10 AI Tools You Should Learn for YouTube Automation in 2026
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π Tutorial how to use Windows virtual server (R-D-P)π₯
β‘οΈ Follow these steps: ππ
1β£Get Your server specifications
When you purchase a Windows Server you will receive the following details:
Server IP e.g. [188.166.252.186]
Username (usually Administrator)
Password
2β£ Connect to the server Using Remote Desktop (Windows PC)
π’Open "Remote Desktop Connection"
π’Press Win + R type mstsc and hit Enter
π’Or search for Remote Desktop Connection in the Start Menu
β¬οΈEnter the server IP Address and click Connect
β¬οΈEnter Your Username and Password
π΄Username is usually Administrator
π΄Enter your password carefully
β‘οΈIf you see a Certificate Warning click Yes to proceed
β‘οΈNow you are connected to your VPS and can use it like a regular computer
3β£ Connect to the server from Mobile (Android & iOS)
π’Download the Microsoft Remote Desktop app from Google Play or the App Store
π’Open the app and tap Add PC then enter your VPS IP Address
π’Enter your username (Administrator) and password
β‘οΈTap on your server to connect
I hope it was usefulβ€οΈπ
π Tutorial how to use Windows virtual server (R-D-P)π₯
β‘οΈ Follow these steps: ππ
1β£Get Your server specifications
When you purchase a Windows Server you will receive the following details:
Server IP e.g. [188.166.252.186]
Username (usually Administrator)
Password
2β£ Connect to the server Using Remote Desktop (Windows PC)
π’Open "Remote Desktop Connection"
π’Press Win + R type mstsc and hit Enter
π’Or search for Remote Desktop Connection in the Start Menu
β¬οΈEnter the server IP Address and click Connect
β¬οΈEnter Your Username and Password
π΄Username is usually Administrator
π΄Enter your password carefully
β‘οΈIf you see a Certificate Warning click Yes to proceed
β‘οΈNow you are connected to your VPS and can use it like a regular computer
3β£ Connect to the server from Mobile (Android & iOS)
π’Download the Microsoft Remote Desktop app from Google Play or the App Store
π’Open the app and tap Add PC then enter your VPS IP Address
π’Enter your username (Administrator) and password
β‘οΈTap on your server to connect
I hope it was usefulβ€οΈπ
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Additional skills aligned with the listed Handshake AI project requirements. These are presented as skills/capabilities and do not claim completion
of the paused or ended projects.
β’ AI Model Response Evaluation: evaluate, compare, rank, and critique model-generated responses using domain-specific reasoning, factuality
relevance, clarity, and quality criteria.
β’ STEM Pairwise Evaluation: compare two AI-generated answers and determine which response is stronger based on technical correctness
,reasoning quality, completeness, and adherence to requirements.
β’ AI Reasoning & Web-Search Evaluation: design difficult prompts, identify model failures, test web-search behavior, assess reasoning chains
and evidence quality, and document failure modes.
β’ Prompt Engineering & Adversarial Testing: create challenging prompts designed to expose weaknesses in AI reasoning, retrieval, instruction
following, and answer quality.
β’ Multimodal AI Data Evaluation: review and assess audio, visual, and text data for quality, consistency, relevance, and annotation accuracy.
β’ Computer Vision & Video Data Collection: capture short smartphone/iPhone videos, follow recording instructions, document everyday
environments, and maintain consistent framing and data quality.
β’ POV Video & Visual Data Capture: first-person video recording, scene coverage, camera positioning, environmental capture, and adherence to
collection protocols.
β’ Software Codebase Analysis: analyze complex codebases, trace program behavior, identify defects or inconsistencies, assess implementation
quality, and reason about existing software architecture.
β’ Software Engineering Evaluation: review coding practices, architecture, maintainability, application-development workflows, documentation
testing, and technical trade-offs.
β’ App Development Assessment: evaluate application functionality, implementation quality, user-facing behavior, technical correctness, and
software-development practices.
β’ AI Annotation & Data Quality: text classification, visual labeling, audio review, multimodal annotation, taxonomy application, consistency
checking, and dataset quality assurance.
β’ AI Safety & Failure Analysis: identify hallucinations, logical errors, unsupported claims, instruction-following failures, and other model
weaknesses through structured evaluation.
β’ Technical Writing & Rubric-Based Judgment: apply evaluation criteria consistently, explain comparative decisions, summarize findings, and
produce concise evidence-based assessments.
β’ Human-in-the-Loop AI Evaluation: provide structured human judgment to improve model accuracy across STEM, software, multimodal
reasoning, and web-search tasks.
of the paused or ended projects.
β’ AI Model Response Evaluation: evaluate, compare, rank, and critique model-generated responses using domain-specific reasoning, factuality
relevance, clarity, and quality criteria.
β’ STEM Pairwise Evaluation: compare two AI-generated answers and determine which response is stronger based on technical correctness
,reasoning quality, completeness, and adherence to requirements.
β’ AI Reasoning & Web-Search Evaluation: design difficult prompts, identify model failures, test web-search behavior, assess reasoning chains
and evidence quality, and document failure modes.
β’ Prompt Engineering & Adversarial Testing: create challenging prompts designed to expose weaknesses in AI reasoning, retrieval, instruction
following, and answer quality.
β’ Multimodal AI Data Evaluation: review and assess audio, visual, and text data for quality, consistency, relevance, and annotation accuracy.
β’ Computer Vision & Video Data Collection: capture short smartphone/iPhone videos, follow recording instructions, document everyday
environments, and maintain consistent framing and data quality.
β’ POV Video & Visual Data Capture: first-person video recording, scene coverage, camera positioning, environmental capture, and adherence to
collection protocols.
β’ Software Codebase Analysis: analyze complex codebases, trace program behavior, identify defects or inconsistencies, assess implementation
quality, and reason about existing software architecture.
β’ Software Engineering Evaluation: review coding practices, architecture, maintainability, application-development workflows, documentation
testing, and technical trade-offs.
β’ App Development Assessment: evaluate application functionality, implementation quality, user-facing behavior, technical correctness, and
software-development practices.
β’ AI Annotation & Data Quality: text classification, visual labeling, audio review, multimodal annotation, taxonomy application, consistency
checking, and dataset quality assurance.
β’ AI Safety & Failure Analysis: identify hallucinations, logical errors, unsupported claims, instruction-following failures, and other model
weaknesses through structured evaluation.
β’ Technical Writing & Rubric-Based Judgment: apply evaluation criteria consistently, explain comparative decisions, summarize findings, and
produce concise evidence-based assessments.
β’ Human-in-the-Loop AI Evaluation: provide structured human judgment to improve model accuracy across STEM, software, multimodal
reasoning, and web-search tasks.
β€3
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Outliet wheezing and laughing project link
Outliet wheezing and laughing project link