A review of startups and VCs focusing on AI, and the investment landscape since the past 20 years. A forecast of the investment going forward in terms of # of deals, valuation, and the impact of being in a bubble.

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Joseph Wei,
Venture Partner, Skychee Ventures
Joseph.Wei@skychee.ventures
www.linkedin.com/in/josephwei
The State of AI Investment - 2019

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• Speaker background
• Global Landscape for AI
• AI Value Chain
• VC funding history and trend
• What is driving investment in AI?
• Are we in a bubble?
• Final thoughts
Topics

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Speaker Background
• 35 yrs corporate executive at DEC and SGI
(both acquired by HP), NEC, and Inventec
• Venture Partner of Skychee Ventures
• Founding Partner of Lab360 Incubator
(acquired by Heuristic Capital)
• Mentor

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AI Value Chain By Best Practice AI Ltd

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Historical VC Investment since 1990’s

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Source:CB Insights

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What’s driving AI investment?

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AI delivers Global Business Value

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• Many $1 billion+ funds were created in 2018
– Sequoia ($8 billion)
– Tiger Global ($3.75 billion)
– Bessemer Venture Partners ($1.85 billion)
– GGV Capital ($1.36 billion)
• Fund Managers need to invest their funds and
generate returns for their Limited Partners in
10 -12 years
Availability of Funds

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# of AI Startups acquisitions from 2010 - 2018

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Samples of acquisition of AI Startups

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Are We in Another Dotcom-Type Bubble?

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Are we in a bubble?
• Yes – in terms of valuation
– Recent lackluster IPO by Uber, Lyft, etc. and the lowered valuation of
WeWork are examples of a repeat of the dotcom era.
• No – in terms of freezing in investment as the total amount of VC
funding is still large as many new funds just raised new funding.
• In the past several years, some investment decisions were based
on Fear Of Missing Out (FOMO), and not based on true technical
and business merits. Therefore, early seed funding will be more
difficult as VCs will now wait to see more customer tractions
before investing

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Final thoughts

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AI is just another new technology
platform, startups need to
understand where their
product/service can add value and
differentiate in order to succeed.

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AI vs. ML vs. DL

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• Similar to Infrastructure as a Service (IaaS) and
Platform as a Service (PaaS) for cloud, Machine
Learning as a Service (MLaaS) will power a
wealth of conversational agents and chatbots,
speech, natural language processing (NLP) and
semantics, vision, and enhanced core
algorithms programs
The emergence of MLaaS

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As AI systems become more powerful, governance
of AI becomes a bigger topic and companies need
to incorporate a governance model for AI that
matches with their business.
AI and Governance

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Contact:
Joseph.Wei@skychee.ventures