Bard gets its biggest upgrade yet with Gemini {Google A.I / LLM}

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Google’s AI now goes by a new name: Gemini

Gemini is coming to your phone, your email, your everything.

www.theverge.com

Google’s AI now goes by a new name: Gemini​

Bard and Duet are gone, as Gemini becomes both the model and the product for getting all of Google’s AI out into the world.

By David Pierce, editor-at-large and Vergecast co-host with over a decade of experience covering consumer tech. Previously, at Protocol, The Wall Street Journal, and Wired.

Feb 8, 2024, 8:00 AM EST

74 Comments74 New

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Illustration by Alex Castro / The Verge

Google is famous for having a million similar products with confusingly different names and seemingly nothing in common. (Can I interest you in a messaging app?) But when it comes to its AI work, going forward there is only one name that matters: Gemini.

The company announced on Thursday that it is renaming its Bard chatbot to Gemini, releasing a dedicated Gemini app for Android, and even folding all its Duet AI features in Google Workspace into the Gemini brand. It also announced that Gemini Ultra 1.0 — the largest and most capable version of Google’s large language model — is being released to the public.

Gemini’s mobile apps will likely be the place most people encounter the new tool. If you download the new app on Android, it can set Gemini as your default assistant, meaning it replaces Google Assistant as the thing that responds when you say, “Hey Google” or long-press your home button. So far, it doesn’t seem Google is getting rid of Assistant entirely, but the company has been deprioritizing Assistant for a while now, and it clearly believes Gemini is the future. “I think it’s a super important first step towards building a true AI assistant,” says Sissie Hsiao, who runs Bard (now Gemini) at Google. “One that is conversational, it’s multimodal, and it’s more helpful than ever before.”

Gemini is part assistant, part chatbot, part search engine.

Image: Google

There’s no dedicated Gemini app for iOS, and you can’t set a non-Siri assistant as the default anyway, but you’ll be able to access all the AI features in the Google app. And just to give you a sense of how important Gemini is to Google: there’s going to be a toggle at the top of the app that lets you switch from Search to Gemini. For the entirety of Google’s existence, Search has been the most important product by a mile; it’s beginning to signal that Gemini might matter just as much. (For now, by the way, Google’s in-search AI is still called Search Generative Experience, but it’s probably safe to bet that’ll be Gemini eventually, too.)

The other changes to Gemini are mostly just branding. Google is ditching the Bard name, but otherwise its chatbot will feel the way it has previously; same goes for all the AI features inside of Google’s Workspace apps like Gmail and Docs, which were previously called “Duet AI” but are now also known as Gemini. Those are the features that help you draft an email, organize a spreadsheet, and accomplish other work-related tasks.

Most users will still be using the standard version of the Gemini model, known as Gemini Pro. In order to use Gemini Ultra, the most powerful version of the model, you’ll have to sign up for a Gemini Advanced subscription, which is part of the new $20-a-month Google One AI Premium plan. (These names are not helpful, Google!) The subscription also comes with 2TB of Google Drive storage and all the other features of the Google One subscription, so Google frames it as just a $10 monthly increase for those users. For everyone else, it’s the same price as ChatGPT Plus and other products — $20 a month seems to be about the going rate for a high-end AI bot.

The Ultra model can contain more context and have longer conversations

For that $20 a month, Hsiao says Gemini Ultra “sets the state of the art across a wide range of benchmarks across text, image, audio, and video.” The Ultra model can contain more context and have longer conversations, and it’s designed to be better at complex things like coding and logical reasoning.

The Google One plans are confusing — this helps.

Image: Google

It’s not a surprise that Google is so all-in on Gemini, but it does raise the stakes for the company’s ability to compete with OpenAI, Anthropic, Perplexity, and the growing set of other powerful AI competitors on the market. In our tests just after the Gemini launch last year, the Gemini-powered Bard was very good, nearly on par with GPT-4, but it was significantly slower. Now Google needs to prove it can keep up with the industry, as it looks to both build a compelling consumer product and try to convince developers to build on Gemini and not with OpenAI.

Only a few times in Google’s history has it seemed like the entire company was betting on a single thing. Once, that turned into Google Plus… and we know how that went. But this time, it appears Google is fully committed to being an AI company. And that means Gemini might be just as big as Google.

