IBM AI Roadmap
Large-scale, self-supervised neural networks, which are known as foundation models, multiply the productivity and the multimodal capabilities of AI. More general forms of AI emerge to support reasoning and commonsense knowledge.
AI
Roadmap
Strategic milestones
All information being released represents IBM’s current intent, is subject to change or withdrawal, and represents only goals and objectives.
You can learn more about the progress of individual items by downloading the PDF in the top right corner.
2023
Extend foundation models beyond natural language processing.
In 2023, we will expand enterprise foundation model use cases beyond natural language processing (NLP). 100B+ parameter models will be operationalized for bespoke, targeted use cases, opening the door for broader enterprise adoption.
2024
Build modular and multimodal transformers for new enterprise applications.
We will deploy enterprise AI assistants and applications using advanced transformers and developer-friendly frameworks to facilitate processing richer contextual information and enhanced control and monitoring of generative AI.
2025
Alter the scaling of generative AI with neural architectures beyond transformers.
We will use a diverse selection of neural architectures beyond, and including, transformers that are co-optimized with purpose-built AI accelerators to fundamentally alter the scaling of generative AI.
2026
Bring robust, strategic reasoning and commonsense knowledge to AI.
We will support faster learning and the ability to provide explanations through better introspection, retrospection, and different forms of reasoning.
2028
Develop broadly intelligent agents that learn autonomously.
We will build autonomous AI that learns reliably and efficiently from its environment and responds to previously unseen situations through broad generalizations. These AI systems will start exhibiting aspects of biological intelligence.
2030+
Build adaptable and generalist AI for effective human-machine collaboration.
Our AI models will be composed of modules with different cognitive abilities (e.g., perception, memory, emotion, reasoning, and action), enabling them to exhibit behavioral norms for social interactions and mutual theory of mind.