Hans Y Combinator Presentation on Lessons from China for Global EntrepreneursGGV Capital
GGV Capital Managing Partner Hans Tung talks about lessons learned from China that can benefit global entrepreneurs. Initially presented at Y Combinator in October 2017
Lessons from US & China for Global EntrepreneursGGV Capital
Hans Tung, managing partner of GGV Capital who has been investing in startups across US and China for almost 20 years, shares his observations on tech in the US and China, and how entrepreneurs can learn from the world’s two most vibrant startup ecosystems.
2016 was a standout year for entrepreneurs in the GGV Capital ecosystem. Our portfolio companies collectively completed more than $26 billion of M&A and IPO activity, raised more than $10 billion to fuel global expansion, and completed one new IPO (BC Pharma in China).
The year also marked expansion on a number of fronts for our firm. We announced the launch of GGV Capital Fund VI and our Discovery Fund with more than $1.2 billion in commitments. A big thank you to our Limited Partners for their continued support. Second, we added 16 new members to the GGV Capital team across the U.S. and China.
GGV Capital Jenny Lee: Next Gen Wearables, Transportation and Robotics June 2016GGV Capital
Jenny Lee, Managing Partner, GGV Capital shared her insights on next generation wearables, transportation and robotics at the WSJ Converge conference in Hong Kong. Here’s the presentation.
Hans Y Combinator Presentation on Lessons from China for Global EntrepreneursGGV Capital
GGV Capital Managing Partner Hans Tung talks about lessons learned from China that can benefit global entrepreneurs. Initially presented at Y Combinator in October 2017
Lessons from US & China for Global EntrepreneursGGV Capital
Hans Tung, managing partner of GGV Capital who has been investing in startups across US and China for almost 20 years, shares his observations on tech in the US and China, and how entrepreneurs can learn from the world’s two most vibrant startup ecosystems.
2016 was a standout year for entrepreneurs in the GGV Capital ecosystem. Our portfolio companies collectively completed more than $26 billion of M&A and IPO activity, raised more than $10 billion to fuel global expansion, and completed one new IPO (BC Pharma in China).
The year also marked expansion on a number of fronts for our firm. We announced the launch of GGV Capital Fund VI and our Discovery Fund with more than $1.2 billion in commitments. A big thank you to our Limited Partners for their continued support. Second, we added 16 new members to the GGV Capital team across the U.S. and China.
GGV Capital Jenny Lee: Next Gen Wearables, Transportation and Robotics June 2016GGV Capital
Jenny Lee, Managing Partner, GGV Capital shared her insights on next generation wearables, transportation and robotics at the WSJ Converge conference in Hong Kong. Here’s the presentation.
EURO BEINAT | Big Data e Intelligenza Artificiale | Ecosistemi Digitali | 2 d...BTO Educational
Ecosistemi Digitali - Strategie, infrastrutture e strumenti digitali per il Turismo della Destinazione Italia
Firenze, 2 dicembre 2016
http://ecosistemi.buytourismonline.com
Interoperabilità e Big Data
Euro Beinat
Professore di Geoinformatica Università di Salisburgo
http://ecosistemi.buytourismonline.com/i-risultati/
Il progresso tecnologico ha dato a una moltitudine di attori la possibilità di analizzare incredibili quantità di informazioni utili per la conoscenza di fenomeni e l’elaborazione di previsioni. Sono informazioni determinanti per i soggetti che hanno la responsabilità di definire strategie a sostegno della programmazione e della progettazione turistica, in funzione della creazione di valore per destinazioni e operatori. Diventa di fondamentale importanza quindi poter disporre di strumenti e metodi automatizzati per svolgere questo compito.
Report from the State of GovTech Market Event in San Francisco on October 27, 2016 in collaboration with the San Francisco Mayor's Office of Civic Innovation, Crunchbase and the Nasdaq Entrepreneurial Center.
