Git Commit 101: IA y GitHub Copilot Revolucionando la Programación

Developer Conference Experience

• The speaker describes their experience at a developer conference, highlighting the positive energy and community atmosphere.
• They mention the conference's focus on open source and the opportunity to connect with experts and solve problems.
• The speaker contrasts the conference's vibrant and approachable environment with more corporate conferences.

Introduction to AI at Git Commit Uruguay 2024

• Luis Sánchez, the speaker, introduces the topic of AI and its potential applications for students and developers.
• Ignacio, another speaker, begins a discussion about AI by asking the audience about their familiarity with AI tools like GitHub Copilot and ChatGPT.

Defining Artificial Intelligence

• Ignacio encourages the audience to define AI in their own words.
• Artificial intelligence (AI) is the ability of a machine to perform tasks typically associated with intelligent beings. Examples include a hamster navigating a maze, a navigation app providing directions, and a spam filter identifying unwanted emails.

Machine Learning and Neural Networks

• Machine learning is a subset of AI that uses data to generate predictions and generalize based on those predictions. This allows AI to learn without explicit programming.
• An example of machine learning is a spam filter that learns to identify spam emails by analyzing patterns in data.
• Machine learning models learn by being trained on large datasets. This allows them to generalize and make predictions based on new data.
• Neural networks are inspired by the human brain, with neurons processing information from left to right.
• Machine learning models, a type of artificial intelligence, learn patterns from data.
• For example, an image classification model could learn to distinguish between cats and dogs by recognizing patterns like ear shapes or mouth features.

Data Science and AI Tools

• The field of data science combines mathematics, statistics, and computer science to develop artificial intelligence.
• Neural networks involve complex mathematical concepts, making them potentially challenging to understand.
• GitHub offers tools for programming and developing artificial intelligence, including Deepnote.
• Deepnote is a tool that allows users to create Jupyter notebooks, which are interactive documents that combine code and text.
• Students can access Deepnote through the GitHub Student Developer Pack, which provides benefits to students worldwide.

Machine Learning Project Example

• The text describes a machine learning project written in Python, a common language for data science and artificial intelligence.
• The project involves importing libraries, loading a pre-trained machine learning model, and analyzing an image.
• The example uses a machine learning model to determine if a brain scan image shows a tumor.
• The project is hosted on GitHub, allowing for collaborative work and version control.

Deepnote and GitHub Integration

• The text highlights the use of Deepnote, a tool for building and sharing machine learning models, and its integration with GitHub.
• Deepnote enables users to make changes to their notebooks and push them to GitHub, facilitating collaboration among researchers.
• The text mentions that the Student Developer Pack offers various tools for data science and machine learning, including Deepnote.

Generative AI and Large Language Models

• The discussion focuses on the concept of generative artificial intelligence (AI), which involves using AI models to generate outputs like text, images, or code.
• Generative AI models are a subset of machine learning models, which are trained on large datasets to learn patterns and make predictions.
• The discussion highlights the role of large language models (LLMs) in generative AI. LLMs are AI models trained on massive amounts of text data, enabling them to generate human-like text.
• The example of ChatGPT is mentioned, which is a popular LLM capable of generating text, translating languages, and writing different kinds of creative content.

GitHub Copilot and AI-Powered Code Completion

• The discussion connects LLMs to the concept of GitHub Copilot, which is an AI-powered code completion tool that uses LLMs to suggest code snippets and complete code based on context.
• The speaker, Miguel Ángel Durán, encourages viewers to embrace the potential of artificial intelligence (AI) and its ability to change the world.
• He emphasizes the importance of effort and learning, stating that while results are not always guaranteed, consistent effort is crucial.
• Durán highlights the potential of AI to help individuals solve problems and make a positive impact on the world.

GitHub Copilot: A Powerful AI Tool

• The speaker introduces GitHub Copilot as a powerful AI tool that can enhance coding skills and streamline the development process.
• He encourages viewers to explore and utilize tools like GitHub Copilot, emphasizing that the choice of tools is ultimately up to the individual.
• Durán shares his personal experience with GitHub Copilot, stating that it has significantly impacted his coding process and inspired new ideas.

