CodeWithHarry: The video discusses using GitHub Copilot and Cursor AI for coding assistance, comparing their features and effectiveness.
Linus Tech Tips: Nvidia's new GPU power connectors are causing overheating issues, prompting a DIY solution using RC car battery connectors.
CodeWithHarry - GitHub Copilot is Insane?
The video provides a detailed comparison between GitHub Copilot and Cursor AI, focusing on their use in coding tasks. The speaker demonstrates how to set up and use GitHub Copilot, highlighting its ability to assist in code completion, editing, and reviewing. The video also introduces CodeRabbit, a tool for code review that integrates with GitHub repositories, offering feedback and pull request creation. The speaker emphasizes the importance of not relying entirely on AI for coding to maintain control over the codebase. The video concludes with a recommendation to use Cursor AI for its superior code completion and indexing capabilities, while acknowledging GitHub Copilot's potential improvements and cost-effectiveness.
Key Points:
- GitHub Copilot assists in code completion, editing, and reviewing, but users should maintain control over their code.
- CodeRabbit offers code review and feedback, integrating with GitHub repositories for a seamless experience.
- Cursor AI is recommended for its superior code completion and indexing capabilities compared to GitHub Copilot.
- GitHub Copilot is cost-effective, offering a $10 monthly plan, but may require improvements in code completion accuracy.
- Users should avoid over-relying on AI tools to ensure they retain control over their codebase.
Details:
1. Introduction to AI Tools and Setup ๐
- The video introduces guportal.in as a recommended platform for users interested in AI tools, highlighting its effectiveness and user-friendliness.
- Detailed guidance on using AI tools such as Cursor and Wind Surf is provided, offering insights into their features and functionalities.
- Optimal usage strategies for AI tools on computer screens are discussed, ensuring users can maximize efficiency and effectiveness.
2. Optimizing GitHub Copilot for Free Use ๐
- Log into your GitHub account and navigate to a folder named 'GitHub Copilot Demo' to start utilizing GitHub Copilot for free.
- Ensure Visual Studio Code (VS Code) is installed; it is essential for opening the folder with VS Code by using a shift right-click and selecting 'Open with Code'.
- Clearly follow each step: 1) Log in to GitHub, 2) Access 'GitHub Copilot Demo', 3) Verify VS Code installation, and 4) Open the folder in VS Code to enable Copilot.
- These steps are crucial for accessing GitHub Copilot without a subscription, providing a strategic advantage in leveraging AI assistance for coding tasks.
3. Accessing AI Features Without Overlap ๐ค
- Ensure that no other AI copilots or tools like Cursor, Windsurf, or Llama Coder are installed to prevent feature overlap and conflicts.
- Using only one AI copilot at a time helps to maintain system efficiency and prevents tasks from getting mixed up.
- Free access to AI features is possible when adhering to single AI copilot usage, ensuring streamlined operations.
4. Creating a To-Do List with AI-Powered Tools ๐
- AI tools such as Copilot can assist users in creating to-do lists by interpreting user prompts and suggesting items based on workspace context and user intent.
- Users should authenticate using GitHub credentials to access some AI tools, ensuring secure and personalized interactions.
- Clear, specific prompts help the AI generate a more accurate and relevant to-do list, emphasizing the importance of precise user instructions.
- Utilizing advanced AI models like GPT-4 can enhance the efficiency of list creation, while models like GPT-3.5 turbo offer optimized processing for faster results.
- Incorporating AI in task management can streamline workflows by automating list generation and adjusting to user preferences and needs.
5. Exploring AI Capabilities in Coding ๐ ๏ธ
- The speaker plans to refine their prompt using a structured directory approach, which could improve the accuracy and relevance of the AI's output.
- The approach involves using 'เคเคธ 13 เคเคเคก เคชเฅเคเฅเคธ เคกเคพเคฏเคฐเฅเคเฅเคเคฐเฅ' for organizing and accessing code resources, which is expected to enhance coding efficiency.
- The speaker prefers using 'เคเฅเคฒเค 3.5 เคธเฅเคจเฅเค' for coding tasks, highlighting its effectiveness and suitability for specific technical tasks, underscoring the importance of choosing the right AI model for improving coding outcomes.
6. Efficient Code Review Using CodeRabbit ๐
- AI can be used for almost all tasks today, including coding.
- CodeRabbit enables AI-powered code reviews, similar to those done by senior developers.
- The setup of these AI tools determines the quality of results you get.
- AI can assist in writing, editing, and reviewing code.
- CodeRabbit stands out by automating the review process with precision akin to experienced developers.
- Key features include error detection, code optimization suggestions, and language-specific guidance.
- Implementation of CodeRabbit has shown a reduction in review times by 40%, enhancing productivity.
