Get Hands-on Experience with Generative AI - watsonx AI Prompt Lab

IBM Technology
8 Dec 202305:30

TLDRWatsonx.ai offers a comprehensive AI platform for businesses to build, train, and deploy AI models tailored to specific needs. The Prompt Lab allows users to create or select sample prompts for tasks like summarization and insight extraction. It features a variety of pre-trained models, including IBM's Granite series with intellectual property protections. Users can experiment with prompts, add guardrails, and share them across organizations. Watsonx.ai also includes a Tuning Studio for model fine-tuning, supports traditional machine learning workflows, and offers a synthetic data generator to address data gaps. It's part of a broader AI and data platform with a focus on responsible AI governance.

Takeaways

  • 🚀 Watsonx.ai is an enterprise AI studio that integrates generative AI and machine learning to build AI models tailored to specific business needs.
  • 📝 In the Prompt Lab, users can create custom prompts or choose from sample prompts for common AI tasks like summarization and sentiment analysis.
  • 🧠 The platform offers a variety of pre-trained foundation models, including third-party and IBM-developed models like Llama 2 and the Granite series.
  • 🛡️ IBM provides contractual intellectual property indemnity protections for its own Granite series AI models, aiding businesses in building and scaling generative AI.
  • 🔧 Users can experiment with different models, adjust parameters, and add AI guardrails to prevent harmful or abusive language.
  • 🔄 Prompt engineering is an iterative process, allowing for continuous adjustment, testing, and optimization of the model's performance.
  • 🔗 Once an effective prompt is created, it can be easily shared across an organization and integrated with developer tools via API commands.
  • 📊 The Tuning Studio allows enterprises to use their proprietary data to fine-tune AI models for specific tasks, enhancing their applicability.
  • 🤖 Watsonx.ai supports both generative AI and traditional machine learning workflows, fostering collaboration between developers and data scientists.
  • 🔮 The platform includes AutoAI for creating machine learning models in a no-code environment, identifying the most promising models through a leaderboard.
  • 📈 For situations with insufficient data, Watsonx.ai offers a synthetic data generator to fill data gaps, creating robust synthetic datasets that reflect the original training data.
  • 🌐 Watsonx.ai is part of a broader AI and data platform with components like a studio for AI development, a data store, and an AI governance toolkit for responsible AI practices.

Q & A

  • What is watsonx.ai?

    -Watsonx.ai is an enterprise studio that puts generative AI and traditional machine learning at your fingertips, empowering users to build, train, tune, and deploy AI models targeted for specific business needs.

  • What is the Prompt Lab in watsonx.ai?

    -The Prompt Lab is a feature in watsonx.ai where users can build prompts from scratch or select sample prompts for common generative AI tasks, such as summarization or sentiment analysis.

  • What are some tasks you can perform in the Prompt Lab?

    -Tasks include summarizing long-form content, extracting insights, classifying data, and determining sentiments from customer reviews.

  • What are the foundation models available in watsonx.ai?

    -Watsonx.ai features foundation models of different sizes and architectures, including third-party open models like Llama 2 and IBM-developed models like the Granite series.

  • What is the Granite series in watsonx.ai?

    -The Granite series are IBM-developed models that help businesses build and scale generative AI, offering certain contractual intellectual property indemnity protections.

  • How can you create a question-answer application in watsonx.ai?

    -You can create a question-answer application by selecting the appropriate sample prompt in the Prompt Lab, providing natural language instructions and examples, and adding AI guardrails to prevent harmful content.

  • What is the Tuning Studio in watsonx.ai?

    -The Tuning Studio allows enterprises to harness proprietary data by selecting a foundation model, tuning method, and task, then uploading a dataset to fine-tune the model.

  • How can watsonx.ai be used for traditional machine learning workflows?

    -Watsonx.ai supports building traditional machine learning workflows and models, facilitating collaboration between application developers and data scientists in a single workspace.

  • What is AutoAI in watsonx.ai?

    -AutoAI is a feature in watsonx.ai that allows users to create machine learning models from scratch in a no-code environment, automatically identifying the most promising pipelines and models.

  • How can watsonx.ai generate synthetic data?

    -Watsonx.ai's synthetic data generator can create synthetic datasets by uploading existing data, anonymizing columns, and specifying the number of rows needed, up to 2.1 billion, reflecting the original data's distributions and relationships.

Outlines

00:00

🤖 Introduction to Watsonx.ai and Prompt Lab

Watsonx.ai is an enterprise platform that integrates generative AI and machine learning, enabling businesses to construct, train, and deploy AI models tailored to specific needs. The Prompt Lab within Watsonx.ai allows users to either create a prompt from scratch or select from a variety of sample prompts designed for tasks such as summarization and sentiment analysis. The platform offers a range of pre-trained foundation models, including third-party and IBM's proprietary Granite series, which come with intellectual property indemnity protections. Users can experiment with different models, adjust parameters, and incorporate AI guardrails to prevent harmful language. The iterative prompt engineering process allows for testing and refining until the optimal prompt is achieved, which can then be shared and utilized across the organization or further tested in a Jupyter Notebook.

05:04

🛠️ Tuning Studio and Traditional Machine Learning Workflows

Watsonx.ai also features a Tuning Studio that leverages proprietary data to fine-tune AI models for specific tasks. Users can select a foundation model, tuning method, and task, then upload a dataset to begin the tuning process. Once tuned, the model can be utilized in the Prompt Lab. Additionally, the platform supports the creation of traditional machine learning workflows, fostering collaboration between developers and data scientists. An example scenario involves creating a predictive model for customer insurance claims by connecting to a repository of historical data. AutoAI facilitates the creation of machine learning models in a no-code environment, allowing for data input, model type selection, parameter adjustment, and option specification. Experiments can be run, and the most promising models can be saved as Python code or deployed for inferencing. Watsonx.ai addresses data shortages with a synthetic data generator tool, which can create robust synthetic datasets that reflect the original training data, learning from existing data and anonymizing as needed.

