ICTC概述 (An ICTC Overview)

Access the full study, including all sources and methodology, here.

在 此处 访问完整的研究，包括所有来源和方法 。

研究范围 (Study Scope)

This study examines Canada’s opportunities for leveraging its current strengths in Artificial Intelligence (AI) to attract high-quality foreign direct investment (FDI).

这项研究考察了加拿大利用其当前在人工智能(AI)上的优势来吸引高质量外国直接投资(FDI)的机会。

Betting on Red and White: International Investment in Canadian AI also assesses recent domestic and international AI developments, and includes the following:

押注红色和白色：对加拿大AI的国际投资还评估了国内外AI的最新发展，包括以下内容：

• AI applications across sectors跨部门的AI应用
• Summary of Canadian AI research and commercialization加拿大AI研究与商业化概述
• Opportunities and barriers to continued AI expansion人工智能持续发展的机遇与障碍

This study extracts insights from industry leaders in over eight countries and seven sector verticals. It builds on ICTC’s 2019 report On the Edge of Tomorrow: Canada’s AI Augmented Workforce.

这项研究从八个国家和七个行业的行业领导者中汲取了见识。 它建立在ICTC 2019年的报告《明天的边缘：加拿大的AI增强型劳动力》上。

条款 (Terms)

Artificial Intelligence (AI): a multi-disciplinary subject, involving methodologies and techniques from mathematics, engineering, natural science, and computer science and linguistics.

人工智能(AI) ：一个多学科的学科，涉及数学，工程学，自然科学，计算机科学和语言学的方法论和技术。

Machine Learning (ML): a subset of AI, the application of algorithms capable of automatically learning from past experiences without being explicitly programmed.

机器学习(ML) ：AI的子集，算法的应用能够自动从过去的经验中学习，而无需进行显式编程。

Neural Networks: computing systems made of numerous simple, interconnected processing elements that respond to external inputs.

神经网络：由众多简单，相互连接的处理元件组成的计算系统，它们可以响应外部输入。

Deep Learning: an AI field closely associated with artificial neural networks. Deep Learning refers to the depth of multiple layers or stacks of neural networks.

深度学习：与人工神经网络紧密相关的AI领域。 深度学习是指神经网络的多层或堆栈的深度。

(Note: AI and Machine Learning are used interchangeably in this report. A further distinction is between “general” and “narrow” AI. General AI refers to the capacity for human-like cognition. To date, this has not been realized in machines. The current state of AI development is Narrow AI, commonly referred to as Machine Learning.)

(注：本报告中人工智能和机器学习可互换使用。“一般”和“狭义”人工智能之间有进一步的区别。通用人工智能指的是类似于人类的认知能力。迄今为止，这尚未在机器中实现AI的当前发展状态是Narrow AI，通常称为机器学习。)

研究背景 (Study Context)

Canada is increasingly a global hub for AI foreign investment. Regional AI development centres in Canada are Toronto, Montreal, and Edmonton.

加拿大日益成为AI外国投资的全球枢纽。 加拿大的区域AI开发中心是多伦多，蒙特利尔和埃德蒙顿。

Global businesses are turning to AI to generate efficiencies, increase productivity, and solve problems. AI can improve internal processes, enhance customer experience, manage risks, and can even create new products or services.

全球企业正在转向AI以提高效率，提高生产率并解决问题。 人工智能可以改善内部流程，增强客户体验，管理风险，甚至可以创建新产品或服务。

Current examples of AI include Netflix movie recommendations, Spotify’s “made for you” playlists, Alexa’s vast search capabilities, Snapchat augmented reality filters, etc.

当前的AI示例包括Netflix电影推荐，Spotify的“为您量身定制”的播放列表，Alexa的强大搜索功能，Snapchat增强现实过滤器等。

Promising new developments in AI have resulted in significant global growth in research, investment, and AI product development.

人工智能的有希望的新发展已导致研究，投资和人工智能产品开发的全球显着增长。

• Between 1998 and 2018, peer-reviewed AI research accelerated by 300%在1998年至2018年之间，经过同行评审的AI研究加速了300％
• In 2019, global AI investment totalled $70 billion2019年，全球AI投资总额达到700亿美元

研究结果 (Study Findings)

加拿大的AI (AI in Canada)

Canada is internationally recognized for academic research into AI. The rapid growth in AI research has recently spurred numerous AI startups across the country.

加拿大是国际上对AI进行学术研究的公认机构。 人工智能研究的快速增长最近刺激了全国众多的人工智能初创企业。

Currently, Canada has more than 650 AI startups, 40 accelerators and incubators, and over 60 research labs. Nearly 30% of Canadian startups were launched in 2017/18. International investment followed, with global giants such as Uber, Google, Facebook, and Samsung establishing AI research centres and operations in Canadian cities.

