At its annual THINK conference, IBM announced several new updates to its watsonx platform one year after its introduction, as well as upcoming data and automation capabilities designed to make artificial intelligence (AI) more open, cost effective, and flexible for businesses. During his opening keynote, CEO Arvind Krishna will share the company’s plans to invest in, build and contribute to the open-source AI community as a core part of IBM’s strategy.
“We firmly believe in bringing open innovation to AI. We want to use the power of open source to do with AI what was successfully done with Linux and OpenShift,” said Krishna. “Open means choice. Open means more eyes on the code, more minds on the problems, and more hands on the solutions. For any technology to gain velocity and become ubiquitous, you’ve got to balance three things: competition, innovation, and safety. Open source is a great way to achieve all three.”
IBM released a family of Granite models into open source and launched InstructLab, a first-of-its-kind capability, in collaboration with Red Hat
Furthering its commitment to the open-source AI ecosystem, IBM has now open-sourced a family of its most advanced and performant language and code Granite models. By open sourcing these models, IBM is inviting clients, developers and global experts to build on these strengths and push the boundaries of what AI can achieve in enterprise environments.
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Available today under Apache 2.0 licenses on Hugging Face and GitHub, the open-source Granite models stand out for their development process, quality, transparency and efficiency. The Granite code models range from 3B to 34B parameters and come in both base and instruction-following model variants, which are suitable for tasks such as complex application modernization, code generation, fixing bugs, explaining and documenting code, maintaining repositories and more. The code models, trained on 116 programming languages, consistently reach state-of-the-art performance among open-source code LLMs across various code-related tasks:
- Testing by IBM found that the Granite Code models overall show very strong performance across all model sizes and benchmarks, often outperforming other open-source code models that are twice as large compared to Granite.
- Testing by IBM on benchmarks including HumanEvalPack, HumanEvalPlus, and reasoning benchmark GSM8K showed Granite code models have strong performances on code synthesis, fixing, explanation, editing, and translation across most major programming languages, including Python, JavaScript, Java, Go, C++, and Rust.
- The 20B parameter Granite base code model was used to train IBM watsonx Code Assistant (WCA) for specialized domains. It also powers watsonx Code Assistant for Z — a product designed to help enterprises transform monolithic COBOL applications into services optimized for IBM Z.
- The 20B parameter Granite base code model was tuned to generate SQL from natural language questions for the purpose of transforming structured data and extracting insights from that data. IBM demonstrated leadership in natural language to SQL, an important industry use case, as benchmarked by BIRD’s independent leaderboard, which ranks models according to Execution Accuracy (EX) and Valid Efficiency Score (VES).
IBM and Red Hat also recently launched InstructLab — a revolutionary approach to advancing true open-source innovation around LLMs.
The InstructLab methodology allows for continuous development of base models through constant incremental contributions, much like software development has worked in open source for decades. With InstructLab, developers can build models specific to their business domains or industries with their own data, so that they can see the direct value of AI rather than just the model providers seeing the value. IBM plans to harness these open-source contributions to bring additional value to its clients through integrations with watsonx.ai and the new Red Hat Enterprise Linux AI (RHEL AI) solution.
RHEL AI comprises an enterprise-ready version of the InstructLab, IBM’s open-source Granite models, and the world’s leading enterprise Linux platform to simplify AI deployment across hybrid infrastructure environments.
IBM Consulting is also launching a practice to help clients leverage InstructLab with their own proprietary data to train purpose-specific AI models that can be scaled to better fit the cost and performance requirements of an enterprise’s business needs. Read this blog to learn more about how IBM Consulting is helping enterprises adopt AI.