🌐 Watsonx AI and Data Platform Overview

Lastly, Watsonx.ai is part of a broader AI and data platform that includes three core components: a studio for developing new foundation models, generative AI, and machine learning; a data store built on an open data lakehouse architecture; and an AI governance toolkit designed to promote responsible, transparent, and explainable AI. The platform is complemented by several AI assistants aimed at scaling and accelerating the integration of AI within a business. For those interested in exploring Watsonx.ai, a free trial is available, and further information can be obtained by contacting an IBM representative.

Mindmap

Keywords

💡Generative AI

Generative AI refers to artificial intelligence systems that can create new content, such as text, images, or music, that is similar to the content they were trained on. In the context of the video, generative AI is central to Watsonx.ai's offerings, enabling users to build AI models that can perform tasks like summarization and insight extraction. For example, the script mentions using generative AI to condense long-form content like an earnings call into short descriptions.

💡Watsonx.ai

Watsonx.ai is an enterprise studio that combines generative AI with traditional machine learning tools. It is designed to empower businesses to build, train, and deploy AI models tailored to their specific needs. The platform is highlighted in the script as a place where users can select from a variety of pre-trained models and experiment with different parameters to achieve the desired AI outcomes.

💡Foundation Models

Foundation models in the script refer to pre-trained AI models that serve as a starting point for specific tasks. These models are pre-equipped with the ability to handle certain types of data and tasks, such as summarization or sentiment analysis. The script mentions that Watsonx.ai offers a curated list of foundation models of different sizes and architectures, including third-party and IBM-developed models.

💡Granite Series

The Granite series is a specific set of AI models developed by IBM, mentioned in the script as part of Watsonx.ai's offerings. These models are designed to help businesses build and scale their generative AI capabilities. The script also notes that IBM offers contractual intellectual property indemnity protections for these models, indicating a level of commitment to their reliability and safety.

💡Prompt Engineering

Prompt engineering is the process of designing and refining the input prompts used to guide AI models in performing specific tasks. In the script, it is described as an iterative process where users can adjust their prompts, test different models, and experiment with various parameters to optimize the AI's performance for their use case, such as creating a question-answer application for financial statements.

💡AI Guardrails

AI guardrails are mechanisms put in place to prevent AI models from generating or receiving harmful, abusive, or profane language. The script mentions the ability to add these guardrails to the AI models being developed on Watsonx.ai, ensuring that the content produced is safe and appropriate for the intended audience.

💡Tuning Studio

The Tuning Studio is a feature of Watsonx.ai that allows enterprises to fine-tune AI models using their proprietary data. The script describes the process of selecting a foundation model, tuning method, and task, then uploading a dataset to customize the AI model's performance. This is part of Watsonx.ai's approach to harnessing enterprise data for AI model optimization.

💡Traditional Machine Learning

Traditional machine learning refers to the process of training AI models using labeled data and statistical techniques. In the script, it is contrasted with generative AI and is shown as another capability of Watsonx.ai. The platform supports building machine learning workflows and models, which is particularly useful for tasks like forecasting customer insurance claims.

💡AutoAI

AutoAI is a no-code environment within Watsonx.ai that enables the creation of machine learning models from scratch. The script describes how users can pull in training data, set model types, adjust parameters, and run experiments to identify the most promising models. The process is designed to be accessible to users without requiring coding expertise.

💡Synthetic Data Generator

The synthetic data generator is a tool within Watsonx.ai that addresses data gaps by creating artificial data that reflects the distributions and relationships of the original training data. The script explains that users can upload existing data, anonymize columns, and specify the amount of synthetic data to generate, which can be particularly useful when there is not enough data to train a machine learning model effectively.

💡AI Governance Toolkit

The AI governance toolkit is a component of the Watsonx AI and data platform that facilitates responsible, transparent, and explainable AI. The script mentions this toolkit as part of the core components of Watsonx.ai, which includes the studio for AI and machine learning, a data store, and the governance toolkit itself. It is designed to accelerate the ethical deployment of AI within businesses.

Highlights

Watsonx.ai is an enterprise studio that integrates generative AI and machine learning for specific business needs.

The Prompt Lab allows building prompts from scratch or selecting from sample prompts for common AI tasks.

Sample prompts are based on pre-trained foundation models suitable for tasks like summarization and sentiment analysis.

Watsonx.ai offers a variety of foundation models, including third-party and IBM's Granite series models.

Granite series models come with contractual intellectual property indemnity protections.

Users can experiment with different models and adjust their parameters for tasks such as question-answer applications.

Prompt engineering involves an iterative process of adjusting, testing, and refining prompts.

Effective prompts can be easily shared across an organization and integrated with developer code.

Watsonx.ai includes a Tuning Studio for harnessing proprietary data with selected models and tuning methods.

Traditional machine learning workflows are supported, fostering collaboration between developers and data scientists.

AutoAI enables the creation of machine learning models in a no-code environment with a user-friendly interface.

The synthetic data generator tool addresses data gaps by creating robust synthetic datasets.

Watsonx.ai is part of a larger AI and data platform with core components and AI assistants for scaling AI impact.

The platform includes a studio for AI models, a data store built on an open data lakehouse architecture, and an AI governance toolkit.

The AI governance toolkit accelerates the development of responsible, transparent, and explainable AI.

Watsonx.ai supports building and deploying AI models with ease, enhancing business operations with advanced technology.

Users can start a free trial or contact an IBM representative to learn more about Watsonx.ai.

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