Google Cloud Next Keynote 2024: What You Need to Know

The Google Cloud Next Keynote 2024 is just around the corner, and you're probably wondering what to expect. The event promises to be a game-changer for businesses and developers alike.

Google Cloud Next Keynote 2024 will feature a packed agenda with keynote speakers and breakout sessions. Keynote speakers include Sundar Pichai, CEO of Alphabet and Google, and Thomas Kurian, CEO of Google Cloud.

The event will take place on March 18-20, 2024, at the Moscone Center in San Francisco. This is a great opportunity to network with industry professionals and learn about the latest advancements in cloud technology.

Google Cloud Next Keynote 2024 will also feature a showcase of new products and services, including AI and machine learning capabilities.

Google Cloud is expanding the capabilities of Vertex AI, its unified artificial intelligence platform, with new models and updates to existing models. This includes adding Meta's Llama 2 and Code Llama, the Technology Innovation Institute's Falcon LLM, and Anthropic's Claude 2 to Model Garden, its catalog of pre-trained models.

Gemini 1.5 Pro is now available as a public preview in Vertex AI, giving developers the world's largest context window. This is a game-changer for those working with large datasets.

The new Vertex AI Agent Builder is a tool that allows organizations to easily and quickly create AI agents. Developers can create and deploy AI experiences using natural language or open source frameworks like LangChain on Vertex AI.

Google Cloud is also making Duet AI generally available in Google Workspace, allowing users to sign up for a no-cost trial. Duet AI is a powerful collaboration partner that can act as a coach, source of inspiration, and productivity booster.

Here are some key updates to Vertex AI:

Google Cloud is expanding the capabilities of Vertex AI, its unified artificial intelligence platform, with new models and updates to existing models.

The platform is now getting a curated collection of models across first-party, open-source, and third-party models, thanks to the addition of Meta's Llama 2 and Code Llama, the Technology Innovation Institute's Falcon LLM, and Anthropic's Claude 2 to Model Garden.

Google is also updating several first-party foundation models, including PaLM, Codey, and Imagen, which are now getting improved performance and capabilities.

PaLM is now getting higher quality outputs, a 32,000-token context window, and grounding capabilities for enterprise data.

Codey is getting better performance, and Imagen is getting improved image quality.

Gemini 1.5 Pro is now available as a public preview in Vertex AI, giving developers everywhere the world's largest context window.

The new Vertex AI Agent Builder is a tool that allows organizations to easily and quickly create AI agents.

Developers can create and deploy AI experiences using natural language or open source frameworks like LangChain on Vertex AI.

Google Cloud announced a wide range of new features and capabilities for its core data and data analytics offerings. These innovations boost the productivity of data teams by reimagining data work with products such as Looker, BigQuery, and Dataplex.

The new BigQuery Studio provides a unified interface for data engineering, analytics, and predictive analysis. This Studio makes building and managing data pipelines, exploring data, and creating machine learning models easy.

BigQuery Data Canvas offers a notebook-like experience with embedded visualizations and natural language support thanks to Gemini. This feature enables data analysts to be more productive and improve query performance throughout the analytics lifecycle.

BigQuery can now be used with Gemini 1.0 Pro Vision to analyze both images and video by combining custom prompts and SQL statements. This integration allows for multimodal analytics and vector embeddings, as well as fine-tuning of LLMs.

The new BigQuery Continuous Queries provide continuous SQL processing over data streams, enabling real-time pipelines with AI operators or reverse ETL. This feature supports secure data sharing, governance, and enhanced support for unstructured data.

BigQuery Studio offers a collaborative data workspace, the choice of SQL, Python, Spark or natural language directly, and new integrations for real-time streaming and governance. This feature also provides enhanced support for cross-cloud analytics.

BigQuery can now connect models in Vertex AI to enterprise data without copying or moving data out of BigQuery. This integration enables data analysts to explore data, create machine learning models, and build and manage data pipelines easily.

Here are some key features of the new BigQuery Studio:

Gemini in BigQuery enables data analysts to be more productive, improve query performance, and optimize costs throughout the analytics lifecycle. This feature also provides new integrations for real-time streaming and governance.

At Google Cloud Next keynote, developer-focused keynotes were delivered by industry experts, highlighting the complex challenges Google has faced in handling legacy workloads.

Forrest Brazeal and Richard Seroter shared real-world examples and testimonials from Google Cloud Champions, showcasing how Google Cloud has helped them scale their products and platforms, and improve security.

The keynote was followed by a showcase of Vertex AI Prompt Management and Vertex AI Rapid Evaluation, two new tools in preview that aim to help users deliver reliable LLM applications more quickly.

The developer keynote at the conference was a highlight, featuring a presentation by Forrest Brazeal and Richard Seroter.

Forrest Brazeal, Head of Developer Media at Google Cloud, and Richard Seroter, Director of Outbound Strategy and Enablement at Google Cloud, took the stage to share their insights on the challenges Google faced with legacy workloads.

Google Cloud Champions shared real-world examples of how Google Cloud helped them scale their products and improve security.

These testimonials showcased the tangible benefits of using Google Cloud, giving attendees a glimpse into the success stories of other developers who have made the switch.

Forrest Brazeal and Richard Seroter's keynote was a valuable resource for developers looking to overcome similar challenges in their own projects.

LLM Developer Tools are a game-changer for AI engineers and developers, and two exciting announcements have just been made.

The release of Vertex AI Prompt Management and Vertex AI Rapid Evaluation, both in preview, aim to help users deliver reliable LLM applications more quickly by supporting important aspects of prompt engineering.

These tools are focused on solving two major pain points for anyone working with LLMs in a serious way: prompt management and model evaluation.

The Prompt Management tool allows teams to easily track and manage their LLM prompts and prompt parameters, and compare the performance of those prompts and prompt versions against one another.

This means that developers can now focus on building apps and Agents around LLMs, without getting bogged down in tedious prompt management tasks.

The Rapid Evaluation tool helps users quickly assess model performance for a specific set of tasks, making it easier to identify areas for improvement.

With these tools, developers can deliver reliable LLM applications more quickly and efficiently, which is a huge win for anyone working with LLMs.