diff --git a/README.md b/README.md
index f11ce36..ad994c3 100644
--- a/README.md
+++ b/README.md
@@ -41,7 +41,7 @@ Tom Cruise
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 If you want a higher quality or better face match, you can train your own face model using <a href="https://github.com/iperov/DeepFaceLab">DeepFaceLab</a>
 
-Here is an <a href="https://www.tiktok.com/@arnoldschwarzneggar/video/6995538782204300545">example</a> of Arnold Schwarzneggar trained on a particular face and used in a video call.
+Here is an <a href="https://www.tiktok.com/@arnoldschwarzneggar/video/6995538782204300545">example</a> of Arnold Schwarzneggar trained on a particular face and used in a video call. Read the FAQ for more information.
 
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@@ -52,7 +52,7 @@ Here is an <a href="https://www.tiktok.com/@arnoldschwarzneggar/video/6995538782
 
 ## Minimum system requirements
 
-any DirectX12-compatible videocard or NVIDIA GTX 750+ 
+any DirectX12 compatible graphics card
 
 Modern CPU with AVX instructions
 
@@ -83,9 +83,7 @@ Windows 10
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 <tr><td align="right"> <a href="https://mega.nz/folder/m10iELBK#Y0H6BflF9C4k_clYofC7yA">Windows 10 x64 (mega.nz)</a>
 </td><td align="center">
-NVIDIA build : NVIDIA cards only
-
-DirectX12 build : NVIDIA, AMD, Intel cards.
+DirectX12 build : NVIDIA, AMD, Intel videocards.
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diff --git a/doc/developer_faq/developer_faq.md b/doc/developer_faq/developer_faq.md
index 1ff0d4c..0ac3b03 100644
--- a/doc/developer_faq/developer_faq.md
+++ b/doc/developer_faq/developer_faq.md
@@ -11,13 +11,9 @@ All CPU-intensive tasks are done by native libraries compiled for Python, such a
 
 It consists of backend modules that work in separate processes. The modules work like a conveyor belt. CameraSource(FileSource) generates the frame and sends it to the next module for processing, so the final FPS is equal to the FPS of the slowest module. The final output module outputs the stream to the screen with the desired delay, which helps to synchronize the sound. Backend modules manage the abstract controls that are implemented in the UI. Thus, the Model-View-Controller pattern is implemented. To reduce latency, some custom interprocess communication elements are implemented directly in Python.
 
-## What are the current problems for implementation for Linux ?
-
-No problems. Technically, you only need to write an installer, and check the work of all the modules. DeepFaceLive supports onnxruntime-gpu and onnxruntime-directml packages. You may have to make some adjustments somewhere. I do not use linux, so I do not have time to support development on it.
-
 ## How many people were involved in the development? 
 
-Just me. It took eight months until the first release.
+Just me. It took eight months from scratch until the first release.
 
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