Tech
The AI Cloud: How Google Gemini can help you build things faster, cheaper, and better
Richard Seroter, chief evangelist at Google Cloud.
When it comes to generative AI, Google has been a major player with its Gemini offering: users experience Gemini with every search, it's available as part of Gmail, and there are coding and development tools that allow users to reap the benefits of Gemini.
I had the opportunity to speak with Richard Seroter, Chief Evangelist at Google Cloud, to learn more about where Google thinks AI is taking us at both the developer and consumer level.
let's start.
And sorry, accountants, but AI will enhance creativity, not replace it.
ZDNET: Can you tell us your story about how you became chief evangelist for Google Cloud?
Richard Seroter: It's a long and dramatic story. It's not really. I joined Google Cloud four years ago as the first external “outbound product manager” working with customers and internal teams on our app development and modernization products.
About two years ago I was asked to lead Developer Relations, and last year I also had the pleasure of welcoming the Cloud Documentation team into the group.
Today, I have the honor of leading a group of talented engineers, technical writers, and product managers who are helping people discover, use, and enjoy Google Cloud.
ZDNET: Can you give us some examples of how AI-powered coding assistants have improved developer productivity?
Seroter: The goal is to help teams ship faster, more efficiently, and with higher quality. An AI-powered coding assistant accomplishes this by reducing context switching and letting you stay in your IDE. [the development environment] AI chat and inline code generation enable more activity and allow you to write code by expressing your intent, without having to remember every aspect of code syntax.
Also, What is Gemini? Everything you need to know about Google's new AI model
A good AI assistant can speed up onboarding of new skills, help find areas of improvement in your codebase, and eliminate repetitive tasks.
For example, using an AI assistant to quickly generate database connection code or data objects can be a huge time saver. While developers don't code all day (yes, they don't), the productivity benefits are certainly there for junior and senior developers.
We've seen some really great use cases for this capability with customers like Turing and Commerzbank, who announced at the recent Google Cloud Next conference.
ZDNET: What measures are taken to ensure the reliability and accuracy of the AI-generated code? As we showed in our coding tests article, Google Gemini failed several coding tests.
Seroter: Products like Gemini Code Assist have rigorously trained models and a series of filters that check the results before returning them to the user, but the answers aren't always perfect.
Also, Google's Gemini 1.5 Pro failed on the first prompt
That's one of the reasons we're building (and pre-announced at Next) the code customization feature, which lets you base answers on your private codebase. We'll continue to improve and refine the underlying model as we incorporate customer feedback on areas for improvement.
ZDNET: How does Google Cloud's partnership with Stack Overflow and other platforms power your AI tools, particularly to help ensure that the vast amount of incomplete or inaccurate information on Stack Overflow isn't included in its knowledge base?
Seroter: The data provided by all our partners (Stack Overflow, Snyk, etc.) gives us additional knowledge to understand where developers are at and provide more comprehensive answers to users' questions.
Additionally, Google Cloud is adding Stack Overflow's knowledge base to Gemini AI
As part of our overall data processing strategy, we filter and evaluate all data contributions, including those from our partners. Whether or not third-party data sources are used, we use a combination of different techniques and tools to justify our answers, and we continuously validate and monitor the quality of our answers through a series of automated and manual tests.
ZDNET: How does Google ensure the security and privacy of customer code when using Gemini Code Assist?
Seroter: Google does not train models based on prompts entered into Gemini Code Assist, and has published documentation on how we encrypt prompts in transit and our overall privacy approach.
Google also announced Gemini Code Assist, and I'm cautiously optimistic that it will be useful to programmers.
We also cite sources where possible, provide indemnification, and use VPC Service Controls to provide secure access to our perimeter networks.
ZDNET: How does Google Cloud address potential bias in AI models used in its development tools?
Seroter: We strive to follow Google's AI principles and apply strong protections during training and response filtering. We also provide multiple feedback mechanisms (in the IDE and elsewhere) so that users can flag anything they find offensive or inaccurate.
ZDNET: Can you talk about the impact of AI on the future of software engineering and development practices?
Seroter: We expect AI to positively impact nearly every role in software development and delivery. Teams use AI-embedded systems to analyze data, create requirements, build prototypes, set up development environments, write and update code, generate test plans, review code, deploy applications, provision and optimize infrastructure, troubleshoot issues, and secure systems.