**Updated with end-of-year numbers for 2016.
Tech Giants, the Moligopoly Hypothesis and Conglomerate CompetitionNicolas Petit
This presentation discusses the nature of competition amongst the US technology giants. It focuses on Google, Apple, Facebook, Amazon and Microsoft (GAFAM). It suggests that the current categorization of those firms as monopolies is wrong. It is based on a misguided frame of reference, which is blind to competition that occurs outside of the core market where those companies operate. Antitrust agencies and regulators should take a more holistic view of the conglomerate competition that exists amongst those firms. They should in particular look at how those companies "compete against the non consumption", in search for new and low end market footholds. The presentation makes a number of policy proposals, including using innovation-based screens and tests to decided which cases to prioritize and exonerate.
A high-level overview of the state and local government technology (GovTech) market. If you're interested in including your company in future research and editorial, please submit it at http://labs.erepublic.com/startups.
Follow me on Twitter @hongsuhyeon. Questions? christine.hong.govtech@gmail.com
The government technology (“govtech”) industry is an emerging ecosystem that has the potential to transform governments. The paper maps out the ecosystem and provide a quantitative understanding of its growth trajectory by answering the following four questions:
1. What is the definition of govtech?
2. What does the ecosystem look like?
3. How is the ecosystem changing?
4. What factors will accelerate market take-off?
In order to answer these questions, experts in the biggest govtech companies, the venture capital community, government and opinion leaders were interviewed. Moreover, the paper selected 98 of the most notable govtech companies in United States based on sources like Govtech.com’s Govtech 100 list, and tracked their private capital deal flows from 2004 to 2015. Details of the Deal Flow Database and the methodology are in the appendix.
Could smart factories of the future make humans redundant? Zane Small
This is a feature I wrote about automation - one of the greatest threats to jobs around the world. Some tech leaders have spoken out in support of a universal basic income (UBI) to avoid technology companies being perceived as job destroyers.
The Amazing Ways Alibaba Uses Artificial Intelligence And Machine LearningBernard Marr
Alibaba is already one of China's most influential tech companies, but it is very focused on becoming China's artificial intelligence leader as well. From altering retail to developing smart cities and nearly every industry and application in between, Alibaba is helping China achieve its goal to become the dominant AI player in the world.
Lee Rainie, director of internet and technology research at Pew Research Center, presented these findings at the International Monetary Fund/World Bank’s Youth Dialogue and its program, “A World Without Work?” The findings tie to several pieces of research at the Center, including reports on the state of American jobs, automation in everyday life, and the future of jobs training programs.
Robots are everywhere, even where you would not expect. Artificial intelligence is already part of our daily lives. What are the robots among us past and present - and what is yet to come?
Irrational Exuberance: A Tech Crash is ComingJeffrey Funk
These slides apply Nobel Laureate Robert Schiller's concept of irrational exuberance (and a book) title to the current speculative bubble of 2019. Over investments in startups and a lack of profitability in them are finally starting to catch up with the venture capital industry and the tech sector that relies on it. Investments by US venture capitalists have risen about six times since 2001 causing the total invested in 2018 to exceed by 40% the peak of 2000, the last big year of the dotcom bubble. But the number of IPOs has never returned to the peak years of 1993 to 2000; only about 250 were carried out between 2015 and 2017 vs. about 1,200 between 1995 and 1997.
The reason is simple: startups are taking longer to go public because they are not profitable. Consider the data. The median time to IPO has risen from 2.8 years in 1998 to 7.7 years in 2016 and the ones going public are less profitable than they were in the past. Although only 22% of startups going public in 1980 were unprofitable, 82% were unprofitable in 2018. The same high percentages of unprofitability have only been achieved twice before, in 1998 and 1999 right before the dotcom bubble burst. Furthermore, startups that have recently done high profile IPOs such as Snap, Dropbox, Blue Apron, Fitbit, Trivago, Box, and Cloudera are still not profitable.
