Replace two minus signs with an em dash (#765)

* Update README.md

* Apply suggestions from code review

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Co-authored-by: Helio Machado <[email protected]>

Author: DhanushNehru

README.md

@@ -38,7 +38,7 @@ Supported cloud vendors [include][auth]:
 There are several reasons to use TPI instead of other related solutions (custom scripts and/or cloud orchestrators):
 
 1. **Reduced management overhead and infrastructure cost**:
-   TPI is a CLI tool, not a running service. It requires no additional orchestrating machine (control plane/head nodes) to schedule/recover/terminate instances. Instead, TPI runs (spot) instances via cloud-native scaling groups[^scalers], taking care of recovery and termination automatically on the cloud provider's side. This design reduces management overhead & infrastructure costs. You can close your laptop while cloud tasks are running -- auto-recovery happens even if you are offline.
+   TPI is a CLI tool, not a running service. It requires no additional orchestrating machine (control plane/head nodes) to schedule/recover/terminate instances. Instead, TPI runs (spot) instances via cloud-native scaling groups[^scalers], taking care of recovery and termination automatically on the cloud provider's side. This design reduces management overhead & infrastructure costs. You can close your laptop while cloud tasks are running — auto-recovery happens even if you are offline.
 2. **Unified tool for data science and software development teams**:
    TPI provides consistent tooling for both data scientists and DevOps engineers, improving cross-team collaboration. This simplifies compute management to a single config file, and reduces time to deliver ML models into production.
 3. **Reproducible, codified environments**: