The Golden Age of AI
•Descargar como PPTX, PDF•
3 recomendaciones•1,445 vistas
Opportunities and challenges presented by the emergence of artificial intelligence technologies, with emphasis in the U.S. and China markets.
Recomendados
Recomendados
Más contenido relacionado
La actualidad más candente
La actualidad más candente (20)
Destacado
Destacado (20)
Similar a The Golden Age of AI
Similar a The Golden Age of AI (20)
Más de Chris Evdemon
Más de Chris Evdemon (7)
Último
Último (20)
The Golden Age of AI
- 1. The Golden Age of AI Opportunities and Challenges Chris Evdemon Partner Sinovation Ventures November 2016
- 2. 10 years from now, Artificial Intelligence will replace 90% of the world’s ... • Can you play a million Chess games a day, while learning like AlphaGo？ • Absorb the cumulative daily experience of Tesla from a million vehicles? • Instantly compare all of the world’s airport cameras against all wanted criminals’ faces? Translation Reporters Assistants Security Taxis Sales Services Traders Accounting Maids Artificial Intelligence is not just an "imitation of the human", but it usually goes "far beyond human” abilities … AI will be the greatest value creation engine
- 3. 70% 75% 80% 85% 90% 95% 100% 2011 2012 2013 2014 2015 2016 Human eye Deep learning Medical Sciences Automated and auxiliary diagnosis, personalized diagnosis, gene sequencing. Education Foreign languages, personalized adaptive learning. Banking and Insurance Targeted marketing, loan approval, credit card fraud prevention Recognition Voice, face, video content applications for security, customer service, etc. Investments AI + high frequency trading, prediction engines, etc. Internet Analytics Purchase conversion, recommendation, pricing, targeting, SNS marketing. Business Intelligence and Process Automation Deep Learning revolution
- 4. Deep Learning Learning from massive data Reinforcement Learning Auto- learning Transfer Learning Solve sparse- data problem Today Future Beyond Deep Learning
- 5. Why AI works now? 5 Conditions of AI Clear Boundaries Auto- Collected Feedback Loop Computing Resources Big Data (ideally closed-loop) Top Data Scientists Prof. Yang Qiang, HKUST
- 6. 1 2 3 4 Own end-to-end data Hire best scientists Buy hardware optimized for AI $100,000,000 $400,000,000 Train young people in “AI alchemy” The right AI approach
- 7. 1 2 3 4 Assist and not replace people “Trick”users to provide data “Error-tolerant”user interface Constrained application scenarios “无人驾驶” Navigating for the short-term
- 8. L1: (AI as input to humans) Vision Voice Language Gesture Industrial and Commercial Robots Home Robots Big Data Perception Robotics Autonomous Driving Stage3–5yr5–10yr10yr+ Internet Analytics All-terrain fully autonomous driving L2-3: (AI assisting human driver) AR/VR and new natural interface Cross-domain and general natural language understanding L4 (Human assisting AI) Investments Insurance Banking Healthcare Education and any industry with big data Artificial intelligence + computing architecture + algorithm framework + sensing platform Business Intelligence and process automation Mass produced sensors Understanding Sensors: infrared, depth camera, gyroscope, Lidar, etc. AI roadmap Typical Duration of an Early Stage VC Fund
- 9. PC era Internet era Mobile Internet era AI era YOU Bill Gates Born in 1955 Steve Jobs Born in 1955 Jeff Bezos Born in 1964 Jerry Yang Born in 1968 Kevin Systrom Born in 1983 Evan Spiegel Born in 1990 The AI era is YOURS!
- 10. Internet era App era O2O era AI era Returnees Product manager On-the-ground Sales + Back-end Technologist AI Scientists + Enterprise Sales Leader YOU The AI era needs a different type of founders
- 11. Research Start-Up Local start-up Local start-up Chinese start-up (U.S. team) U.S. start-up (China team) Own start-up Own start-up YOUR CAREER CHOICES Industry Local company Local company Chinese company (U.S. ops) U.S. company (China ops) Increasing risk and return
- 12. Overflow of capital. Staging deliverables. Limited talent pool. Big corporates’ muscle. One-dimensional team. Building a business. Building for the long-term. Challenges for AI start-up projects
- 13. $7/hour$15/hour From creating additional revenue for millions of people around the world to … eliminating it! Partial vs. complete substitution of human labour Social implications of AI
- 14. The U.S. – China relationship: “it’s complicated” …
- 15. Attract top AI talent Collecting industry big data Build up a platform and clusters Top engineers Collaborating with industry leaders Researching the best AI opportunities AI Institute - Incubation Sinovation Ventures AI strategy Series A + B Start-Up Local company Local company Chinese company U.S. company Own start-up Own start-up
- 16. 300+ 创业公司 天使投资 人 国内外企业 13,000+创业者 Team, offices, and partnerships with leading corporations in the three largest economic regions in China. A complete cross-border business services ecosystem Presence, resources and investment activity in Silicon Valley.
- 17. ActionDecisionPerception Sinovation Ventures AI portfolio
- 18. Join the 工场 family! Thank you. chris@sinovationventures.com ricky@sinovationventures.com @SinovationVC
Notas del editor
- From supervised to unsupervised (looking for optimal return), to transferring knowledge from existing solutions to new problems.
- All this favours big companies.
- 一步一步的. The problem with venture capital.
- B2C vs. B2B. For China you always need a 草根 (grassroots) component too.
- Most and best choices in the world. Two most important ecosystems and markets. SV and Beijing. Personal choice, no right or wrong. Industry and start-up both offer opportunities to be at the forefront of the AI evolution. Glass ceiling in the U.S. Relocalization in China. Chinese companies operating in the U.S. need to learn from the mistakes of the U.S. companies entering China. 入乡随俗 (“when in Rome do as the Romans do”).
- AI not a sector, like mobile internet wasn’t. Too much capital. Realizing how important tech is in creating new jobs, the Chinese government has embarked on one of the largest efforts ever to spark innovation by funneling some $383 billion into 911 government guidance funds, an assortment of different types of funds whose goals are policy before profits. Arbitrage in valuations. Investors do not have the right background. AR/VR examples of Chinese investments. Google, Intel, IBM, Microsoft, Salesforce, Apple, Amazon. Companies getting desperate of missing the AI train and rushing to jump onboard.
- Interdependent economies but trying to reduce that. Political situation deteriorating by the month (HK/Taiwan/SE Asia/Trump). Immigration in the US becoming tougher. China encourages capital inflows / outflows but controls scope very tightly. Tencent/Webank example. U.S. concerned with IP going to China.
- Designed for maximum options. Led by Kai-Fu himself. $500M available to invest between USD / RMB and publicly listed entity in 新三板.
- 工场 is not a normal VC firm. Full service model. $1.2B under management. More than 300 portfolio companies, 36 in the U.S., 13,000 persons employed, 4 offices, 60 people staff, top tier LPs incl. value add corporates like Foxconn. AI is a truly cross-border opportunity, and 工场 is a truly cross-border fund.