Attention, foreign-policy makers. You will soon be working with, or competing against, a new type of robot with the potential to change the game of international politics forever. Diplomacy is similar to a strategic board game. A country makes a move, the other(s) respond. All want to win. Artificial intelligence is good at board games. […]
Attention, foreign-policy makers. You will soon be working with, or competing against, a new type of robot with the potential to change the game of international politics forever.
Diplomacy is similar to a strategic board game. A country makes a move, the other(s) respond. All want to win.
Artificial intelligence is good at board games. To get the game started, the system analyses previous play, learns lessons from defeats or even repeatedly plays against itself to devise a strategy that can be never thought of before by humans.
It has defeated world champions in chess and Go. More recently, it has won at no-limit Texas Hold’em poker, an “imperfect information game” in which a player does not have access to all information at all times, a situation familiar in the world of diplomatic affairs.
Several prototypes of a diplomatic system using artificial intelligence are under development in China, according to researchers involved or familiar with the projects. One early-stage machine, built by the Chinese Academy of Sciences, is already being used by the Ministry of Foreign Affairs.
The ministry confirmed to the South China Morning Post that there was indeed a plan to use AI in diplomacy.
“Cutting-edge technology, including big data and artificial intelligence, is causing profound changes to the way people work and live. The applications in many industries and sectors are increasing on daily basis,” a ministry spokesman said last month.
The ministry “will actively adapt to the trend and explore the use of emerging technology for work enhancement and improvement”.
China’s ambition to become a world leader has significantly increased the burden and challenge to its diplomats. The “Belt and Road Initiative”, for instance, involves nearly 70 countries with 65 per cent of the world’s population.
The unprecedented development strategy requires up to a US$900 billion investment each year for infrastructure construction, some in areas with high political, economic or environmental risks.
The researchers said the AI “policymaker” was a strategic decision support system, with experts stressing that it will be humans who will make any final decision.
The system studies the strategy of international politics by drawing on a large amount of data, which can contain information varying from cocktail-party gossip to images taken by spy satellites.
When a policymaker needs to make a quick, accurate decision to achieve a specific goal in a complex, urgent situation, the system can provide a range of options with recommendations for the best move, sometimes in the blink of an eye.
Dr. Feng Shuai, senior fellow with the Shanghai Institutes for International Studies, whose research focuses on AI applications, said the technology of the AI policymaking system was already attracting attention despite being in its early stages.
Several research teams were developing these systems, Feng said. A conference discussing the impact of AI on diplomacy was hosted by the University of International Business and Economics last month in Beijing, in which researchers shared some recent progress.
“Artificial intelligence systems can use scientific and technological power to read and analyse data in a way that humans can’t match,” Feng said.
“Human beings can never get rid of the interference of hormones or glucose.”
The AI policymaker, however, would be immune to passion, honour, fear or other subjective factors. “It would not even consider the moral factors that conflict with strategic goals,” Feng added.
Other nations are believed to be conducting similar research into AI uses in policymaking fields, though details are not available publicly.
But AI does have its own problems, researchers say. It requires a large amount of data, some of which may not be immediately available in certain countries or regions. It requires a clear set of goals, which are sometimes absent at the start of diplomatic interaction. A system operator can also temper the results by altering some parameters.
With its confluence of academics, international accessibility, culture of collaboration, many startups and access to capital, Montreal may be poised to become the next Silicon Valley. This might be especially true given the current America political climate hostile to the international cooperation on which research institutions and technology companies thrive. Montreal is benefitting today from […]
With its confluence of academics, international accessibility, culture of collaboration, many startups and access to capital, Montreal may be poised to become the next Silicon Valley. This might be especially true given the current America political climate hostile to the international cooperation on which research institutions and technology companies thrive.
Montreal is benefitting today from a long-term commitment by the Canadian government to fund AI research.
“Canada has supported the fundamental basics of AI by financing Bengio (Yoshua Bengio,University of Montreal and MILA), LeCun (Yann LeCun, VP and Chief AI Scientist, Facebook) and Geoff Hinton (University of Toronto and Google), over 25 years, back to when AI was not as strong a bet “ said Chris Arsenault, General Partner, iNovia Capital, Montreal, in an interview with AI Trends. “That’s why Canada is in such a great position right now.”