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Spoiler: related tweets

The next chapter of our Gemini era

We\u0027re bringing Gemini to more Google products. Bard will now be called Gemini, and you can access our most capable AI model, Ultra 1.0, in Gemini Advanced.

deepmind.google

Frederic Lardinois (@fredericl) on Threads

When Google creates a general artificial intelligence, the AI's one task before announcing itself to the world will be to fix Google's confusing branding. Then it will call itself the Google Assistant...

www.threads.net

Christophe Dubos on LinkedIn: The next chapter of our Gemini era

Drum Roll, please - Today we're Introducing Gemini Advanced Bard has been the best way for people to directly experience our most capable models. To reflect…

www.linkedin.com

Dave Lee (@daveleebbg) on Threads

Might ask ChatGPT to make sense of this

www.threads.net

Greta Krupetsky on LinkedIn: The next chapter of our Gemini era

Today is a very proud moment for us all at Google as we enter the next chapter of our #Gemini era, bringing our most capable #AI technology to the entire…

www.linkedin.com

Bard rebranded: Google's ChatGPT rival is now called Gemini

Google has renamed its AI chatbot Bard as Gemini, giving a new identity to its ChatGPT rival

www.newsbytesapp.com

Aaron Lax on LinkedIn: Google’s AI now goes by a new name: Gemini | 18 comments

BARD no longer, the reports earlier this week about Google changing the name of their AI competitor from Bard to Gemini has occurred. Another bit of news that… | 18 comments on LinkedIn

www.linkedin.com

Vikas Kansal on LinkedIn: The next chapter of our Gemini era

🚀 Launching Google One AI Premium plan that comes with Gemini Advanced (formerly Bard) with our most capable AI model, Ultra 1.0 and offers the best of…

www.linkedin.com

 

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Spoiler: thread continued

 

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[DPresidential]

I pay for CHATGPT 4 premium and use it in my labor law practice as my assistant.

Would yall suggest I look into Gemini as a better alternative?

 

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Spoiler: images

 

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https://archive.is/ZUz1m

I showed Gemini 1.5 Pro the ENTIRE Self-Operating Computer codebase, and an example Gemini 1.5 API call.

From there, it was able to perfectly explain how the codebase works...

and then it implemented itself as a new supported model for the repo!

Not perfect, but very close.

Spoiler: larger images

 

[bnew]

https://archive.is/tbHEm

Spoiler: full text

Gemini 1.5 pro is STILL under hyped

I uploaded an entire codebase directly from github, AND all of the issues (
@vercel
ai sdk,)

Not only was it able to understand the entire codebase, it identified the most urgent issue, and IMPLEMENTED a fix.

This changes everything

Spoiler: larger images

 

[bnew]

Google Gemma: because Google doesn’t want to give away Gemini yet

Gemma could be faster and more cost-efficient.

www.theverge.com

Google Gemma: because Google doesn’t want to give away Gemini yet​

Gemma 2B and Gemma 7B are smaller open-source AI models for language tasks in English.​

By Emilia David, a reporter who covers AI. Prior to joining The Verge, she covered the intersection between technology, finance, and the economy.

Feb 21, 2024, 8:00 AM EST

Google’s new model Gemma.
Image: Google

Google has released Gemma 2B and 7B, a pair of open-source AI models that let developers use the research that went into its flagship Gemini more freely. While Gemini is a big closed AI model that directly competes with (and is nearly as powerful as) OpenAI’s ChatGPT, the lightweight Gemma will likely be suitable for smaller tasks like simple chatbots or summarizations.

But what these models lack in complication, they may make up for in speed and cost of use. Despite their smaller size, Google claims Gemma models “surpass significantly larger models on key benchmarks” and are “capable of running directly on a developer laptop or desktop computer.” They will be available via Kaggle, Hugging Face, Nvidia’s NeMo, and Google’s Vertex AI.

Gemma’s release into the open-source ecosystem is starkly different from how Gemini was released. While developers can build on Gemini, they do that either through APIs or by working on Google’s Vertex AI platform. Gemini is considered a closed AI model. By making Gemma open source, more people can experiment with Google’s AI rather than turn to competitors that offer better access.

Both model sizes will be available with a commercial license regardless of organization size, number of users, and the type of project. However, Google — like other companies — often prohibits its models from being used for specific tasks such as weapons development programs.

Gemma will also ship with “responsible AI toolkits,” as open models can be harder to place guardrails in than more closed systems like Gemini. Tris Warkentin, product management director at Google DeepMind, said the company undertook “more extensive red-teaming to Gemma because of the inherent risks involved with open models.”

The responsible AI toolkit will allow developers to create their own guidelines or a banned word list when deploying Gemma to their projects. It also includes a model debugging tool that lets users investigate Gemma’s behavior and correct issues.

The models work best for language-related tasks in English for now, according to Warkentin. “We hope we can build with the community to address market needs outside of English-language tasks,” he told reporters.

Developers can use Gemma for free in Kaggle, and first-time Google Cloud users get $300 in credits to use the models. The company said researchers can apply for up to $500,000 in cloud credits.

While it’s not clear how much of a demand there is for smaller models like Gemma, other AI companies have released lighter-weight versions of their flagship foundation models, too. Meta put out Llama 2 7B, the smallest iteration of Llama 2, last year. Gemini itself comes in several weights, including Gemini Nano, Gemini Pro, and Gemini Ultra, and Google recently announced a faster Gemini 1.5 — again, for business users and developers for now.

Gemma, by the way, means precious stone.