Benefits of GitHub Copilot

• The text discusses the benefits of using GitHub Copilot, an AI-powered coding assistant, for programmers.
• The speaker highlights that GitHub Copilot allows programmers to communicate with the AI in their native language, eliminating the language barrier that often exists with other AI tools.
• The speaker emphasizes that this feature is particularly beneficial for programmers who do not speak English as their first language, as it allows them to access and utilize AI tools more effectively.

Impact of GitHub Copilot on the Future of Programming

• The speaker believes that GitHub Copilot will significantly impact the future of programming, making it easier for developers to write code and potentially eliminating the need for traditional coding education in the future.
• The speaker also points out that the accessibility of technology has improved significantly, with most people having access to computers and smartphones, which gives them a significant advantage over previous generations.
• The speaker concludes by stating that the ability to communicate with AI in one's native language is a crucial development that will empower programmers and make coding more accessible to a wider audience.

Learning in One's Native Language

• Learning in one's native language is easier because it eliminates the need to process another language on top of the knowledge being acquired.
• Tools like GitHub Copilot allow users to communicate in their native language, bridging the gap between thinking about an idea and implementing it.
• While GitHub Copilot can provide structure and code in English, users can specify conventions in other languages.

GitHub Copilot: Empowerment and Psychological Safety

• GitHub Copilot is a tool that empowers users, but it does not replace the need for human creativity, innovation, and problem-solving.
• The speaker views GitHub Copilot as a tool that provides psychological safety, allowing users to overcome initial barriers and focus on their ideas.
• When joining a new project or company, there is a learning curve to understand the team's best practices, preferred tools, and existing codebase.
• Tools like GitHub Copilot can help bridge this gap by providing context and suggestions based on existing code and natural language prompts.
• Copilot can help reduce the need for constant questions, fostering a sense of psychological safety and preventing the feeling of being an imposter.

Copilot: A Valuable Tool, Not a Replacement

• While Copilot can be a valuable tool, it's important to remember that it's not a replacement for human engineers.
• Users need to understand the context and provide clear instructions to ensure Copilot provides accurate and helpful suggestions.
• With the right education and support, engineers can leverage Copilot to accelerate their progress and achieve more than previous generations.

Understanding the Basics of GitHub Copilot

• The speaker emphasizes the importance of understanding the basics of how tools like GitHub Copilot work, even though they offer significant advancements in programming.
• The speaker highlights that GitHub Copilot is built on a specialized model called Codex, which is specifically designed for programming, unlike other tools that rely on general-purpose models.
• The speaker explains that GitHub Copilot was trained on a massive dataset of public code, providing it with a deep understanding of programming concepts and practices.
• The speaker mentions that GitHub Copilot's training data includes information from public repositories, similar to how Google uses publicly available information for its search engine.
• The speaker encourages viewers to explore a blog post (accessible through a QR code) that provides further details about the history and development of GitHub Copilot.

Contextual Awareness and Prompt Engineering

• GitHub Copilot uses context from open tabs, editor data, and libraries to generate code suggestions.
• Copilot creates a vector database based on this context.
• Users are responsible for prompt engineering, which involves providing clear instructions and context to Copilot.
• The code generated by Copilot is owned by the user, as they are responsible for the prompts and context provided.
• The context used by Copilot is ephemeral, meaning it is not permanently stored or used to train models unless the user chooses to contribute their code.
• Copilot differs from other tools in the market by allowing users to choose whether or not to contribute their code to model training.

Terms and Conditions of Generative AI Tools

• The terms and conditions of generative AI tools are not always clear or concise, and may contain disclaimers that are not readily apparent to users.
• The code generated by Copilot is owned by the user, even though it uses the user's prompts and context.