These scientists are a big pull for Canada to attract students and the many big technology companies who have opened research labs in Canada, especially in Montreal and Toronto. These include: IBM AI Lab; Facebook AI Center (FAIRE); Google AI Lab; Microsoft (acquired Maluuba in January 2017); Tencent, via an investment in Element.ai; Intel, also via Element.ai; Google DeepMind Center; Samsung AI Center; Thales Centre of Research & Tech in AI; the RBC (Royal Bank of Canada) Borealis AI Center; Uber AI; ADM AI lab (opening soon); NVIDIA, SunLife, Adobe; LG, Fujitsu; and TD (Toronto-Dominion Bank)/Layer 6.
“We are just starting to see the fruits of the results of all this research in the form of companies with business models and platforms incorporating AI,” Arsenault said. Advances in chip design and availability of compute power via the cloud are also enabling the rush. “This was not possible five or 10 years ago,” Arsenault added.
Companies Finding AI Talent in Montreal
A chief attraction for companies pursuing AI research and commercialization, is the access to top talent centered around the universities, in particularly the McGill University and the University of Montreal, which includes the Montreal Institute for Learning Algorithms (MILA), said to be one of the largest deep learning labs in the world. Partly this is due to the accomplishments of Dr. Bengio, one of the world’s leading deep learning researchers. (See Executive Interview with Dr. Bengio in AI Trends.)
“Montreal has the largest concentration of deep learning academics in the world. This attracts some of the best students, postdocs, professors, researchers, engineers and entrepreneurs interested in contributing to the ongoing AI revolution,” Dr. Bengio stated.
The Canadian government’s commitment to AI is exemplified in its support for MILA. The government of Quebec recently allocated $80 million over the near five years to support its growth, and the federal government’s Pan-Canadian AI Strategy unit has granted MILA $44 million to supports its activities.
The MILA mission is to attract and retain talent in the machine learning field; to propel advanced research in deep learning and reinforcement learning; to transfer technology by supporting private AI startups and established businesses; and to contribute to the social dialogue and the development of applications that benefit society.
The new Facebook Artificial Intelligence Research (FAIR) in Montreal will be led by McGill University professor Joelle Pineau, a member of MILA. The plan is to employ research scientists and engineers engaged in a wide range of projects, with a focus on reinforcement learning and dialog systems.
“Montreal already has an existing fantastic academic AI community, an exciting ecosystem of startups, and promising government policies to encourage AI research,” stated LeCun in a press release about the investment. “We are excited to become part of this larger community, and we look forward to engaging with the entire ecosystem and helping it continue to thrive.”
“For many years, I have seen a steady stream of talented AI researchers with Masters and PhDs from our universities move to the US to find the best research jobs,” Prof. Pineau stated in a release from McGill University. “They will now have an opportunity to do this right here in Montreal. The Montreal FAIR Lab will initially launch with ten researchers, with the aim of scaling up to more than 30 researchers in the coming year.”
Technical talent in Montreal is attracted to companies who offer a chance to publish papers and “do something good for humanity,” in the words of Patrick Poirier, chief technology of startup Erudite AI. “Trying to fight for talent with pure cash is a losing bet for startups in Montreal,” he told Daniel Faggella, the founder of Tech Emergence, a market research company focused on AI and machine learning, who spent 12 days visiting AI related ventures and executives in Montreal last year and wrote an account of his conclusions.
Montreal Cost of Living, Diversity Are Strengths
The Montreal culture, lifestyle and relatively low cost of living compared to other urban tech centers such as San Francisco and Boston, is also attractive.
One technologist who made the move from Silicon Valley to Montreal is Maxime Chevalier-Boisvert, who returned to Montreal in mid-2017 after working at Apple for 13 months, according to an account in the New York Times. She had an opportunity to work with Yoshua Bengio at MILA and could not pass it up. Her title at MILA is Architect of Imaginary Machines. While her salary was about one-third of what she made at Apple, her rent for a two-bedroom apartment in Montreal was less than a third of the monthly rent she paid for a one-bedroom apartment in Sunnyvale. “Living in Montreal is pretty good,” she stated.
The Montreal AI culture has also attracted investments from those concerned with the social impact and risks of AI. The Open Philanthropy Project in July 2017 awarded $2.4 million to MILA to support “technical research on potential risks from advanced AI,” stated the announcement from OPP, which has a focus area on Global Catastrophic Risks that includes advanced AI. The OPP’s two primary aims are to increase high-quality research on the safety of AI, and the number of people knowledgeable about both machine learning and the potential risks of AI.
