The BootstrapLabs Applied Artificial Intelligence Conference 2019 #AAI19 brought together the brightest and most experienced experts in the field of AI for an immersive day of learning, discussion, and connection.

On BootstrapWorks we have released the videos from this past conference to relive the moments and spread the knowledge around the diverse topics covered by our experts on stage. 

BootstrapLabs has built a community of more than 40,000 people from over 60 countries who care about applying Artificial Intelligence to solve the hardest problems of our society.

Get access to practical wisdom on Applied AI methodologies and take advantage of AI’s powerful potential, sign up here to receive the videos directly into your inbox. 

Construction, manufacturing, and industrial design projects are often far too complex to be effectively managed by people. It is in this capacity that AI is uniquely suited to help. This keynote and fireside chat brings together Matt Man, Co-Founder and CEO of Indus.ai, and Mike Haley, Senior Director of AI and Robotics at Autodesk. They will discuss how to leverage AI’s capacity for synthesizing real-time data in support of managing, predicting, and optimizing for safety, quality, productivity, and efficiency within the construction and manufacturing industries.

Presenter: Matt Man, Founder & CEO, indus.ai

Panelist: Mike Haley, Senior Director of AI & Robotics, Autodesk

Some of the key takeaways from the session are:

• Choosing the right problem to solve with AI is as important as the problem.
• Manufacturing ($31T), real estate & construction ($25T) and industrial (mining, agriculture, utilities etc.) ($15) are trillion dollar markets for next generation services. Opportunities for AI include better planning and scheduling, safer environments, higher productivity, less waste and more agility and resilience.
• Try to look at a problem with a limited amount of failure in the system still provides high value (e.g. 97% of accuracy). Automate existing processes – then take a look where there are new capabilities to do things differently.
• Monitoring construction sites nowadays is still mostly done via pen and paper and a few people on site. This is a reason why 90% of construction projects over-budget by 80% which represents $10T of waste.
• Indus.ai created a tool for the smart construction site, where computer vision and ML/AI deliver actionable insights on progress tracking, worker metrics, truck/materials arrivals and overall site production analytics. This provides 10x of the normal visibility, and helps avoiding mistakes early, checking progress and giving insight on how to build a much better plan.
• Traditionally manufacturers and designers were separated from each other, but with large amounts of data and AI one can incorporate the process how something is built and used as well as the used materials and supply chains into the design process to create an optimal design that flows right into the process of manufacturing and construction.
• Generative design explores a design with thousands of permutations e.g. on the different forces that impact a seatbelt bracket. This way, a car company designed a new bracket that uses 30% less materials and is 40% lighter.
• Autodesk’s BrickBot project consists of an adaptive robot that learns how to build Lego from a physics and visual simulator that simulates what the camera and torque sensor on the arm will feel. This way it can go through a million iterations in a few hours so when it actually starts building, it already knows what to do.
• Future outlook:
  • Imagine if construction sites had three adaptable machines instead of hundreds of specialists – it would be much more flexible, safe and efficient.
  • Today, most AI is very limited on an area of expertise – there is no AI that is applied at the systems level because it is quite complex with high levels of freedom. The only way to be efficient is to understand the system – evolving AI to gain to that level of understanding is a vision with tremendous reward.

About Matt Man:
Matt Man is the founder and CEO of indus.ai, a construction intelligence company. Before indus.ai, Matt co-founded a mobile technology company GreenOwl Mobile and deployed 40+ smart city products in over 25 cities, worldwide. GreenOwl Mobile was acquired by one of the largest architecture and design technology firms in the world, IBI Group. Matt has specialized in deploying technology to Enterprise and Industrial markets for 20 years and has developed a deep understanding of the challenges operating in the industrial environments. His experience with AI was first developed at the University of Toronto, where he pioneered his first neural network to translate sign language to spoken words 25 years ago.

About Mike Haley:
Mike leads the Machine Intelligence group at Autodesk Research where they identify, evaluate, and develop disruptive technologies that improve the practice of imagining, designing, and creating a better world. His team combines research, development, and user experience in coupled iterative cycles to develop new products and foundational technology. For the last several years Mike’s team has been focused on bringing geometric shape analysis and large scale machine learning techniques to 3D design information with the intent to make software a true partner in the design process.

Formerly, Mike led the move of Autodesk products from the desktop to the cloud by driving the adoption of scalable distributed compute and data technology. Prior to joining Autodesk, Mike performed research and product development in the fields of volumetric graphics, distributed multimedia, computer vision, and embedded systems. He is drawn to areas where he can combine his 25 years of experience in computer graphics, distributed systems, and mathematical analysis. Mike holds an MS in computer science from the University of Cape Town, South Africa.

