IBM WatsonX, is a next-generation AI platform, designed to help companies build, train, and fine-tune foundation models, generative AI, and machine learning systems. Building on the incredible history of IBM Watson, this toolkit represents the next step in IBM’s AI journey.
For years now, IBM has stood as a leader in the world of artificial intelligence, not only is it one of the biggest AI vendors by market cap, but it’s also one of the oldest AI veterans. The company has been investing in AI development for more than 70 years.
WatsonX combines numerous tools, from a studio and data store, to an AI assistant and governance toolkit, all intended to help enhance access to AI development. Additionally, WatsonX’s capabilities are embedded into a range of IBM products for code development, AIOps, and security.
Here, we’ll tell you everything you need to know about IBM WatsonX, from where it came from to what it can do for your AI-focused enterprise.
What is IBM WatsonX?
IBM WatsonX is a cloud-based AI and data platform, designed by IBM. It combines a studio for AI development, with a data store, governance toolkit, and various other advanced features. The solution also supports multiple large language models, alongside IBM’s own Granite models.
According to IBM, the platform is intended for companies who want to build custom AI applications, accelerate responsible AI workflows, and manage their data sources in one convenient place. It was introduced in May 2023, at IBM’s annual Think conference, and builds on the existing heritage of IBM Watson, which first appeared in 2007.
With IBM WatsonX, companies can train, validate, and deploy generative AI models, manage their AI data systems, customize pre-existing AI assistants, and govern AI applications. We’ll discuss all of the core features and use cases of IBM WatsonX in a minute, but first, let’s take a look at its history.
The Evolution of IBM Watson: The Path to WatsonX
Most people will already be familiar with IBM Watson, the data analytics processor named after IBM CEO Thomas J. Watson. In the 1950s, IBM started experimenting with artificial intelligence and big data, exploring new ways to bring cutting-edge intelligence to businesses.
Watson was originally developed as part of IBM’s DeepQA research project. The team’s goal was to develop a natural language processing system that could interpret questions like humans, analyze huge volumes of data, and issue human-like responses to queries.
Although the first version of Watson was developed in 2007, the solution only burst into the spotlight four years later when it won a game of Jeopardy! on national television.
At that point, Watson started to spark curiosity among computer scientists, researchers, and consumers around machines that could “think.” Companies started deploying versions of Watson for their own use cases, and new AI developers began developing alternatives.
The IBM WatsonX Timeline
- 2007: IBM starts work on the Watson data analytics processor, eventually showcasing its capabilities in a nationally streamed Jeopardy! competition.
- 2013: IBM introduces the Watson Developer Cloud, allowing application providers and vendors to experiment with the system for their own use cases.
- 2014: The IBM Watson Discovery Advisor is introduced, offering organizations a way to search for connections in raw data rapidly.
- 2017: Teams of IBM NLP (Natural Language Processing) experts worldwide combine IBM’s NLP models into a unified stack, allowing for greater integration of AI into IBMs tools.
- 2020: IBM introduces the IBM Watson Assistant, a new intent detection model that combines machine, deep, and transfer learning techniques.
- 2023: IBM unveils the WatsonX platform, the latest development in the Watson ecosystem. This platform allows users to train, fine-tune, and distribute models with machine learning and generative AI capabilities.
What is IBM WatsonX? The Core Features
According to IBM, and its partners BUCK, the IBM WatsonX platform represents a new era in generative AI and machine learning development. It allows AI developers to leverage a huge range of LLMs, from IBM’s Granite series, to Meta’s LLaMA models, and other open-source systems. There are a few key components in the WatsonX portfolio, each with its own specific purpose.
IBM WatsonX.AI
The IBM WatsonX.ai platform is a next-gen AI studio where developers, scientists, and enterprises can build, run, and deploy AI applications and models. The studio forms part of the IBM WatsonX AI and data platform, combining generative AI capabilities (powered by foundation models), and traditional machine learning capabilities.
The studio includes a prompt lab, for experimenting with generative AI outputs, and IBM even collaborated with Hugging Face, to provide access to a range of different datasets for model fine-tuning. The available models come pre-trained, and designed to excel in various NLP applications, from question answering and text classification, to summarization and content generation.
The Tuning studio allows users to add their own data into the models, while the ModelOps environment empowers teams to manage machine learning models through all lifecycle stages. APIs, libraries, and SDKs are also available for users with varying levels of expertise.
IBM WatsonX.Data
WatsonX.Data is a data store built on open Lakehouse architecture, available both on-premises and in the cloud. It allows users to simplify complex data landscapes, and minimize data silos, combining all of the resources they need to train AI models. With this system, users can unify, curate, and prepare data for the applications of their choice and leverage a built-in analytics environment.
