Organizations across industries are looking to AI to turn troves of data into intelligence, powered by the latest advances in generative AI. Yet for many organizations, there is a barrier to adopting the latest models because they can be costly to train or serve. A new class of cloud GPUs is needed to lower the cost of entry for businesses that want to tap the power of AI. 

Today, we’re introducing G2, the newest addition to the Compute Engine GPU family in Google Cloud. G2 is the industry’s first cloud VM powered by the newly announced NVIDIA L4 Tensor Core GPU, and is purpose-built for large inference AI workloads like generative AI. G2 delivers cutting-edge performance-per-dollar for AI inference workloads that run on GPUs in the cloud. By switching from NVIDIA A10G GPUs to G2 instances with L4 GPUs, organizations can lower their production infrastructure costs up to 40%. We also found that customers switching from NVIDIA T4 GPUs to L4 GPUs can achieve 2x-4x better performance. As a universal GPU offering, G2 instances also help accelerate other workloads, offering significant performance improvements on HPC, graphics, and video transcoding. Currently in private preview, G2 VMs are both powerful and flexible, and scale easily from one up to eight GPUs. 

Currently organizations require end-to-end enterprise ready infrastructure that will future proof their AI and HPC initiatives for a new era. G2s will be ready to be deployed on Vertex AI, GKE, and GCE, giving customers the freedom to architect their own custom software stack to meet their performance requirements and budget. With optimized Vertex AI support for G2 VMs, AI users can tap the latest generative AI models and technologies. With an easy to use UI and automated workflows, customers can access, tune and serve modern models for video, text, images, and audio without the toil of manual optimizations. The combination of these services with the power of G2 will help customers harness the power of complex machine models for their business.

NVIDIA L4 GPUs with Ada Lovelace Architecture

G2 machine families enable machine learning customers to run their production infrastructure in the cloud for a variety of applications such as language models, image classification, object detection, automated speech recognition, and language translation. Built on the Ada Lovelace architecture with fourth-generation Tensor Cores, the NVIDIA L4 GPU provides up to 30 TFLOPS of performance for FP32, and 242 TFLOPs for FP16. Newly added FP8 support, on top of existing INT8, BFLOAT16 and TF32 capabilities, makes the L4 ideal for ML inference. 

With the latest third-generation RT Cores and DLSS 3.0 technology, G2 instances are also great for graphics-intensive workloads such as rendering and remote workstations when paired with NVIDIA RTX Virtual Workstation. NVIDIA L4 provides 3x video encoding and decoding performance, and adds new AV1 hardware-encoding capabilities. For example, G2 can enable gaming customers running game engines such as Unreal and Unity with modern graphics cards to run real-time applications. Likewise, media and entertainment customers that need GPU-enabled virtual workstations can use the L4 to create photo-realistic, high-resolution 3D content for movies, games, and AR/VR experiences using applications such as Autodesk Maya or 3D Studio Max.

What customers are saying

A handful of early customers have been testing G2 and have seen great results in real-world applications. Here are what some of them have to say about the benefits that G2 with NVIDIA L4 GPUs bring:

AppLovin

AppLovin enables developers and marketers to grow with market leading technologies. Businesses rely on AppLovin to solve their mission-critical functions with a powerful, full stack solution including user acquisition, retention, monetization and measurement.

“AppLovin serves billions of AI powered recommendations per day, so scalability and value are essential to our business,” said Omer Hasan, Vice President, Operations at AppLovin. “With Google Cloud’s G2 we’re seeing that NVIDIA L4 GPUs offer a significant increase in the scalability of our business, giving us the power to grow faster than ever before.”

WOMBO

WOMBO aims to unleash everyone’s creativity through the magic of AI, transforming the way content is created, consumed, and distributed. 

“WOMBO relies upon the latest AI technology for people to create immersive digital artwork from users’ prompts, letting them create high-quality, realistic art in any style with just an idea,” said Ben-Zion Benkhin, Co-Founder and CEO of WOMBO. “Google Cloud’s G2 instances powered by NVIDIA’s L4 GPUs will enable us to offer a better, more efficient image-generation experience for users seeking to create and share unique artwork.”

Descript

Descript’s AI-powered features and intuitive interface fuel YouTube and TikTok channels, top podcasts, and businesses using video for marketing, sales, and internal training and collaboration. Descript aims to make video a staple of every communicator’s toolkit, alongside docs and slides. 

