#Google

AIGoogle's productivity advisor Laura Mae Martin explains how Workspace Studio and Gemini can lighten users' workloads by reducing routine tasks. The post promotes a Google article on the topic but gives no specific features, figures, or availability details.

AIGoogle Flow says it partnered with Divine to create the music video for "Tequila Dance," framing the project as a showcase of how technology can amplify human expression. The post provides no further details about the tools or production process used.

AIGoogle's Nano Banana 2.1, model gemini-nano-banana-2.1, is now available and is said to outperform the previous Pro model at about a quarter of the price, $0.034 per image versus $0.134. The quoted post lists improved instruction following, better in-image text rendering, grounding with Google Image Search, and up to 5 characters of consistency plus 14 reference images. It is available in Google AI Studio, the Gemini API, Google Cloud, the Gemini app, and Flow. The author's own post is a playful reaction praising its design ability and shows a generated vegan basketball food truck poster.

AIGoogle released EmbeddingGemma 2, a 740M-parameter open embedding model under Apache 2.0 that combines a 270M text model with vision (170M) and audio (300M) encoders. The 270M text model can run locally with 0.5GB of RAM, and the full multimodal model with 1GB, and Unsloth provides GGUF files and fine-tuning support.

AIGoogle's EmbeddingGemma 2 is a 740M-parameter embedding model that outperforms some models more than twice its size while using about 191MB to 567MB of active RAM. It offers an 8K context window, 4x larger than the first generation, and can process up to 5.5 minutes of audio, 29 images, or 58 video frames in one pass.

AIGoogle says EmbeddingGemma 2, paired with Gemma 4, enables efficient on-device retrieval-augmented generation with a lower memory footprint. In this setup, EmbeddingGemma 2 retrieves local files and Gemma 4 reasons over them to produce grounded answers while keeping data private.

AIGoogle has released Nano Banana 2.1, its latest image generation and editing model, which it says outperforms previous versions with gains in visual design, mask-based editing, and subject consistency. Paige Bailey shared a pug smile example made with the model and invited users to try it in Google AI Studio.

AIGoogle's Nano Banana 2.1 (gemini-nano-banana-2.1) is now available and outperforms the previous Pro model at $0.034 per image, versus $0.134 before. It adds improved instruction following, better in-image text rendering, grounding with Google Image Search, and consistency for up to 5 characters with 14 reference images. It is available in Google AI Studio, the Gemini API, Google Cloud, the Gemini app, and Flow by Google.

AIGoogle's Gemini Nano Banana 2.1 is now available on fal, offering significantly faster generation than Nano Banana 2. The model adds major gains in visual design, mask-based editing, and subject consistency.

AIGoogle Gemma announces EmbeddingGemma 2, a lightweight embedding model that maps text, code, images, video, and audio into a single unified embedding space. The model has a 740M parameter form factor with modular encoders, Matryoshka Representation Learning dimensions from 768 down to 128, and an 8K context window that is 4x larger than the text-only EmbeddingGemma. It is released under the commercially permissive Apache 2.0 license.

AIGoogle Gemma says EmbeddingGemma 2 delivers best-in-size-class performance on MTEB (Code) and MIEB (Lite). The post highlights local codebase indexing, semantic code search, and coding agent retrieval, with a 9.92-point code performance gain over EmbeddingGemma.

AIGoogle has released EmbeddingGemma 2, a compact 740M-parameter model built for on-device and edge applications. It natively embeds text, images, audio, and video into one shared space, enabling cross-format search without manual organization, translation, or labeling.

AIGoogle's new multimodal embedding setup processes image, audio, and video entirely offline with zero server calls. Its modular design lets developers drop unused vision and audio components to save memory, and flexible dimension sizes cut local database storage by up to 6x. It can also pair with Gemma 4 to build RAG pipelines with minimal memory and processing requirements.

AIGoogle DeepMind released EmbeddingGemma 2, a 740M-parameter embedding model, under an Apache 2.0 license. The post says it is competitive across benchmarks and outperforms some specialist models more than twice its size, and that developers can use it for multimodal search or pair it with Gemma 4 for on-device RAG. Weights are available on Hugging Face and Kaggle.

AIGoogle DeepMind introduced EmbeddingGemma 2, its first natively multimodal open model for on-device embeddings. The model expands beyond text to unify code, images, audio, and video in a shared embedding space.

AIGoogle introduces EmbeddingGemma 2, its first open, natively multimodal embedding model, covering text, code, image, video, and audio tasks. It has a 740M parameter form factor, is positioned for offline, privacy-first RAG when paired with Gemma 4, and the post claims it outperforms some specialist models more than twice its size. Weights are available now on Hugging Face.

AIGoogle AI Studio introduced Nano Banana 2.1, an image generation model that Google says outperforms its previous models across the board. The update highlights better visual design, mask-based editing, subject consistency, and more natural-looking images. It is available to try today in AI Studio.

AIGoogle, as a Diamond Sponsor of COLM 2026, will have researchers from Google Research and Google DeepMind present 28 papers and participate in 16 workshops at the Hilton Union Square in San Francisco from October 6–9. Attendees can visit Google booth #107 to explore work on agentic systems, reasoning, and multimodal AI.

AIGoogle Research shares results from five partner-driven case studies showing how Google Earth AI's Population Dynamics Foundation Model addresses public health data gaps. The post frames the work as empowering global health research, with details available in the linked blog.

AIGoogle Flow's CultureCon conversation with Arlander Taylor, Ceej Vega, and Mattaniah Aytenfsu covered how creators intentionally integrate emerging tools into their work. The panelists discussed protecting early brainstorming stages from tools and using AI as a creative partner to overcome blocks. They framed the goal as leveraging these tools to amplify existing skills.

AIGoogle Labs is hosting a beginner-friendly Google Flow digital workshop starting October 8 at 9 AM PT. Led by Google Labs Staff Experience Designer Reed Enger, it offers an in-depth guided walkthrough of the tool. Registration is available through the RSVP link in the post.

AIGoogle for Developers highlights Art Codec, an interactive web experience built by @soumyadesign in Google AI Studio. It lets users explore classic masterpieces through dynamic hotspots, motifs, and visual techniques.