IBM and AI

Everyone is talking about Artificial Intelligence (AI) these days. Either it’s going to take over the world or, apparently, it thinks the bald head of a football referee is the ball and follows that instead! Clearly, we have a few years to go before we become extras in a Terminator movie.

In the meantime, there are lots of interesting AI developments being announced. IBM has announced IBM watsonx at its annual Think conference. Watson is a new AI and data platform enabling enterprises to scale and accelerate the impact of the most advanced AI with trusted data. It will help them to train, tune, and deploy AI models, including foundation models and machine learning capabilities, across their organization with trusted data, speed, and governance – all in one place and to run across any cloud environment.

So, what do you get with watsonx? There’s an AI development studio with access to IBM-curated and trained foundation models and open-source models, access to a data store to enable the gathering and cleansing of training and tuning data, and a toolkit for governance of AI that will ensure a business’s AI models are compliant with regulations.

IBM Chairman and CEO, Arvind Krishna, said, “Foundation models make deploying AI significantly more scalable, affordable, and efficient. With IBM watsonx, clients can quickly train and deploy custom AI capabilities across their entire business, all while retaining full control of their data.”

IBM watsonx consists of three product sets:

• IBM watsonx.ai is an enterprise studio for AI builders to train, test, tune, and deploy both traditional machine learning and new generative AI capabilities powered by foundation models through an open and intuitive user interface.
• IBM watsonx.data is a data store built on open lakehouse architecture that is optimized for governed data and AI workloads, supported by querying, governance, and open data formats to access and share data.
• IBM watsonx.governance is an AI governance toolkit to enable trusted AI workflows.

The AI studio provides a range of foundation models, training and tuning tools, and infrastructure that facilitate the entire data and AI lifecycle, from data preparation to model development, deployment, and monitoring. The studio also includes a foundation model library giving users access to IBM curated and trained foundation models. Examples of model categories include:

• fm.code – models built to automatically generate code for developers through a natural-language interface to automate many IT tasks.
• fm.NLP – a collection of large language models (LLMs) for specific or industry-specific domains that utilize curated data where bias can be mitigated more easily and can be quickly customized using client data.
• fm.geospatial – model built on climate and remote sensing data to help organizations understand and plan for changes in natural disaster patterns, biodiversity, land use, and other geophysical processes that could impact their businesses.

The watsonx.ai studio will build on Hugging Face's open-source libraries and offer thousands of Hugging Face open models and datasets.

IBM watsonx.data can manage workloads both on-premise and across multi-cloud environments, reducing data warehouse costs by up to 50 percent. Watsonx.data will allow users to access their data through a single point of entry while applying multiple query engines to uncover valuable insights.

IBM watsonx.governance operationalizes governance to help mitigate the risk, time, and cost associated with manual processes and provides the documentation necessary to drive transparent and explainable outcomes. It also provides the mechanisms to protect customer privacy, proactively detect model bias and drift, and help organizations meet their ethics standards.

IBM also plans to infuse watsonx.ai foundation models throughout all its major software products going forward, for example:

• Watson Code Assistant uses generative AI to allow developers to generate code with a straightforward English language command.
• AIOps Insights provides greater visibility into performance across IT environments, helping (ITOps and SREs resolve incidents in a more expedient and cost-efficient way.
• Watson Assistant and Watson Orchestrate will be combined with an NLP foundation model to enable enhanced employee productivity and customer-service experiences.
• Environmental Intelligence Suite (EIS) Builder Edition can use the geospatial foundation model, allowing organizations to create tailored solutions that address and mitigate environmental risks based on their unique goals and needs.

Also announced was a GPU-as-a-service infrastructure offering, which is designed to support AI-intensive workloads, an AI-powered dashboard to measure, track, manage, and help report on cloud carbon emissions, and a new practice for watsonx and generative AI from IBM Consulting that will support client deployment of AI.

Elsewhere, Google has made its AI available. Go to bard.google.com and register with an existing Google account. Google Bard runs on Google’s large language model, Language Model for Dialogue Applications. Google has announced plans to integrate it with Google Search. And currently, it only comes in US English.

Microsoft has AI built into its Azure product and Copilot coming to help with its Office suite. It’s also using OpenAI’s GPT-4 with its Bing search engine. Open AI was the first to really hit the headlines with its ChatGPT product that most people have now had a play with. And there are others out there.

Interesting times!