Google Cloud Next made waves in Las Vegas last week with its dynamic presence! From the captivating opening keynote highlighting remarkable customer achievements to thrilling product unveilings, the event delved into how AI is revolutionizing corporate landscapes. With nearly 400 partner sponsors, the energy from the show floor permeated through sessions and evening events all week long.
Building on last year’s discourse on the potential of generative AI, this year’s event showcased real-world applications transforming business operations. Google Next ’24 spotlighted over 300 customer and partner AI success stories, along with 500+ breakout sessions, hands-on demos, interactive training sessions, and much more. It was a packed week, and here at Inflexion Analytics, we’ve compiled a summary of our announcements on how Google is reshaping the cloud landscape with Data & AI technology.
Gemini for Google Cloud
Google shared how Google’s Gemini family of models will help teams accomplish more in the cloud, including:
- Gemini for Google Cloud, a new generation of AI assistants for developers, Google Cloud services, and applications.
- Gemini Code Assist, which is the evolution of the Duet AI for Developers.
- Gemini Cloud Assist, which helps cloud teams design, operate, and optimize their application lifecycle.
- Gemini in Security Operations, generally available at the end of this month, converts natural language to new detections, summarizes event data, recommends actions to take, and navigates users through the platform via conversational chat.
- Gemini in BigQuery, in preview, enables data analysts to be more productive, improve query performance and optimize costs throughout the analytics lifecycle.
- Gemini in Looker, in private preview, provides a dedicated space in Looker to initiate a chat on any topic with your data and derive insights quickly.
- Gemini in Databases, also in preview, helps developers, operators, and database administrators build applications faster using natural language; manage, optimize and govern an entire fleet of databases from a single pane of glass; and accelerate database migrations.
Vertex AI
- Gemini 1.5 Pro is now available in public preview in Vertex AI, bringing the world’s largest context window to developers everywhere.
- Gemini 1.5 Pro on Vertex AI can now process audio streams including speech, and the audio portion of videos.
- Imagen 2.0, our family of image generation models, can now be used to create short, 4-second live images from text prompts.
- Image editing is generally available in Imagen 2.0, including inpainting/outpainting and digital watermarking powered by Google DeepMind’s SynthID.
- We added CodeGemma, a new model from our Gemma family of lightweight models, to Vertex AI.
- Vertex AI has expanded grounding capabilities, including the ability to directly ground responses with Google Search, now in public preview.
- Vertex AI Prompt Management, in preview, helps teams improve prompt performance.
- Vertex AI Rapid Evaluation, in preview, helps users evaluate model performance when iterating on the best prompt design.
- Vertex AI AutoSxS is now generally available, and helps teams compare the performance of two models.
- We expanded data residency guarantees for data stored at-rest for Gemini, Imagen, and Embeddings APIs on Vertex AI to 11 new countries: Australia, Brazil, Finland, Hong Kong, India, Israel, Italy, Poland, Spain, Switzerland, and Taiwan.
- When using Gemini 1.0 Pro and Imagen, you can now limit machine-learning processing to the United States or European Union.
- Vertex AI hybrid search, in preview, integrates vector-based and keyword-based search techniques to ensure relevant and accurate responses for users.
- The new Vertex AI Agent Builder, in preview, lets developers build and deploy gen AI experiences using natural language or open-source frameworks like LangChain on Vertex AI.
- Vertex AI includes two new text embedding models in public preview: the English-only text-embedding-preview-0409, and the multilingual text-multilingual-embedding-preview-0409.
Data Analytics
- BigQuery is now Google Cloud’s single integrated platform for data to AI workloads, with BigLake, BigQuery’s unified storage engine, providing a single interface across BigQuery native and open formats for analytics and AI workloads.
- BigQuery better supports Iceberg, DDL, DML and high-throughput support in preview, while BigLake now supports the Delta file format, also in preview. · BigQuery continuous queries are in preview, providing continuous SQL processing over data streams, enabling real-time pipelines with AI operators or reverse ETL.
- The above-mentioned Gemini in BigQuery enables all manner of new capabilities and offerings:
- New BigQuery integrations with Gemini models in Vertex AI support multimodal analytics and vector embeddings, and fine-tuning of LLMs. · BigQuery Studio provides a collaborative data workspace, the choice of SQL, Python, Spark or natural language directly, and new integrations for real-time streaming and governance; it is now generally available. · The new BigQuery data canvas provides a notebook-like experience with embedded visualizations and natural language support courtesy of Gemini.
- BigQuery can now connect models in Vertex AI with enterprise data, without having to copy or move data out of BigQuery.
- You can now use BigQuery with Gemini 1.0 Pro Vision to analyze both images and videos by combining them with your own text prompts using familiar SQL statements.
- Column-level lineage in BigQuery and expanded lineage capabilities for Vertex AI pipelines will be in preview soon.
- Other updates to our data analytics portfolio include:
- Apache Kafka for BigQuery as a managed service is in preview, to enable streaming data workloads based on open source APIs.
- A serverless engine for Apache Spark integrated within BigQuery Studio is now in preview.
- Dataplex features expanded data-to-AI governance capabilities in preview.