Today is a revolutionary moment for artificial intelligence (AI). After some impressive progress over the past decade, thanks largely to machine learning (ML) and deep learning techniques, the technology seems to have taken a sudden leap forward. Suddenly, everyone is talking about generative AI with excitement and trepidation. But few doubt that the progress we are seeing is significant, or a huge opportunity for companies to act quickly and strategically.
But why now? The answer is that generative AI leverages recent advances in underlying models. Unlike traditional ML, where each new use case requires designing and building a new model with specific data, the underlying model is trained on large amounts of unlabeled data and then adapted to new scenarios and business applications. can. The underlying model therefore has much lower data requirements for fine-tuning additional models, thus allowing massive AI scalability while amortizing the initial work of model building each time it is used. This improves ROI and significantly reduces time to market.
For decades, IBM has been at the forefront of AI breakthroughs, from the world’s first checkers play program to building AI supercomputers in the cloud. Today, we offer the most comprehensive portfolio of enterprise AI solutions. Our Watson suite has been deployed to over 100 million users across 20 industries and our dedicated team at IBM Research continues to push the frontiers of technology.
AI is already delivering business results. This strengthens our supply chain, protects critical corporate data from cyber attackers, and enables us to deliver a seamless experience to millions of customers across multiple industries every day. But the underlying models that power generative AI make these achievements look like preludes to major acts. And this is especially true when it comes to making technology as accessible as possible. At IBM, we believe it’s time to put the power of his AI in the hands of all sorts of “AI builders,” from data scientists to developers to everyday users who never wrote a single line of code. increase.
IBM’s next-generation AI platform, Watsonx, is designed to do just that. It provides self-service access to high-quality, trusted data, enables users to collaborate on a single platform, and allows them to build and refine both new generative AI-founded models and traditional machine learning systems. The early use cases we have identified range from digital labor, IT automation, application modernization, security to sustainability.
Watsonx has three components: watsonx.ai, watsonx.data, and watsonx.governance. Empower users with advanced machine learning, data management, and generative AI capabilities to train, validate, tune, and deploy AI systems with speed, trusted data, and governance across your business. It helps drive the entire data and AI lifecycle, from data preparation to model development, deployment, and monitoring. And we believe cutting-edge AI has the potential to magnify and accelerate the impact it can have on every business.
Train, validate, tune and deploy AI across your business with watsonx.ai
Watsonx.ai is the AI studio designed for today’s business and tomorrow. It combines the power of IBM Watson Studio, which enables data scientists, developers, and analysts to build, run, and deploy AI based on machine learning, with modern generative AI capabilities that harness the power of underlying models. It’s a thing.
At the heart of watsonx is the principle of trust. As AI becomes more prevalent, companies need to be confident that their models won’t “hallucinate” facts or use inappropriate language when interacting with customers. Our approach is to establish the right level of rigor, processes, technology and tools to nimbly adapt to the evolving legal and regulatory landscape. Watsonx.ai gives users access to her unique IBM foundation models that are high quality and pre-trained for enterprises. They are domain-specific and built with a strict focus on data acquisition, provenance and quality. Additionally, IBM makes a wide range of open source models available through his watsonx.ai.
Trust is part of the equation. The second is access. For AI to be truly transformative, its benefits must be accessible to as many people as possible. That’s why we designed watsonx.ai with user-friendliness in mind. Watsonx.ai is not just for data his scientists and developers. Business users can also access it through an easy-to-use interface that responds to natural language prompts for various tasks.
The Prompted Lab allows users to experiment with the model by entering prompts for a wide range of tasks, such as summarizing transcripts or performing sentiment analysis on documents. Depending on the task, watsonx.ai allows the user to select a foundation model from a dropdown her menu. Developers can build workflows directly in her ModelOps environment using APIs, SDKs and libraries to manage machine learning models from development to deployment. Advanced users can use Tuning Studio to customize models with labeled data and create new trusted models from pre-trained models.
However, at IBM we believe that language is only the beginning of the underlying model. We also build models trained on different types of business data, including code, time series data, tabular data, geospatial data, and IT event data. Initial foundational models, available in beta to select clients, include foundational models for language (also known as LLM), geospatial data, molecules, and code.