目前，加拿大拥有650多个AI初创公司，40个加速器和孵化器以及60多个研究实验室。 在2017/18年度，近30％的加拿大初创公司成立了。 随后进行了国际投资，Uber，谷歌，Facebook和三星等全球巨头在加拿大城市建立了AI研究中心并开展业务。

• In 2019, Canada ranked among the top five countries for innovative AI-based research2019年，加拿大在基于AI的创新研究中名列前五名
• Canada is becoming an international hub for AI startups, alongside US, Japan, and the UK加拿大正与美国，日本和英国一起成为AI创业公司的国际枢纽
• Regionally, Toronto, Montreal, Edmonton dominate AI research and startups, with Vancouver, Waterloo, and Quebec City also attracting attention在区域上，多伦多，蒙特利尔，埃德蒙顿主导着AI研究和初创公司，温哥华，滑铁卢和魁北克市也吸引了人们的注意

规模AI (Scale AI)

Scale AI is an AI innovation ecosystem comprised of industry, researchers, and business for improving productivity across Canada’s economy through the integration of AI. It is part of the Canadian federal government’s supercluster initiative.

Scale AI是一个由行业，研究人员和企业组成的AI创新生态系统，可通过集成AI来提高整个加拿大经济的生产率。 它是加拿大联邦政府超级集群计划的一部分。

Scale AI also aims to advance Canada’s global standing in AI and attract high-quality investment from abroad. It received more than $250 million from the federal and Quebec governments.

Scale AI还旨在提高加拿大在AI方面的全球地位，并吸引来自国外的高质量投资。 它从联邦政府和魁北克政府获得了超过2.5亿加元的资助。

To date, Scale AI has supported a total of 14 projects across industries such as retail, natural resources, and digital technology. Combined, these projects received over $32 million in funding to develop and scale their businesses.

迄今为止，Scale AI已为零售，自然资源和数字技术等行业的14个项目提供了支持。 这些项目加在一起获得了超过3200万美元的资金，用于发展和扩展业务。

区域中心 (Regional Hubs)

Edmonton

埃德蒙顿

The University of Alberta is a top-tier institution for computer science and AI. It is home of Canada’s first Computing Science department (est. 1964), with about 20 faculty members work in AI-related research.

艾伯塔大学是计算机科学和AI的顶级大学。 它是加拿大第一个计算机科学系(成立于1964年)的所在地，约有20名教职员工从事与AI相关的研究。

Edmonton-based AI trailblazer, the Alberta Machine Intelligence Institute (Amii) is a key fixture of Alberta’s thriving machine intelligence ecosystem and a key partner in many notable AI achievements over the past 15 years.

总部位于埃德蒙顿的AI开拓者，艾伯塔省机器智能研究所(Amii)是艾伯塔省蓬勃发展的机器智能生态系统的重要组成部分，并且是过去15年中许多卓越的AI成就的重要合作伙伴。

• The UofA recently partnered with Amii, with a focus on projects such as a digital chat companion for elderly Albertans, game development, clinical decision making, and financial portfolio balancingUofA最近与Amii合作，专注于一些项目，例如针对艾伯塔省年长者的数字聊天伙伴，游戏开发，临床决策和财务投资组合平衡
• Google’s DeepMind, the Royal Bank of Canada, Mitsubishi Electric, IBM and Volkswagen have partnered with Amii to conduct research on AI applications and solutions across sectors谷歌的DeepMind，加拿大皇家银行，三菱电机，IBM和大众汽车已经与Amii合作进行跨部门的AI应用程序和解决方案研究
• Local startup-support groups also work with Amii to grow talent and accelerate local ecosystem growth本地创业支持小组还与Amii合作，以培养人才并加快本地生态系统的增长
• Edmonton.AI works with Amii. Its mission is to create 100 AI and machine learning companies and projects in the cityEdmonton.AI与Amii合作。 其任务是在城市创建100个AI和机器学习公司及项目

Montreal

蒙特利尔

Montreal has the highest concentration of AI researchers in the world, with world-renowned research talent and more than 9,000 students in AI-related programs.

蒙特利尔是全球AI研究人员最集中的国家，拥有世界知名的研究人才，并且有9,000多名与AI相关计划的学生。

McGill University was ranked 35th top university in the world by QS World University Rankings in 2019.

麦吉尔大学在2019年QS世界大学排名中排名全球第35名。

The Montreal Institute for Learning Algorithms (Mila) is another key pillar of Montreal’s strength in AI research. Mila was founded by AI expert Yoshua Bengio, one of the world’s most cited computer scientists, famous for his work in neural networks and deep learning.

