2. Historical Context and Evolution of AI Hardware
The evolution of AI hardware has been pivotal for advancements in artificial intelligence technology, transforming early systems reliant on limited processing power into modern deep learning networks. This chapter discusses the historical milestones in AI hardware development, highlighting the emergence of GPUs, TPUs, FPGAs, and ASICs, which have significantly enhanced AI performance. It also explores future trends like neuromorphic computing and quantum computing that promise further innovations in the field.
Enroll to start learning
You've not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- AI hardware has evolved significantly, impacting the development of AI technology.
- The introduction of GPUs revolutionized AI processing capabilities, enabling rapid advancements in deep learning.
- Future developments in AI hardware focus on energy efficiency and specialized computing solutions.
Key Concepts
- -- Symbolic AI
- An early form of AI focusing on symbolic representation and logical reasoning.
- -- Neural Networks
- Computational models inspired by biological neural networks that learn from data.
- -- Graphics Processing Units (GPUs)
- Specialized hardware designed for parallel processing, particularly effective in training deep learning models.
- -- Tensor Processing Units (TPUs)
- Custom-designed chips specifically for accelerating machine learning tasks, excelling at matrix operations.
- -- FieldProgrammable Gate Arrays (FPGAs)
- Customizable hardware that can be configured for specific tasks, providing versatility and rapid adaptability.
- -- ApplicationSpecific Integrated Circuits (ASICs)
- Custom chips optimized for specific tasks, offering high efficiency for particular AI workloads.
- -- Neuromorphic Computing
- A computing approach that mimics the human brain's architecture to improve efficiency and learning in AI systems.
- -- Quantum Computing
- An evolving technology that uses quantum mechanics to perform complex calculations more efficiently than classical computers.
Additional Learning Materials
Supplementary resources to enhance your learning experience.