Caution and Critical Thinking with AI Tools

• The speaker emphasizes the importance of being cautious about sharing one's thoughts and ideas with AI tools, particularly when it comes to potentially groundbreaking concepts.
• The speaker highlights that while GitHub Copilot is designed to assist programmers, it is not intended to replace human creativity and ingenuity.
• The speaker draws a comparison between GitHub Copilot and a "know-it-all" friend or relative who may offer unsolicited advice or suggestions that are not always relevant or helpful.
• The speaker explains that GitHub Copilot, like other AI models, can sometimes generate inaccurate or irrelevant suggestions, known as "hallucinations."
• The speaker stresses the importance of human oversight and critical thinking when using AI tools like GitHub Copilot, emphasizing that programmers should not blindly accept every suggestion provided.

GitHub Copilot: Versions and Features

• The speaker acknowledges that GitHub Copilot comes in two versions: a "ghost" version that provides suggestions as the user types and a more interactive version that allows for more direct collaboration.
• GitHub Copilot has evolved from a simple code completion tool to a more sophisticated AI assistant that provides suggestions and even entire code blocks.
• Users can accept or reject Copilot's suggestions, as they may not always be accurate.
• Copilot Chat is a feature that allows users to have a conversation with Copilot, providing a record of the interaction for future reference.
• Copilot can be used in various environments, including Visual Studio Code, and even in the cloud with the help of Codespaces.

Activating and Using GitHub Copilot

• To activate Copilot, users need to install the extension in their preferred editor, such as Visual Studio Code.
• The activation process is straightforward, involving searching for the extension in the marketplace and installing it.
• Copilot Chat can be identified by two chat boxes within the editor.
• GitHub Copilot can be invoked using keyboard shortcuts, such as Command Shift I or Command I on macOS, and Control Enter on Windows.

GitHub Copilot for Documentation and Debugging

• GitHub Copilot can be used to generate documentation for code.
• The command "for Slash doc" can be used to generate documentation for a specific section of code.
• GitHub Copilot will attempt to understand the context of the code and generate documentation based on its understanding.
• Users can edit the generated documentation to ensure accuracy.
• Debugging: GitHub Copilot can assist with debugging by suggesting fixes for code errors. It can identify common mistakes like missing commas or spaces and provide solutions.
• Unit Testing: Copilot can automatically generate unit tests for code, promoting good engineering practices and reducing the need for manual testing.

Contextual Awareness and Communication Conventions

• Contextual Awareness: Copilot leverages the context of open files and tabs to understand the code's purpose and provide relevant suggestions. This includes accessing relevant libraries and files for projects in languages like TypeScript.
• Communication and Naming Conventions: Clear communication and consistent naming conventions are crucial for effective use of Copilot. This involves using descriptive language and leveraging Copilot's suggestions for naming variables and functions.

Improving Programming Efficiency with GitHub Copilot

• The text discusses the use of GitHub Copilot, an AI-powered coding assistant, to improve programming efficiency.
• It highlights the importance of prompt engineering, which involves providing clear and concise instructions to Copilot to generate the desired code.
• The text emphasizes that Copilot can provide multiple suggestions, allowing users to choose the most suitable option based on their specific needs and context.
• It also mentions the ability to provide natural language comments in Spanish, which can enhance the user experience and facilitate communication with the tool.
• The text suggests that starting with a basic code structure and then using Copilot to complete the code can lead to better results.

Prompt Engineering for Effective Code Generation

• It introduces the concept of prompt engineering, which involves crafting effective prompts to guide Copilot in generating the desired code.
• The text provides an example of how to improve a prompt by providing more context, such as specifying the desired function and its purpose.
• It concludes by emphasizing the importance of prompt engineering in maximizing the effectiveness of GitHub Copilot.

Providing Context for AI Tools

• The speaker emphasizes the importance of providing sufficient context when using AI tools like GitHub Copilot to generate code.
• The speaker uses the example of creating a function to calculate the average grade, demonstrating how to provide context to Copilot to generate the desired code.

Documentation and Communication in Collaborative Projects

• The speaker highlights the importance of documentation and clear communication in collaborative projects, especially when using GitHub.
• The speaker mentions using GitHub Copilot to create a simple "rock, paper, scissors" game, showcasing how the tool can be used to quickly generate code based on a description.