蒙特利尔学习算法研究所(Mila)是蒙特利尔在AI研究领域的实力的另一个重要Struts。 Mila由AI专家Yoshua Bengio创建，Yoshua Bengio是世界上被引用次数最多的计算机科学家之一，以在神经网络和深度学习领域的工作而闻名。

• In 2018, Mila’s Bengio (along with French-American Yann LeCun and British-Canadian Geoffrey Hinton) won the Turing Award — the” Nobel Prize” of computing2018年，Mila的Bengio(以及法裔美国人Yann LeCun和英裔加拿大人Geoffrey Hinton)获得了图灵奖-计算机的“诺贝尔奖”。
• Mila attracted substantial investment from government, industry, Google, and MicrosoftMila吸引了来自政府，行业，谷歌和微软的大量投资
• Currently, the Mila community has more than 450 researchers, focussed on deep learning, bioinformatics, computer vision, and neural networks目前，Mila社区拥有450多名研究人员，专注于深度学习，生物信息学，计算机视觉和神经网络

Montreal has over 120 AI startups, including Canada’s most recognizable AI company, Element AI (founded by Yoshua Bengio).

蒙特利尔拥有120多家AI初创公司，其中包括加拿大最知名的AI公司Element AI(由Yoshua Bengio创建)。

Toronto

多伦多

Canada’s largest city is an epicenter for AI Startups, currently with about 250 AI startups. Among them:

加拿大最大的城市是人工智能初创企业的震中中心，目前拥有约250家人工智能初创企业。 其中：

• ecobee, a developer of residential smart thermostatsecobee，住宅智能恒温器开发商
• AlayaCare, a cloud-based platform for healthcare practitionersAlayaCare，面向医疗保健从业者的基于云的平台
• Xanadu, a quantum photonic processor and open source software platformXanadu，量子光子处理器和开源软件平台

Toronto’s AI presence is backed by the city’s financial services sector strength and world-renowned academics such as Geoffrey Hinton and Richard Zemel.

多伦多的人工智能业务得到了该市金融服务业实力的支持和Geoffrey Hinton和Richard Zemel等世界知名学者的支持。

• Hinton is a University of Toronto professor, often referred to as the “Godfather of Deep Learning.” He was named one of the world’s top 100 influencers in 2016 and leads Brain Team Toronto for Google欣顿是多伦多大学的教授，通常被称为“深度学习教父”。 他被评为2016年全球百大影响者之一，并领导Google多伦多大脑团队
• Zemel, also a UofT computer science professor, specialized in machine learning. He was selected as the Google/ NSERC Industrial Research Chair for Machine Learning in 2018. His AI distinctions include the NVIDIA Pioneers of AI AwardZemel，也是UofT计算机科学教授，专门研究机器学习。 他于2018年被选为Google / NSERC机器学习工业研究主席。他的AI杰出成就包括NVIDIA AI先锋奖
• Hinton and Zemel also figure in the Vector Institute, a Toronto AI research and development centre for advancing AI research and applications in deep learning and machine learningHinton和Zemel还在多伦多AI研究与开发中心Vector Institute开展工作，该研究所致力于推进AI在深度学习和机器学习中的研究和应用
• The Vector Institute secured $135 million in funding in 2017 (over five years)Vector Institute在2017年(五年内)获得1.35亿美元的资金
• Vector Institute partnerships include Scotiabank, Accenture, Shopify, and St. Michael’s Hospital. The hospital partnership led to the creation of an early warning system for patients in need of transfer to intensive care unitsVector Institute的合作伙伴包括丰业银行，埃森哲，Shopify和圣迈克尔医院。 医院的伙伴关系为需要转移到重症监护病房的患者创建了预警系统
• The Vector Institute’s research and commercialization in AI and talent attraction is closely followed by investors and industry partnersVector Institute在人工智能和人才吸引方面的研究和商业化紧随投资者和行业合作伙伴之后

加拿大AI对Covid-19的回应 (Canadian AI Response to Covid-19)

COVID-19 derailed anticipated AI growth in 2020. However, the federal government’s spending to combat the pandemic includes 49 COVID research projects for manufacturing, life sciences, and AI (totaling $55 million across 100 projects).

COVID-19破坏了2020年AI的预期增长。但是，联邦政府在抗击流感大流行上的支出包括49个用于制造业，生命科学和AI的COVID研究项目(100个项目总计5500万美元)。

Canadian AI innovators and researchers are pivoting to develop solutions for this global crisis.