Montreal’s diversity of culture is also helping to attract talent. Dr. Alexandre Le Bouthillier, founder of machine vision healthcare company Imagia, observed that most talent in Montreal’s AI community is foreign-born, with his own team coming from all over the globe. “Smart people know that talent attracts talent,” he has stated.
Montreal and Toronto are benefitted from a Canadian immigration strategy consistent with the country’s AI initiative. Canada launched a fast-track visa program for high-skilled workers in the summer of 2017. Today, foreign students make up 20 percent of all students at Canadian universities compared with less than five percent in the US, according to a recent account in Politico written by two University of Toronto professors, Richard Florida and Joshua Gans. Canadian immigration law also makes it easier for foreign students to remain in Canada after they graduate.
Since the election of Donald Trump as US president in November 2016, applications to Canadian universities have spiked upward. International student applications jumped 70 percent in the fall of 2017 compared to the previous year; applications to McGill University in Montreal jumped 30 percent; and those to the University of British Columbia in Vancouver increased by 25 percent, according to the authors.
Canadian Prime Minister Justin Trudeau views immigrants as contributing to the growth of the Canadian economy, particularly in areas of technical innovation. “People choosing to move to a new place are self-selected to be ambitious, forward-thinking, brave and builders of a better future,” he stated in a recent account in TechCrunch. “For someone who chooses to do this to ensure their kids have a good life is a big step.” The Canadian perspective on innovation is helping to attract talent not only for the opportunity to conduct technical research but also to study “the consequences of AI, the consequences of automation,” Trudeau stated.
French culture has a big impact on Montreal, expanding beyond the delis and coffee shops and into business life. Many of the larger businesses primarily speak French in the office and in many of the top universities, including the University of Montreal.
Montreal Attracting Investment Capital
The ability of Montreal’s universities and startups to attract capital from tech giants and investors has helped to cement its position. The ability of Montreal-based platform and incubator Element AI, to raise $102 million in a Series A round of investment in June 2017, was a tipping point. The firm’s mission is to lower the barrier to entry for commercial applications in AI by offering AI talent and resources to companies that need to supplement their own staffs.
The round was led by Data Collective, which backs entrepreneurs applying deep learning technologies to transform giant industries, and included as partners Microsoft Ventures and NVIDIA. The Series A round came six months after Element AI announced a seed round from Microsoft Ventures (for an undisclosed amount) and eight months after the company launched.
The firm’s approach is to build an “incubator” or “safe space” where companies that might sometimes compete, sit alongside each other and collaborate to build new products. Some believe this may be an industry first. Data Collective sees an opportunity to close the gap between the AI have and have-nots.
“There is not a lot left in the middle,” Data Collective managing partner Matt Ocko told TechCrunch. “The issue with corporations, governments and others trapped in that no man’s land of AI ‘have-nots’ is that their rivals with superior AI-powered decision making and signal processing will dominate global markets.”
Element AI foresees initial product pickup in areas of: predictive modeling, forecasting models for small data sets, conversational AI and natural language processing, aggregation techniques based on machine learning, reinforcement learning for physics-based motion control, statistical machine learning algorithms, voice recognition, fluid simulation and consumer engagement optimization.
Element AI is not yet discussing customer engagements in depth, a spokesman told AI Trends, but they have signed up as customers the Port of Montreal, Radio-Canada (Canadian media company) and the Canadian Space Agency. According to a recent article in Fortune, the company sees an opportunity to embed itself in large organizations that may use Google for email and Amazon for web services, but are reluctant to give those companies access to internal databases with company-sensitive information. Element AI sees an opportunity to position as a more ethical AI company than those involved with military contracts and election influencers.
The future looks good for AI innovation out of Montreal. Karam Thomas, founder and CEO of CognitiveChem, a company leveraging AI to help chemists develop safer chemicals, stated, “Montreal’s unique advantage lies in its collaborative research between academia, startups and corporations.” Montreal’s AI boosters are hoping that collaboration will spur more entrepreneurs to build sizable new companies.