Scale and manage AI with watsonx.data
For AI to deliver truly impactful results across your business, it must be integrated into existing workflows and systems to automate key processes across areas such as customer service, supply chain, and cybersecurity. Enterprises need to be able to easily and securely move AI workloads. In today’s world, this can mean not only the entire cloud, but also the entire modern and legacy software and hardware systems.
watsonx.data enables businesses to quickly connect to data, gain trusted insights, and reduce data warehousing costs. Built on an open lakehouse architecture, data stores run both on-premises and in multicloud environments.
Optimized for all data, analytics, and AI workloads, watsonx.data combines the flexibility of a data lake with the performance of a data warehouse, empowering enterprises to harness data analytics and AI wherever their data lives. Help you expand. By empowering this solution, organizations can reduce their data warehouse costs by up to 50% through workload optimization.[1]
Users can access data through a single point of entry using a shared metadata layer across cloud and on-premises environments. Watsonx.data also has built-in governance, security, and automation so data scientists and developers can use governed enterprise data to train and tune underlying models, while ensuring enterprise compliance across the data ecosystem. and security can also be addressed.
watsonx.data enables enterprises to build trusted AI models, take full advantage of interoperability with IBM and third-party services, and automate the AI lifecycle on multi-cloud architectures. increase.
Build trust in your AI lifecycle with watsonx.governance
Trust is central to AI models, both during their construction and tuning, and after they are embedded within products and workflows.
In fact, the more AI is embedded into everyday workflows, the greater the need for proactive governance to drive responsible and ethical decision-making across the business.
Watsonx.governance helps build the necessary guardrails around AI tools and AI use. It is an automated data and model lifecycle solution for creating policies, assigning decision-making authority, and holding organizations accountable for risk and investment decisions.
Watsonx.governance employs software automation to reduce risk and meet regulatory requirements without the undue cost of switching data science platforms, even for models developed using third-party tools. Strengthen the client’s ability to meet requirements and address ethical concerns. It enables companies to automate and integrate multiple tools, applications and platforms while documenting the origin of datasets, models, associated metadata and pipelines.
watsonx.governance helps organizations meet ethical standards and proactively manage risk and reputation by providing mechanisms to protect customer privacy and proactively detect model bias and drift. We support. Ensure compliance by translating regulations into policies and business processes, while maintaining stakeholder visibility and collaboration with customizable reports and dashboards.
Bring AI to your business with IBM today
IBM has implemented the watsonx.ai foundational model across all of its major software solutions and services, embedding it in its core AI and automation products and consulting practice. These include:
- Watson Assistant and Watson Orchestrate: Core digital labor products are enhanced with an NLP foundation model to improve employee productivity and customer service experience.
- Watson Code Assistant: Generation AI allows developers to automatically generate code with simple commands like “deploy web application stack” or “install Nodejs dependencies”.
- Watson AIOps Insights: AI operations (AIOps) capabilities are enhanced with underlying models for code and language processing, providing greater visibility into performance data and dependencies across IT environments, enabling IT operations (ITOps) managers and site reliability engineers (SRE) to help resolve incidents. A more convenient and cost-effective way.
- Environmental Intelligence Suite: IBM EIS Builder Edition will be available as-a-Service this year through the IBM Environmental Intelligence Suite (EIS). It leverages a geospatial foundation model, enabling organizations to create customized solutions to address and mitigate environmental risks. Based on your own goals and needs.
Put trust at the core of your AI strategy
The possibilities we started imagining are quickly becoming commonplace, as these new AI models will dramatically affect the way people interact with technology, changing not only how they do business, but how they think about it. will be
But to reach its full potential, AI must be built on a foundation of trust and transparency, and made as widely available as possible so that everyone can benefit. must be IBM believes trustworthy AI has five pillars: explainability, fairness, robustness, transparency and privacy.
IBM designed watsonx to adhere to these core principles of trust while making it as accessible as possible. A trustworthy AI future that increases productivity and powers innovation is not only possible, it’s already here. These are exciting times. Let’s work together to make the world work better with AI.
Check out what’s new in Watsonx
All statements regarding IBM’s future direction and intent are subject to change or withdrawal without notice. Represents goals and objectives only.
[1]When comparing the 2023 public list price normalized to VPC hours of watsonx.data against several leading cloud data warehouse vendors. Savings may vary by configuration, workload and vendor.
