Highlights
- Google integrates Gemini AI across Gmail, Docs, Slides, Sheets, and Meet.
- Gemini Advanced introduces Python code editing and execution directly in its interface.
- Gemma, a lightweight open-source AI, is launched to democratize AI technology.
- Google One AI Premium tier offers 2TB of storage and advanced Gemini AI capabilities.
Google has been at the forefront of AI innovation, and this month marks another significant leap forward with the rebranding of Bard AI, the launch of the Gemini Android app, and the unveiling of a new Google One AI Premium tier.
Gemini Coming to Gmail and Google Workspace
This new tier not only offers a hefty 2TB of storage but also integrates the advanced capabilities of Gemini’s AI across various Google services, including Gmail, Docs, Slides, Sheets, and Meet.
Previously known as Duet AI in Google Workspace apps, this suite of AI tools, just like Google Bard, is now unified under the Gemini brand.
The heart of Gemini’s prowess lies in its Ultra 1.0 Large Language Model (LLM), which Google has praised for its processing efficiency, nuanced comprehension, and sophisticated problem-solving abilities.
The Mountain View-based tech giant says that Ultra 1.0 is crafted to enrich data analysis, generate high-quality code across multiple programming languages, and seamlessly integrate into Workspace apps, enhancing user experience without the need to juggle between different applications.
Gemini Advanced: A Playground for Python Enthusiasts
With the introduction of Gemini Advanced, Google takes a bold step towards empowering developers and aspiring programmers.
This premium service allows the direct editing and execution of Python code within the Gemini interface, offering a sandbox for users to experiment, learn, and validate code with instant feedback.
This feature caters to two main audiences: novices looking to grasp coding principles through hands-on practice and seasoned developers eager to verify AI-generated Python code’s functionality before its project integration.
Launching on February 21, Gemini Advanced promises to elevate coding workflows with enterprise-grade data protection and comprehensive administrative controls.
Gemma: Democratizing AI with Lightweight Models
In parallel to the Gemini suite, Google has introduced Gemma, a series of lightweight, open-source AI models derived from the same innovative research behind Gemini.
Gemma, as per Google, embodies the essence of its namesake, the Latin word for “precious stone,” signifying the model’s value and potential.
Available in two versions, with two and seven billion adjustable parameters respectively, Gemma is designed to deliver unparalleled performance on AI-capable desktops and laptops, despite its text-only input and output capability and initial limitation to English language processing.
Unlike its more versatile cousin Gemini, Gemma focuses on making high-quality AI accessible and practical for a broad audience, from developers to researchers.
FAQs
What is Gemini Advanced?
Gemini Advanced is a premium feature offered by Google that allows users to directly edit and run Python code within its interface. Aimed at both beginners and experienced developers, it provides an interactive environment for learning and code verification.
How does Gemini integrate with Google Workspace?
Gemini AI is now integrated into Google Workspace applications such as Gmail, Docs, Slides, Sheets, and Meet, enhancing these services with advanced AI capabilities like data analysis, code generation, and problem-solving.
What is Gemma and how is it related to Gemini?
Gemma is a family of lightweight, open-source AI models developed by Google, using the same foundational technology as the more powerful Gemini AI. Designed for practical use on AI-enabled devices, Gemma focuses on text processing and is initially available in English.
Who can benefit from Gemini Advanced’s Python code feature?
Gemini Advanced’s Python code feature is designed for both aspiring programmers who wish to learn and experiment with Python and seasoned developers who need to quickly verify the functionality of AI-generated code.
What are the key differences between Gemini and Gemma?
While Gemini is a robust, multimodal AI model capable of processing audio, video, and images, Gemma specializes in text input and output. Gemini supports multiple languages, whereas Gemma is initially limited to English.
What does Google Docs cover in addition to spelling and grammar suggestion ?
Conciseness: Suggestions for making your writing more concise
Active voice: Suggestions for making your writing more clear to readers
Wording: Suggestions for making words sound more dynamic or formal in context
Sentence Split: Suggestions for splitting up complex sentences to make your writing easier to read
What are the three studio features in Google meet ?
In Google Meet, there’s Generate a background and three Studio features:
Studio Lighting (below): Simulate studio-quality lighting with movable light sources and color/brightness options
Studio Look: Improves details to show you more clearly
Studio Sound: Recreates higher audio frequencies
What does the new Google One AI Premium ?
The new Google One AI Premium plan now provides access to Gemini features in Gmail, Docs, and other Workspace apps for personal accounts. Google says the integration lets you “get more done without jumping between tabs or apps.”
Formerly known as Duet AI, this starts with Gmail and Help me write in the Compose screen on Android, iOS, and the web. You enter a prompt and can insert what was generated. Another way to use this tool is writing something and then having Gemini “Formalize,” “Elaborate,” or “Shorten” it, while you can “Recreate” — generate again — at any time.
Help me write, powered by Gemini models, is also available in Google Docs on the web where you get additional “Bulletize,” “Summarize,” and “Tone” (“Formal” or “Casual”) refinements. You can also write a “Custom” prompt, like “make it a poem.
Then there’s a Proofread feature that offers an AI-powered upgrade to the existing “Spelling and grammar check” capability.
You can Create images in Google Slides, while Google Sheets offers Help me organize for custom tables and templates. There’s also Enhanced Smart Fill (see below) to reduce “manual data organization and analysis.” This includes “sentiment classification, combining and generating text, extracting specific text, formatting addresses, structuring phone numbers and emails, condensing text, and more.”
What tools are supported by Gemma ?
Gemma supports a wide variety of tools and systems:
Multi-framework tools: Bring your favorite framework, with reference implementations for inference and fine-tuning across multi-framework Keras 3.0, native PyTorch, JAX, and Hugging Face Transformers.
Cross-device compatibility: Gemma models run across popular device types, including laptop, desktop, IoT, mobile and cloud, enabling broadly accessible AI capabilities.
Cutting-edge hardware platforms: We’ve partnered with NVIDIA to optimize Gemma for NVIDIA GPUs, from data center to the cloud to local RTX AI PCs, ensuring industry-leading performance and integration with cutting-edge technology.
Optimized for Google Cloud: Vertex AI provides a broad MLOps toolset with a range of tuning options and one-click deployment using built-in inference optimizations. Advanced customization is available with fully-managed Vertex AI tools or with self-managed GKE, including deployment to cost-efficient infrastructure across GPU, TPU, and CPU from either platform.
What does Gemma toolkit include?
The toolkit includes:
Safety classification: We provide a novel methodology for building robust safety classifiers with minimal examples.
Debugging: A model debugging tool helps you investigate Gemma’s behavior and address potential issues.
Guidance: You can access best practices for model builders based on Google’s experience in developing and deploying large language models
What are two ways python can work?
According to Google, this feature can work in two main ways:
Learn: Aspiring programmers can use Gemini to experiment with code snippets, observe the impact of modifications, and gain a deeper understanding of coding principles. This interactive learning environment fosters a practical approach to mastering Python.
Verification: Developers can use Gemini to quickly verify the functionality of AI-generated Python code before integrating it into their projects. This not only saves valuable time but also ensures seamless operation of the implementation code.
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