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diff --git a/systemes_libre/Systemes_Libres_Amazon_Alexa_IOT_Pitch_10-JUN-2020.mdwn b/systemes_libre/Systemes_Libres_Amazon_Alexa_IOT_Pitch_10-JUN-2020.mdwn
index 1808703da1fa9e6bdcf8aa6d0f930fc8e14e5add..0dfa405b3ef6d5fa1d79239744e13468d6341285 100644 (file)
--- a/systemes_libre/Systemes_Libres_Amazon_Alexa_IOT_Pitch_10-JUN-2020.mdwn
+++ b/systemes_libre/Systemes_Libres_Amazon_Alexa_IOT_Pitch_10-JUN-2020.mdwn
@@ -20,14 +20,11 @@ Delivering robust low power, high-performance hardware for IOT and Edge Compute
   b. Power: 2 separate cores (CPU, GPU) leads to much higher
      power consumption
   
-  c.  Cost: BOM and manufacturing/assembly costs (No: because usually
-     they're "embedded" (shared memory bus architecture, same die)
-
-  d. Capability: In RTOS devices, can't make effective use of the GPU
+  c. Capability: In RTOS devices, can't make effective use of the GPU
   
-  e. the drivers involve an inter-core RPC mechanism: which is unacceptably high latency and complexity
+  d. the drivers involve an inter-core RPC mechanism: which is unacceptably high latency and complexity
 
-  f. Furthermore, current RTOS microcontrollers have much lower mathematical numerically intensive computational performance at the same power and silicon area compared to our chip.
+  e. Furthermore, current RTOS microcontrollers have much lower mathematical numerically intensive computational performance at the same power and silicon area compared to our chip.
 
 2. Time/Ease of Use/Development: Proprietary development tools and documentation result in an often difficult and long development cycle, especially when rebuilding and optimizing arithmetically intensive algorithms for embedded systems.