“G2 with L4’s AI Video capabilities allow us to deploy new features augmented by natural-language processing and generative AI to create studio-quality media with excellent performance and energy efficiency” said Kundan Kumar, Head of Artificial Intelligence at Descript.

Workspot

Workspot believes that the software-as-a-service (SaaS) model is the most secure, accessible and cost-effective way to deliver an enterprise desktop and should be central to accelerating the digital transformation of the modern enterprise.

“The Workspot team looks forward to continuing to evolve our partnership with Google Cloud and NVIDIA. Our customers have been seeing incredible performance leveraging NVIDIA’s T4 GPUs. The new G2 instances with L4 GPUS through Workspot’s remote Cloud PC workstations provide 2x and higher frame rates at 1280×711 and higher resolutions” said Jimmy Chang, Chief Product Officer at Workspot.

Pricing and availability

G2 instances are currently in private preview in the following regions: us-central1, asia-southeast1 and europe-west4. Submit your request here to join the private preview, or to receive a notification as when the public preview begins. Support will be coming to Google Kubernetes Engine (GKE), Vertex AI, and other Google Cloud services as well. We’ll share G2 public availability and pricing information later in the year.

Over the last two years, we’ve seen a significant uptick in the number of people using messaging to connect with businesses. Whether it was checking hours of operation, verifying what was in stock, or scheduling a pick-up, the pandemic caused a significant shift in consumer behavior.

• 45% of users are spending more time on messaging services because of the pandemic 
• 85% of consumers would like to message brands directly

With the rise in demand for messaging, consumers expect communication with businesses to be  speedy, simple, and convenient. For businesses, keeping up with customer inquiries can be a labor-intensive process, and offering 24/7 support outside of store hours can be costly.  

To help businesses seamlessly deliver helpful, timely, and engaging conversations with customers when and where they need help, we introduced AI-powered Business Messages.

https://youtube.com/watch?v=fcgP3RHjBLY%3Fenablejsapi%3D1%26

What is AI-powered Business Messages?

With AI-powered Business Messages, you can connect with your customers in their moment of need, in the places they’re looking for answers—such as Google Search, Google Maps, or any brand-owned channel. For instance, check out how Walmart customers in the US are able to receive real-time information on product availability, straight from a search results page.

People turn to Google when they are searching for answers to their questions, looking to buy something, or trying to accomplish a particular task with one of our many tools. In fact, 68% of all online experiences begin with a search engine.

At Google, we know how important it is for interactions with a brand to be personalized, helpful, and simple. With AI-powered Business Messages, customers are able to chat with virtual agents that understand, interact, and respond in natural ways.

We are also combining smart automation with the ability for customers to chat with live agents when it’s really needed. This approach saves your customers precious time, while also saving you money. And with Business Messages automatically handling many customer inquiries in the background, businesses have the option to distribute their human customer service agents to address other needs. 

Getting started with conversational AI is easy with Bot-in-a-Box

We know it can be difficult to get started with AI. That’s why we are utilizing existing Google AI tools like Dialogflow—part of Google Cloud Contact Center AI—to create the capability within Google’s Business Messages called Bot-in-a-Box, which makes getting started with Conversational AI easy. Bot-in-a-Box allows for fast and effective adoption of automation for businesses of all sizes. 

Enabling Business Messages with Bot-in-a-Box can be as simple as leveraging an existing customer FAQ document you already have, whether it’s from a web page or an internal document. And since the conversational AI is powered by Business Messages and Dialogflow working together, your chat bot is able to understand and respond to customer questions automatically without the need to write code. 

Bot-in-a-Box also supports other critical journeys like “Custom Intents.” That means that your bot is able to understand the different ways customers express a similar question and respond accurately by using machine learning capabilities.

Finding success 

In April 2021, Wake County courthouses in North Carolina partnered with Tango Technology to implement Business Messages when it became apparent that being able to provide the public and attorneys with around-the-clock access to information would significantly reduce the pressure on courthouse staff. Using Bot-in-a-Box, Tango Technology was able to customize a solution for Wake County Courthouse, Justice Center, and Clerk of Superior Court in just four days.