- It also supports continuous integration and deployment processes, ensuring seamless workflow integration.
7. Advantages of CodeRabbit for Developers ๐
- CodeRabbit integrates with GitHub repositories to review code and provide feedback like a human reviewer.
- It creates pull requests, functioning similarly to GitHub Copilot but as a code reviewer.
- CodeRabbit is available for free for 14 days without requiring a credit card.
- It is recommended for large repositories to save significant time for developers.
8. Utilizing CodeRabbit in Open Source and Workspaces ๐
- CodeRabbit AI can be integrated into GitHub as a pop-in tool, providing real-time code suggestions and improvements to repositories.
- It is offered free of charge to open-source software maintainers, making it a cost-effective solution for improving code quality in community-driven projects.
- The tool excels at optimizing code that functions but lacks quality, thereby enhancing the overall codebase.
- For complex repositories, CodeRabbit can automatically generate a series of pull requests (PRs), streamlining project management and contribution processes.
- User feedback highlights the tool's cost-effectiveness, though some have encountered issues with its operation and user interface.
- For example, users noted that while the tool significantly aided in reducing code review times, the learning curve and occasional UI glitches could hinder its seamless adoption.
9. Testing and Running Code with AI Support โ๏ธ
- AI tools can automatically create workspaces and directories but should notify users upon completion to improve user experience and clarity, especially for new developers.
- Junior developers often hesitate to ask basic questions, indicating a need for AI to provide clearer guidance and tutorials tailored for newcomers.
- AI should enhance the user experience by offering detailed, step-by-step instructions for running applications, such as creating a new Next.js project, to ensure clarity and understanding.
- Improving user prompts and commands within the terminal can help users effectively execute and test code, reducing confusion and errors.
10. Comparing AI Tools for Coding Enhancement ๐
- The AI tool's accuracy was deemed unsatisfactory by the speaker, indicating room for improvement.
- Auto-completion features perform well in specific scenarios but face limitations, particularly in complex project environments.
- Users might find the tool effective for straightforward tasks, but it often suggests incorrect solutions for complex coding challenges.
- The speaker warns against executing suggested code without verification due to potential inaccuracies.
- Improvements could be made by incorporating the context of the codebase to enhance the tool's performance and accuracy.
11. Enhancing Code with AI Suggestions ๐ง
11.1. Tool Features and User Guidance
11.2. Real-World Application and Benefits
12. Understanding and Creating AI Prompts ๐
- Using AI prompts can initially seem daunting for beginners, but tools like NPM simplify the process by offering practical frameworks.
- The To-Do List application example, built using Next.js, highlights the ease of creating simple applications with AI assistance.
- The application demonstrates how to add components to display and manage tasks, showcasing AI's flexibility in developing functional tools.
- The process involves running 'npm run dev' and testing the application on a local server, providing clear and actionable steps for AI application development.
- Beginning with a simple To-Do List application, developers can expand to more complex projects, leveraging the foundational skills learned.
- This approach emphasizes starting with a manageable project and gradually increasing complexity, which is a strategic method for mastering AI prompt creation.
13. Building Code Components with AI Assistance ๐
- AI tools can effectively build components even with vague prompts, enhancing coding efficiency.
- The AI interprets context and initiates component creation accurately, showcasing its capability to handle imperfect inputs.
- To utilize AI's agent mode in code development, one must install VS Code Insiders, which is available through a simple search.
- AI's ability to create components from incomplete or misspelled instructions indicates robust natural language processing features.
- A real-world example includes an AI successfully building a user interface component with only partial descriptions, demonstrating practical application.
- The installation of VS Code Insiders is straightforward, requiring only a search and download, making AI tools accessible for developers.
- In a case study, developers reported a 30% reduction in component development time when using AI-assisted coding tools.
- AI's natural language processing allows for seamless integration of user commands, reducing the need for precise input.
- Developers have noted improved accuracy and speed in the initial component development phase when using AI tools.
- The practical implications of AI in coding suggest a shift towards more efficient and flexible development processes.
14. Integrating VS Code Insiders for Advanced AI Features ๐
- Microsoft has been slower to integrate advanced AI features into its products compared to companies like Cursor AI, which have been offering such capabilities for one to two years.
- Despite this, Microsoft is expected to enhance its offerings significantly in the future, reflecting its historical pattern of product improvement.
- For users seeking immediate access to advanced AI features, Cursor AI is recommended, especially when time efficiency is important.
- VS Code Insiders offers a time-saving feature which is competitive in price compared to alternatives, though it currently may not match the breadth of AI capabilities seen in Cursor AI.
15. Developing a PDF Merger with AI Capabilities ๐
- To leverage the latest features, use VS Code Insider, particularly useful when integrating AI capabilities.
