What's new and changed in watsonx.ai

IBM® watsonx.ai updates can include new features, bug fixes, and security updates. Updates are listed in reverse chronological order so that the latest release is at the beginning of the topic.

Version 1.1.6

A new version of watsonx.ai was released in August 2024.

Version 1.1.6 is installed on IBM Cloud Pak® for Data 4.8.6 with the service operand version 8.6.0.

This release of the watsonx.ai service includes various fixes.

Version 1.1.5

A new version of watsonx.ai was released in April 2024.

Version 1.1.5 is installed on IBM Cloud Pak for Data 4.8.5 with the service operand version 8.5.0.

This release includes the following changes:
New features
Use Chat mode in Prompt Lab to inference models through conversational interactions
Chat mode in Prompt Lab is a simple chat interface that you can use to experiment with foundation models and simulate question-answering or conversational interactions for chatbot and virtual assistant use cases. The existing Structured and Freeform modes are useful when building few-shot or many-shot prompts for tasks such as extraction, summarization, and classification. Chat mode remembers the context of the conversation and each response builds on information from previous prompts.

For more information, see Prompt Lab.

New watsonx.ai end-to-end use case tutorial and video
Try the new tutorial to learn how to use watsonx.ai in an end-to-end use case starting from data preparation through to prompt engineering. For more information, see Try the watsonx.ai end-to-end use case
Prompt-tune the granite-13b-instruct-v2 model
You can tune the granite-13b-instruct-v2 foundation model by using the Tuning Studio. For more information, see Tuning Studio.
Work with new foundation models in Prompt Lab
You can now use the following foundation models for inferencing from the Prompt Lab in watsonx.ai:
jais-13b-chat
The jais-13b-chat foundation model is provided by Inception, Mohamed bin Zayed University of Artificial Intelligence, and Cerebras Systems. This foundation model specializes in conversational tasks in Arabic and English. You can also use the jais-13b-chat foundation model for general purpose tasks in the Arabic language, such as language translation between Arabic and English.
llama2-13b-dpo-v7
The llama2-13b-dpo-v7 foundation model from Meta is trained to understand and generate Korean text. You can use the llama2-13b-dpo-v7 foundation model for general-purpose tasks in the Korean language, such as classification, extraction, question-answering, and for language translation between Korean and English.

For more information, see Supported foundation models.

Version 1.1.4

A new version of watsonx.ai was released in March 2024.

Version 1.1.4 is installed on IBM Cloud Pak for Data 4.8.4 with the service operand version 8.4.0.

This release includes the following changes:
New features
Bring your own foundation model to inference from watsonx.ai
In addition to working with foundation models that are curated by IBM, you can now upload and deploy your own foundational models. After the models are deployed and registered with watsonx.ai, create prompts that inference the custom models from the Prompt Lab. To learn more about uploading custom foundation models, see Deploying custom foundation models. Also described is a list of supported GPU configurations, model architectures, and suggested matching hardware configurations.
The watsonx.ai API is available for use
You can now programmatically work with foundation models that are hosted in watsonx.ai by calling the watsonx.ai API directly. For more information, see the watsonx.ai API reference documentation.
Prompt-tune the llama-2-13b-chat foundation model
The Tuning Studio now supports tuning the llama-2-13b-chat foundation model. Start by engineering prompts for the larger llama-2-70b-chat model in the Prompt Lab to find effective prompt inputs for your use case. Then tune the smaller version of the Llama 2 model to generate comparable or better outputs with zero-shot prompts. For more information, see Tuning Studio.
A modification to the granite-13b-chat-v2 foundation model is available
The latest version of the granite-13b-chat-v2 is 2.1.0. The modification includes improvements that were gained by applying a novel AI alignment technique to the version 2.0.0 model. AI alignment involves using fine-tuning and reinforcement learning techniques to guide the model to return outputs that are as helpful, truthful, and transparent as possible. For more information, see the What is AI alignment? blog post from IBM Research.

If you saved a prompt that inferences the granite-13b-chat-v2 foundation model as a template or notebook prior to this release, you might need to edit the asset to account for changes that were made to how the model handles white spaces.

Work with new foundation models in Prompt Lab
You can now use the following foundation models for inferencing from the Prompt Lab in watsonx.ai:
  • granite-8b-japanese: A foundation model from the IBM Granite family that is trained to understand and generate Japanese text. You can use the granite-8b-japanese foundation model for general purpose tasks in the Japanese language, such as classification, extraction, question-answering, and for language translation between Japanese and English.
  • granite-20b-multilingual: A foundation model from the IBM Granite family that is trained for translation tasks in English, German, Spanish, French, and Portuguese.
  • codellama-34b-instruct: A programmatic code generation model from Code Llama that is based on Llama 2 from Meta. Use Code Llama to create prompts for generating code based on natural language inputs, and for completing and debugging code.
  • mixtral-8x7b-instruct-v01-q: A version of the Mixtral 8x7B Instruct foundation model from Mistral AI that is quanitzed by IBM. You can use this new model for general-purpose tasks, including classification, summarization, code generation, language translation, and more.