“With the combination of Google’s Business Messages, GCP, and Dialogflow, we were able to spin up an AI-driven bot for the courts in days. And the technology stack allows us to continually improve by adding functionality in an agile process.”— Mike Lotz, Co-Founder, Tango Technology

With Business Messages, North Carolina courthouses saw a 37% decrease in the call volume handled by courthouse staff.  With 398,298 fewer phone calls during the first year of operation, the AI-based messages helped Wake County Courthouse work more efficiently and productively.

We’ve seen many brands benefiting from AI-powered Business Messages. For instance, Levi’s saw a 30% increase in off-hours shoppers and surpassed 85% customer satisfaction scores after implementing Business Messages. They also drove 30x more store-related questions than Levi’s website chat. 

Bring Google’s conversational AI to your storefront with Business Messages

Google’s Business Messages makes it easier for businesses of all sizes to engage their existing or potential customers in a virtual conversation, when and where they need it. 

To learn more, watch our Cloud Next session here or visit us at g.co/businessmessages. We have specialized services to help you get started  and can share the wisdom of our channel partners and dedicated experts who specialize in unleashing the potential of conversational AI.

In order to be successful, research needs to be replicable, so scientists can build on past work and insights. However, an article in Nature warned that as much as 50% of published drug development research could not be reproduced in subsequent trials. As a result, promising drug candidates sometimes led to disappointment, as well as wasted time and money, when key findings could not be replicated. 

The shift to cloud computing helps solve this problem because it allows researchers to use open-source tools that work across platforms. As demand for cloud computing rises, our customers have asked us for more ready-made solutions to assure reproducibility of results by their collaborators, regardless of the platform they are using. They asked for secure and effective collaboration tools as well as faster time-to-insight from any type of data.

We listened. Google’s new research and data insights solution includes three sets of functionalities to address these key challenges. Each can be activated on demand and may be eligible for subscription pricing. “HPC in a box” offers abstract complexity to run high performance computing (HPC) workloads by automatically managing your cluster in the most effective manner. It integrates seamlessly with some of the industry’s most-used schedulers like Slurm and PBS. It makes it easier than ever to answer bigger questions faster by accessing Google’s fast, powerful hardware like TPUs and GPUs, all for one predictable flat fee for eligible workloads. Healthcare Innovation Hub provides healthcare-specific functionality to help ingest, aggregate, and de-identify any type of healthcare data in its original format. It unlocks cross-modality analysis and collaboration and empowers researchers with harmonization tools to overcome healthcare interoperability issues. Google Cloud Real-World Insights (formerly FDA MyStudies) accelerates and streamlines drug development and clinical trials to address urgent medical challenges with reproducible results.

The solution enables researchers to ask new questions, get answers more quickly, and work more collaboratively–with no wait times or down times. Institutions can scale to more ambitious projects and generate actionable, real-time insights from any data source–all while staying within budget.

Many top research centers have already found it faster and more cost effective to shift from downloading and storing data on their own servers to storing and analyzing data on Google Cloud. Here are some of the real-world projects already yielding breakthroughs:

• Clemson analyzed 8,500 hours of traffic camera feeds with 2.1M vCPUs in three hours to improve evacuation routes for disaster planning.
• The Colorado Center for Personalized Medicine saved $2.9M by building their Compass data warehouse on Google Cloud rather than on on-prem.
• The Broad Institute slashed costs of genomic sequencing by 90% with Google Cloud.

Our partners, such as Atos, Burwood, Omnibond, Mavenwave, Quantiphi, and Deloitte, can help you first design and develop, then install and implement your own solution, including training. To assess your institution’s needs and develop a customized plan for your next-generation research solution with research and insights, contact our sales team.

Introduction

The Google Cloud Professional Services Organization’s (PSO) mission is to help our customers get the most out of Google products. PSO is responsible for customer success by sharing our technical expertise in order to unlock business value from the cloud by providing cloud strategy and best practice advice, implementation guidance, and training using our proven methodology. 

In this blog post, we want to focus specifically on Operational Health Reviews and how PSO engages in a myriad of activities to ensure the overall success and health of a customer engagement while ensuring we are meeting customer expectations and objectives, managing risk, and ultimately delivering value during or after the Google Cloud migration. We will discuss the assets, methodology, and tools that we leverage to ensure this success.

What is an Operational Health Review and what purpose does it serve?

