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    Home » CLO » Google Cloud: a 15-year race to the cloud
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    Google Cloud: a 15-year race to the cloud

    It's a time for miracles, and even more so, a time of the greatest uncertainty. Google Cloud's profitability has restored confidence in the industry, but its slowness in responding to the big models has left investors feeling helpless.
    Updated: Jul 17, 2025
    Google Cloud: a 15-year race to the cloud

    Although Google is currently in the large language model by OpenAI gap, but it still has its own differentiation advantage, that is, "open, flexible private customization service model to cohesion of thousands of enterprises, planning to bend the road to overtake the car".

         01 late profitability

    In the first quarter of 2023, Google Cloud recorded a revenue of $191 million, which is the first time in the history of the company's cloud business development, and Ray Wang, founder and principal analyst of Constellation Research, even regarded this as a landmark event, "For Google Cloud, which started in April 2008, this is an important milestone: it is a significant milestone in the history of the company after fifteen years. milestone: it's profitable after fifteen years."

    Ray Wang's praise is not overstated, as the world's largest cloud computing provider, Amazon Cloud, also took 10 years to become profitable; this reveals a harsh reality of the industry: the cloud business requires long-term investment, and short-term profitability is virtually impossible. Not only is it difficult to make a profit, but before the emergence of generative AI, the global cloud service providers are collectively entering the doldrums.

    It was a time of miracles, and even more so, a time of the greatest uncertainty. Google Cloud's profitability has renewed the industry's confidence, but its slowness in responding to the big models has left investors feeling helpless. Looking back over the past 15 years, Google Cloud has created a number of industry firsts, but now it is a little out of its depth on the road to catching up.

         02 10 years of silence

    Although currently behind Microsoft Cloud and Amazon Cloud, Google Cloud is the earliest pathfinder.Since 2006, Google formally put forward the concept of cloud computing, and internal use of cloud computing platform.Since then just a few years, Google has launched Google Docs, Google Calendar and other free SaaS services and PaaS platform. With advanced technology concepts, Google Cloud quickly attracted the attention of developers around the world.

    However, Google Cloud did not take advantage of this to seize the market, a major reason is the slow progress in the field of IaaS. It was not until after 2011 that Google successively launched Google Cloud Storage and Google Compute Engine, which is a full five years later than Amazon Cloud's IaaS service.

    Google is a fanatical technology company, in terms of cloud native, Google released the open source container orchestration tool Kubernetes in 2014, and became the market standard at that time; in terms of hosting services, Google was the first to realize the real-time migration of virtual machines in 2014; in terms of infrastructure, it was the first to launch the layered network in 2017 to provide users with a variety of choices. But in terms of commercial realization, Google is not good at it and is not keen on it.

         03 3 years of catching up

    From the beginning of 2018, Google began to express its serious attitude towards the cloud computing business.  In response to how to develop Google Cloud, Alphabet's top leaders, including Google CEO Sundar Pichai, Alphabet CFO Ruth Porat, and Larry Page, who was still Alphabet's CEO at the time, engaged in a big discussion centered on how Google Cloud was going to catch up with the competitors.

    After a heated discussion, Page ultimately set an ambitious goal for Google Cloud: to either surpass Microsoft and Amazon or one of them, with that deadline being 2023. And in the short term, the centerpiece move for Google Cloud is a change of command.

    In 2019, Google completed the split of its cloud services portfolio with the launch of Anthos. Unlike similar offerings like AWS' Outposts, Microsoft's Azure Stack, and Oracle's Cloud@Customer, Anthos is a pure software product that doesn't require customers to buy the accompanying Google hardware.

         04 Differentiation in Progress

    In late 2022, ChatGPT, the AI conversational chatbot software from US-based OpenAI, began to take the world by storm. 2 months later, ChatGPT's monthly activity exceeded 100 million, making it the fastest-growing consumer app in history.Microsoft's Intelligent Cloud business began to fully embrace ChatGPT. the role of generative AI began to react to the business, Microsoft Intelligent Cloud in the AI computing (Azure ML) business, has been four consecutive quarters of revenue growth of more than 100%.

    Not only the intelligent cloud business, all of Microsoft's products will fully integrate ChatGPT, including Office software, Teams chat program, and the search business.On March 15, Microsoft added the OpenAI-developed GPT-4 technology to Bing search; on May 5, Microsoft announced that it had upgraded Bing search and Edge browser to fully open Bing Chat.

    In the market anxiously waiting, in June this year, Google announced that the generative artificial intelligence service based on Vertex AI was fully online.Vertex AI is a machine learning platform service (ML PaaS) provided by Google Cloud. With this release, Google's Big Model service is now generally available, allowing businesses and organizations to integrate the platform's capabilities with their own applications. In addition to the base models, Vertex AI provides a complete ecosystem of tools to help builders tune, deploy and manage models in production environments.

    Google says Vertex AI is the first enterprise-grade machine learning platform to offer Reinforcement Learning with Human Feedback (RLHF), which helps to increase the utility of models and reduce costs, and it has also upgraded Vertex AI's suite of MLOps tools for model development and maintenance for customers who need to manage large models.

    In addition, Google assures all customers that with Vertex AI and Gen App Builder, their data remains under full control. Although Google is currently pulling ahead of OpenAI in terms of large language models, it can still leverage its differentiation to bring together thousands of enterprises in an open, flexible, and privately-tailored differentiation model, and plan to overtake them.

    cloud computing google Big Models
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