Unveiling the Future of AI: IBM's Unwavering Commitment to Innovation and Collaboration

Enterprises are grappling with AI's transformative power, a technology poised to automate and elevate both creative and analytical tasks. Despite its early stages, AI adoption holds immense growth potential. Recognizing this, IBM took center stage at Think 2024, showcasing its unwavering commitment to AI innovation.

IBM's leadership in driving enterprise AI is evident through its three key pillars: open-source initiatives, which democratize AI and make it more accessible; leveraging the combined expertise of its consulting arm and ecosystem partners, which ensures the highest quality of AI solutions; and significant updates to the watsonx platform, which enhance the performance and capabilities of AI. These updates are about technological advancements and making AI more accessible and impactful for businesses worldwide. By prioritizing openness, affordability, and flexibility, IBM is breaking down barriers and paving the way for widespread AI adoption.

Open-Source Innovations and InstructLab

AI, a field deeply rooted in open collaboration, has been shaped by a tradition that dates back to its inception. Consider Alan Turing's groundbreaking 1950s paper, 'Computing Machinery and Intelligence,' which introduced the world to AI. This vision turned into reality thanks to the open sharing of work by countless researchers worldwide, laying the foundation for the AI we know today. IBM, a torchbearer of this tradition, continues to place open-source innovation at the core of its latest AI initiatives, inviting users and businesses to be part of this rich and impactful tradition.

IBM has unveiled a family of Granite models, a significant addition to the open-source AI ecosystem. These models, with parameter counts ranging from 3 billion to 34 billion, have been trained in 116 programming languages. They are available in base and instruction-following variants, offering a wide range of applications from complex modernization to bug fixing. These models represent some of IBM's most advanced language and code capabilities and are available under Apache 2.0 licenses on collaborative platforms such as HuggingFace and GitHub. This exciting development opens up a world of possibilities.

IBM's approach to AI development sets it apart from other major companies. While many have chosen to release pre-trained models, withholding the datasets used for training, IBM has taken a different path. It has offered open-source models, democratizing AI development and inviting clients, developers, and experts worldwide to explore new AI advancements in enterprise settings. This unique strategy, coupled with IBM's commitment to quality and efficiency, ensures that these models consistently generate high-quality code superior to many alternative large language models (LLMs) and excel at various code-related tasks, surpassing larger open-source counterparts.

“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,” IBM CEO Arvind Krishna at IBM’s Annual Think Conference.

To further its commitment to open-source AI, IBM has announced InstructLab, an open-source project designed to address challenges in fine-tuning LLMs for specialized tasks. This project focuses on scalability by efficiently handling large volumes of data for model training and specialization by tailoring models to specific industry needs.

InstructLab’s approach to enhancing LLMs begins with curating diverse training data representing various domains of knowledge and skills. Following this, advanced fine-tuning techniques are applied to the curated data, and models are continuously updated based on real-world feedback and new data inputs. This curated data is the foundation for enhancing LLMs by providing a rich and varied dataset covering multiple domains. This targeted enhancement makes models more proficient in specific areas, such as natural language processing for healthcare or financial data analysis.

IBM aims to enhance client value by integrating InstructLab with watsonx.ai and Red Hat Enterprise Linux AI (RHEL AI) solution. This integration will streamline AI deployment in hybrid cloud settings. These combined integrations give enterprises a robust and adaptable approach to adopting AI technologies. RHEL AI includes an enterprise-ready version of InstructLab, IBM’s open-source Granite models, and a Linux platform designed to simplify AI deployment across hybrid infrastructures.

Major watsonx Innovations

In addition to open-source advancements, IBM is pushing the boundaries of its AI and data platform, watsonx, by introducing new watsonx AI assistants. These assistants aim to address the skills gap and data complexity hindering many enterprises' AI deployment. Some of the key innovations include:

• watsonx Code Assistant for Enterprise Java Applications (expected launch: Oct’24): Specifically designed to enhance developers' productivity working with Java applications by aiding in the generation, explanation, and documentation of code. Its capability to do so helps reduce the time and effort developers spend on coding, ultimately accelerating the development process and improving code quality.