Operational Health Reviews (OHR) are regular reviews to proactively address the below topics: 

• A customer’s support experience
• Analysis of trends in key operational metrics
• Analysis of trends in Google Cloud usage
• Status reports for high-priority cloud projects
• Discussion of upcoming events
• Discussion of potential opportunities for training
• Review of feature requests

The core aim of an OHR is to measure progress and advise customers on the overall health of the account and migration progress while providing recommendations as a team on what adjustments should be considered to ensure continued success. During the OHR, we will address any pain points as well as identify and remediate any negative trends in support interfaces and usage metrics. 

The intention of the activity is to also perform a blameless reflection for continuous improvement. This supports the effort to maintain common ground and obtain mutual optimism for the next phase of the customer’s journey on Google Cloud. 

Let’s dive a little deeper into some of the activities that go into an OHR. 

Support experience

One of the Google Cloud’s Support Organization’s goals is to simplify and streamline our customer’s support experience with a scalable and flexible set of offerings built with the customer needs at the center. This includes supporting an ongoing partnership model, with a proactive and collaborative approach. Premium Support is our top-tier support model which is a paid support offering designed for enterprises that run mission critical workloads and require fast response times, platform stability, and increased operational efficiencies. As part of this offering, customers are provided with a Technical Account Manager (TAM) who is in charge of delivering frequent touchpoints, including OHRs. 

During the support experience section of an OHR, some of the following topics may be reviewed:

• Case volume by priority
• Case volume by product
• Cases linked to Google Cloud incidents
• Escalated cases or incidents
• Case initial response time (IRT)
• Case IRT SLO Met Rate
• Case total resolution time (TRT) hours

The purpose of this activity is to better understand the efficiency of both the customer’s and Google’s cloud operations from a support trend perspective. The goal is to celebrate any positive trends, but also to identify potential negative trends and proactively determine a remediation strategy. 

Status reports for high-priority cloud projects

The purpose of this part of the OHR is to ensure the senior management stakeholders have continued visibility into the status of all their high-priority cloud initiatives with an easy-to-read, sometimes color-coded assessment on the status of each project. The assessment [Figure 1] may include, but is not limited to potential identified risks, key next steps, key stakeholders, and a mitigation plan for any high priority issues that may occur during their migration engagement. Additionally, the TAM may also cover any upcoming milestones or events, as well as any potential anticipated future blockers [Figure 2]. 

Review trends in Google Cloud usage

This part of the OHR is meant to provide the customer with a holistic view of their overall Google Cloud usage. The purpose is to provide understanding around what products are being used on Google Cloud and also where cost is generally being allocated for overall cost management and budget tracking purposes. This can help customers with their overall cost optimization efforts. Some of the metrics we may cover in this section are:

• Current Google Cloud usage by service
• Google Cloud growth trends
• Google Cloud growth trends by service
• Google Cloud growth trends by project
• Review of used and available service credits

Feature request review and advocacy

TAMs will work with customers to help identify product needs and advocate for feature requests with Google Product Management and Engineering teams. While feature request advocacy is an ongoing activity, during the OHR, the TAM will review any high priority feature requests that have previously been submitted, providing updates on status including potential release dates. 

When a feature is coming up for the release, the TAM can help the customer prepare for implementation (providing early Preview access, coordinating a meeting with the Product Manager to review the feature, etc.) and then continue to provide support until the feature is successfully implemented in the customer environment. Similarly, if a high priority or technical blocking feature is not yet coming available, the TAM can help offer an alternative solution that can unblock the customer in the short term. 

The OHR is also a great time for the TAM to work with the customer to ensure they have early access to new and exciting features that are in Alpha or Beta, and that would be beneficial to the customer and their environment. 

Training strategy

Training is a primary component to ensuring the overall success in adopting Google Cloud. During the OHR, a review of training metrics will be provided. This may include tracking metrics to determine how the customer is tracking towards an initially agreed upon learning plan or coming up with additional upskilling strategies as necessary. Additionally, throughout an engagement, the customer’s TAM will provide opportunities for both free and paid Google Cloud training. 

Conclusion 

PSO is the voice of customer health, maintaining priority to proactively and strategically guide large enterprise customers to operate effectively and efficiently in the cloud, both during and after the migration process. The OHR is an efficient and effective way to maintain alignment, ensure expectations and objectives are being met, manage risk, and overall ensure the success of the customer.

Learn more about our methodology and get started with Google Cloud by completing a free discovery and assessment of your migration. Alternatively, if you’d like to engage directly with our PSO team on your migration, contact us!