The BootstrapLabs Applied Artificial Intelligence Conference 2019 #AAI19 brought together the brightest and most experienced experts in the field of AI for an immersive day of learning, discussion, and connection.

On BootstrapWorks we have released the videos from this past conference to relive the moments and spread the knowledge around the diverse topics covered by our experts on stage. 

BootstrapLabs has built a community of more than 40,000 people from over 60 countries who care about applying Artificial Intelligence to solve the hardest problems of our society.

Get access to practical wisdom on Applied AI methodologies and take advantage of AI’s powerful potential, sign up here to receive the videos directly into your inbox. 

Though Applied AI is widely known for its role in facial recognition and self-driving technology, few people think of AI when they think of computer networks. As computer networks become increasingly complex, encrypted, and under attack, machine learning and applied AI is well situated to support keeping networks safe while maintaining privacy. From finding malware in encrypted traffic without decrypting the traffic to moving from Cloud-based ML to distributing ML across Edge and Cloud, applying ML and AI to computer networks can lead to improved scalability, cost, and privacy.  Join VP and CTO of Cisco’s Enterprise Networking Business, John Apostolopoulos, as he discusses the next generation of computer networking.

Speaker: John Apostolopoulos, VP/CTO of Enterprise Networking, Lab Director of Innovation Labs, Cisco

Some of the key takeaways from the session are:

• Cisco uses AI to:
  • count people to automate processes in buildings or to display individual names in video-conferencing.
  • detect and classify irregular noises to propose muting audio during video calls.
  • identify problems in large networks and propose solutions.
  • identify which devices are on the network to increase efficiencies, reliability and security.
  • identify malware in end-to-end-encrypted traffic without requiring decryption.
• Reasons for moving AI processes to the edge of the network (instead of in the cloud or at the client side):
  • In video analytics, sensors create plenty of data even with compression
  • Cloud-based ML has issues with bandwidth, latency and privacy. If we move execution and learning to the edge we gain reduced bandwidth, improved scaling, lower latency and privacy-preserved learning. The question that many institutions research is how we can aggregate learning across multiple edges.
• Cisco achieved privacy-preserved learning with AI at the edge by generating synthetic images of people that captured the key attributes needed by the AI agent but preserved the privacy by anonymizing the images.
• We need more of these tools that analyze if a system successfully preserves privacy. If we jointly design networking and AI carefully together, we can solve a lot of current issues and provide the base for new technologies like AR/VR, autonomous vehicles, blockchain and smart cities.

About John Apostolopoulos:
As VP and CTO of Cisco’s Enterprise Networking Business, John Apostolopoulos is designing the next generation of computer networking. His work includes wireless (from WiFi to 5G), Internet of Things, multimedia networking, visual analytics, and machine learning. John is an IEEE Fellow and was named “one of the world’s top 100 young innovators” by MIT Technology Review, and contributed to the US Digital TV Standard (Engineering Emmy 1997). He published over 100 papers, receiving 5 best paper awards, and about 75 granted patents. John was a Consulting Associate Professor at Stanford and received his B.S., M.S., and Ph.D. from MIT.

The BootstrapLabs Applied Artificial Intelligence Conference 2019 #AAI19 brought together the brightest and most experienced experts in the field of AI for an immersive day of learning, discussion, and connection.

On BootstrapWorks we have released the videos from this past conference to relive the moments and spread the knowledge around the diverse topics covered by our experts on stage. 

BootstrapLabs has built a community of more than 40,000 people from over 60 countries who care about applying Artificial Intelligence to solve the hardest problems of our society.

Get access to practical wisdom on Applied AI methodologies and take advantage of AI’s powerful potential, sign up here to receive the videos directly into your inbox. 

Companies are under tremendous pressure to adopt AI technology across their organizations in order to stay competitive, with the majority of companies needing to re-invent their core products and services using proprietary AI technology instead of off-the-shelf SaaS solutions. Moderator Jaime Fitzgibbon, Innovation Strategist at Booz Allen Hamilton, leads a conversation with panelists Rahul Sachdev, Co-Founder and CEO of Fortella; Alex Holub, CEO of Vidora; Vidya Raman, Director of Product Management and ML at Cloudera; and Bahman Bahmani, Director of Data Science at Rakuten, about best practices and design principles for Enterprise AI. Panelists address how to make AI productivity gains accessible to as many people as possible across an organization, how to increase adoption of AI within an organization, and how to innovate faster by making the development process of AI for enterprise more inclusive of non-data scientists.

