News from the AI & ML world
DeeperML - #vertexai
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Michael Nuñez@AI News | VentureBeat
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Google has recently rolled out its latest Gemini 2.5 Flash and Pro models on Vertex AI, bringing advanced AI capabilities to enterprises. The release includes the general availability of Gemini 2.5 Flash and Pro, along with a new Flash-Lite model available for testing. These updates aim to provide organizations with the tools needed to build sophisticated and efficient AI solutions.
The Gemini 2.5 Flash model is designed for speed and efficiency, making it suitable for tasks such as large-scale summarization, responsive chat applications, and data extraction. Gemini 2.5 Pro handles complex reasoning, advanced code generation, and multimodal understanding. Additionally, the new Flash-Lite model offers cost-efficient performance for high-volume tasks. These models are now production-ready within Vertex AI, offering the stability and scalability needed for mission-critical applications. Google CEO Sundar Pichai has highlighted the improved performance of the Gemini 2.5 Pro update, particularly in coding, reasoning, science, and math. The update also incorporates feedback to improve the style and structure of responses. The company is also offering Supervised Fine-Tuning (SFT) for Gemini 2.5 Flash, enabling enterprises to tailor the model to their unique data and needs. A new updated Live API with native audio is also in public preview, designed to streamline the development of complex, real-time audio AI systems. Recommended read:
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@github.com
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Google Cloud recently unveiled a suite of new generative AI models and enhancements to its Vertex AI platform, designed to empower businesses and developers. The updates, announced at Google I/O 2025, include Veo 3, Imagen 4, and Lyria 2 for media creation, and Gemini 2.5 Flash and Pro for coding and application deployment. A new platform called Flow integrates the Veo, Imagen, and Gemini models into a comprehensive platform. These advancements aim to streamline workflows, foster creativity, and simplify the development of AI-driven applications, with Google emphasizing accessibility for both technical and non-technical users.
One of the key highlights is Veo 3, Google's latest video generation model with audio capabilities. It allows users to generate videos with synchronized audio, including ambient sounds, dialogue, and environmental noise, all from text prompts. Google says Veo 3 excels at understanding complex prompts, bringing short stories to life with realistic physics and lip-syncing. According to Google Deepmind CEO Demis Hassabis, users have already generated millions of AI videos in just a few days since its launch and the surge in demand led Google to expand Veo 3 to 71 countries. The model is still unavailable in the EU, but Google says a rollout is on the way. The company has also made AI application deployment significantly easier with Cloud Run, including deploying applications built in Google AI Studio directly to Cloud Run with a single click, enabling direct deployment of Gemma 3 models from AI Studio to Cloud Run, complete with GPU support, and introducing a new Cloud Run MCP server, which empowers MCP-compatible AI agents to programmatically deploy applications. In addition to new models, Google is working to broaden access to its SynthID Detector for detecting synthetic media. Veo 3 was initially web-only, but Pro and Ultra members can now use the model in the Gemini app for Android and iOS. Recommended read:
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@techradar.com
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AWS News Blog
, Data Phoenix
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AI adoption is accelerating rapidly, with Amazon reporting that a UK business is adopting AI every 60 seconds. This surge in adoption is highlighted in a recent AWS report, which indicates a 33% increase in the past year, bringing the total of UK businesses utilizing AI to 52%. Startups appear to be leading the charge, with 59% adoption rate, and are also more likely to have comprehensive AI strategies in place compared to larger enterprises, 31% versus 15% respectively. Benefit realization is also on the rise, with 92% of AI-adopting businesses reporting an increase in revenue, a substantial jump from 64% in 2024.
Amazon is also introducing new tools to assist developers in building and scaling AI solutions. Amazon Q Developer is now available in preview on GitHub, enabling developers to assign tasks to an AI agent directly within GitHub issues. This agent can develop features, conduct code reviews, enhance security, and migrate Java code. The tool aims to accelerate code generation and streamline the development process, allowing developers to quickly implement AI-driven functionalities within their projects. Installation is simple, and developers can begin using the application without connecting to an AWS account. Adding to its suite of AI offerings, Amazon has launched Nova Premier, its most capable foundation model, now generally available on Amazon Bedrock. Nova Premier is designed to handle complex workflows requiring multiple tools and data sources. It boasts a one-million token context window, enabling it to process lengthy documents and large codebases. One notable feature of Nova Premier is its model distillation capabilities, allowing users to transfer its advanced features to smaller, faster models for production deployment. Amazon is investing in AI training, with a UK initiative to train 100,000 people in AI skills by the end of the decade, collaborating with universities such as Exeter and Manchester. Recommended read:
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@cloud.google.com
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Google is significantly expanding the AI and ML capabilities within its BigQuery and Vertex AI platforms. BigQuery is receiving a boost with the integration of the TimesFM forecasting model, a state-of-the-art, pre-trained model from Google Research designed to simplify forecasting problems. This managed and scalable engine enables users to generate forecasts for both single and millions of time series within a single query. Additionally, BigQuery now supports structured data extraction and generation using large language models (LLMs) through the AI.GENERATE_TABLE function, alongside new row-wise inference functions, expanded model choice with Gemini and OSS models, and the general availability of the Contribution Analysis feature.