The thriving AI ecosystem in Toronto can serve as a model for other tech hubs. The system is underpinned by the region’s AI talent and expertise, by increasing support from venture capitalists for startups, and by leadership from the top. Canadian Prime Minister Pierre Trudeau is into coding, welcomes entrepreneurs to Canada, has tuned the […]
The thriving AI ecosystem in Toronto can serve as a model for other tech hubs. The system is underpinned by the region’s AI talent and expertise, by increasing support from venture capitalists for startups, and by leadership from the top. Canadian Prime Minister Pierre Trudeau is into coding, welcomes entrepreneurs to Canada, has tuned the immigration system to help attract experts and has backed the effort with government grants.
Toronto is home to world-class academic institutions including the nearby University of Waterloo and the University of Toronto. “These institutions are world leaders in scientific research, creating an ecosystem ripe with opportunities for novel applications for AI, particularly in the fields of heal and life sciences,” stated Naheed Kurji, president and CEO of Cyclica, writing in VentureBeat. Cyclica offers an AI platform for use in the pharmaceuticals industry.
Toronto is welcoming, with a diverse, international and well-educated population. A strong local network of investors, incubators, technologists and support staff is sustaining and growing AI companies focused on transforming specific industries, Kurji stated.
Organizations headed by AI pioneers are leading and advising startups in the Toronto region. These include: Geoffrey Hinton, called by some the “Godfather of Deep Learning,” who splits his time between Google and teaching at the University of Toronto; Sanja Fidler, assistant professor of computer science at the University of Toronto, and a director of AI at NVIDIA; Raquel Urtasun of the University of Toronto and the head of Uber Advanced Technology Group in Toronto.
Urtasun started at Uber in May 2017, to pursue her work on machine perception for self-driving cars. The work entails machine learning, computer vision, robotics and remote sensing. Before coming to the university, Urtasun worked at the Toyota Technological Institute at Chicago. Uber committed to hiring dozens of research and made a multi-year, multi-million dollar commitment to Toronto’s Vector Institute, which Urtasun co-founded. She still works one day per week at the University of Toronto.
Urtasan has argued that self-driving vehicles need to wean themselves off LIDAR (Light Detection and Ranging), a remote sensing method that uses a pulsed laser to measure variable distances. Her research has shown in some cases that vehicles can obtain similar 3D data about the world from ordinary cameras, which are much less expensive than LIDAR units, which costs thousands of dollars.
“If you want to build a reliable self-driving car right now we should be using all possible sensors,” Urtasun told Wired in an interview published in November 2017. “Longer term the question is how can we build a fleet of self-driving cars that are not expensive.”
The Vector Institute is one of a group of business-growth focused institutions that call Toronto home, the others being the MaRS Discovery District and the Creative Destruction Lab. Each shares a commitment to advancing AI innovation in the city. Each organization is connected to academic programs, cultivating local technology talent. All three bring technical and business talent together to optimize innovations and position them for the market.
The Vector Institute is an independent, non-profit research institution focused on deep learning and machine learning. Its global partners include Google, Shopify, Accenture, Thomson Reuters, NVIDIA, Uber, Air Canada and five major Canadian banks. Its chief scientific advisor is Hinton, who has said, “The Institute will build on Canada’s pool of globally recognized AI expertise by training, attracting and retaining more top researchers who want to lead the world in machine learning and deep learning research.” This while having the flexibility to work on commercial applications within companies or in their own startups.
The MaRS Discovery District is a non-profit, public-private partnership founded in 2000, originally to commercialize publicly-funded medical research. The original name stood for “Medical and Related Sciences,” but that narrower association was later abandoned to include information and communications technology, engineering and social innovation. As of 2016, startup companies emerging from MaRS had created more than 6,000 jobs and raised over $3.5 billion in capital (2008 to 2016) and generated $1.8 billion in revenue (2008 to 2016).
The Creative Destruction Lab at the University of Toronto’s Rotman School of Management is a seed-stage program focusing on the transition from pre-seed to seed-stage funding. One of the lab’s co-founders is Dennis Bennie, an entrepreneur who co-founded the software company Delrina Corp., sold to Symantec in 1995 for shares valued at $760 million. He has since founded the XDL Venture Fund, focused on early stage opportunities.
Dr. Ajay Agrawal, founder of the Creative Destruction Lab, in April published a book co-authored with Joshua Gans and Avi Goldfarb: “Prediction Machines: The Simple Economics of Artificial Intelligence.” Hal Varian, the chief economist at Google, commented, “What does AI mean for your business? Read this book to find out.”