加拿大的AI创新者和研究人员正致力于开发针对这一全球危机的解决方案。

• The Vector Institute recently produced a list of tools, including open source research and data sets for anyone interested in contributing to COVID-19 research.Vector Institute最近发布了一系列工具，其中包括对有兴趣对COVID-19研究做出贡献的任何人的开源研究和数据集。
• Toronto-based BlueDot developed AI-based “outbreak risk software” that searches news, reports, and tracks flight paths (and other networks) to help anticipate the spread and impact of the disease.总部位于多伦多的BlueDot开发了基于AI的“暴发风险软件”，该软件可以搜索新闻，报告并跟踪飞行路线(和其他网络)，以帮助预测疾病的传播和影响。
• A special taskforce was created across Canada’s three main geographic AI hubs to battle the spread of COVID. Mila, the Vector Institute, and Amii joined researchers from the Canadian Institute for Advanced Research (CIFAR) to work on AI projects related to COVID-19.在加拿大的三个主要地理AI枢纽中创建了一个特别工作组，以对抗COVID的传播。 Mila，媒介研究所和Amii加入了加拿大高级研究所(CIFAR)的研究人员，从事与COVID-19相关的AI项目。

研究受访者对加拿大AI的观点 (Study Interviewee Perspectives on Canadian AI)

ICTC completed 20 in-depth interviews with key industry experts (including CEOs, CTOs, Directors, and technical leads) with international companies capable of making investments abroad. These interviews were critical to extracting primary research on AI use cases, investment needs, perceptions of Canada as a destination for investment, and international awareness of Canadian advances in AI.

ICTC与关键行业专家(包括CEO，CTO，董事和技术负责人)对有能力在国外进行投资的国际公司进行了20次深度访谈。 这些访谈对于提取有关AI用例，投资需求，对加拿大作为投资目的地的认识以及国际上对加拿大AI进步的认识的关键研究至关重要。

为什么要投资人工智能？ (Why Invest in AI?)

The study interviewees predominantly look to AI to solve specific problems in three areas:

研究受访者主要希望AI解决三个方面的特定问题：

• Product enhancement: 50% of interviewees use AI to develop or enhance existing products. Another 25% look to AI to develop new products.

  产品增强： 50％的受访者使用AI开发或增强现有产品。 另有25％的人希望AI开发新产品。

• Generating Efficiency and Improving Internal Processes: About 33% of interviewees are using AI to improve internal processes and generate efficiencies.

  产生效率并改善内部流程：约33％的受访者正在使用AI改善内部流程并提高效率。

• Improving Customer Experience: 20% of interviewees use AI to improve the customer experience, primarily through chatbots, machine learning to analyze customer data, and other tools for building business relationships.

  改善客户体验： 20％的受访者主要通过聊天机器人，机器学习来分析客户数据以及其他用于建立业务关系的工具，使用AI来改善客户体验。

公司对AI的投资 (Company Investments into AI)

Most interviewees in this study noted that their investments in AI are relatively new.

这项研究中的大多数受访者指出，他们在人工智能方面的投资相对较新。

• Nearly 60% started their investment and use of AI began less than five years ago将近60％的人开始投资，而AI的使用不到五年前
• 25% have been using AI for five to nine years25％的人已经使用AI五到九年了
• 15% have been investing in AI for over 10 years15％的人已经在AI上投资了10多年

Irrespective of length of experience with the technology, all interviewees have plans to continue growing their capabilities through AI-based investments, (despite that most were unable to quantify the economic value of AI to their organizations).

无论使用该技术的时间长短，所有受访者都计划通过基于AI的投资来继续提高其能力(尽管大多数人无法量化AI对组织的经济价值)。

人工智能实施的障碍 (Barriers to AI Implementation)

About 80% of interviewees rated barriers to implementing AI as “insignificant.”

大约80％的受访者将实施AI的障碍定为“微不足道”。

• For those that cited barriers, insufficient talent topped the list对于那些提到障碍的人来说，人才不足是最重要的
• “Cultural reluctance” to an “emerging or risky technology” was also noted还指出“不愿接受”新兴或冒险技术”

对加拿大AI发展的认识 (Awareness of Canadian AI Development)

Many interviewees were familiar with the Canadian AI ecosystem.

许多受访者熟悉加拿大的AI生态系统。

• 95% of interviewees were aware of developments in Canadian AI95％的受访者了解加拿大AI的发展
• 75% of interviewees were most familiar with Toronto, Edmonton, and Montreal as Canada’s main AI hubs75％的受访者最熟悉多伦多，埃德蒙顿和蒙特利尔作为加拿大的主要AI枢纽
• Most interviewees knew about Canada’s Scale AI Supercluster and key educational institutions for AI researchers大多数受访者了解加拿大的Scale AI Supercluster和AI研究人员的主要教育机构

对加拿大成长中的AI社区的认可 (Recognition of Canada’s Growing AI Community)

Canada is perceived as a top destination for skilled international talent, with an effective immigration system, and a welcoming and friendly culture.