• watsonx Assistant for Z (expected launch: Jun’24): For mainframe environments, IBM has introduced watsonx Assistant for Z, a generative AI (Gen AI) assistant that enhances user interaction with IBM Z systems. The AI assistant identifies everyday user tasks and translates them into automated processes. Users can import existing automations (Ansible, JCL, REXX) as skills, accessible through a context-aware chat interface. This leverages watsonx Orchestrate's automation framework to boost mainframe productivity and efficiency

• Expansion of watsonx Code Assistant for Z Service with Code Explanation (expected launch: Jun’24): This update helps maintain and modernize legacy COBOL applications. It uses Gen AI to provide natural language explanations of COBOL code, simplifying understanding and documentation. Automating code explanations bridges knowledge gaps using AI to break complex code into understandable language. This empowers developers to grasp the codebase logic faster, fostering collaboration and accelerating development

• IBM Concert (expected launch: Jun'24): IBM introduced' IBM Concert' on the automation portfolio front, a central tool for managing technology infrastructure powered by watsonx AI capabilities. Concert provides actionable insights across application portfolios, forecasting issues and proposing solutions. It integrates seamlessly with existing systems, offering a comprehensive view of connected applications. This allows teams to streamline operations and make data-driven decisions.

These advancements are all part of IBM's broader strategy to integrate AI seamlessly into business processes to unlock new levels of productivity and efficiency.

Expanding the Open-Source Ecosystem

At the forefront of enterprise AI, IBM isn't going it alone. To empower businesses with unmatched AI flexibility, IBM is pioneering a collaborative ecosystem approach. By co-creating AI solutions alongside a diverse range of partners, IBM dismantles silos and fosters an open ecosystem. This translates to more choices and flexibility for businesses, and the collaborative spirit translates into several key benefits for businesses. For example:

Unmatched Flexibility: Through partnerships like the one with Adobe, IBM is enabling businesses to leverage the power of watsonx.ai, Red Hat OpenShift, and Adobe Acrobat AI Assistant, even within on-premise and private cloud environments. This shatters limitations and caters to businesses with specific infrastructure needs.

Expanded AI Toolkit: The partnership with Meta takes this a step further. By integrating Meta's Llama 3 model into watsonx, IBM is expanding the AI toolbox available to enterprises. This broader range of models empowers businesses to tackle their unique AI challenges more efficiently.

Supercharged Decision-Making: CRM is a crucial area for data-driven insights. The collaboration with Salesforce exemplifies how IBM's ecosystem approach enhances this. By embedding IBM Granite models into the Salesforce Einstein platform, businesses gain access to a broader range of models, enabling them to make more informed and accurate decisions within their CRM operations.

Faster, Secure Deployments: The partnership with NVIDIA tackles a crucial aspect of AI implementation – speed and security. This collaboration grants businesses access to cutting-edge NVIDIA L40S and L4 Tensor Core GPUs, significantly accelerating deployment. Furthermore, supporting RHEL AI and OpenShift AI ensures robust security protocols, data protection, and regulatory compliance.

Embracing Partnerships for AI Growth

IBM's legacy was once defined by closed systems and a one-size-fits-all partner program ("PartnerWorld"). While it treated all partners equally, it missed opportunities for deeper collaboration. Recognizing this, IBM launched Partner Plus a year ago, a program designed for flexibility and catering to diverse partner needs.

This shift towards openness and collaboration marks a new chapter for IBM. It signals their recognition of partnerships' immense value to the AI landscape. CEO Arvind Krishna's ambitious goal of exceeding 50% of revenue from partners exemplifies this strategic pivot. This creates a win-win situation, unlocking new possibilities for both IBM and its partner ecosystem.

IBM recently previewed a dedicated Managed Service Providers (MSP) program to help achieve this ambitious goal. This program offers solutions specifically designed to empower MSPs, starting with including automation tools. Kate Woolley, General Manager of IBM's ecosystem, stated, "We see a unique opportunity for MSPs in the market. We are doubling down on our commitment to the MSP community. We're launching a new MSP program to further streamline collaboration in the coming months."

IBM's metamorphosis from a solitary player to a collaborative leader in AI is a testament to the transformative power of partnerships. By leveraging this ecosystem, they're unlocking the full potential of AI for businesses worldwide. For example, leveraging the success of the IBM-AWS partnership, IBM is significantly expanding its software availability in the AWS Marketplace to 92 countries. This strategic move empowers IBM sellers to reach a wider audience and convert AWS's vast customer base into IBM users. With access to over 330,000 potential clients, IBM gains a significant advantage in its quest for new customers and partners.

Unlocking the Potential of AI with IBM Consulting

The growing importance of AI in innovation brings new challenges. Businesses struggle to customize models for their specific needs, integrate them seamlessly, and ensure effective governance. IBM Consulting bridges this gap by connecting cutting-edge technology with successful implementation.