The book is a guide for companies for how to set strategies, for governments to design policies and for people to plan their lives for a different world that AI will bring. The three prominent economists recast the rise of AI as a drop in the cost of prediction. The authors show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors and entrepreneurs.
Tech Investors Bullish on Canada
Toronto continues to attract significant interest from the investment community. Toronto saw a 165% increase in funding with $321 million invested across 38 deals in Q1 2018, according to a report from PwC Canada and CB Insights.
Toronto accounted for 34% of $1.7 billion in VC funding invested in Canada in 2016, according to Fintech Finance. Active technology startups in the Toronto region number between 2,500 and 4,100, according to Tech Toronto, an organization that supports and monitors the community.
As more Canadian companies have proven to be successful, interest from VCs has increased, according to Chris Erickson, general partner of Pangaea Ventures of Vancouver. “More VCs have been getting good returns, raising more money and investing it in Canadian companies. We’d like to see that improve and grow,” he stated in a recent account in Crunchbase News.
The Canadian Venture Capital and Private Equity Association (CVCA) reports that in the first half of 2017, Canada saw 21 exits compared with 32 in all of 2016. This included two venture-backed initial public offerings: Ontario’s Real Matters, Inc., in financial services; and Zymeworks, Inc., a biotech firm.
Toronto saw a 165% increase in funding with $321 million invested across 38 deals in Q1 2018, according to a report from PwC Canada and CB Insights.
Toronto is also attractive to foreign tech companies. Paytm, a leading fintech startup from India, last year chose to develop its lab in Toronto for the close links between the financial and technology sectors, and the available talent pool. PayCommerce, a fintech firm from New Jersey specializing in cross-border payments, chose to launch an R&D operation in Mississauga. WeWork, a coworking space provider based in New York City, last year rented 60,000 square feet of office space in downtown Toronto to capitalize on the entrepreneurial energy.
Major technology firms that have chosen to locate their Canadian headquarters in the Toronto region include: IBM Canada, Markham; Alphabet (Google), Toronto; HP Canada, Mississauga; Cisco Systems Canada, Toronto; and Microsoft Canada, Mississauga.
In addition, GM Canada recently announced plans to open a 15,000 square foot technical center in Markham to conduct R&D on autonomous cars, with the potential to create some 700 high-quality jobs. The government of Ontario, as part of a national “super cluster” initiative, will invest $80 million in the Autonomous Vehicle Innovation Network, in partnership with the Ontario Centers for Excellence, a public-private accelerator.
The Canadian government continues to invest in its AI initiative. The Canadian Institute for Advanced Research (CIFAR) will fund a $125 million Pan-Canada strategy to “promote national collaboration, develop a robust AI talent pipeline, attract companies seeking to invest in AI, and build a Canadian AI brand.”
The Ontario government plans to expand its Business Growth Initiative to $650 million over five years, targeted towards helping innovation-driven small and medium enterprises grow and compete internationally.
More recent announcements about setting up AI labs in Toronto have come from Adobe, Samsung, LG Electronics and Etsy. Vivek Goel, VP of research and innovation with the University of Toronto, was quoted in the Globe and Mail as saying companies are moving core development operations to the region to take advantage of local talent. “From my perspective, it’s very positive. It’s creating opportunities for our folks to develop careers in Canada, where traditionally these individuals maybe have gone abroad,” she stated.
A Few Notable Toronto Startups
Deep Genomics is using AI to focus on early-stage development of drugs for inherited diseases that result from a single genetic mutation, diseases estimated to affect 350 million people worldwide. The company has raised $16.7 million to date and has hired a team of geneticists, molecular biologists and chemists working on treating disease using biologically-accurate AI technology.
Deep Genomics was founded by Brendan Frey, a professor at the University of Toronto who specializes in machine learning and genomic medicine. The current work is driven by cost-effective new ways of sequencing whole genomes, the entire readout of a person’s DNA. “There’s an opening of a new era of data-rich, information-based medicine,” stated Frey in an article in MIT Technology Review published in May 2017. “There’s a lot of different kinds of data you can obtain. And the best technology we have for dealing with large amounts of data is machine learning and artificial intelligence,” he stated.