加拿大被认为是国际熟练人才的最佳目的地，拥有有效的移民制度和热情友好的文化。

• Interviewees praised Canada’s educational institutions for producing high-quality AI talent at the entry level受访者赞扬加拿大的教育机构在入门级培养了高素质的AI人才
• Canada’s growing AI capabilities — specifically in research — is internationally recognized加拿大日益增长的AI能力(尤其是研究能力)已得到国际认可
• Top researchers, such as Yoshua Bengio and Geoffrey Hinton, are essential to the recognition of Canada’s AI ecosystemYoshua Bengio和Geoffrey Hinton等顶尖研究人员对于承认加拿大的AI生态系统至关重要

人工智能投资的障碍 (Barriers for AI Investment)

Approximately 30% of interviewees couldn’t identify any barriers for AI investment attraction to Canada; the remainder noted the following investment barriers:

大约30％的受访者无法发现任何阻碍AI投资加拿大的障碍； 其余的指出以下投资障碍：

• Nearly 65% of interviewees identified “unclear” regulation as the top barrier近65％的受访者认为“不清楚”的法规是最大的障碍
• Over 40% expressed concern about the Canadian talent pipeline (challenges in senior level AI talent recruitment). A greater worry is talent retention (losses to US competitors)超过40％的人表示担心加拿大的人才储备(高级AI人才招聘面临的挑战)。 更令人担忧的是人才保留(对美国竞争对手的损失)
• 25% of interviewees noted concerns over scaling startups (confirmed by a recent report finding by the Impact Centre at the University of Toronto that Canada “dramatically underperforms” the US in scaling private companies)25％的受访者指出了对扩展初创公司的担忧(多伦多大学冲击中心最近的一份报告证实，加拿大在扩展私人公司方面“大大落后于美国”)

A clear majority of interviewees felt that Canada was a favourable destination for foreign direct investment in AI and indicated interest in Canada for their own investment strategies.

显然，大多数受访者认为加拿大是外国直接投资人工智能的有利目的地，并表示对加拿大自己的投资策略感兴趣。

Despite some hurdles, Canada is a top contender for AI-based FDI and is positioned to make a significant contribution to the global AI ecosystem.

尽管有一些障碍，加拿大还是基于人工智能的外国直接投资的最大竞争者，并有能力为全球人工智能生态系统做出重大贡献。

世界各地的AI (AI Around the World)

Globally, many countries are working to use AI to boost economic growth, generate efficiency, and create solutions to important societal challenges, such as the current pandemic. In 2018, there were an estimated 4,500 public AI companies around the world.

在全球范围内，许多国家正在努力使用人工智能来促进经济增长，提高效率并为重要的社会挑战(例如当前的流行病)创建解决方案。 2018年，全球估计有4,500家公共AI公司。

美国人工智能的发展 (US Developments in AI)

The US is currently the undisputed leader in AI, with nearly half of the world’s AI companies (over 2000). Many are supported by government agencies like the Department of Justice (DOJ), the Securities Exchange Commission, and NASA.

美国目前是人工智能领域无可争议的领导者，全球有近一半的人工智能公司(2000多家)。 许多机构得到了司法部(DOJ)，证券交易委员会和NASA等政府机构的支持。

• The closest AI competitor to the US is China, with over 1,000 companies与美国最接近的AI竞争对手是中国，拥有1000多家公司
• American AI companies typically generate nearly 50% more funding per investment than AI companies located in China美国的AI公司通常每笔投资比位于中国的AI公司多产生近50％的资金

In 2019, Intel made a total of 19 investments in US AI startups, followed by Google at 16, and Microsoft with 11 investments.

2019年，英特尔对美国AI初创公司进行了19笔投资，其次是Google(16位)，微软(11位)

The top three AI hubs in the US are:

美国排名前三的AI中心是：

San Francisco

旧金山

• San Francisco has some of the biggest startup incubators in the world, with world-renowned institutions, including:旧金山拥有世界上最大的初创企业孵化器，并拥有世界知名的机构，其中包括：
• Stanford University’s AI Lab, SRI International’s Artificial Intelligence Centre (AIC), and Google-NASA’s Quantum AI Lab)斯坦福大学的AI实验室，SRI国际的人工智能中心(AIC)和Google-NASA的Quantum AI实验室)

Boston

波斯顿

• Boston is the second largest US AI hub and the premier location for biopharmaceutical developments. It is also home to institutions such as the Massachusetts Institute of Technology (MIT), MIT’s Computer Science and Artificial Intelligence Laboratory, and the Centre for Brains, Minds, and Machines.波士顿是美国第二大AI枢纽，也是生物制药开发的主要地点。 它也是麻省理工学院(MIT)，麻省理工学院的计算机科学和人工智能实验室以及大脑，思维和机器中心等机构的所在地。

