Merge branch 'refs/heads/tsp1-not-neuromorphic-chip' into staging

Author: neural-loop

content/workshops/tsp1-neural-network-accelerator-chip-chris-eliasmith/index.md

@@ -1,6 +1,5 @@
 ---
-title: "The TSP1 Neural Network Accelerator Chip: Advancing
-Brain-Inspired Computing"
+title: "The TSP1 Neural Network Accelerator Chip: Advancing Brain-Inspired Computing"
 author:
 - "Chris Eliasmith"
 - "Danny Rosen"
@@ -12,51 +11,51 @@ description: "Join Chris Eliasmith for an in-depth exploration of the TSP1 chip
 upcoming: true
 video: ""
 aliases:
-  - /workshops/tsp1-neuromorphic-chip-chris-eliasmith/
+  - /workshops/tsp1-neural-chip-chris-eliasmith/
 image: "ABR-TSP1-Chip.jpg"
 type: "workshops"
 hardware_tags: ["tsp1"]
-software_tags: ["nengo"]
 ---
 
 ## About This Workshop
 
-Join us for an exciting workshop featuring Dr. Chris Eliasmith as he presents the TSP1 neural network accelerator chip, a cutting-edge hardware platform developed by Applied Brain Research. This event will provide insights into how brain-inspired computing can bridge the gap between artificial intelligence and biological neural systems.
+Join us for an exciting workshop featuring Dr. Chris Eliasmith as he presents the **TSP1 (Time Series Processor 1)** neural network accelerator chip — a cutting-edge hardware platform developed by Applied Brain Research.  
+This event will provide insights into how brain-inspired computing can set world records in efficiency for AI applications.
 
 ## What You'll Learn
 
 In this workshop, Dr. Eliasmith will cover:
 
 - **The TSP1 Architecture**: An overview of the TSP1 chip's unique design and capabilities
 - **Brain-Inspired Computing**: How the TSP1 embodies principles from neuroscience to create efficient, low-power computing solutions
-- **Real-World Applications**: Practical use cases where neural network accelerators like TSP1 excels, including edge computing, robotics, and adaptive systems
-- **Integration with Nengo**: How the TSP1 chip works seamlessly with the Nengo neural modeling framework
+- **Real-World Applications**: Practical use cases where neural accelerator hardware like TSP1 excels, including edge computing, robotics, and adaptive systems
 - **Performance and Efficiency**: Comparisons with traditional computing architectures and insights into power consumption and speed
 
 ## About the TSP1 Chip
 
-The TSP1 (Temporal Semantic Pointer 1) is a neural network accelerator designed to efficiently implement the Neural Engineering Framework (NEF) and Semantic Pointer Architecture (SPA). Developed by Applied Brain Research, the TSP1 chip represents a significant advancement in brain-inspired computing hardware, offering:
+The **TSP1 (Time Series Processor 1)** represents a significant advancement in brain-inspired computing, offering:
 
 - **Ultra-low power consumption** suitable for edge deployment
 - **Real-time processing** of complex neural computations
-- **Scalable architecture** for building large-scale brain models
-- **Native support** for temporal dynamics and structured representations
+- **Scalable architecture** for building large-scale AI applications
+- **Native support** for temporal dynamics and time series processing
 
 This hardware platform enables researchers and developers to deploy sophisticated cognitive models and neural networks in real-world applications where power efficiency and real-time performance are critical.
 
 ## Who Should Attend
 
 This workshop is ideal for:
 
-- Researchers in neuromorphic computing and computational neuroscience
+- Researchers in neural computing and efficient AI
 - Engineers working on edge AI and embedded systems
 - Developers interested in brain-inspired computing platforms
-- Students exploring neuromorphic hardware and neural modeling
+- Students exploring neural accelerator hardware and time series modeling
 - Anyone curious about the future of efficient AI computing
 
-## Prerequisites
+## Speaker
 
-No specific prerequisites are required, though familiarity with neural networks and basic neuroscience concepts will enhance your understanding. Prior experience with Nengo is helpful but not necessary.
+**Chris Eliasmith**, Professor and Canada Research Chair in Theoretical Neuroscience, and CTO at Applied Brain Research.  
+His research focuses on large-scale brain modelling, neural dynamics, efficient AI, and brain-inspired computing.
 
 ## Resources