#337 ensured correct spelling for ai lab (#442)

* #337: Ensured correct spelling for AI Lab
* Shortened docker-usage.md
Added mounting docker.sock for SLC.
* Updated version number in docs
and also fixed spelling of 3rd party trademarks in README. 

Co-authored-by: Ariel Schulz <[email protected]>

Author: ckunki

.github/ISSUE_TEMPLATE/release.md

@@ -1,6 +1,6 @@
 ---
 name: Create Release
-about: Create a new release of the AI-Lab
+about: Create a new release of the AI Lab
 title: "\U0001F4E6 Create Release <version>"
 labels: task
 assignees: ''
@@ -19,11 +19,10 @@ Always
 * latest file `doc/changes/changes_*.md`
   * [ ] Append release date to first line
   * [ ] Add a code name and a summary
-* Update version number in user guide
+* Update version number
   * [ ] `user_guide/docker/docker-usage.md`
   * [ ] `user_guide/vm-edition/win-vbox.md`
-* Update version number in developer guide
-  * [ ] `testing.md`
+  * [ ] `developer_guide/testing.md`
 * Replace dependencies to unreleased version (e.g. git dependencies) in files, see instructions in [notebooks.md](https://github.com/exasol/ai-lab/blob/main/doc/developer_guide/notebooks.md):
   * [ ] [notebook_requirements.txt](https://github.com/exasol/ai-lab/blob/main/exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook_requirements.txt)
   * [ ] [jupyter_requirements.txt](https://github.com/exasol/ai-lab/blob/main/exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/jupyter_requirements.txt)

.github/workflows/notebook_tests.yaml

@@ -66,14 +66,14 @@ jobs:
 
       - uses: ./.github/actions/prepare_test_env/
 
-      - name: Download ai-lab image ${{matrix.nb_test.wip}}
+      - name: Download AI Lab image ${{matrix.nb_test.wip}}
         id: download-image
         uses: actions/download-artifact@v5
         with:
           name: "${{ env.DOCKER_IMG_ARTIFACT }}"
           path: "."
 
-      - name: Load ai-lab image ${{matrix.nb_test.wip}}
+      - name: Load AI Lab image ${{matrix.nb_test.wip}}
         run: docker load -i "./$DOCKER_IMG_FILENAME"
 
       - name: Run notebook tests

README.md

@@ -1,21 +1,21 @@
-# Exasol AI-Lab
+# Exasol AI Lab
 
-The Exasol AI-Lab is a pre-configured container designed to empower data scientists. It streamlines common data science and AI tasks, including data loading, preparation, exploration, model training, and deployment. Whether you’re a seasoned practitioner or just getting started, the AI-Lab provides a hassle-free experience.
+The Exasol AI Lab is a pre-configured container designed to empower data scientists. It streamlines common data science and AI tasks, including data loading, preparation, exploration, model training, and deployment. Whether you’re a seasoned practitioner or just getting started, the AI Lab provides a hassle-free experience.
 
-![Transformers Extension](https://github.com/exasol/ai-lab/blob/3.3.0/doc/user_guide/ai-lab-screenshot.png)
+![Transformers Extension](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/ai-lab-screenshot.png)
 
 Key Features:
-* Jupyter Notebook Environment: The heart of the AI-Lab is a robust Jupyter Notebook environment. It’s where you’ll work on your data science projects.
-* Exasol Integration: Leverage Exasol’s power for your AI and machine learning use cases. The AI-Lab includes essential Exasol packages, extensions, and configuration tasks.
-* Example Notebooks: Jumpstart your work with ready-to-use example notebooks. Explore classic machine learning scenarios (think scikit-learn), seamlessly integrate Exasol with AWS Sagemaker, and tap into Huggingface models directly within Exasol.
+* Jupyter Notebook Environment: The heart of the AI Lab is a robust Jupyter Notebook environment. It’s where you’ll work on your data science projects.
+* Exasol Integration: Leverage Exasol’s power for your AI and machine learning use cases. The AI Lab includes essential Exasol packages, extensions, and configuration tasks.
+* Example Notebooks: Jumpstart your work with ready-to-use example notebooks. Explore classic machine learning scenarios (think scikit-learn), seamlessly integrate Exasol with AWS SageMaker, and tap into Hugging Face models directly within Exasol.
 
-Feel free to explore the Exasol AI-Lab and unleash your data science potential!
+Feel free to explore the Exasol AI Lab and unleash your data science potential!
 
-The AI-Lab is available in multiple [Editions](https://github.com/exasol/ai-lab/blob/3.3.0/doc/user_guide/editions.md) involving different technology stacks, see also common [System Requirements](https://github.com/exasol/ai-lab/blob/3.3.0/doc/user_guide/system-requirements.md).
+The AI Lab is available in multiple [Editions](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/editions.md) involving different technology stacks, see also common [System Requirements](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/system-requirements.md).
 
-After downloading the required files and having started the AI-Lab you can connect to AI-Lab's [Jupyter Service](https://github.com/exasol/ai-lab/blob/3.3.0/doc/user_guide/jupyter.md).
+After downloading the required files and having started the AI Lab you can connect to AI Lab's [Jupyter Service](https://github.com/exasol/ai-lab/blob/4.0.0/doc/user_guide/jupyter.md).
 