Moderator: Jaime Fitzgibbon, Innovation Strategist, Booz Allen Hamilton

Panelists: Rahul Sachdev, Co-Founder & CEO, Fortella; Alex Holub, CEO, Vidora; Vidya Raman, Director of Product Management & ML, Cloudera; Bahman Bahmani, Director of Data Science, Rakuten

Some of the key takeaways from the session are:

• AI councils in companies have three main mandates:
  • Ensure a common understanding about AI and ML within the organization.
  • Create a tabular layout where investments in ML are being made and which represent the highest ROI.
  • Sharing case studies between business units and organizations.
• Three main areas where value can be made with the help of AI in enterprises:
  • Operational excellence
  • Product leadership
  • Customer intimacy
• Implementing AI: Data is the foundation of AI – make sure you have the right clean data pipeline into a centralized location and start small and collaborate early to tailor the data collection to the AI tool.
• Regulation is important to preserve privacy and the option to delete PII needs to be built in the data structure, while it is also a driver for more automation in the data analytics process.
• Enabling the AI tool user to override predictions or decisions is key for critical applications to give quality control over the system.
• Three sources of scale at Rakuten:
  • Automation in DevOps to forward the full CI/CD pipeline from development to deployment.
  • Outsource data wrangling to junior positions which creates a good career path and frees the schedule for the data scientist who can focus on doing their most productive work.
  • Building and managing a globally distributed team.
• The mindset of building everything in-house gets in the way of broader adoption of AI because talent is scarce and automation tools like Vidora help to solve time-consuming processes like data wrangling and modeling, enabling data scientists to focus on the problem itself.
• Venture capital investment increased from $4B in 2016 to $10B in 2018 which produced many tools that can be utilized rather than building everything in-house.
• Open source will be a tremendous opportunity for companies to experiment before fully committing and machine learning enables people to do more while opening up time for creativity.

About Jaime Fitzgibbon:
Jaime Fitzgibbon is Senior Associate at technology strategy consultancy Booz Allen Hamilton. Over the past 3 years, she has been building an innovation office focused on tracking technology trends and emerging tech solutions for client’s toughest mission challenges. She serves as a mentor to start-ups, has spoken and written articles on the core elements for building a viable innovation ecosystem, and developed the classroom of the future strategy for a local school. She serves on the board of the German School of San Francisco as well as other community organizations’ advisory councils.

About Rahul Sachdev:
Rahul Sachdev is the co-founder and CEO of Fortella – an AI-based Revenue Driven Marketing software company. He is a technology executive with experience in marketing, CRM and social domains. Prior to Fortella, Rahul served as the CEO of Get Satisfaction, an online community platform for marketing and customer support. Earlier Rahul was the head of content sharing and workplace products at LinkedIn, and General Manager of the Communications, Media & Energy product at Siebel Systems. Rahul holds an MBA from the University of Chicago’s Booth School of Business and a BSc with Honors in Electrical and Electronic Engineering from Loughborough University (UK).

About Alex Holub:
Alex Holub studied artificial intelligence throughout his academic career at Cornell University and during his Ph.D at Caltech. He has published over 15 academic papers and holds numerous patents in the areas of machine learning, computer vision, and artificial intelligence. Prior to co-founding Vidora, Alex was a technical and product management lead at Ooyala.

About Vidya Raman:
Together with different product teams, Vidya Raman has built and grown enterprise businesses as a product leader in several industry verticals ranging from Telecom, Healthcare, Energy and IoT. Most recently, she led product management for Cloudera’s AI platform, where she was responsible for making AI at scale a reality for customers spanning industries such as autonomous driving, biotech, banking to governments. Prior experience includes eMeter (Sequoia-funded, acquired by Siemens), Silver Spring (Kleiner funded and IPO exit), Medtronic (healthcare). Currently she is an early-stage venture investor.

About Bahman Bahmani:
Bahman Bahmani is a Director of Data Science at Rakuten (the 7th largest internet company in the world), managing an AI organization with engineering and data science managers, data scientists, machine learning engineers, and data engineers, globally distributed across 3 continents and in charge of the end-to-end AI systems behind the Rakuten Intelligence suite of products. Bahman has built and managed engineering and data science teams across industry, academia, and the public sector in areas including digital advertising, consumer web, cybersecurity, and non-profit fundraising, where he has consistently delivered substantial business value. He has also designed and taught courses, led an interdisciplinary research lab, and advised several theses in the Computer Science department at Stanford University, where he also did his own PhD focused on large-scale algorithms and machine learning, topics on which he is a well-published author.