GitHub Copilot for Project Setup and Best Practices

• The speaker suggests using the command "@wp.pl" to create a new workspace for the project, demonstrating how Copilot can assist with project setup.
• The speaker emphasizes that Copilot can help with best practices and project organization, leveraging its knowledge of common coding standards and conventions.

Using GitHub Copilot to Generate Code

• The speaker is discussing the use of GitHub Copilot to generate code.
• The speaker suggests using Copilot to create the basic structure of a program, including loops and requirements.
• The speaker provides an example of using Copilot to create a function that asks the user for input.
• The speaker emphasizes the importance of providing context to Copilot, such as the name of the project and the desired functionality.
• The speaker notes that Copilot can learn from the user's existing code and provide more relevant suggestions.

Copilot's Suggestions and Function Naming

• The speaker demonstrates how Copilot can generate a function called "preguntar" (Spanish for "ask") to prompt the user for input.
• The speaker highlights that Copilot can suggest names for functions and variables based on the context of the code.

Building a Rock, Paper, Scissors Game with Copilot

• The user is building a rock, paper, scissors game in the terminal.
• The user is using GitHub Copilot to help them write the code.
• Copilot is a probabilistic system, meaning that the code it generates can vary each time.
• The user is trying to understand the code that Copilot has generated.
• The user asks Copilot to explain the code in Spanish.
• Copilot provides a description of the code, but it is not working correctly.
• The user tries to fix the code by asking Copilot for help.
• Copilot is unable to fix the code.

Debugging with GitHub Copilot

• The speaker is working on a JavaScript project and encounters an error related to a missing module.
• The speaker uses GitHub Copilot to suggest a fix, which involves calling a function that was not previously called.
• The speaker attempts to run the code again, but encounters a new error indicating that the module cannot be found.
• The speaker realizes that they have closed and reopened the terminal, causing them to be in a different directory.
• The speaker returns to the correct directory and attempts to run the code again.
• The speaker encounters a different error and asks Copilot for assistance.
• The speaker decides to start over and close the project, as they are unable to resolve the issue.
• The speaker acknowledges that the error was likely due to a human error, but also notes that Copilot can be helpful in debugging more complex issues.

GitHub Copilot as a Coding Partner

• The speaker is demonstrating how to use GitHub Copilot to help with coding.
• The speaker is using Copilot to help them write code for a game of rock, paper, scissors.
• The speaker emphasizes that they are not coding alone and that Copilot is a valuable tool for programmers.

Introduction to Mario Rodriguez, Senior Vice President of Product at GitHub

• The speaker introduces Mario Rodriguez, a Senior Vice President of Product at GitHub, as a guest.
• Mario Rodriguez is described as a passionate advocate for education and a co-founder and co-president of a public school in the United States.
• The speaker highlights the importance of Mario Rodriguez's role in shaping the vision and strategy of GitHub products, including GitHub Copilot.

The Speaker's Journey in the Tech Industry

• The speaker has been working in the tech industry for 20 years and has been with their current company for 6 years.
• The speaker believes that software will be the driving force behind future advancements and wants to provide developers with the best tools to achieve this.
• The speaker emphasizes the importance of practice and building a strong foundation in software development.
• The speaker mentions that they were interested in technology after a positive experience with programming during an internship.
• The speaker's initial interests were in sports and entrepreneurship, but they ultimately pursued a degree in electrical engineering.
• The speaker's internship at Lu and Technologies involved programming in a language called Perel, which they no longer recommend learning.
• The speaker was inspired to pursue a career in software development after writing 10,000 lines of code in Perel within 10-12 weeks.
• The speaker began their career at Microsoft, working on game development.
• They started as a developer, specifically focusing on game testing and some game programming.
• After a year, they transitioned to a game producer role, where they focused on game design and level design.
• This experience led them to realize that there was more to game development than just coding, and they moved into product management in 2006 or 2007.
• They have remained in product management since then, working on various products and seeking opportunities for advancement.
• Their most recent role before becoming a product SVP at GitHub was working on GitHub Copilot.