Artificial intelligence is impacting both the economy and daily lives of Chinese people and is widely used across many industries. A comprehensive report on the AI technologies in China is offered by Daxue consulting
EURO BEINAT | Big Data e Intelligenza Artificiale | Ecosistemi Digitali | 2 d...BTO Educational
Ecosistemi Digitali - Strategie, infrastrutture e strumenti digitali per il Turismo della Destinazione Italia
Firenze, 2 dicembre 2016
http://ecosistemi.buytourismonline.com
Interoperabilità e Big Data
Euro Beinat
Professore di Geoinformatica Università di Salisburgo
http://ecosistemi.buytourismonline.com/i-risultati/
Il progresso tecnologico ha dato a una moltitudine di attori la possibilità di analizzare incredibili quantità di informazioni utili per la conoscenza di fenomeni e l’elaborazione di previsioni. Sono informazioni determinanti per i soggetti che hanno la responsabilità di definire strategie a sostegno della programmazione e della progettazione turistica, in funzione della creazione di valore per destinazioni e operatori. Diventa di fondamentale importanza quindi poter disporre di strumenti e metodi automatizzati per svolgere questo compito.
Report from the State of GovTech Market Event in San Francisco on October 27, 2016 in collaboration with the San Francisco Mayor's Office of Civic Innovation, Crunchbase and the Nasdaq Entrepreneurial Center.
**Updated with end-of-year numbers for 2016.
Tech Giants, the Moligopoly Hypothesis and Conglomerate CompetitionNicolas Petit
This presentation discusses the nature of competition amongst the US technology giants. It focuses on Google, Apple, Facebook, Amazon and Microsoft (GAFAM). It suggests that the current categorization of those firms as monopolies is wrong. It is based on a misguided frame of reference, which is blind to competition that occurs outside of the core market where those companies operate. Antitrust agencies and regulators should take a more holistic view of the conglomerate competition that exists amongst those firms. They should in particular look at how those companies "compete against the non consumption", in search for new and low end market footholds. The presentation makes a number of policy proposals, including using innovation-based screens and tests to decided which cases to prioritize and exonerate.
A high-level overview of the state and local government technology (GovTech) market. If you're interested in including your company in future research and editorial, please submit it at http://labs.erepublic.com/startups.
Follow me on Twitter @hongsuhyeon. Questions? christine.hong.govtech@gmail.com
The government technology (“govtech”) industry is an emerging ecosystem that has the potential to transform governments. The paper maps out the ecosystem and provide a quantitative understanding of its growth trajectory by answering the following four questions:
1. What is the definition of govtech?
2. What does the ecosystem look like?
3. How is the ecosystem changing?
4. What factors will accelerate market take-off?
In order to answer these questions, experts in the biggest govtech companies, the venture capital community, government and opinion leaders were interviewed. Moreover, the paper selected 98 of the most notable govtech companies in United States based on sources like Govtech.com’s Govtech 100 list, and tracked their private capital deal flows from 2004 to 2015. Details of the Deal Flow Database and the methodology are in the appendix.
Could smart factories of the future make humans redundant? Zane Small
This is a feature I wrote about automation - one of the greatest threats to jobs around the world. Some tech leaders have spoken out in support of a universal basic income (UBI) to avoid technology companies being perceived as job destroyers.
The Amazing Ways Alibaba Uses Artificial Intelligence And Machine LearningBernard Marr
Alibaba is already one of China's most influential tech companies, but it is very focused on becoming China's artificial intelligence leader as well. From altering retail to developing smart cities and nearly every industry and application in between, Alibaba is helping China achieve its goal to become the dominant AI player in the world.
Lee Rainie, director of internet and technology research at Pew Research Center, presented these findings at the International Monetary Fund/World Bank’s Youth Dialogue and its program, “A World Without Work?” The findings tie to several pieces of research at the Center, including reports on the state of American jobs, automation in everyday life, and the future of jobs training programs.
Robots are everywhere, even where you would not expect. Artificial intelligence is already part of our daily lives. What are the robots among us past and present - and what is yet to come?
Irrational Exuberance: A Tech Crash is ComingJeffrey Funk
These slides apply Nobel Laureate Robert Schiller's concept of irrational exuberance (and a book) title to the current speculative bubble of 2019. Over investments in startups and a lack of profitability in them are finally starting to catch up with the venture capital industry and the tech sector that relies on it. Investments by US venture capitalists have risen about six times since 2001 causing the total invested in 2018 to exceed by 40% the peak of 2000, the last big year of the dotcom bubble. But the number of IPOs has never returned to the peak years of 1993 to 2000; only about 250 were carried out between 2015 and 2017 vs. about 1,200 between 1995 and 1997.
The reason is simple: startups are taking longer to go public because they are not profitable. Consider the data. The median time to IPO has risen from 2.8 years in 1998 to 7.7 years in 2016 and the ones going public are less profitable than they were in the past. Although only 22% of startups going public in 1980 were unprofitable, 82% were unprofitable in 2018. The same high percentages of unprofitability have only been achieved twice before, in 1998 and 1999 right before the dotcom bubble burst. Furthermore, startups that have recently done high profile IPOs such as Snap, Dropbox, Blue Apron, Fitbit, Trivago, Box, and Cloudera are still not profitable.
Artificial intelligence is impacting both the economy and daily lives of Chinese people and is widely used across many industries. A comprehensive report on the AI technologies in China is offered by Daxue consulting
Global innovation Trends for 2018 and How to SurviveKyle Ellicott
This presentation gives an overview of the upcoming industry and technology trends for 2018.
I presented this deck at the China Entrepreneurship Service Summit in Shenzhen, China on November 18, 2017.
Unfolding the Industry Blueprint of an Intelligent World —Huawei Global Indus...Huawei Technologies
Huawei has released its Global Industry Vision (GIV) 2025, a new forward-looking report that provides quantitative and qualitative predictions about the future of industry and society.
Relying on Huawei's own business strengths and insights into industry trends, GIV 2025 has its own unique research methodology. It adopts a mix of data and trend analysis to elaborate on global ICT trends and lay out the blueprint for the ICT industry. The data used in GIV 2025 spans more than 170 countries and regions. This report covers three dimensions (all things connected, all things sensing, and all things intelligent) and 37 metrics, including the amount of data generated, the percentage of enterprises that adopt artificial intelligence (AI), and the number of personal smart devices.
According to the report, by 2025 all things will be able to sense and all things will be connected, bringing us all into a world where everything is intelligent. GIV 2025 predicts that by 2025, the number of personal smart devices will reach 40 billion and the total number of connections around the world will reach 100 billion, creating a digital economy worth US$23 trillion.
In recent years, the construction of smart cities around the world has gradually entered a new round of development, especially in China, where major cities are actively exploring smart cities in the traditional sense and evolving into new smart cities.
IT/Telecom Service/Media: China Shenzhen visit note
IT industry in Shenzhen: Opportunities and risks
IOTE 2016 overview
Market trends in Chinese media content
Visits to Shenzhen-based Tencent and DJI
The GGV Capital Digital Economy Index looks at the IRR of publicly-traded ecommerce companies that are shaping economic performance in consumer industries ranging from ecommerce, fintech, education technology, food technology, wellness and health tech, and more.
The GGV Capital Digital Economy Index looks at the IRR of publicly-traded ecommerce companies that are shaping economic performance in consumer industries ranging from ecommerce, fintech, education technology, food technology, wellness and health tech, and more.
GGV Capital and Max Ventures co-hosted its second annual Evolving E NYC Summit in the heart of midtown Manhattan. More than 300 founders, executives, and investors of top consumer companies gathered to share ideas and insights on growth, culture and product. While the private event was off-the-record, we wanted to capture some key takeaways from the evening’s speakers to share.
On Thursday, March 9th, we hosted Evolving Enterprise, an afternoon event with top founders and leaders in SaaS. Here are some of the more memorable quotes from our speakers.
Monetization in the US and China: Where to InvestGGV Capital
In this presentation, GGV Capital Managing Partner Hany Nada analyzes the differences in the US and China advertising markets, areas of opportunity and other methods of monetization.
In this deck we look at key industries being disrupted by mobile, including transportation and travel, online and offline commerce, and hardware and IoT.
A look at the shifts in focus in Silicon Valley as mobile has taken technology to a global scale. This presentation looks at the impact of mobile and emerging markets on how people consume and the disruption coming to traditional industries, such as food, CPG, and spirits.
Sales and Marketing 3.0: The High Velocity ModelGGV Capital
This deck looks at the evolution of the next model in enterprise sales and marketing: the high velocity organization. See how high velocity teams use technology, data and automation to align sales and marketing and drive faster leads and conversions.