On March 10th, Luigi was featured on Forbes Italia as one of the young emerging venture capitalists of artificial intelligence in Silicon Valley. Below you can find an extract of Luigi’s interview:

“Your work will fill a large part of your life and the only way to be truly satisfied is to do what you think is great work. And the only way to do great work is to love what you do. If you haven’t found it yet, keep looking. Don’t settle for it. As with all matters of the heart, you will know when you find it ”. So believed Steve Jobs, who was able to inspire many entrepreneurs and visionaries like him. Luigi Congedo , 31, venture capitalist of BootstrapLabs , arrived in Silicon Valley at a very young age, becoming one of the 30 under 30s of Forbes Italia for 2018. “Steve Jobs was the first great entrepreneur, inventor and visionary I was inspired by.” […]

“He comes from Naples.”

“I consider myself very lucky to have been born in Naples. My hometown has a great cultural and soul wealth. This has allowed me to be a social and positive person, qualities that have helped me to be successful.” […]

“Do you think AI can also be dangerous?”

“It is up to us – society, politicians and entrepreneurs – to decide how to use technology and innovation. BootstrapLabs philosophy is to choose investments that create long-term utility and vertical solutions in specific industries, such as healthcare, logistics, agriculture, energy, and smart government.” […]

“How has Covid-19 changed the world of investments?”

“Our core investment theses have not changed, but we have seen a strong acceleration of many tech trends. The coronavirus has caused an acceleration of digital transformation on a global scale and in all sectors.” […]

“What are the most interesting sectors in the future?”

“I think the use of artificial intelligence is among the most promising trends. Among the sectors I look at with great interest there are cybersecurity, healthcare and climate.” […]

Below you can read the full press release:

MILANO, Italy, Mar. 10, 2021 /Forbes/ — La storia di Luigi Congedo, il giovane napoletano diventato venture capitalist dell’intelligenza artificiale nella Silicon Valley. Read More.

The BootstrapLabs Applied Artificial Intelligence Conference 2019 #AAI19 brought together the brightest and most experienced experts in the field of AI for an immersive day of learning, discussion, and connection.

On our BootstrapWorks we have released the videos from this past conference to relive the moments and spread the knowledge around the diverse topics covered by our experts on stage. 

BootstrapLabs has built a community of more than 40,000 people from over 60 countries who care about applying Artificial Intelligence to solve the hardest problems of our society.

Get access to practical wisdom on Applied AI methodologies and take advantage of AI’s powerful potential, sign up here to receive the videos directly into your inbox. 

AI is a critical tool for using observed data to make and predict decisions. While most industries work with curated data, transportation is a different situation: self-driving cars rely on volumes of real-time information. AEye chief scientist Dr. Allan Steinhardt discusses the role of AI in abstracting and extracting the right information from a car’s environment, including how to deal with the influx of data in vehicle autonomy and ADAS. Additionally, he explores the role of transportation AI in smart highways and how smart cities with next-generation wireless (5G) will impact transportation AI trends.

Speaker: Dr. Allan Steinhardt, Chief Scientist, AEye

Some of the key takeaways from the session are:

• If you look at the individual components of a system you learn nothing, it is important to understand the overlaying complex adaptive systems.
• The mathematics of understanding complex adaptive systems is similar to mathematics of quantum theory.
• If we think about AI for transportation in cities, we have to think like complex adaptive systems with all the different layers of meaning that intersect in very complex ways: Merging the different tribes of car makers, transportation engineers and Perception/AI engineers and their respective areas of focus is important to understand the different layers around transportation AI.
• Signals from autonomous vehicle sensors are plotted in a point cloud, but the noise in the data can be used to identify road surface features, background light that is interfering with the laser etc.
• MIT students were able to utilize RF exhaust noise from various wireless signals as a radar beacon to track humans through walls.
• Massive amounts of RF bandwidth is being used for communication in transportation AI: One of six radars on a car might use 2 Gigahertz of bandwidth meaning that one car needs more bandwidth than dozens of cell-towers which is clearly not sustainable.
• Complex adaptive systems do brokering between layers and today there are many start-ups that provide various technologies for brokering of communication networks.
• Congestion represents a lot of wasted capital assets.
• The current data mindset is the more data, the better. AEye’s mindset however is described as the latest time of value: Navigating space-time obstacles safely because it is essential to make a decision immediately since there will not be a better decision later in any traffic situation. Therefore it is essential to increase the quality of the data capture process which can be modeled to focus only on key objects like the human brain.

