Why Google needs to make machine learning its growth fuel
- In 2017 Google outspent Microsoft, Apple, and Facebook on R&D spending with the majority being on AI and machine learning.
- Google needs new AI- and machine learning-driven businesses that have lower Total Acquisition Costs (TAC) to offset the rising acquisition costs of their ad and search businesses.
- One of the company’s initial forays into AI and machine learning was its $600M acquisition of AI startup DeepMind in January 2014.
- Google has launched two funds dedicated solely to AI: Gradient Ventures and the Google Assistant Investment Program, both of which are accepting pitches from AI and machine learning startups today.
- On its Q4’17 earnings call, the company announced that its cloud business is now bringing in $1B per quarter. The number of cloud deals worth $1M+ that Google has sold more than tripled between 2016 and 2017.
- Google’s M&A strategy is concentrating on strengthening their cloud business to better compete against Amazon AWS and Microsoft Azure.
These and many other fascinating insights are from CB Insight’s report, Google Strategy Teardown (PDF, 49 pp., opt-in). The report explores how Alphabet, Google’s parent company is relying on Artificial Intelligence (AI) and machine learning to capture new streams of revenue in enterprise cloud computing and services. Also, the report looks at how Alphabet can combine search, AI, and machine learning to revolutionise logistics, healthcare, and transportation. It’s a thorough teardown of Google’s potential acquisitions, strategic investments, and partnerships needed to maintain search dominance while driving revenue from new markets.
Key takeaways from the report include the following:
Google needs new AI- and machine learning-driven businesses that have lower total acquisition costs (TAC) to offset the rising acquisition costs of their ad and search businesses
CB Insights found Google is experiencing rising TAC in their core ad and search businesses. With the strategic shift to mobile, Google will see TAC escalate even further. Their greatest potential for growth is infusing greater contextual intelligence and knowledge across the entire series of companies that comprise Alphabet, shown in the graphic below.
Google has launched two funds dedicated solely to AI: Gradient Ventures and the Google Assistant Investment Program, both of which are accepting pitches from AI and machine learning startups today
Gradient Ventures is an ROI fund focused on supporting the most talented founders building AI-powered companies. Former tech founders are leading Gradient Ventures, assisting in turning ideas into companies. Gradient Venture’s portfolio is shown below:
In 2017 Google outspent Microsoft, Apple, and Facebook on R&D spending with the majority being on AI and machine learning
Amazon dominates R&D spending across the top five tech companies investments in R&D in 2017 with $22.6B. Facebook leads in percent of total sales invested in R&D with 19.1%.
Google AI led the development of Google’s highly popular open source machine software library and framework Tensor Flow and is home to the Google Brain team
Google’s approach to primary research in the fields of AI, machine learning, and deep learning is leading to a prolific amount of research being produced and published. Here’s the search engine for their publication database, which includes many fascinating studies for review. Part of Google Brain’s role is to work with other Alphabet subsidiaries to support and lead their AI and machine learning product initiatives. An example of this CB Insights mentions in the report is how Google Brain collaborated with autonomous driving division Waymo, where it has helped apply deep neural nets to vehicles’ pedestrian detection The team has also been successful in increasing the number of AI and machine learning patents, as CB Insight’s analysis below shows:
Mentions of AI and machine learning are soaring on Google quarterly earnings calls, signaling senior management’s prioritising these areas as growth fuel
CB Insights has an Insights Trends tool that is designed to analyse unstructured text and find linguistics-based associations, models and statistical insights from them. Analysing Google earnings calls transcripts found AI and machine learning mentions are soaring during the last call.
Google’s M&A strategy is concentrating on strengthening their cloud business to better compete against Amazon AWS and Microsoft Azure
Google acquired Xively in Q1 of this year followed by Cask Data and Velostrata in Q2. Google needs to continue acquiring cloud-based companies who can accelerate more customer wins in the enterprise and mid-tier, two areas Amazon AWS and Microsoft Azure have strong momentum today.
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