Also, from AI trainers to ethicists: AI may eliminate some jobs, but it may also create new ones
Faster models that take into account local knowledge repositories and code bases will provide contextual answers across the entire app delivery lifecycle. Our practices need to keep up as we think about creation and curation activities, providing AI-enabled platforms to build teams on, and even how to test non-deterministic systems.
Research shows that developers want AI to help them improve engineering efficiency, not fundamentally change their workflows. At least not yet, but stay tuned.
ZDNET: How does Google Cloud's AI technology help manage and reduce technical debt in software projects?
Seroter: Technical debt comes from many directions, and sometimes it's “good” debt accumulated by teams bringing value to the market. But AI-assisted tools, and AI in general, can help teams apply best practices faster and remediate existing debt faster.
A well-trained AI assistant like Gemini Code Assist can generate and validate code as developers work, minimizing compromises and future debt. For existing codebases, Gemini 1.5's huge context window allows teams to explore the entire codebase and look for problems to solve.
ZDNET: What advancements do you expect to see in future AI-assisted development tools on Google Cloud?
Seroter: We're excited to bring to market something we recently announced as a preview at our Google Cloud Next conference. By providing Gemini 1.5 as a base model, we're able to provide full awareness of your codebase, empowering teams to perform complex modernization and code exploration faster than ever before.
We'll also introduce Gemini 1.5, Google's latest AI model, which is a major upgrade from its predecessor.
And you can customize responses based on code from GitHub, GitLab, and Bitbucket, giving your teams more trust and context from their AI-generated results. Explore other foundational options to ensure your developers get timely, relevant help.
We also know that AI assistance doesn’t just work within IDEs, but also benefits developers: Gemini’s overall investment in Google Cloud will provide AI assistance to a wide variety of people, including BigQuery users trying to generate complex queries, Cloud SQL users explaining large store procedures, security experts analyzing threats, and developers creating low-code integrations and APIs.
The AI-assisted cloud will help us “build” all kinds of things faster, cheaper, and with higher quality.
ZDNET: Can you talk about the role of AI and machine learning in powering cloud services?
Seroter: Building software is exciting, but most software spends its day in production. We recently announced Cloud Assist, a new service as part of Google Cloud's Gemini that will change the way teams manage their cloud services.
Plus: Introducing Google Threat Intelligence from Gemini Pro, a Google Cloud security solution
From personalized optimization suggestions to helping identify issues and get systems back online faster, tools like this have the potential to fundamentally change the way (cloud) services are operated.
At the same time, Google Cloud's Gemini is designed to improve usability across the cloud: getting an AI-generated threat overview in Security Command Center is powerful, and seeing an AI-assisted log overview in Cloud Logging makes the product even easier to use.
An always-on AI chat window in the Cloud Console eliminates the need for context switching to ask a product question or understand a CLI command, providing an experience that provides support in context and has a profound impact on your day-to-day cloud usage.
ZDNET: What innovative use cases for Google Cloud have impressed you recently?
Seroter: I'm inspired by Google's broad research-based work and the ways in which customers can apply technology to solve specific problems. Our recent work with AlphaFold 3 is predicting the structure and interactions of life's molecules. This is remarkable. We're mapping new aspects of the human brain. It's awe-inspiring.
Companies like Chugai Pharmaceutical are leveraging some of our research findings by adopting cloud systems to accelerate drug discovery, and we are impressed with the Aviator team's efforts to help developers be more productive across the entire development lifecycle.
And companies like Goldman Sachs are democratizing data access by open-sourcing their data platforms. Google Cloud customers are solving big problems and consistently having a major impact on their industries.
And why AI solutions can prove their value in just three months
What do you think?
Do you currently use Gemini for search, email, or as part of your coding process? Did Richard's answer help you understand how Google thinks about AI? Let us know in the comments below.
You can follow my daily project updates on social media: subscribe to my newsletter for weekly updates and follow me on Twitter/X (@DavidGewirtz), Facebook (Facebook.com/DavidGewirtz), Instagram (Instagram.com/DavidGewirtz) and YouTube (YouTube.com/DavidGewirtzTV).
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