IBM unveils a new class of watsonx assistants
This new wave of AI innovation has the potential to unlock an estimated $4 trillion in annual economic benefits across industries.[v] However, IBM’s annual Global AI Adoption Index recently found that while 42% of enterprise-scale companies (> 1,000 employees) surveyed have implemented AI in their business, another 40% of those companies that are exploring or experimenting with AI have yet to deploy their models. For the companies stuck in the sandbox, 2024 is the year of overcoming barriers to entry such as the skills gap, data complexity and – perhaps most importantly – trust.
To address these challenges, IBM is announcing several upcoming updates and enhancements to its family of watsonx assistants, along with an upcoming capability in watsonx Orchestrate to help clients build their own AI Assistants across domains.
The new AI Assistants include watsonx Code Assistant for Enterprise Java Applications (planned availability in October 2024), watsonx Assistant for Z to transform how users interact with the system to quickly transfer knowledge and expertise (planned availability in June 2024), and an expansion of watsonx Code Assistant for Z Service with code explanation to help clients understand and document applications through natural language (planned availability in June 2024). Read more on watsonx Code Assistant for Enterprise Java Applications, watsonx Assistant for Z, and Watsonx Code Assistant for Z.
IBM is expanding its NVIDIA GPU offerings to now offer NVIDIA L40S and NVIDIA L4 Tensor Core GPUs, as well as support for Red Hat Enterprise Linux AI (RHEL AI) and OpenShift AI to help enterprises and developers address the needs of AI and other mission-critical workloads. Additionally, to help clients accelerate time to value for AI, IBM is using deployable architectures for watsonx to enable quick AI deployment while empowering enterprises with security and compliance capabilities to help them protect their data and manage compliance controls. Read this blog to learn more about IBM Cloud capabilities.
Additionally, IBM has announced several new and upcoming generative AI powered data products and capabilities to augment how organizations observe, govern, and optimize their increasingly robust and complex data for AI workloads. Learn more about the upcoming IBM Data Product Hub (planned availability in June 2024), Data Gate for watsonx (planned availability in June 2024), and a host of the latest and planned updates on watsonx.data. Read this blog to learn more about these data capabilities.
IBM previews new vision and capabilities for AI-powered automation
Hybrid cloud and AI are transforming how companies do business. The average enterprise today manages multiple cloud environments — public and private — and around 1,000 apps,[vi] each with multiple dependencies. They also deal with petabytes of data. With generative AI expected to drive up to 1 billion apps by 2028,[vii] automation is no longer an option – it is how businesses will save time, solve problems, and make decisions faster.
IBM is addressing these challenges by delivering a set of AI-powered automation capabilities that will allow CIOs to move from proactive management of their IT environments to AI-powered predictive automation. AI-powered automation will be an essential tool for driving the speed, performance, scalability, security, cost efficiency of an enterprise’s infrastructure.
Today, IBM’s portfolio of automation, networking, data, application, and infrastructure management products help businesses manage their increasingly complex IT environments. For technology business management, Apptio enables organizations to make informed, data-driven decisions about their investments by driving clarity on technology spend and how it drives business value — enabling organizations to quickly respond to changing market conditions. Clients can also combine Apptio with the power of Instana for automated observability and Turbonomic for performance optimization to help clients efficiently allocate resources and control IT spend through enhanced visibility and real-time insights, allowing them to focus more time on deploying and scaling AI to drive new innovative initiatives.
To complement these products, IBM recently announced its intent to acquire HashiCorp, which helps organizations automate multi-cloud and hybrid environments with Infrastructure Lifecycle Management and Security Lifecycle Management with products including Terraform, Vault and others. With HashiCorp, clients can easily move to and operate across multi-cloud and hybrid cloud environments.
Now, at THINK, IBM is continuing to advance its state-of-the-art in automation portfolio by previewing a new generative AI-powered tool called IBM Concert, which will be generally available in June 2024. IBM Concert will serve as the ‘nerve center’ of an enterprise’s technology and operations.
Powered by AI from watsonx, IBM Concert will provide generative AI-driven insights across clients’ portfolios of applications to identify, predict, and suggest fixes for problems. The new tool integrates into clients’ existing systems, using generative AI to connect with data from their cloud infrastructure, source repositories, CI/CD pipelines and other existing application management solutions to build out a detailed view of their connected applications.
By allowing clients to eliminate unnecessary tasks and accelerate others, Concert is designed to make teams more informed so they can be fast and responsive in addressing issues and solving problems before they happen. Concert will initially focus on helping application owners, SREs and IT leaders gain insights about, pre-empt and more quickly address issues around application risk and compliance management. Read this blog to learn more about IBM Concert.
IBM expands ecosystem access to watsonx, adds third-party models
IBM continues to foster a strong ecosystem of partners to offer clients choice and flexibility through bringing third-party models onto watsonx, enabling leading software companies to embed watsonx capabilities into their technologies, and offering IBM Consulting expertise for enterprise business transformation. IBM Consulting has rapidly expanded its global generative AI expertise, with more than 50,000 practitioners certified in IBM and strategic partner technologies. Our ecosystem of partners, large and small, are helping clients adopt and scale tailored AI across their businesses.
- AWS: IBM and AWS are partnering to bring together Amazon SageMaker and watsonx.governance on AWS. Available now, this product will equip Amazon SageMaker clients with advanced AI governance capabilities for their predictive machine learning and generative AI models. Clients can now govern, monitor, and manage their models across platforms, simplifying risk management and compliance processes for their AI operations.
- Adobe: IBM and Adobe are collaborating on hybrid cloud and AI, bringing Red Hat OpenShift and watsonx to Adobe Experience Platform and are exploring making watsonx.ai and Adobe Acrobat AI Assistant available on-prem and private cloud. IBM is also introducing a new consulting service to advance client adoption of Adobe Express. These capabilities are expected to become available in 2H24.
- Meta: IBM has announced the availability of Meta Llama 3 — the next generation of Meta’s open large language model — on watsonx to help enterprises innovate on their AI journeys. The addition of Llama 3 builds on IBM’s collaboration with Meta to advance open innovation for AI. The two companies launched the AI Alliance — a group of leading organizations across industry, startup, academia, research and government — late last year, and it has since grown to more than 100 members and collaborators.
- Microsoft: IBM is announcing that the watsonx AI and data platform is supported by IBM to run on Microsoft Azure and available to purchase through IBM and our business partner ecosystem as a customer-managed solution on Azure Red Hat OpenShift (ARO).
- Mistral: IBM is announcing its intent to create a new strategic partnership with Mistral AI to bring its latest commercial models to the watsonx platform, including the leading Mistral Large model, which the company plans to make available in 2Q24. IBM looks forward collaborating with Mistral AI on open innovation, building on both companies’ work in the open-source community.
- Palo Alto Networks: IBM has expanded its partnership with Palo Alto to jointly deliver AI-powered security offerings and several initiatives to improve security outcomes for clients. For more, read the full press release.
- Salesforce: IBM and Salesforce are exploring making the IBM Granite model series available later this year for use across the Salesforce Einstein 1 platform, with the aim to provide clients access to more models to enhance decision making for AI CRM use cases.
- SAP: IBM Consulting and SAP are also collaborating to find ways to help more customers accelerate their cloud journeys leveraging RISE with SAP so they can realize the transformative benefits of generative AI for business in the cloud. This work seeks to expand on IBM and SAP’s collaboration around embedding IBM Watson AI technology into SAP solutions. As part of this initiative with SAP, the IBM Granite Model Series is expected to be accessible for use across SAP’s portfolio of cloud solutions and applications – which is underpinned by the generative AI hub in SAP AI Core.
- SDAIA: IBM has launched the Saudi Data and Artificial Intelligence Authority (SDAIA) ‘ALLaM’ Arabic model on watsonx, adding new language capabilities to the platform, including the ability to understand multiple Arabic dialects.
SOURCE: IBM