From 005ecce12e46a3944eb362e7caf0b97d468982bc Mon Sep 17 00:00:00 2001
From: LT <17088165+ngatilio@users.noreply.github.com>
Date: Sun, 22 Oct 2023 10:47:48 -0400
Subject: [PATCH] Update README.md

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 README.md | 5 ++---
 1 file changed, 2 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index a1e6d34..d0cbafb 100644
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+++ b/README.md
@@ -13,12 +13,11 @@ CertEye has 5 core features:
 `certeye-governance`: choose, prioritize, time, implement, track, and review AI ethics policies and controls suitable for your organization (https://doi.org/10.1109/TAI.2022.3225132).
 
 
-`certeye-pcp`: continuously identify AI ethics issues in your AI pipelines using CI/CDs, playbooks, and testing sandboxes (https://arxiv.org/abs/2206.11981). Testing sandboxes use the
-concept of ethical twins to run multiple tests on the AI components using a virtual emulator. 
+`certeye-pcp`: continuously identify AI ethics issues in your AI pipelines using CI/CDs, playbooks, and testing sandboxes (https://arxiv.org/abs/2206.11981). Testing sandboxes use the concept of ethical twins to run multiple tests on AI components using a virtual emulator. 
 
 
 `certeye-pep`: continuously fix AI ethics issues in your AI pipelines using CI/CDs, playbooks, and patching sandboxes. Patching sandboxes use the
-concept of ethical twins to run and validate multiple patches on the AI components using a virtual emulator. 
+concept of ethical twins to run and validate multiple patches on AI components using a virtual emulator. 
 
 
 `certeye-observability`: monitor various metrics such as fairness loss, PII exposure, carbon footprint per unit, audit traces, and well-know metrics (e.g., response time, peak load, cache hit rate) during the execution of AI models in deployment and post-deployment stages (https://arxiv.org/abs/2306.01788). Compliance reports are generated to help organizations having a 360 view on AI trustworthy postures on