Specialist
Former executive at Google LLC (Alphabet Inc)
Agenda
- Update on Google Cloud Platform’s (GCP’s, NASDAQ: GOOGL) full stack of AI and machine learning offerings including positioning and competitive dynamics vs Azure (NASDAQ: MSFT), AWS (NASDAQ: AMZN) and others
- Enterprise customer penetration for AI offerings, go-to-market improvements and strategic positioning to leverage AI technology
- Compute power as a market growth barrier and Google’s outlook vs AWS Graviton
- Impact of generative AI on the market, noting Google Bard, Microsoft’s partnership with Open AI and AWS’s partnership with Hugging Face
- Macroeconomic impact on customer spending habits
- Industry trends, innovation and consolidation outlook
Questions
1.
What’s your overview of the core categories of AI offerings at Google today?
2.
You mentioned that several business segments or products are research products and initiatives. Which products are generating and driving revenue at Google today?
3.
Could you discuss Google Cloud AI, GCP [Google Cloud Platform] and Vertex AI? What goes into these platform AI offerings for the enterprise segment?
4.
How do you see Google’s longer-term AI product roadmap and strategy? What are the business’s most important AI products today and how do you see this developing over the next 2-3 years?
5.
Do you have any confidence on a timeline for Google Pathways reaching a significant milestone?
6.
We’ve recently seen large language models such as OpenAI’s ChatGPT taking the market by storm and capturing consumers’ imaginations. Is Pathways offering any significant differentiation? What use case might help paint a picture for why this is such an important offering?
7.
Google Bard’s introduction felt reactive to ChatGPT, and certain occurrences around hallucinations and erroneous feedback were reported. What’s your opinion on the company’s introduction of Bard to the marketplace? How do you see market adoption evolving in the near term?
8.
How is Google thinking about bringing AI products to market while incorporating responsible AI principles to maintain the integrity of its products? You started discussing a few challenges. Could you elaborate on how you see this playing out as the company tries to gain traction with Bard?
9.
There have been a lot of key data privacy issues that are top-of-mind for AI, especially given the consistent looming threat of regulation in the US and abroad. These kinds of challenges might be less significant for OpenAI, but what do you think is a priority for Google AI’s management team, regarding data privacy challenges?
10.
How do you think Google’s generative AI technology, including Bard, compares with ChatGPT?
11.
Considering Google and Microsoft’s various strengths and weaknesses, how do you think competition for AI and large language models will play out between the two companies in the long term? Does Microsoft’s head-start and traction with OpenAI play into the competitive dynamics in the longer term?
12.
How should we think about Google’s positioning in AI and generative AI vs AWS, which notably has a large number of offerings for AI and machine learning? AWS partnered with Hugging Face in February 2023 to build out capabilities that are more developer-friendly. How should we think about AI competition between these two vendors?
13.
How do you think Google might implement AI in Google Search? How could this impact the monetisation structure of ad revenue, given the increased costs of running these queries?
14.
What’s your opinion on how generative AI will ultimately be integrated into the standard Google Search?
15.
Could you estimate what proportion of total Google search results you expect to eventually be made up of generative AI outputs?
16.
In terms of OPEX, how should we think about the potential impact on CAPEX and the higher compute intensity of AI tools as Google funnels R&D dollars and its overall strategy towards AI?
17.
Google reported that its machine learning infrastructure with Cloud TPU [tensor processing unit] v4 Pods was run at a benchmark for large-scale training workloads and was 80% faster than alternatives. Could you discuss the importance of the company’s TPUs? What advantage might it have, given these TPUs vs market competitors such as AWS’s Graviton?
18.
Do you have any general comments on the potential for GPU [graphics processing unit] shortages and how it affects Google?
19.
How have enterprise spending habits on AI trended over the past year?
20.
Google has been working on refocusing its enterprise go-to-market motion to increase enterprise sales and AI adoption among its enterprise customers. Do you have any comment on the company’s progress in retooling its sales motion for enterprise customers to expand AI revenue?
21.
What’s your view on Google’s AI acquisition opportunities? What kind of company or sub-industry might be of particular interest?
22.
Do you have any other expectations for how Google might add AI to the consumer market outside of its standard search?
23.
Which companies come to mind as being potentially disruptive in the generative AI space? Which smaller private companies might be on your radar?