The Speaker's GitHub Username and Experience with AI

• The speaker has a unique GitHub username, "Mario r," which is associated with their email address.
• They receive a new GitHub username every two or three years.
• The speaker was asked about their first experience with artificial intelligence.
• Machine learning (ML) has been around for a while, with companies like Google, Amazon, and Microsoft utilizing it for tasks like ad recommendations.
• The emergence of large language models (LLMs) has revolutionized the field, particularly due to their ability to understand and interact with human language.
• The speaker observed the capabilities of OpenAI's Codex LLM in 2021, noting its ability to solve a significant number of Python coding challenges, exceeding the performance of previous ML models.
• This breakthrough led to the development of GitHub Copilot, a tool that provides code suggestions and completions to developers, significantly speeding up the development process.

The Future of Software Development with AI

• The speaker believes that the rise of AI tools like Copilot will not replace developers but rather augment their capabilities, leading to an increase in the number of developers and engineers in the future.
• The speaker envisions a future where a significant portion of the human population will be involved in software development, with AI tools playing a crucial role in enabling this growth.
• The speaker argues that while everyone can learn to code, not everyone will become a professional developer.
• The speaker believes that tools like GitHub Copilot can help people who are not professional developers to create things they wouldn't be able to otherwise.
• The speaker uses the example of wanting to create a graph showing Uruguay's football team's wins and losses. They believe that GitHub Copilot could help them create this graph quickly and easily.
• The speaker believes that GitHub Copilot is not replacing developers, but rather augmenting their abilities.
• The speaker believes that GitHub Copilot can help people who are not professional developers to achieve their goals and make a difference in the world.

Importance of Passion, Creativity, and Perseverance

• The speaker emphasizes the importance of passion in choosing a career path, especially in technology.
• The speaker shares their personal experience of changing their career path after almost finishing university, highlighting the importance of following one's passion.
• The speaker believes that creativity is a key human trait that computers and AI lack.
• The speaker encourages people to be curious and creative in their pursuits.
• The speaker discusses the importance of perseverance, passion, and curiosity in any career path.
• The speaker emphasizes that success is not solely determined by financial gain, but by pursuing one's passions.

The Speaker's Personal Story and Influence

• The speaker shares their personal story, highlighting their father's experience as a political prisoner in Cuba.
• The speaker describes the hardships they faced during their childhood, including limited resources and their father's frequent arrests.
• The speaker's father instilled in them the importance of stoicism and maintaining a balanced perspective in life, even amidst challenges.
• The speaker mentions winning a lottery that allowed them to immigrate to the United States in 1994.
• The speaker's father, an engineer, secured employment at Pico after arriving in the United States.
• The speaker discusses their personal journey, including their father's influence and their own path to becoming a developer.
• The speaker emphasizes the importance of perseverance and maintaining a balanced perspective, referencing Stoicism.

"Los Gatos" and Support for Latinx Employees

• The speaker mentions a group called "Los Gatos" within their company, which aims to support Latinx employees and foster community.
• The speaker highlights the importance of real impact and genuine support for employees, emphasizing that "Los Gatos" is a genuine initiative.

Gratitude and Encouragement for the Audience

• The speaker expresses gratitude for the opportunity to share knowledge and connect with the audience, emphasizing the shared experience of immigration.
• The speaker encourages the audience to take away the message that everyone has the potential to achieve their goals.
• The speaker encourages viewers to embrace opportunities and not be afraid to try new things.
• The speaker expresses gratitude for the viewers' participation and emphasizes the importance of learning and continuous improvement.
• The speaker highlights the value of sharing knowledge and encourages viewers to connect with each other and the speaker through social media and the website.
• The speaker emphasizes the importance of taking action despite fear and encourages viewers to try new things, even if they are afraid.
• The speaker expresses appreciation for the support of viewers and emphasizes the importance of investing in Spanish-language resources.
• The speaker encourages viewers to share the video and resources with others to increase the impact and reach of the content.
• The speaker motivates viewers to work hard and pursue their goals, emphasizing that success requires effort and dedication.
• The speaker expresses excitement for the future and believes in the potential of the viewers to achieve great things.
• The speaker invites viewers to see the rest of the events that will be held.
• The speaker thanks the K Uruguay team.