WatsonX.data also supports workload optimization across various storage tiers and query engines, which IBM says can reduce the costs of managing a data warehouse by 50%. The solution includes built-in governance tools, integrations with existing databases and systems, end-to-end analytics, and automation workflows.
IBM WatsonX.Governance
Intended to support companies struggling to manage data governance in the world of generative AI, WatsonX.Governance gives users more control over their ecosystems. With it, companies can govern generative AI and machine models from any vendor, including IBM WatsonX.Ai, Amazon Sagemaker, Google Vertex, and Bedrock.
The system allows companies to automate the evaluation and monitoring of models for accuracy, drift, health, bias, and overall quality. It also includes access to a range of risk and compliance capabilities, such as approval workflows, risk scorecards, and reports. IBM even offers users a wide range of documents they can use to boost their governance strategy. For instance, there’s end-to-end guidance on policies like the EU AI Act.
IBM WatsonX Assistant
The newest addition to the IBM WatsonX portfolio, WatsonX assistant is a next-generation conversational AI solution designed to help anyone create AI assistants. This pre-trained assistant provides direct access to a customizable assistant with generative AI and machine learning capabilities. With it, users with varying technical knowledge can design AI apps.
There’s a user-friendly drag-and-drop conversation builder and various pre-built templates to get you started. You get out-of-the-box large language models, NLP and NLU models, speech models, and context-gathering systems. There’s even retrieval-augmented generation built-in, to help ensure accurate, contextual and consistent conversations with bots.
Additionally, the IBM WatsonX assistant includes built-in security features, robust analytics and reporting tools, and support for integrations with various business applications.
Exploring IBM WatsonX: The Use Cases
IBM created WatsonX to be one of the most versatile solutions for AI development and management available to businesses today. The ecosystem is based on open technologies, giving users access to countless models for different use cases. Plus, every tool is highly customizable, allowing teams to create specific solutions for every department, from HR to customer service.
Just some of the use cases IBM outlines for WatsonX include:
Boost Employee Productivity with Knowledge Resources
With IBM WatsonX.ai and WatsonX.Data, companies can build an intuitive Q&A resource using their own proprietary data. You can connect the generative AI capabilities of WatsonX.ai with the retrieval generation technologies offered in the data tools to curate and share insights.
Create Content with IBM WatsonX
Content creation has emerged as one of the most popular use cases for generative AI. With IBM WatsonX, companies can use the WatsonX.ai studio to build models that can generate all kinds of content, such as social media posts, blogs, emails, sales campaigns and scripts. With the added governance features of WatsonX, you can also monitor models for accuracy and bias.
Build and Deploy Custom Chatbots
Building highly customized chatbots isn’t easy, even in today’s world of no-code and low-code solutions. IBM WatsonX Assistant offers easy access to a conversational AI application that is pre-trained and infused with large language models. The intuitive user interface makes it easy to create AI-powered chatbots and voice agents to support users across multiple touchpoints.
Transform Coding Workflows
Another great use case for IBM WatsonX is that it allows developers to code more efficiently with AI recommendations. Teams can access the dedicated WatsonX Code assistant, built on the WatsonX Assistant, to get code suggestions and reduce coding complexity. The system even derives insights from IBM’s leading Granite models.
Enhance Customer Experiences with IBM WatsonX
Aside from building bespoke chatbots and voice bots, companies can also use WatsonX for other CX applications. You can leverage data from various environments in one unified ecosystem to create comprehensive journey maps for customers. Companies can even use the WatsonX assistant to spot patterns in customer behaviors.
Unlock New Insights
Finally, companies can use the WatsonX.AI studio to develop AI models capable of analyzing huge data sets. These models can extract insights from customer interactions, documents, and security incidents in the WatsonX.Data Lakehouse. Plus, the generative AI models can suggest patterns, highlight anomalies, and help businesses make more informed decisions for growth.
The IBM WatsonX Ecosystem: Finishing Thoughts
For years, IBM Watson has stood as one of the most powerful innovations in the AI landscape. The IBM WatsonX ecosystem has marked a significant new step in the company’s AI journey.
This end-to-end platform gives businesses everything they need to train, develop, customize, and fine-tune their AI models. It also ensures companies can adapt their systems to their specific needs. They can add their own proprietary data and customize without compromising governance.
If IBM’s history in AI is anything to go by, we can expect constant evolution from WatsonX. If you’re investing in AI development, IBM is a vendor you should be watching.