2014 was all about...people. The world-class entrepreneurs who feed off the energy of the companies they are building and the industries they are changing.
The Global Mobile Revolution - GGV CapitalGGV Capital
The birth of the smartphone and then the app store have provided companies with a revolutionary platform to reach consumers all over the world. But this also means that any business that has an app is essentially global from day 1. This presentation analyzes how this global mobile revolution has occurred and offers strategies for tackling international mobile markets, specifically China and Europe.
Overview of the mobile commerce market across the US and China, including its relationship to social, mobile payments and offline retail plus the key trends to watch.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
WSJ Converge 2017 Final: China Frontier Tech Trends
1. China Frontier Tech Trends
2017 WSJ Converge
Presentation by:
Jenny Lee
Managing Partner, GGV Capital
2. Strong support from Chinese government will help this sector flourish
Source: China Gov’t 13th 5 year plan, 2017 China Gov’t work report, GGV research
13th 5 Year Plan Puts Internet, AI, Big data as Priorities
China sets aggressive targets to become an innovation
driven country by 2020
18 15
2015 2020
$3.1T $4.8T
15% 20%
48 60
Country innovation ranks
High tech Co. revenue
Percentage of GDP by high tech Co.
R&D talents per 10k labor
GGV CONFIDENTIAL Slide 2
3. Frontier Tech Trends in China
Smart
Transportation
Robotics
Innovation
Age of
Intelligence
Smart, Green &
Autonomous
Human Machine
Interaction
Human Machine
Integration
GGV CONFIDENTIAL Slide 3
4. Environmental Pressure Natural Resource Constraints Consumer Upgrade
Source: China 13th 5-year plan, National Bureau of Statistics of China, GGV research
Chinese Government Highly Motivated
GGV CONFIDENTIAL Slide 4
Greener, smarter transportation will elevate pressure
5. Total Government
Pledged Investment
$16 Billion
Policy Support 2020 Targets
Free License Plates
20-60K RMB
Subsidy/Vehicle
5M EV Car Lots
3.1K Charging Stations
500K Charging Piles
Source: www.gov.cn, GGV research
Chinese Ambitions for Smart Transportation
Notes: 2014-2020 pledged amount
GGV CONFIDENTIAL Slide 5
6. Full EV
Hybrid
Total
(Units) YOY
263K
81K
344K
73%
30%
60%
(Units) YOY
Q1 2017
64K
14K
78K
67%
-32%
31%
2017 Chinese EV Market Statistics
Source: auto.sohu.com, www.chinaev.net, ResearchInChina: 2016-2020 China EV report, GGV research
Consumer
2016
GGV CONFIDENTIAL Slide 6
New EV ownership exceeds 1 million units in 2016, expected to exceed 5 million units in 2020
8. NINEBOT
NEXTEV LETV FARADAY
NIU
Emerging EV Startups for Different Consumer Needs
Source: Company Website, GGV research GGV CONFIDENTIAL Slide 8
CHEHEJIA
BIKE SHARING
Including the trending bike sharing wave hitting all China cities
9. Raised $5.5Bn for Frontier Tech
and Globalization
Established Apollo Project, an Open Source
Ecosystem on Self-Driving
AI + Self-driving R&D Set up Silicon Valley
AI Lab
Baidu WuZhen Fleet
Demo
Baidu L4 in Beijing
More Autonomous; Startups with Chinese Founders ..
