IBM Research
Creating reliable and adaptable AI solutions
About
IBM Research, established in 1945 and based in Armonk, New York, has been an influential player in the field of artificial intelligence (AI) for decades, setting benchmarks through various historical milestones. Noteworthy achievements include the development of Arthur Samuel's self-learning checkers program in the 1950s and William Dersh's voice-operated "Shoebox" in 1962. These early innovations paved the way for the development of more sophisticated AI systems, including Deep Blue's famous 1997 chess victory over Garry Kasparov and Watson's win on Jeopardy! in 2011. These milestones are foundational to IBM's ongoing innovations in generative AI and large language models (LLMs). Currently, IBM Research focuses on creating powerful foundation models and generative AI systems that prioritize trust and transparency. This commitment is reflected in their open-source approach, designed to make AI development more accessible to enterprises. One such initiative is InstructLab, an open-source project aimed at reducing the costs associated with fine-tuning LLMs. By using Large-Scale Alignment for ChatBots (LAB) to generate high-quality synthetic data, InstructLab enhances models efficiently without necessitating complete retraining. Additionally, the Granite model series, implemented on watsonx.ai, forms the backbone for products like watsonx Assistant and watsonx Orchestrate, noted for their exceptional transparency score on Stanford's Foundation Model Transparency Index. IBM Research's innovation extends to exploring LLM routers, which can dynamically select the most cost-effective model for each query, potentially lowering inference costs by up to 85%. The collaborative efforts in these projects feature contributions from key individuals like David Cox, IBM Research's vice president for AI models, and Akash Srivastava, principal AI product advisor at Red Hat. Additionally, researchers such as Michael Muller, focused on human-centered AI, embody IBM's dedication to ethical AI development. The organization's extensive history in AI research, coupled with its current strategic initiatives, underscores its stature as a leading entity in generative AI and LLMs. IBM Research's commitment to ethical, open-source, and transparent AI systems, alongside its innovative tools like InstructLab and LLM routers, demonstrate its pivotal role in generative AI's ongoing evolution. Applications of these technologies span various domains, including drug discovery and software modernization, highlighting IBM's versatility and forward-thinking approach in the realm of AI.