 

[bnew]

Gemma: Introducing new state-of-the-art open models

Gemma is a family of lightweight, state\u002Dof\u002Dthe art open models built from the same research and technology used to create the Gemini models.

blog.google

DEVELOPERS

Gemma: Introducing new state-of-the-art open models​

Feb 21, 2024
3 min read

Gemma is built for responsible AI development from the same research and technology used to create Gemini models.

Jeanine Banks
VP & GM, Developer X and DevRel

Tris Warkentin
Director, Google DeepMind

Listen to article7 minutes​

At Google, we believe in making AI helpful for everyone. We have a long history of contributing innovations to the open community, such as with Transformers, TensorFlow, BERT, T5, JAX, AlphaFold, and AlphaCode. Today, we’re excited to introduce a new generation of open models from Google to assist developers and researchers in building AI responsibly.

Gemma open models​

Gemma is a family of lightweight, state-of-the-art open models built from the same research and technology used to create the Gemini models. Developed by Google DeepMind and other teams across Google, Gemma is inspired by Gemini, and the name reflects the Latin gemma, meaning “precious stone.” Accompanying our model weights, we’re also releasing tools to support developer innovation, foster collaboration, and guide responsible use of Gemma models.

Gemma is available worldwide, starting today. Here are the key details to know:

• We’re releasing model weights in two sizes: Gemma 2B and Gemma 7B. Each size is released with pre-trained and instruction-tuned variants.
• A new Responsible Generative AI Toolkit provides guidance and essential tools for creating safer AI applications with Gemma.
• We’re providing toolchains for inference and supervised fine-tuning (SFT) across all major frameworks: JAX, PyTorch, and TensorFlow through native Keras 3.0.
• Ready-to-use Colab and Kaggle notebooks, alongside integration with popular tools such as Hugging Face, MaxText, NVIDIA NeMo and TensorRT-LLM, make it easy to get started with Gemma.
• Pre-trained and instruction-tuned Gemma models can run on your laptop, workstation, or Google Cloud with easy deployment on Vertex AI and Google Kubernetes Engine (GKE).
• Optimization across multiple AI hardware platforms ensures industry-leading performance, including NVIDIA GPUs and Google Cloud TPUs.
• Terms of use permit responsible commercial usage and distribution for all organizations, regardless of size.
  

State-of-the-art performance at size​

Gemma models share technical and infrastructure components with Gemini, our largest and most capable AI model widely available today. This enables Gemma 2B and 7B to achieve best-in-class performance for their sizes compared to other open models. And Gemma models are capable of running directly on a developer laptop or desktop computer. Notably, Gemma surpasses significantly larger models on key benchmarks while adhering to our rigorous standards for safe and responsible outputs. See the technical report for details on performance, dataset composition, and modeling methodologies.

 

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Responsible by design​

Gemma is designed with our AI Principles at the forefront. As part of making Gemma pre-trained models safe and reliable, we used automated techniques to filter out certain personal information and other sensitive data from training sets. Additionally, we used extensive fine-tuning and reinforcement learning from human feedback (RLHF) to align our instruction-tuned models with responsible behaviors. To understand and reduce the risk profile for Gemma models, we conducted robust evaluations including manual red-teaming, automated adversarial testing, and assessments of model capabilities for dangerous activities. These evaluations are outlined in our Model Card.

1​

We’re also releasing a new Responsible Generative AI Toolkit together with Gemma to help developers and researchers prioritize building safe and responsible AI applications. 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.

Optimized across frameworks, tools and hardware​

You can fine-tune Gemma models on your own data to adapt to specific application needs, such as summarization or retrieval-augmented generation (RAG). 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.

Free credits for research and development​

Gemma is built for the open community of developers and researchers powering AI innovation. You can start working with Gemma today using free access in Kaggle, a free tier for Colab notebooks, and $300 in credits for first-time Google Cloud users. Researchers can also apply for Google Cloud credits of up to $500,000 to accelerate their projects.

Getting started​

You can explore more about Gemma and access quickstart guides on ai.google.dev/gemma.

As we continue to expand the Gemma model family, we look forward to introducing new variants for diverse applications. Stay tuned for events and opportunities in the coming weeks to connect, learn and build with Gemma.

We’re excited to see what you create!

 

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Mind officially blown:

I recorded a screen capture of a task (looking for an apartment on Zillow). Gemini was able to generate Selenium code to replicate that task, and described everything I did step-by-step.

It even caught that my threshold was set to $3K, even though I didn't explicitly select it.

"This code will open a Chrome browser, navigate to Zillow, enter "Cupertino, CA" in the search bar, click on the "For Rent" tab, set the price range to "Up to $3K", set the number of bedrooms to "2+", select the "Apartments/Condos/Co-ops" checkbox, click on the "Apply" button, wait for the results to load, print the results, and close the browser."

 

[Family Lives Matter]

I use this shyt to check over my work and just take out the sensitive information

 

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