New York

纽约

• New York City AI development is heavily supported by institutions like New York University’s Courant Institute of Mathematical Sciences, Facebook’s AI Research Group (FAIR), and others纽约市的AI开发得到了纽约大学库randint数学科学学院，Facebook的AI研究小组(FAIR)等机构的大力支持

Many US AI-based products have found consumer applications. Assistants like Google Home or Amazon Echo are among top-selling gifts. New US trade restrictions in 2020 (requiring US companies that export AI for geospatial analysis to apply for an export licence), however, could dampen sales of some US AI products worldwide.

许多基于美国AI的产品已经找到了消费类应用程序。 诸如Google Home或Amazon Echo之类的助手是最畅销的礼物。 但是，2020年美国的新贸易限制(要求出口AI的美国公司进行地理空间分析以申请出口许可证)可能会抑制某些AI产品在全球的销售。

美国AI对COVID-19的回应 (US AI Response to COVID-19)

The use of AI in the life sciences could play a key role in curbing the spread of COVID-19.

在生命科学中使用AI可以在遏制COVID-19的传播中发挥关键作用。

The US National Institutes of Health (NIH) announced funding for researchers and businesses developing solutions to COVID-19. Tech giants Apple and Google are codeveloping technology for contact tracing.

美国国立卫生研究院(NIH)宣布为研究人员和企业开发COVID-19解决方案的资金。 科技巨头苹果和谷歌正在共同开发联系人追踪技术。

中国 (China)

In 2018, a quarter of the world’s AI companies were in China.

2018年，全球AI公司的四分之一在中国。

A significant asset for China in the AI race is the data of its 1.3 billion citizens. Coupled with strong economic growth, China is expected to expand its global leadership in AI.

中国在AI竞赛中的一项重要资产是其13亿公民的数据。 加上强劲的经济增长，预计中国将扩大其在人工智能领域的全球领导地位。

• China’s top AI companies include SenseTime, currently the world’s highest-valued AI startup. It received investment from Qualcomm, Fidelity International, and Hopu Capital中国顶尖的AI公司包括SenseTime，这是目前全球价值最高的AI初创公司。 它获得了高通，富达国际和厚朴资本的投资
• Cloudwalk, a facial recognition technology giant in China, makes over 1 billion comparisons of faces against its database each day and has accumulated more than 100 billion data points中国人脸识别技术巨头Cloudwalk每天通过其数据库对人脸进行超过10亿次比较，并积累了超过1000亿个数据点

China expansion of surveillance capabilities through AI raises questions about data use and AI ethics, and influences China’s ability to source international investment. China currently receives one-third the investment that US AI companies receive ($15 billion in China vs. $45 billion in the US, in 2017).

中国通过AI扩展监视能力引发了有关数据使用和AI伦理的问题，并影响了中国获取国际投资的能力。 中国目前获得美国AI公司获得的投资的三分之一(中国为150亿美元，而美国为450亿美元，2017年)。

Emerging Chinese AI Hubs

新兴的中国AI枢纽

Of China’s 1,000-plus AI companies, approximately 40% are in Beijing and 15% are in Shenzhen.

在中国1000多家AI公司中，约40％在北京，而15％在深圳。

Hangzhou City has gained recognition, with Alibaba, one of the world’s largest technology companies. Over 1,000 AI patents have been submitted by Hangzhou-based companies.

杭州市与全球最大的科技公司之一阿里巴巴(Alibaba)一起获得认可。 杭州的公司已经提交了1,000多项AI专利。

Other emerging AI hubs in China include Shanghai and Hefei. Hefei recently established China’s first national library for “brain-like” artificial intelligence technology.

中国其他新兴的AI中心包括上海和合肥。 合肥最近建立了中国第一个“类脑”人工智能技术国家图书馆。

中国AI对COVID-19的React (Chinese AI Response to COVID-19)

Wuhan was ground zero for the COVID-19 pandemic, and China focussed its AI efforts on combatting the health crisis.

武汉因COVID-19大流行而处于零地面，而中国则将AI的工作重点放在了应对健康危机上。

• China accessed citizen data and large-scale acceptance of surveillance technology to develop new interventions for the spread of COVID-19中国获得了公民数据并广泛接受了监视技术，从而为传播COVID-19制定了新的干预措施
• AI-assisted temperature testing curbed the spread of the infection on public transit in China (passengers with high temperatures were contacted and advised to self-isolate)人工智能辅助的温度测试可抑制感染在中国公共交通中的传播(联系了高温乘客并建议他们进行自我隔离)
• AI-assisted CT scans were piloted for faster detection of the virus in radiology departments试验了AI辅助的CT扫描，以便在放射科更快地检测病毒

欧盟AI (European Union AI)

Europe has a thriving AI industry, with over 3,000 companies (public and private) across sectors, including data analytics, sales, marketing, healthcare, process automation, and image recognition.

