep learning to identify key performance optimization criteria and thus enable efficient uptake of the generated power into the smart grid.

Cybersecurity. Ironically, the very action of creating a smart grid makes it more vulnerable to cyber-attacks. Standardizing hardware and software, as well as creating a high degree of connectivity, enables hackers easier access to the grid through a greater variety of means. Programmed backdoors, firmware chip hacks, and even fake chips on motherboards 31 can all compromise the security of a given system.

Humans are inherently limited in what we can accomplish in cybersecurity. Our minds require rest, eating, drinking, etc.; cyber-attack bots require none of that. Thus, even though we might have the best intentions to be ever-diligent in the face of malware or phishing attacks, eventually we will slip up and allow nefarious actors access to sensitive computer systems.

Four years ago, seeing the rapid advances occurring in AI and knowing the challenges of human-centered cybersecurity, one author [TAC] forecasted that soon cybersecurity would enter the realm of “AI vs. AI,” i.e., AI algorithms would be both sources of attacks and defense. We are close to that time now. In the last few years, there has been a surge of interest in coupling the powers of AI, especially deep learning, to cybersecurity. 32 Thousands of companies globally now claim some form of AI in their cybersecurity offerings. Although it is debatable whether all these startups and corporate entities are truly using AI (some startups treat “AI” as a form of pixie dust—sprinkle it in a pitch in attempts to get funding), it makes sense to leverage the powers of learning algorithms to monitor and to react to cyber-attacks.

Ultimately, using AI for cybersecurity may not be just a choice but an imperative in the energy industry. In the United States, the complexity of the grid—with more than 8,000 power plants, 200,000 miles of high-voltage transmission lines, and 5.5 million miles of local distribution lines 33 34—necessitates that even local utilities must think hard about how they monitor their systems for intrusive cyber-attacks.

The Means

So how do utilities leverage the power (no pun intended) of AI? One challenge for cash-strapped utilities is that AI experts are in such demand that a starting salary for a star AI programmer can exceed seven dollar figures35. Thus, a more cost-effective approach may be partnerships among established startups and corporate entities that already have in-house expertise in AI. One such partnership was announced recently between BootstrapLabs (a leading venture capital firm focused on Applied AI in San Francisco) and innogy SE (a leading Germany energy company):

“BootstrapLabs and the innogy Innovation Hub will coordinate globally to build the largest artificial intelligence community for energy ecosystems, and provide a combination of capital and support to Applied AI startups that reimagine the future of energy production, distribution and management across decentralized and interconnected energy services for consumers, machines, enterprises, and public sector agencies.” 36

Sebastian Niestrath, SVP Infrastructure Platform Ventures at innogy New Ventures LLC, further clarified: “The need to interpret massive amounts of data and use AI-supported algorithms for grid operations is becoming increasingly important, especially in Germany – where electricity from renewable sources has pretty much quadrupled during the last 15 years and where millions of solar panels are now installed on residential buildings.” Moreover, with the California Energy Commission unanimously voting 5-0 in favor of mandating that all single-family homes, apartments and condominium complexes of three stories or less require solar panels as of January 2020, California will quickly follow suit in the need for AI-supported algorithms for grid operations.

Further such engagements among all major energy players – including utilities, AI experts, and local/regional/national governments – will be imperative as grid demands and threats increase.

The Future

As our population continues to grow and more technology gets plugged into existing grids, it will be incumbent upon utilities to increase efficiencies to remain cost-effective and to avoid grid failures. Moreover, the growing threat from cyber-attacks will demand that power companies better protect their grids from nefarious actors. AI is one approach that can significantly help utilities move into this challenging world. Opportunities will be strong and risks could be minimized for those leaders who embrace the capabilities of advanced computation.


Authors

Thomas A. Campbell, Special Advisor, BootstrapLabs and Founder of FutureGrasp, LLC

Thomas A. Campbell, Ph.D., is Founder and President of FutureGrasp, LLC (https://www.futuregrasp.com/), which advises organizations worldwide on trends and implications of emerging technologies.

Thomas is also serving as Special Advisor of BootstrapLabs, for Applied AI intellectual propriety development as well as assisting BootstrapLabs to expand its network reach and meet new opportunities into government sectors.

From February 2015 to August 2017, he was the first National Intelligence Officer for Technology (NIO-TECH) with the National Intelligence Council (NIC) in the Office of the Director of National Intelligence (ODNI). Tom’s insights have informed senior policymakers, enabled millions of dollars in industry and academic funding, broken ground in multiple new research areas, and kept diverse groups abreast of the rapid pace and implications of technology change.

Dr. Campbell is focused on emerging & disruptive science and technologies, especially identifying, tracking, forecasting and implications. He has extensive experience in government, academia, and industry – nationally and internationally. More about Tom at this link here.

Nicolai Wadstrom, Founder & CEO, BootstrapLabs

Nicolai is the Founder, CEO and Managing Partner of BootstrapLabs, a leading venture capital firm, based in Silicon Valley and focused on Applied Artificial Intelligence.

Nicolai has spent all of his professional life building technology companies. He started his first business at the age of 15 in the late 1980s and in 2008 he founded BootstrapLabs to build a scalable investment platform focused on being the most valuable partner for entrepreneurs to build successful companies.

With decades of operational and entrepreneurial experience, and having invested in, advised, and mentored over 30 companies, Nicolai works with investment decisions, and post investment mentorship to support scaling for BootstrapLabs’ portfolio companies.

BootstrapLabs is a Venture Capital company focused on Applied Artificial Intelligence that combines Venture Capital and Human Capital to build companies that define our future.

BootstrapLabs unique Venture Builder platform provides all the resources top-tier entrepreneurs need to take their companies from innovation to a Scalable Product Market Fit and from there to growth.

Prior to BootstrapLabs, Nicolai among other things founded a cutting edge Enterprise Software company (in the ECM and EAI space), he also co-founded and IPO’d the first CFD/FSB trading platform in the Nordics, and pioneered Virtual Reality in 1996. More about Nicolai at this link.


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