Google Cloud uses Anthos and AutoML to differentiate itself from AWS and Azure.



Google Cloud now uses Anthos and AutoML to differentiate itself from market leaders, Amazon Web Services (AWS) and Microsoft Azure, Chief Scientist Andrew Moore, and Product Management Manager Rajen Sheth at VentureBeat.

"If I run a small business or start-up that relies on cloud provider technology, if I work with Google, I can actually offer customers the ability to run their models on-premise, or on GCP, or other clouds. Great flexibility helps, "Moore told VentureBeat during a conversation with reporters Thursday.

Google Cloud has become much more flexible this week with the introduction of Anthos, a hybrid cloud management system that connects to AWS and Azure. Moore, who became responsible for artificial intelligence at Google Cloud in late 2018, also called BigQuery and Google's Bigtable products.

In an increasingly competitive cloud computing market, Google has made itself known by launching dozens of new products and services at the upcoming conference in San Francisco this week.

The introduced products include new classes for AutoML, a predefined collection of AI services for retailers and contact centers, and AI Platform, a collaborative model-building tool. Developers with little coding experience can use AutoML, while AI Platform is aimed at computer scientists, as part of Google's attempt to provide artificial intelligence tools for creators covering a wide range of experiments.

The sheets connected in BigQuery for the analysis of data in Google Sheets, also presented this week, constitute another important development, explained to VentureBeat, ISG analyst.

"Spreadsheets are an essential tool for business analysts to generate value from data. This connection allows them to work much more easily on large volumes of information while using tools with which they are already comfortable, "he said.

BigQuery ML and AutoML tables to learn from tabular data were also introduced this week.

"With AutoML, we can also extend this platform to a much wider range of people. So you do not have to be a computer scientist who understands how to use a laptop. You can go to the developer at the other end of the wire, and then connect the developer to a computer scientist. I think this distinction is essential for Google, "said Sheth.

Given the power of Google Cloud's suite of artificial intelligence services, Frank does not find this surge in artificial intelligence surprising.

"Artificial intelligence capabilities are one of the main reasons why companies are considering adopting Google Cloud, so it's important for the tech giant to maintain a strong position because to attract new businesses, "he said.

Patrick Moorhead, an analyst at Moor Insights, acknowledged that Cloud Next's BigQuery ML developments were noteworthy, but said that AI services were a decreasing distinction between Google and other public clouds.

Anthos could be the most important new product announced by Google this week.

"Anthos was definitely the most impressive ads, for me, basically, because market leaders do not really talk much about multi-cloud," Moorhead told VentureBeat during a phone interview.

He noted that there remained a number of unanswered questions regarding Anthos, since clouds have different instances of computing and storage and different security models.

"The idea of ​​doing it easily and arbitrating between three different public clouds, it just seems more complex than what has been shown," he said.

Anthos could also have another drawback: it only works with Kubernetes containers, a format that can exclude the majority of on-site workloads.

Although Google has created open source projects – such as TensorFlow and Kubernetes – that have become important to many AI developers, this has not translated into a cloud market share. In fact, competition among leading cloud providers has led everyone to offer similar artificial intelligence services.

From Google TPUs to Microsoft FPGAs and AWS Inferentia, each company offers hardware to accelerate AI inference and training. Each of them has services to extract unstructured data from documents, artificial intelligence services for recommendations, vision and voice.

"I think we're going to enter a benchmarking phase," he said, adding that people generally hated benchmarking, but now it becomes necessary that so many services are similar.

Moorhead said he believed that the Next conference revealed that Google Cloud's new CEO, Thomas Kurian, had chosen not to focus on complicated conversations or conquering potential customers claiming superior technology.

"I think Google Cloud is trying to win today by saying," You're going to have a better experience on our cloud. It will be easier, "as opposed to" We have the best technology, "said Moorhead.


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