欧洲拥有蓬勃发展的AI产业，在数据分析，销售，市场营销，医疗保健，流程自动化和图像识别等各个领域拥有3,000多家公司(公共和私营)。

EU AI hubs:

欧盟AI枢纽：

• Stockholm (with approximately 1,166 AI jobs per 1 million people)斯德哥尔摩(每100万人中约有1,166个AI工作)
• Amsterdam (730 AI jobs per 1 million people)阿姆斯特丹(每100万人中730个AI工作)
• And Berlin (677 AI jobs per million)柏林(每百万677个AI工作)

In 2018, Germany launched a digitization initiative aimed at becoming a global leader in AI.

2018年，德国发起了数字化计划，旨在成为AI的全球领导者。

Ethical AI Development: European Commission

符合道德规范的AI开发：欧洲委员会

The European Commission is seeking to ensuring that AI developments reflect core EU values. The EU is a global leader in the analysis of AI from ethical, legal, and socio-economic perspectives.

欧盟委员会正在努力确保AI的发展反映出欧盟的核心价值。 欧盟是从道德，法律和社会经济角度分析人工智能的全球领导者。

Under the EU’s Horizon 2020 framework, over €2.5 billion was allocated to AI-related research and development projects in robotics, big data, health, transportation, and emerging technologies.

在欧盟的Horizo​​n 2020框架下，超过25亿欧元分配给了与人工智能相关的机器人，大数据，健康，交通和新兴技术研究与开发项目。

This initial investment is expected to be followed by €100 billion of funding under Horizon Europe, the EU’s forthcoming research and innovation framework program set to launch in January 2021.

预计将在Horizo​​n Europe(欧洲即将推出的将于2021年1月启动的研究和创新框架计划)下获得1000亿欧元的资金支持。

Key EU Startups

欧盟主要初创企业

In March 2020, CB Insights ranked the top 100 most promising AI startups in the world. The list included six companies located in four EU countries.

2020年3月，CB Insights将全球前100名最有前途的AI初创公司排名。 该名单包括位于四个欧盟国家的六家公司。

France — Heuritech develops a deep learning powered automatic real-time recognition of objects, including shapes and people

法国 — Heuritech开发了一种基于深度学习的自动实时识别物体的方法，包括形状和人物

Germany — KONUX smart sensors utilize advanced analytics to enable predictive maintenance for industrial products.

德国 — KONUX智能传感器利用高级分析功能对工业产品进行预测性维护。

• NavVis develops fully managed digital twinsNavVis开发完全托管的数字双胞胎

Spain — Sherpa is a dual platform digital assistant using machine learning

西班牙 — Sherpa是使用机器学习的双平台数字助理

Sweden — Mapillary computer vision createS better maps.

瑞典 -Mapillary计算机视觉可以创建更好的地图。

• PerceptiLabs offers a unique way of building and visualizing models used by data scientists, machine learning engineers, and developersPerceptiLabs提供了一种独特的方式来构建和可视化数据科学家，机器学习工程师和开发人员使用的模型

欧盟AI对COVID-19的回应 (EU AI Response to COVID-19)

Many EU organizations focused on battling COVID-19. Hospitals shared data to help train algorithms through “federated learning” (data never left hospitals or touched a private server).

许多欧盟组织专注于与COVID-19作战。 医院共享数据，以通过“联合学习”(数据从未离开医院或接触过私人服务器)来帮助训练算法。

Other efforts included the ImaginingCovid19ai.eu project, which had hospitals transfer data to Quibim, a Spanish-based company using AI to improve the reading of chest CT scans when testing COVID-19 in patients with respiratory disorders.

其他工作包括ImaginingCovid19ai.eu项目，该项目使医院将数据传输到西班牙的Quibim公司，该公司使用AI来改善呼吸系统疾病患者的COVID-19测试时胸部CT扫描的读数。

人工智能对加拿大经济部门的影响 (Impact of AI Across Canadian Economic Sectors)

AI has a growing presence across all areas of the economy. The following sectors serve as examples for the application of AI:

人工智能在经济的各个领域都在增长。 以下部门是AI应用的示例：

Agriculture Ocean Technology: A growing global population will require unique, effective, and climate-neutral approaches to improving agricultural yields. Weather date, soil quality, crop growth, and even animal health can then be improved by machine learning algorithms