Frey trained as a computer scientist and studied at the University of Toronto under Geoffrey Hinton, a noted figure in the development of deep learning. Deep Genomics will seek to partner with a pharma company on drug development, Frey told MIT Tech Review. “There’s going to be a really massive shakeup of pharmaceuticals,” he stated. “In five years or so, the pharmaceutical companies that are going to be successful are going to have a culture of using these AI tools.”
Layer 6 AI was a startup until it got acquired by Toronto-Dominion Bank in January for more than $100M. Launched in 2016, the company uses AI in its platform to analyze data to learn and anticipate an individual customer’s needs. Layer 6 founders Jordan Jacobs and Tomi Poutanen are among the founders of Vector Institute. Jacobs told the Globe and Mail as the company was looking to raise more money from venture capital last fall, it began getting acquisition offers from a variety of companies “both inside and outside of Canada.”
The startup, which employed 17 people, Jacobs stated was guided by a desire to help “build a global AI ecosystem in Canada.” In addition to heading Layer 6 AI, Jacobs is now the Chief AI Officer, Business and Strategy, for TD Bank Group. Trained as a lawyer, Jordan spent 15 years advising tech entrepreneurs, Grammy and Oscar winners and sports teams in complex transactions and financings.
Winterlight Labs monitors cognitive health by speech sample analysis. The company has raised $1.5 million total from investors. The firm’s AI technology is said to quickly and accurately quantify speech and language patterns to help detect and monitor cognitive and mental diseases.
Its diagnostic system aims to analyze natural speech to detect and monitor dementia, Alzheimer’s, aphasia and other cognitive conditions. The scalable platform uses short recorded speech samples to analyze hundreds of linguistic cues, detecting dementia and other conditions with a high level of accuracy. The platform has applications in drug trials, long-term and primary care, and speech language pathology.
Co-founder Frank Rudzicz called these verbal clues “jitters” and “shimmers” – high frequency wavelets only computers can year, in a recent interview with Wired. Winterlight positions its tool as more sensitive than pencil and paper-based tests doctors currently use to assess Alzheimer’s. Winterlight’s tool can also be used multiple times per week, instead of once every six months like the pape method. That lets it track good days and bad days in measuring a patient’s cognitive function. The product is still in its beta test stage, and is being piloted by medical professionals in Canada, the US and France.
Watch this space for more on AI innovation in Canada.
The San Jose Smart City Vision is a plan that uses technology and data-driven decision-making to promote safety, sustainability, economic opportunity and quality of life for its constituents. The California city’s endgame is to become the most innovative city in America by 2020. However, to get there, the city needs some internal planning — and […]
The San Jose Smart City Vision is a plan that uses technology and data-driven decision-making to promote safety, sustainability, economic opportunity and quality of life for its constituents. The California city’s endgame is to become the most innovative city in America by 2020.
However, to get there, the city needs some internal planning — and a little help from its friends.
Last year, San Jose established a new Office of Civic Innovation to implement its vision to become as safe, inclusive, user-friendly and sustainable as possible, as well as to demonstrate the possibilities of technology and innovation.
The office will oversee a number of projects, programs and opportunities related to the city’s goal of making the city more efficient and effective, such as public safety, demonstration projects, data analytics, sustainability and public-private collaborations.
San Jose smart city projects are being narrowed down by focusing on three questions:
Is the problem causing a lot of people pain and annoyance?
Is it something that is core to what the city should do?
Is the problem amenable to solution at scale with either technology or process improvement?
“If the answers are yes, yes, yes, then the problem is something we want to address in our innovation portfolio,” said Kip Harkness, deputy city manager for Civic Innovation. “One of the projects at the top of the list is hiring. If we’re going to be a smart city — actually, we like to think of it as a ‘learning city’ — that is going to be powered by the people who work for us.”
Earlier this year, the John S. and James L. Knight Foundation awarded the city of San Jose $200,000 in funding to explore how to develop and implement smart technology “in responsible and equitable ways.” The award was part of a $1.2 million commitment from the Knight Foundation to help San Jose and other cities, including Akron, Ohio; Boston; Detroit; Miami; and Philadelphia, explore IoT applications in their respective cities.
For San Jose, smart city funding will be used to support IoT strategic planning to make better IoT investments, IoT infrastructure financing, smart technology assets regulation and how to create private sector partnerships to benefit citizens.