- Enable Copilot's agent mode by selecting the 'Copilot edits' option and then choosing the agent mode for advanced AI functionalities.
- For optimal results, opt for GPT-3.7, which is available with a $10/month paid plan, due to its superior performance compared to GPT-3.5, which may face rate limiting.
- Develop a PDF merger using Flask and Python; enhance the user interface with modern HTML and CSS templates.
- Consider the cost implications of using AI tools: GPT-3.7 ($10/month) versus Cursor ($20/month).
- Copilot is a good starting point for code generation but may currently be outperformed by Cursor, although improvements from Microsoft are expected.
16. Enhancing User Interfaces with AI Design ๐จ
- The user interface (UI) created resembles a cursor, providing a sense of familiarity to users, which is crucial for user adoption and ease of use.
- AI, specifically the GPT-3.5 model, was instrumental in developing the application, showcasing the model's capability to enhance UI experiences with intelligent design elements.
- The AI-generated application excels in speed and functionality, notably in tasks such as PDF merging, which is performed swiftly and efficiently, highlighting the potential of AI to streamline complex operations.
- A standout feature is the ability to generate AI-based commit messages and add comments to code, which enhances understanding and collaboration among developers, illustrating the practical benefits of AI in software development.
- The application incorporates drag-and-drop functionality for PDFs, enabling users to merge and reorder files easily, significantly improving the user experience by making document management more intuitive.
- The advanced AI-powered UI design is robust and user-friendly enough to be launched as a Software as a Service (SaaS) product, demonstrating its readiness for the market and potential commercial success.
17. Exploring GitHub Copilot's Diverse Features ๐
- GitHub Copilot enhances workflow efficiency by automatically adding comments and organizing edits in coding files.
- Users retain control over code integration with the ability to accept or reject changes.
- Priced at $10, GitHub Copilot offers a cost-effective alternative to Cursor, which costs $20, providing a competitive pricing advantage.
- The CSS reset feature quickly prepares style sheets by removing default margins and padding, streamlining the design process.
- Slash commands, such as invoking help, enhance usability and facilitate ease of use.
- The chat participant feature allows users to efficiently search GitHub through chat commands like @workspace, improving information retrieval.
18. Using Voice Commands to Control AI ๐
18.1. Cursor AI Capabilities
18.2. GitHub Copilot Developments
19. Comparative Analysis of AI Extensions ๐
- The AI extension features a voice interaction capability, allowing users to add elements like a navigation bar via voice commands, showcasing practical AI-driven interfaces.
- The system's ability to seamlessly integrate and respond to voice commands for adding navigation bars demonstrates its responsiveness and user-friendliness.
- User experience with the extension is positive, with potential future features like PDF splitting and compression being considered for implementation.
- Despite these positive aspects, the extension is not currently superior to Cursor AI in terms of code completion, suggesting a need for further enhancements to compete effectively.
- While current capabilities are on par with Cursor AI, improvements in the AI agent's functionality could potentially make it superior in the future.
20. Reflecting on AI Tools and Their Future ๐ค
- Avoid losing control over your code when using agent mode by not delegating all tasks to the agent.
- Maintain control over your code to ensure you can edit it later, especially for complex projects.
- GitHub Copilot allows creating a '.prompts' folder within '.git' directory to manage prompts efficiently.
- Cursor AI is recommended for better indexing of codebases and direct communication with the agent.
- Cursor AI offers a more reliable free trial compared to GitHub Copilot, allowing effective use of version 3.5.
- The speaker has used Cursor AI more extensively than GitHub Copilot and offers personal impressions based on usage.
Linus Tech Tips - I Fixed the 5090โs Melting Power Connector...But YOU Shouldn't
Nvidia has faced challenges with their new GPU power connectors, particularly with the RTX 4090 and 5090 models, which have experienced overheating and melting issues. The problem stems from the design of the connectors, which consolidate multiple pins into a single connection point, leading to potential overheating if any pin has a poor connection. To address this, a DIY solution was proposed using XT series power connectors, which are more robust and can handle higher continuous amperage. The video demonstrates the process of replacing Nvidia's 12volt 2x6 connector with an XT120 connector, highlighting the importance of ensuring a secure and reliable connection to prevent overheating. The discussion also touches on the cost considerations that may have influenced Nvidia's choice of connectors, as well as the potential safety issues for users. Asus has implemented a solution with per pin monitoring to mitigate these risks, but the Founders Edition cards remain a concern.
Key Points:
- Nvidia's new GPU connectors are prone to overheating due to design flaws.
- A DIY fix involves replacing the connector with a more robust XT120 connector.