About Allan Steinhardt:
Dr. Allan Steinhardt is among the world’s most widely esteemed defense scientists. An IEEE fellow, he is a sought-after expert on radar, missile defense, GMTI and space surveillance. He was Chief Scientist for DARPA, co-author of a book on adaptive radar, and assistant professor in Electrical Engineering and Applied Mathematics at Cornell University, where he researched sensor arrays and optimal detection capabilities. Allan also served as chief scientist at Booz Allen at MIT Lincoln Laboratory, and director of signal processing for the defense industry with BAE/Alphatech. He holds a bachelor’s in Mathematics, and graduate degrees in Electrical and Computer Engineering from the University of Colorado, Boulder.

The BootstrapLabs Applied Artificial Intelligence Conference 2019 #AAI19 brought together the brightest and most experienced experts in the field of AI for an immersive day of learning, discussion, and connection.

On our BootstrapWorks portal we have released the videos from this past conference to relive the moments and spread the knowledge around the diverse topics covered by our experts on stage.

BootstrapLabs has built a community of more than 40,000 people from over 60 countries who care about applying Artificial Intelligence to solve the hardest problems of our society.

Get access to practical wisdom on Applied AI methodologies and take advantage of AI’s powerful potential, sign up here to receive the videos directly into your inbox. 

The Global South is home to some of the fastest growing economies on the planet despite being crippled by a general lack of traditional infrastructure, trade frictions, political and currency risks, and corruption. And yet, the benefits far outweigh the risks of bringing the next billion people into the Global Economy. In fact, massive investments are already being made in infrastructure, healthcare, IT, and transportation by governments, NGOs, and foundations alike. In this mini keynote and fireside chat, Chris Hale of Kountable and Jonas Svensson of UNOPS discuss how AI can empower entrepreneurs in the region by accelerating their growth, job creation, and taxable income recognition.

Presenter: Christopher Hale, Founder & CEO, Kountable

Panelist: Jonas Svensson, Head of Global Innovation and Technology, UNOPS

Some of the key takeaways from the session are:

• The global south is a relatively new term that describes countries which are not high-income countries. They represent 5B+ people or 60% of the world population.
• Africa’s population will double by 2050 and by 2100, 80% of the world’s population will live in Africa and Asia.
• Entrepreneurs are engines of change in these emerging markets, but it is difficult to identify and analyze them and their behaviors.
• Kountable built a tech platform that organizes entrepreneur behaviors as they access global markets with the help of NLP, currency forecasting, behavioral scoring & feedback loops to learn what a good trader looks like and to optimize and train against that behavior.
• The UNOPS reach is $2B to invest globally, but to innovate inside such a large structure becomes difficult. Therefore, they invest in  innovation procurement from the private sector who are able to generate profits. The EU innovation procurement policy (2018) focuses on outcome and lifetime cost instead of upfront cost and usage which facilitates innovation.
• Today, there is a funding gap of $15T to reach the sustainable development goals for 2030, which represents tremendous business opportunities for the private sector. This allows co-development with the UN, where private companies are enabled to keep the IP for usage in other sectors.
• We need to make technology available and understandable by facilitating education to bridge the social gaps around the world: The motivational driver is not shareholder profit, but global change by bringing critical infrastructure to the fastest-growing markets in the world. For example, AI is used to analyze infrastructure, food waste and to predict extreme weather patterns to facilitate support.

About Christopher Hale:
Chris Hale is founder and CEO of Kountable, Inc., an SF-based start-up that combines data science, social capital and proven financial instruments to provide highly scalable financing solutions to underserved entrepreneurs in developing countries. Kountable creates a low-friction, cloud-based bridge between investors and a massive opportunity to finance the most promising and well-networked entrepreneurs in emerging economies. Chris also doubled headcount and grew assets under management almost six-fold as the COO of Perigon Wealth Management, one of 2014’s 50 fastest growing RIAs in the country, serving approximately 100 families and managing almost $1 billion in assets.

About Jonas Svensson:
Jonas Svensson is the Head of Global Innovation and Technology at UNOPS. The UNOPS Global Innovation and Technology program operates under the Social Impact Investing Initiative with the mission to facilitate innovation wherever it happens. Connecting with Global stakeholders who share the UN foundation values regarding sustainability and the understanding that Innovation happens everywhere UNOPS together with partners have created a toolkit providing Education, Incubation, Investment and Policy support.

Prior to the role with UNOPS Mr Svensson has worked within the startup industry for the past 20 years as founder, incubator manager, business consultant, investor, last as President for a Venture capital company headed out of Tokyo Japan. Mr Svensson holds a Master in Global Management from the University of Salford and is currently pursuing his PhD.