Source: finance.sina.com, it.sohu.com GGV research GGV CONFIDENTIAL Slide 9
10. Chinese Robotics Market ($Bn)
Chinese Robotics Market Set to Grow
Source: www.robot-china.com, iResearch, GGV research GGV CONFIDENTIAL Slide 10
11. Robotics R&D Investment by Revenue
IP per ¥100Mn revenue
Units of Local Brand Production
Sales of Consumer/Service Robots
2015 2020
0.95%
0.44
n/a
$1.2Bn
1.26%
0.70
100K
$4.3Bn
Chinese Targets for the Robotics Industry
Source: www.miit.gov.cn, China Smart Manufacturing Plan 2025, GGV research GGV CONFIDENTIAL Slide 11
12. Source: IFR, China Robotics Industry Development Plan, Company Website, GGV research
Fast Growing Chinese Industrial Robots Market
GGV CONFIDENTIAL Slide 12
Global stock of operational robots expected to increase from 1.6m units in 2015 to 2.6m by 2019
China expected to lead purchase of robots at 40%(160k units) of global supply in 2019 (from 27% in 2016)
• China domestic technology still lags behind foreign players and needs to catch up
• Policies look to support R&D and startups through investment. Set targets of 100k Made-In-China
industrial robots, 500k robots with six axis and sales to exceed 30Bn yuan by 2020
0
20
40
60
80
100
120
140
160
2014 2015 2016 2017 E 2018 E 2019 E
Thousands
Annual Supply of Industrial Robots (Units)
China Asia/Australia Europe USA
Average Robot Density in 2016
Unit per 10K employees
Global Average at 69
13. Industrial Production Warehousing/Logistics
Warehousing/ Picking
Sorting Systems
Source: IFR, China Robotics Industry Development Plan, Company Website, GGV research
Examples of Chinese Industrial Robots Manufacturers
GGV CONFIDENTIAL Slide 13
E-DeodarSINSUN
15. Devices for the Home
Examples of Chinese Consumer Robots Startups
Source: Company Websites, GGV research GGV CONFIDENTIAL Slide 15
16. Chinese government positions AI as the next priority for development
Next Priority for Chinese Development: AI+
Premier Li included AI in 2017 Government Work Report
• Build up AI ecosystem, industrial standard and public service
platform
• Support AI R&D and commercialization
• Build up IP and talent education system
Government released ‘16-’18 Internet and AI 3-year plan
NDRC initiated a National Deep Learning Lab, led by Baidu in 2017
Government plans to invest $15Bn to develop AI industry
Source: 2017 China Gov’t Work Plan, www.gov.cn, GGV research GGV CONFIDENTIAL Slide 16
17. Computing
Infrastructure
Algorithm Data
AI Infrastructure, Talent, Data: China is Ready
Source: World Bank, CNNIC, US Office of Science and Technology Policy, GGV research
21%
15%
Note: China expected to generate 15% of global data
in 2017, growing to over 21% in 2020
GGV CONFIDENTIAL Slide 17
18. Chinese Startups in Computer Vision
Facial and Image Recognition API for Different Applications
Raised ~ $120M in 2017 Raised ~ $100M in 2017
Source: Company Websites, GGV research GGV CONFIDENTIAL Slide 18
19. Chinese Startups in Natural Language Processing
Speech Recognition Semantics Comprehension
Ticmirror, NLP enabled for cars
Ticwatch, NLP enabled for consumers
Input Voice
Assistant
Voice Touch Dictation
• 97% accuracy for Chinese language
• Supports 40+ dialects
• Realtime speech2text translation
Source: Company Websites, GGV research GGV CONFIDENTIAL Slide 19
20. China is leveraging AI capabilities to build up next gen applications across industriesAI + Education
AI + Surveillance
AI + Medical
AI + Security
AI + Customer Service
AI + Finance
Emerging AI+ Chinese Startups Across Industry Verticals
Source: Company Websites, GGV research GGV CONFIDENTIAL Slide 20
21. Government Support Rising Innovation
Towards a Technology and Innovation Driven China
GOVERNMENT SUPPORT
China State Council 13th
five-year plan to
accelerate dev. of high
tech industry by 2020
BUDDING TALENT
By 2030, 27% of all 25-
34 years with a degree
will be in China, and
more overseas talents
will return
RISING INNOVATION
Since 2014, China has
outstripped both US and
Japan in number of global
patent filing at 34% market
share (wipo.int)
LARGE DATA SET
China is expected to have
772Mn internet users,
generating 15~20% of global
online data by 2020
HUGE MARKET
China has a population of
1.4Bn, 30Mn enterprises,
290Mn vehicles, and 1.1Bn
smart phones
Source: Company Websites, GGV research GGV CONFIDENTIAL Slide 21