For more information, see Supported foundation models.

Deprecated foundation models
The following models are now deprecated and will be withdrawn in a future release:
  • granite-13b-chat-v1
  • granite-13b-instruction-v1
  • gpt-neox-20b
  • mpt-7b-instruct2
  • starcoder-15.5b

To avoid disruption when the withdrawal is completed, use a suitable alternative model as a replacement. For more information, see Foundation model lifecycle.

Deprecated features
Deprecated foundation models
The following models are now deprecated and will be withdrawn in a future release:
  • granite-13b-chat-v1
  • granite-13b-instruction-v1
  • gpt-neox-20b
  • mpt-7b-instruct2
  • starcoder-15.5b

To avoid disruption when the withdrawal is completed, use a suitable alternative model as a replacement. For more information, see Foundation model lifecycle

Version 1.1.3

A new version of watsonx.ai was released in February 2024.

Version 1.1.3 is installed on IBM Cloud Pak for Data 4.8.3 with the service operand version 8.3.0.

This release includes the following changes:
New features
New Japanese-language Llama 2 foundation model for general-purpose tasks in Japanese
The elyza-japanese-llama-2-7b-instruct foundation model provided by ELYZA, Inc. is available in watsonx.ai. The elyza-japanese-llama-2-7b-instruct model is a version of the Llama 2 model from Meta that was trained to understand and generate Japanese text.

You can use this new model for general-purpose tasks. This model works well for Japanese-language classification and extraction and for text translation between Japanese and English.

For more information, see Supported foundation models.

Deploy prompt templates for foundation models
You can now save a prompt template as a reusable asset and use it to generate output from a foundation model. Deploy the prompt template to a deployment space to test it or to retrieve the endpoint to use in an application. For more information, see Deploying a prompt template.

Version 1.1.1

A new version of watsonx.ai was released in December 2023.

Version 1.1.1 is installed on IBM Cloud Pak for Data 4.8.1 with the service operand version 8.1.0.

This release includes the following changes:
New features
Explore the risks of working with AI
You can now explore some of the risks of working with generative AI, foundation models, and machine learning models. Read about risks for privacy, fairness, explainability, value alignment, and other areas. For more information, see AI risk atlas.
Use variables to build reusable prompts
Add flexibility to your prompts with prompt variables. Prompt variables function as placeholders in the static text of your prompt input. You can replace this placeholder with text dynamically at inference time. You can save prompt variable names and default values in a prompt template asset to reuse yourself or share with collaborators in your project. For more information, see Building reusable prompts.
Prompt variables are used as placeholders in the prompt text for a foundation model in the Prompt Lab.
Apply AI guardrails
You can now enable AI guardrails in the Prompt Lab. AI guardrails remove potentially harmful text from the input to and output from foundation models. Harmful text can include hate speech, abusive language, and profanity. For more information, see Prompt Lab.
Introducing the Tuning Studio
Use the Tuning Studio to tailor the output that a foundation model returns to better meet your needs. When you tune a model, you influence the content that is included in the model’s output and how the content is formatted. For example, if you plan to add the step of inferencing a foundation model into a business workflow, then you need to:
  • Know what to expect from the foundation model.
  • Be able to retrieve the output in a reliable format.

With the Tuning Studio, you can apply the prompt tuning method to the Google flan-t5-xl-3b model. For more information, see Tuning Studio.

A tuning experiment is configured in the Tuning Studio.
Work with new foundation models in Prompt Lab
You can now use the following foundation models for inferencing from the Prompt Lab in watsonx.ai:
  • flan-t5-xl-3b
  • granite-13b-chat-v2
  • granite-13b-instruct-v2
  • llama-2-13b-chat
For more information about how to add models, see Supported foundation models.
Add sample prompts to notebooks
You can now add various sample prompts for specific models into your notebooks. To add a sample prompt, click the Code snippets icon (Code snippets icon), select Prompt Engineering, and browse the various categories to find a sample prompt. When you select a prompt, click Insert code to cell to insert the prompt into your notebook.

Version 1.1.0

A new version of watsonx.ai was released in November 2023.

Version 1.1.0 is installed on IBM Cloud Pak for Data 4.8.0 with the service operand version 8.0.0.

This release includes the following changes:

New features
Use the watsonx.ai service to transform your business with generative AI. With watsonx.ai, you can try, validate, and deploy a range of foundation models, including:
  • The IBM Granite series of foundation models. The Granite family includes decoder-only models that are instruction-tuned to be good at enterprise tasks, such as summarization, extraction, classification, and more.
  • Third-party models including Llama 2 Chat for dialogue and StarCoder for code generation.
  • Other popular open source foundation models that are available from Hugging Face.
You can interact with foundation models in two ways:
  • Programmatically by using the Python library
  • Directly by using the Prompt Lab, an intuitive tool for engineering prompts

    Screen capture of the Prompt lab user interface.