What Is Hybrid AI? Neuro-Symbolic, On-Device and Cloud Explained
Hybrid AI usually means combining rule-based symbolic AI with machine learning. The term also covers AI split between device and cloud. Definitions, examples and the differences.
Hybrid AI usually means combining symbolic AI, which works with rules and logic, with machine learning, which learns patterns from data. The same term is used for AI that splits work between a device and the cloud, and sometimes for people and AI working together. This page explains all three.
What is hybrid AI?
Lenovo defines hybrid AI as a system that integrates several AI methods, such as symbolic AI (rule-based systems) and sub-symbolic AI (machine learning) [1]. Information Age lists the usual pairings: symbolic AI with machine learning, neural networks with knowledge graphs, and deep learning with reinforcement learning [2]. IBM Research calls the same idea neuro-symbolic AI: combining statistical AI such as machine learning with symbolic knowledge and reasoning [3].
Why combine symbolic and neural AI
Each approach is weak where the other is strong. Symbolic AI is good at reasoning but struggles with unstructured data. Machine learning models handle that data but are often hard to interpret and can struggle with tasks that need logical reasoning [2]. In the examples below, the neural part suggests and the symbolic part checks.
Examples: AlphaGeometry and AlphaProof
Google DeepMind's AlphaGeometry, announced in January 2024, is a neuro-symbolic system made of a neural language model and a symbolic deduction engine [4]. The language model quickly predicts constructs that may be useful, and the deduction engine does the rigorous reasoning the language model lacks. AlphaGeometry solved 25 of 30 olympiad geometry problems and was trained on 100 million synthetic examples [4].
AlphaProof, announced in July 2024, proves mathematical statements in the formal language Lean. It couples a pre-trained language model with the AlphaZero reinforcement learning algorithm [5]. Together with AlphaGeometry 2 it solved four of six International Mathematical Olympiad problems, scoring 28 of 42 points. The problems were translated into formal language by hand first [5].
The other meaning: on-device and cloud AI
Qualcomm uses hybrid AI for an architecture that distributes AI workloads between the cloud and edge devices such as phones and PCs [6]. Its 2023 white paper says the main motivation is cost: when the model, prompt and output are small enough, inference can run entirely on the device. Qualcomm also claims benefits for performance, personalisation, privacy and security [6].
Apple Intelligence follows the same pattern. Apple says it favours on-device processing, but more complex requests need larger models in the cloud, which run on its Private Cloud Compute system [7].
Hybrid AI as people plus AI
Some vendors use hybrid AI to mean human expertise combined with AI capabilities. SymphonyAI's glossary defines it that way [8].
The three meanings side by side
| Meaning | What is combined | Example |
|---|---|---|
| Neuro-symbolic AI | Machine learning or neural networks with symbolic rules and logic | AlphaGeometry, AlphaProof [4][5] |
| On-device and cloud | Smaller models on the device with larger models in the cloud | Qualcomm's hybrid AI, Apple Intelligence [6][7] |
| People and AI | Human expertise with AI | SymphonyAI's usage [8] |
When you meet the term, check which meaning the writer has in mind. Most explainers mean the first.
Related: our LLM hub and LLM agents: the practical guide.
Frequently asked questions
What is hybrid AI in simple terms?
Hybrid AI is AI that combines more than one method, most often rule-based symbolic AI with machine learning. The same term is also used for AI that splits work between a device and the cloud.
What is an example of hybrid AI?
Google DeepMind's AlphaGeometry pairs a neural language model with a symbolic deduction engine. It solved 25 of 30 olympiad geometry problems.
Is hybrid AI the same as neuro-symbolic AI?
In its most common sense, yes. IBM Research uses the name neuro-symbolic AI for combining machine learning with symbolic knowledge and reasoning, which is what most definitions of hybrid AI describe.
How is hybrid AI different from machine learning alone?
Machine learning models handle unstructured data well but are often hard to interpret and can struggle with logical reasoning. Hybrid AI adds a symbolic part that handles the reasoning.
What does hybrid AI mean for phones and PCs?
It means running some AI on the device and sending larger jobs to the cloud. Qualcomm says the main reason is cost, and Apple Intelligence uses on-device models with larger cloud models for complex requests.
Sources
- What is hybrid AI? — Lenovo glossary
- What is hybrid AI? — Information Age (October 2024)
- Neuro-symbolic AI — IBM Research
- AlphaGeometry: an olympiad-level AI system for geometry — Google DeepMind (January 2024)
- AI achieves silver-medal standard solving International Mathematical Olympiad problems — Google DeepMind (July 2024)
- The future of AI is hybrid, part 1 (white paper, PDF) — Qualcomm (May 2023)
- Private Cloud Compute — Apple Security Research (June 2024)
- Hybrid AI — SymphonyAI glossary