NotebookLM is also seeing expansion with the "Audio Overviews" feature now available in approximately 75 languages. This feature, powered by Gemini, allows users to listen to AI-generated summaries of documents, slides, web pages, and YouTube transcripts in multiple languages. This feature distills any mix of documents into a scripted back-and-forth between two synthetic hosts. Users can direct tone and depth through a prompt and then download an MP3 or keep playback inside the notebook. Early testers report that multilingual voices make long reading lists easier to digest on commutes and provide an alternative channel for blind or low-vision audiences. Furthermore, Google is experimenting with AI-powered language learning formats through its “Little Language Lessons,” integrated directly into NotebookLM and running on Gemini. These tools support situational learning, generating content dynamically based on user-described scenarios, rather than relying on fixed vocabulary lists. Google is also preparing new Gemini AI subscription tiers, potentially including a "Gemini Ultra" plan, evidenced by code discoveries in the Gemini web interface referencing distinct tiers with varying capabilities and usage limits. Recommended read:
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@docs.google.com
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AI & Machine Learning
, Kyle Wiggers ?
Google Cloud's Vertex AI is expanding its generative media capabilities, now boasting models across video, image, speech, and music. The platform is integrating Google's Lyria text-to-music model, allowing users to generate high-fidelity audio, and enhancing existing features in Veo 2, Chirp 3, and Imagen 3. These additions enable enterprises to create complete, production-ready assets from a single text prompt, encompassing images, videos with music, and speech elements. Vertex AI aims to provide a comprehensive solution for media creation across various modalities.
The enhancements to existing models include new editing and camera control features for Veo 2, providing creative control over video content. Chirp 3 now includes Instant Custom Voice, enabling users to create custom voices with only 10 seconds of audio input, as well as AI-powered narration and speech transcription with speaker distinction. Imagen 3 has improved image generation and inpainting capabilities for seamless object removal. These updates aim to help users refine and repurpose content with precision, reduce post-production time, and produce higher-quality assets. Google emphasizes the importance of safety and responsibility in the development and deployment of these models on Vertex AI. Built-in precautions include digital watermarking through SynthID, safety filters, and data governance measures. Additionally, Google offers IP indemnification, assuring users that they are protected from third-party intellectual property claims when using content generated with these tools. New customers can also start building with $300 in free credits to try Google Cloud AI and ML. Recommended read:
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@blogs.nvidia.com
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Google Cloud is making significant strides in the realm of multi-agent systems with new enhancements to its Vertex AI platform. This move is designed to empower enterprises to build and manage AI agents more effectively, recognizing the increasing importance of these agents in various business operations. The key highlight is the introduction of the Agent Development Kit (ADK), an open-source framework that streamlines the agent creation process, allowing developers to construct AI agents with minimal code. This approach fosters greater control over agent behavior and ensures seamless integration within the enterprise ecosystem.
To further enhance multi-agent collaboration, Google Cloud is championing the Agent2Agent protocol, an open language that enables agents built on different frameworks or by various vendors to communicate and work together seamlessly. This interoperability is crucial for creating comprehensive AI solutions that span different systems and data sources. Google Cloud is actively partnering with over 50 industry leaders to drive the adoption of this open standard, fostering a shared vision for the future of multi-agent systems. Vertex AI offers a comprehensive platform that integrates models, data, and agents, enabling enterprises to orchestrate the three pillars of production AI. This combination ensures agents perform reliably, mitigating the need for fragmented solutions. With the addition of Lyria, Google’s text-to-music model, Vertex AI now stands as the only platform with generative media models across all modalities – video, image, speech, and music. The platform allows enterprises to build and test concepts with free credits for new customers and offers free monthly usage of over 20 products, including AI APIs. Recommended read:
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