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SlopeCraft · Jan 4, 2022 · fe76176 · fe76176
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diff --git a/README.md b/README.md
@@ -511,4 +511,3 @@ This project started after seeing that a lot of new and renowned ML & DL project
 The Vulkan SDK offers a great low level interface that enables for highly specialized optimizations - however it comes at a cost of highly verbose code which requires 500-2000 lines of code to even begin writing application code. This has resulted in each of these projects having to implement the same baseline to abstract the non-compute related features of the Vulkan SDK. This large amount of non-standardised boiler-plate can result in limited knowledge transfer, higher chance of unique framework implementation bugs being introduced, etc.
 
 We are currently developing Kompute not to hide the Vulkan SDK interface (as it's incredibly well designed) but to augment it with a direct focus on the Vulkan SDK's GPU computing capabilities. [This article](https://towardsdatascience.com/machine-learning-and-data-processing-in-the-gpu-with-vulkan-kompute-c9350e5e5d3a) provides a high level overview of the motivations of Kompute, together with a set of hands on examples that introduce both GPU computing as well as the core Kompute architecture.
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diff --git a/SECURITY.md b/SECURITY.md
@@ -10,4 +10,3 @@ Kompute aims to follow the two following policies:
 ## Reporting a Vulnerability
 
 If you identify a vulnerability the best way to report it is by sending an email to the team via [email protected]. The discussion can then take place there on next steps (ie updating library, reaching out to 3rd party projects, etc).
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Expand Up		@@ -511,4 +511,3 @@ This project started after seeing that a lot of new and renowned ML & DL project
		The Vulkan SDK offers a great low level interface that enables for highly specialized optimizations - however it comes at a cost of highly verbose code which requires 500-2000 lines of code to even begin writing application code. This has resulted in each of these projects having to implement the same baseline to abstract the non-compute related features of the Vulkan SDK. This large amount of non-standardised boiler-plate can result in limited knowledge transfer, higher chance of unique framework implementation bugs being introduced, etc.

		We are currently developing Kompute not to hide the Vulkan SDK interface (as it's incredibly well designed) but to augment it with a direct focus on the Vulkan SDK's GPU computing capabilities. [This article](https://towardsdatascience.com/machine-learning-and-data-processing-in-the-gpu-with-vulkan-kompute-c9350e5e5d3a) provides a high level overview of the motivations of Kompute, together with a set of hands on examples that introduce both GPU computing as well as the core Kompute architecture.
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Expand Up		@@ -10,4 +10,3 @@ Kompute aims to follow the two following policies:
		## Reporting a Vulnerability

		If you identify a vulnerability the best way to report it is by sending an email to the team via [email protected]. The discussion can then take place there on next steps (ie updating library, reaching out to 3rd party projects, etc).