农业海洋技术：不断增长的全球人口将需要独特，有效且与气候无关的方法来提高农业产量。 然后可以通过机器学习算法来改善天气日期，土壤质量，作物生长甚至动物健康

• AI is increasingly key in detecting diseases in plants, aiding in pest control, and can identifying farm-wide problems (in combination with drones)人工智能在检测植物疾病，辅助害虫控制以及识别农场范围内的问题(与无人机结合)方面越来越重要
• Machine learning algorithms can draw upon historical data on rainfall, temperatures, and evaporation to predict the likelihood of a droughts机器学习算法可以利用有关降雨，温度和蒸发的历史数据来预测干旱的可能性

Advanced Manufacturing: AI, robotics, the Internet of Things, and 3D printing are enhancing manufacturing output

先进制造业：人工智能，机器人技术，物联网和3D打印正在提高制造业产出

• Various human activities may not be suitable for automation but can still be improved through AI-generated insights. (Eg. California-based Drishti uses cameras equipped with deep leaning architecture to generate real-time analytics of human-performed actions analyzed by AI to optimize human performance)各种人类活动可能不适合自动化，但仍可以通过AI生成的见解加以改进。 (例如，总部位于加利福尼亚州的Drishti使用配备了深层倾斜架构的相机来生成由AI分析的人类执行动作的实时分析，以优化人类绩效)
• Business and Finance: Financial advisers, investment bankers, tax advisers, and human resources professionals leverage large amounts of data to make informed decisions. Automated and algorithm-based financial and business products are gaining ground商业和金融：财务顾问，投资银行家，税务顾问和人力资源专业人员利用大量数据做出明智的决定。 自动化和基于算法的金融和商业产品正在普及

Digital Technology: AI in the digital technology sector is fast evolving and diverse

数字技术：数字技术领域的AISwift发展且多样化

• Facial recognition technology automatically “logs in” iPhone owners面部识别技术自动“登录” iPhone所有者
• Apple’s Overton AI-based apps answer billions of questions and analyze trillions of data records苹果基于Overton AI的应用可回答数十亿个问题并分析数万亿条数据记录

Life Sciences: Data and analysis-intensive healthcare applications can benefit from AI for improved diagnosis, patient experience, and accelerate drug development

生命科学：数据和分析密集型医疗保健应用可受益于AI，以改善诊断，患者体验并加快药物开发

• Toronto-based ConversationHEALTH offers messaging apps, websites, voice devices, and banner ads, allowing healthcare companies to enter the “conversational age”位于多伦多的ConversationHEALTH提供消息传递应用程序，网站，语音设备和横幅广告，使医疗保健公司能够进入“对话时代”
• Swift Medical uses AI to identify the severity of wounds and speed healingSwift Medical使用AI识别伤口的严重程度并加快愈合速度
• Telecom giant Telus developed an application called Babylon that uses a chat-style symptom checker powered by AI电信巨头Telus开发了一个名为Babylon的应用程序，该应用程序使用由AI驱动的聊天式症状检查器

Natural Resources: Further automation and increasing use of AI is expected in this sector. Digital technologies are improving environmental performance, costs efficiencies, and safety

自然资源：预计该领域将进一步实现自动化并增加对AI的使用。 数字技术正在改善环境绩效，成本效率和安全性

• In the forestry industry, machine learning is improving the speed and accuracy of tree species analysis, estimating wood volume, and tree dimensions在林业行业，机器学习正在提高树木种类分析的速度和准确性，估计木材体积和树木尺寸
• Vancouver-based PhotoSat uses machine learning algorithms to transform pictures taken from satellites into 3D models of worksites位于温哥华的PhotoSat使用机器学习算法将卫星拍摄的图片转换为工作场所的3D模型

Transportation and Logistics: AI is improving transportation, logistics, and supply chains

运输和物流：人工智能正在改善运输，物流和供应链

• Ocado, a supermarket chain in the United Kingdom, uses a robot called the “hive-grid-machine” to execute 65,000 orders per week, dramatically reducing labour costs while optimizing the movement of items to their final destination英国的一家连锁超市Ocado使用名为“蜂巢网格机”的机器人每周执行65,000个订单，从而大大降低了劳动力成本，同时优化了商品到最终目的地的运输
• Attabotics, a Calgary-based robotics supply chain company, replaces warehouse shelving with vertical storage structures attended by robotic shuttlesAttabotics是一家位于卡尔加里的机器人供应链公司，以由机器人班车陪同的垂直存储结构代替仓库货架
• AI is a significant component of smart mobility options like autonomous vehicles, but many transportation businesses are already using AI to generate efficiencies and manage traffic flow人工智能是自动驾驶等智能出行选择的重要组成部分，但是许多运输企业已经在使用人工智能来提高效率和管理交通流量