 ## Additional Links
 
 * [Troubleshooting](doc/user_guide/troubleshooting.md)
-* [Developer Guide](https://github.com/exasol/ai-lab/blob/3.3.0/doc/developer_guide/developer_guide.md)
+* [Developer Guide](https://github.com/exasol/ai-lab/blob/4.0.0/doc/developer_guide/developer_guide.md)

doc/changes/changes_4.1.0.md

@@ -1,4 +1,4 @@
-# AI-Lab 4.0.0 released 2025-11-26
+# AI-Lab 4.1.0 released ????-??-??
 
 Code name:
 
@@ -7,3 +7,4 @@ Code name:
 ## Documentation
 
 * #432: Fixed structure and links in notebook first-steps
+* #337: Ensured correct spelling for AI Lab

doc/developer_guide/aws.md

@@ -1,4 +1,4 @@
-## How to Release the AI-Lab
+## How to Release the AI Lab
 
 1. Take care to update latest file `doc/changes/changes_*.md`
    * Correct version number
@@ -81,4 +81,4 @@ The command tags only the dynamically created entities with the *asset-id* but n
 
 The command `show-aws-assets` lists all assets which were created during the execution.
 * This is very useful if an error occured.
-* If the creation of a sandbox finished normally the list should contain only the AMI, images (S3 objects) and the export tasks (one for each image).
+* If the creation of a sandbox finished normally the list should contain only the AMI, images (S3 objects) and the export tasks (one for each image).

doc/developer_guide/commands.md

@@ -54,8 +54,8 @@ The following commands can be used to deploy the infrastructure onto a given AWS
 * `setup-waf`: Deploy an AWS cloudformation stack with a Web Application Firefall (WAF ACL) configuration for the Cloudfront distribution of an S3 bucket, requires option `--purpose` (see below).
 
 Option `--purpose` is required for both commands `setup-s3-bucket` and `setup-s3-bucket-waf` to select the purpose of the s3 bucket. Supported values are
-* `vm` for virtual machine images of the AI-Lab
-* `example-data-http` for example data to be used in the AI-Lab and accessed via HTTP.
+* `vm` for virtual machine images of the AI Lab
+* `example-data-http` for example data to be used in the AI Lab and accessed via HTTP.
 * `example-data-s3` for example data to be used via S3 protocol.
 
 For all deployment commands:

doc/developer_guide/dependencies.md

@@ -2,7 +2,7 @@
 
 ## Multiple Types of Dependencies
 
-AI-Lab contains dependencies on multiple levels and specified in multiple places, each requiring specific steps for [updating dependencies](#updating-dependencies).
+AI Lab contains dependencies on multiple levels and specified in multiple places, each requiring specific steps for [updating dependencies](#updating-dependencies).
 
 * [pyproject.toml](https://github.com/exasol/ai-lab/blob/main/pyproject.toml) and [poetry.lock](https://github.com/exasol/ai-lab/blob/main/poetry.lock)
 * Requirements files in ansible scripts

doc/developer_guide/design_goals.md

@@ -1,6 +1,6 @@
 ## Design Goals
 
-The Exasol AI-Lab (XAIL) uses AWS as backend, because it provides the possibility to run the whole workflow during a ci-test.
+The Exasol AI Lab (XAIL) uses AWS as backend, because it provides the possibility to run the whole workflow during a ci-test.
 
 This project uses
 

doc/developer_guide/developer_guide.md

@@ -1,4 +1,4 @@
-# Exasol AI-Lab Developer Guide
+# Exasol AI Lab Developer Guide
 
 ## Overview
 
@@ -17,4 +17,4 @@ the virtual image formats.
 7. [Dependencies and Updating Packages](dependencies.md)
 8. [Notebooks](notebooks.md)
 
-Section [Dependencies](dependencies.md) is dedicated to enumerating all places defining dependencies as the AI-Lab contains dependencies on multiple levels and specified in multiple places.
+Section [Dependencies](dependencies.md) is dedicated to enumerating all places defining dependencies as the AI Lab contains dependencies on multiple levels and specified in multiple places.

doc/developer_guide/notebooks.md

@@ -1,18 +1,18 @@
 # Notebook Files
 
-AI-Lab repository includes some Jupyter notebooks and scripts to add these notebooks to AI-Lab images (the old name - DSS images), e.g. AMI or Docker Images.
+AI Lab repository includes some Jupyter notebooks and scripts to add these notebooks to AI Lab images (the old name - DSS images), e.g. AMI or Docker Images.
 
 Please add or update the notebook files in folder [exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook](../../exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook).
 
 ## Notebook Connector
 
 Most notebooks use the `exasol-notebook-connector` - the component providing various helper functions for notebooks.
-We typically put there the code we don't want to show in a notebook. Logically, this component is a part of the AI-Lab.
+We typically put there the code we don't want to show in a notebook. Logically, this component is a part of the AI Lab.
 It is listed in the [notebook_requirements.txt](../../exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook_requirements.txt) and gets installed in the container with pip.
 In order to simplify making simultaneous changes to both notebooks and the notebook-connector we allow referencing the latter temporarily through a git dependency,
 e.g. `exasol-notebook-connector @ git+https://github.com/exasol/notebook-connector@e3a8525`.
 It is important to reference a commit in the `main` branch, not the `main` branch itself. The git dependency should be
-replaced with the proper pypi dependency before releasing of the AI-Lab.
+replaced with the proper pypi dependency before releasing of the AI Lab.
 
 ## Work-in-progress Notebooks
 
@@ -50,4 +50,4 @@ However, with the following pytest commandline parameters you can keep them or r
                         Name and version of existing Docker image for Notebook testing to use for tests
   --keep-docker-image-notebook-test
                         Keep the created notebook-test docker image for inspection or reuse.
-```
+```