IBM Consulting leverages hybrid cloud and AI technologies to help accelerate clients’ business transformation through its extensive network of consultants and partners. With expertise in strategy, design, technology, and operations across various industries, it assists clients in modernizing and securing their most complex systems.

Among its most notable offerings is IBM Consulting Advantage, an advanced AI platform that equips IBM's 160,000 consultants with a portfolio of AI assistants, assets, and methods for accelerated value creation, enhanced productivity, and consistency. The platform utilizes watsonx AI and a range of IBM Granite and third-party models to offer tailored AI assistants for different consulting roles, thereby helping streamline processes and yield superior outcomes. For example, specific assistants help tackle tasks from everyday functions like creating executive summaries and presentations to designer-focused persona generation to software development lifecycle tasks that generate stories, code, and test scripts. The platform's security features also safeguard sensitive data and allow real-time bias checking of assistant outputs, enhancing its appeal.

Furthermore, IBM Consulting Advantage is leveraged via the IBM Garage engagement model to create an even more powerful solution. This integration facilitates a collaborative approach to innovation using tools like IBM Garage Experience, a foundational AI asset on IBM Consulting Advantage. IBM Garage Experience is a digital workflow and value orchestration asset that allows for faster realization of client objectives by transparently assigning and tracking the value of a program and its components from business initiative down to the related process change or new product feature. It serves as the entry point, guiding decisions on why and how to develop specific models or deploy specific assets, focusing on ROI and co-creation with clients. This engagement model ensures that projects align with client objectives and generate tangible value.

Focus on AI Governance

Like Prometheus, who gifted fire to humanity, unleashing warmth, and destruction, AI presents us with a powerful tool. While its potential for progress is undeniable, the ethical and regulatory considerations surrounding its development are equally vast. Recognizing this critical need for responsible AI implementation, IBM has placed governance at the forefront of its AI strategy. Last year, IBM introduced watsonx.governance, a robust platform crafted to infuse transparency, accountability, and ethical oversight across the model lifecycle for both generative AI (Gen AI) and Machine Learning (ML) workflows.

This time, IBM unveiled another significant step forward: integrating watsonx.governance with Amazon SageMaker. Available in June’24, this integration empowers clients to achieve several key benefits. Streamlined workflows and faster time-to-market for AI initiatives are just the beginning. Clients can also manage AI projects across diverse IT landscapes, configure risk assessments, and model approval workflows tailored to their needs. Notably, both watsonx.governance and SageMaker will maintain a comprehensive audit trail, ensuring complete transparency.

By seamlessly combining the power of these two platforms, IBM is addressing governance from the very foundation of AI projects. This paves the way for responsible and secure development, ensuring that AI delivers on its immense potential.

What sets IBM watsonx.governance apart is its ability to manage both in-house and externally developed AI models, including those from open-source and third-party vendors. Plus, it offers the flexibility to work across different cloud environments, whether private, public, or a combination.

Final Techaisle Take

My first interaction with IBM Executives as an analyst was in 1994 in Tokyo. That initial meeting ignited a series of monthly gatherings in Hong Kong. IBM had a sense of urgency, passion, and strong ambition to lead the IT industry. Fast forward to today, 2024. I see that same burning desire, unwavering passion, and collaborative spirit renewed among IBM's leadership. It is clear they are relentlessly pursuing excellence and propelling IBM forward. As a longtime observer, I am invested in their success. This is a new IBM, and I am cheering them on from the sidelines.

AI has much potential, but there is still much to discover to harness its abilities fully. IBM's initial strategy of focusing on prominent, integrated solutions was complex, but the company's strategic change under Arvind Krishna's leadership, since he became CEO in April 2020, represents a significant improvement. The focus on hybrid cloud and AI and the revival of the Watson brand positioned IBM to market its AI products for businesses effectively. The enterprise AI space is very competitive, with Microsoft, Google, and Amazon all competing for market share. However, IBM's recent progress at Think 2024 shows a promising new direction. IBM's dedication to open-source innovation, demonstrated by the Granite model family and the InstructLab initiative, positions it to create scalable and efficient AI solutions designed specifically for enterprise applications. This progress, along with the smooth integration with watsonx, highlights IBM's strategic vision for the future of AI. As the field keeps changing, IBM's approach could serve as a valuable model for using open collaboration to unleash the transformative potential of AI within the enterprise sector.