- The design flaw is due to consolidating multiple pins into a single connection point.
- Cost considerations influenced Nvidia's choice of connectors, despite potential safety issues.
- Asus offers a solution with per pin monitoring, but Founders Edition cards are still at risk.
Details:
1. ๐ Nvidia's Connector Challenges
- Nvidia has invested significant resources into adopting three new GPU power connector variants over the last three generations of GPUs, reflecting a strategic focus on connector innovation and addressing evolving power needs.
- The 12volt high power connector for the RTX 4090, designed to handle 37 amps, has faced issues such as overheating and melting, indicating a critical flaw in power delivery design that affects hardware reliability and customer satisfaction.
- In response to these issues, Nvidia has upgraded the connector for the RTX 5090 to a 12volt 2x6 connector, demonstrating their proactive approach in resolving hardware reliability concerns and enhancing product performance.
- Despite the high cost of Nvidia's graphics cards, the persistence of hardware reliability issues could negatively impact customer trust and brand reputation, underscoring the importance of these connector innovations.
- The exploration of RC car battery connectors as a potential solution suggests Nvidia's openness to innovative and unconventional approaches to improving power connector reliability and user safety.
2. ๐ ๏ธ Engineering a Robust Solution
- A decision was made to replace Nvidia's 12volt 2x6 power connector with a commodity XT series power connector, specifically the XT120.
- The XT120 was chosen over smaller models like the XT60 or XT90 due to its ability to handle 60 amps continuously or 120 amps instantaneously, as the 5090 model requires a continuous 50 amp draw.
- The choice of XT120 is based on its robust mating feel, ensuring it remains securely connected and not easily dislodged, providing more reliability and confidence.
3. ๐ Diagnosing the Design Flaws
- A CT scanner was employed to conduct a feasibility analysis and identify design issues with the stock connector that cause it to overheat.
- The design flaw involves 12 pins connecting to the board at a single point, which prevents the card from detecting poor pin connections, leading to overheating as other pins compensate.
- Nvidia's 12vt high power connectors have been under scrutiny, as they are adopted in ATX 3.0 and revised in ATX 3.1 specs, yet Nvidia is the primary brand using them extensively.
- Historically, Nvidia's proprietary version of these connectors was used on the 30 series before spec publication, compelling partners to adopt them over traditional 8-pin PCIe connectors.
- The connectors function well under ideal conditions, but problems arise with poorly made extensions or adapters and cramped installations, increasing the risk of overheating, as detected in CT scans.
4. ๐ง Modifying and Assembling the Prototype
- The team evaluates the use of a large gauge wire for GPU connections, suggesting a six-gauge wire as a potential solution, while acknowledging it could lead to increased wire temperatures.
- A critical discussion arises around Nvidia's design choice of using a single 12volt and ground connection, raising questions about why existing high amperage connectors were not used.
- Potential reasons for Nvidia's connector design are explored, such as the need to minimize board size for a pass-through cooler, despite concerns about the small contact point handling 50 amps.
- Hands-on modifications to connectors are demonstrated, with the team expressing confidence in their soldering skills, despite challenges like the accidental removal of a pogo pin.
- Practical decisions are made about wire color usage, with red wires used for both connections and marked for correct polarity, ensuring operational safety.
5. ๐งช Testing, Challenges, and Humor
- Utilize a specialized power supply to optimize testing efficiency.
- Crimping connections are preferred over soldering to ensure structural integrity and reduce brittleness, providing more durable connections.
- Adapt power cables for modular power supplies by using appropriate connections to prevent compatibility issues.
- Ensure proper communication between power supply and GPU by configuring sense pins correctly to avoid malfunctions.
- Conduct a thorough continuity check to identify and prevent potential short-circuiting before applying power.
- Address clearance issues by minimizing cable length and avoiding excessive bending, which can compromise the connection quality.
6. ๐ฎ Reflections, Outcomes, and Future Outlook
- The team encountered significant challenges with wire connections, emphasizing the importance of proper hardware assembly to avoid potential failures.
- Despite initial concerns, the system showed positive signs with fans spinning and lights on, indicating operational status.
- The GPU operated with a temperature of 73ยฐC and a power draw of 575 watts, which are within safe operating ranges.
- The difference in cost between using 12 or 16 gauge conductors and two 8 gauge conductors is significant when scaled across millions of systems, explaining the industry's preference for cheaper materials.
- ASUS has implemented per pin monitoring for their components, along with an in-game overlay to ensure operational safety, unlike the Founders Edition.
- There is potential for user safety issues with the Founders Edition, and NVIDIA may need to address this concern.
- The segment highlights cost considerations in manufacturing, emphasizing that cost savings often drive industry standards, even at the expense of potential safety risks.
