github
237 TopicsAI Sparks: AI Toolkit for VS Code - from playground to production
Are you building AI-powered applications from scratch or infusing intelligence into existing production code and systems? AI Sparks is your go-to webinar series for mastering the AI Toolkit (AITK) for VS Code from foundational concepts to cutting-edge techniques. In this bi-weekly, hands-on series, we’ll cover: SLMs & Local Models – Test and deploy AI models and applications efficiently on your own terms locally, to edge devices or to the cloud Embedding Models & RAG – Supercharge retrieval for smarter applications using existing data. Multi-Modal AI – Work with images, text, and beyond. Agentic Frameworks – Build autonomous, decision-making AI systems. What will you learn from this session? Whether you're a developer, startup founder, or AI enthusiast, you'll gain practical insights, live demos, and actionable takeaways to level up your AI integration journey. Join us and spark your AI transformation! You can click here and register for the entire series on the reactor page Episode list You can also sign up for the individual episode and read about the topics covered using the following links: Feb 13 th 2025 – Introduction to AI toolkit and feature walkthrough In In this episode, we’ll introduce the AI Toolkit extension for VS Code—a powerful way to explore and integrate the latest AI models from OpenAI, Meta, Deepseek, Mistral, and more. With this extension, you can browse state-of-the-art models, download some for local use, or experiment with others remotely. Whether you're enhancing an existing application or building something new, the AI Toolkit simplifies the process of selecting and integrating the right model for your needs. Feb 27 th 2025 – A short introduction to SLMs and local model with use cases In this episode, we’ll explore Small Language Models (SLMs) and how they compare to larger models. SLMs are efficient, require less compute and memory, and can run on edge devices while still excelling at a variety of tasks. We’ll dive into the Phi-3.5 and Phi-4 model series and demonstrate how to build a practical application using these models. Mar 13 th 2025 – How to work with embedding models and build a RAG application In this episode, we’ll dive into embedding models—important tools for working with vector databases and large language models. These models convert text into numerical representations, making it easier to process and retrieve information efficiently. After covering the core concepts, we’ll apply them in practice by building a Retrieval-Augmented Generation (RAG) app using Small Language Models (SLMs) and a vector database. Mar 27 th 2025 – Multi-modal support and image analysis In this episode, we’ll dig deeper into multi-modal capabilities of local and remote AI models and use visualization tools for better insights. We’ll also dive into multi-modal support in the AI Toolkit, showcasing how to process and analyze images alongside text. By the end, you’ll see how these capabilities come together to enhance powerful AI applications. Apr 10 th 2025 – Evaluations – How to choose the best model for you applications needs In this episode, we’ll explore how to evaluate AI models and choose the right one for your needs. We’ll cover key performance metrics, compare different models, and demonstrate testing strategies using features like Playground, Bulk Run, and automated evaluations. Whether you're experimenting with the latest models or transitioning to a new version, these evaluation techniques will help you make informed decisions with confidence. Apr 24 th 2025 – Agents and Agentic Frameworks In this episode, we’ll explore agents and agentic frameworks—systems that enable AI models to make decisions, take actions, and automate complex tasks. We’ll break down how these frameworks work, their practical applications, and how to build and integrate them into your projects. By the end, you’ll have a clear understanding of how to build and leverage AI agents effectively. We will explore how to use and build agentic frameworks using AI Toolkit. Resources AI toolkit for VSCode - https://aka.ms/AIToolkit AI toolkit for VSCode Documentation - https://aka.ms/AIToolkit/doc Building Retrieval Augmented Generation (RAG) apps on VSCode & AI Toolkit Understanding and using Reasoning models such as DeepSeek R1 on AI toolkit - Using Ollama and OpenAI, Google and Anthropic hosted models with AI toolkitConstruindo uma Aplicação Web de IA com Python e FastAPI usando o GitHub Copilot
Aprenda a desenvolver uma API moderna em Python usando FastAPI e GitHub Copilot, com base na apresentação do GitHub Copilot Bootcamp. Descubra como criar um CRUD completo com boas práticas e acelerar seu desenvolvimento usando IA.80Views0likes0CommentsMicrosoft's Student Opportunities: A Gateway to Professional Growth
Are you a student looking to give your career in tech a boost? Look no further than Microsoft's student opportunities. From scholarships to internships, Microsoft provides a range of programs designed to help students develop their skills, gain practical experience, and build connections in the industry. In this article, we'll explore Microsoft's opportunities and events, and how they can be the gateway to professional growth for students seeking a career in technology.24KViews3likes3CommentsEngenharia de Prompt com o GitHub Copilot
No mundo da tecnologia, a engenharia de prompt está se tornando uma habilidade importante para desenvolvedores que utilizam ferramentas de inteligência artificial, como o GitHub Copilot. Nesta sessão, explora-se como o GitHub Copilot pode ser utilizado para aumentar a produtividade e a eficiência no desenvolvimento de software. Neste artigo, são reunidos alguns recursos complementares da primeira sessão do bootcamp. Antes de seguir, é importante lembrar os recursos disponíveis para todas as pessoas participantes do Bootcamp: Registre-se e receba as gravações das aulas do bootcamp GitHub Copilot Challenge: participe do desafio de aprendizagem e ganhe uma badge digital GitHub Copilot GRATUITO no Visual Studio Code Participe da Comunidade Azure AI no Discord Utilize o cupom de desconto da sessão para fazer uma certificação do GitHub GitHub Copilot na prática O GitHub Copilot é uma ferramenta de inteligência artificial que apoia desenvolvedores na escrita de código de forma mais rápida e eficiente. Ele oferece sugestões de código em tempo real, com base no contexto do projeto. O GitHub Copilot pode ser utilizado nas versões de extensão e chat para o VSCode, como uma extensão para o Azure (GitHub Copilot for Azure) e CLI (linha de comando). No vídeo a seguir, você vai aprender a utilizar o GitHub Copilot para atualizar um projeto de API em Python. A engenharia de prompt com o GitHub Copilot representa uma evolução significativa na forma como desenvolvedores interagem com ferramentas de IA. Ao seguir os princípios de IA responsável e utilizar os recursos do GitHub Copilot, é possível alcançar um desenvolvimento de software mais eficiente e ético. Nota: Cada aula do GitHub Copilot Bootcamp Brasil inclui um código de 64% de desconto para um exame de certificação do GitHub, válido por 4 dias. Assista à aula para conhecer as políticas e utilize o voucher dentro do prazo.333Views1like0CommentsHow Reasoning Models are transforming Logical AI thinking
Introduction Reasoning models are a new category of specialized language models. They are designed to break down complex problems into smaller, manageable steps and solve them through explicit logical reasoning (This step is also called “thinking”). Unlike general-purpose LLMs which might generate direct answers, reasoning models are specifically trained to show their work and follow a more structured thought process. Some models don’t show their logical reasoning phase while others explicitly show their logical reasoning phase. The reasoning phase shows how the model can break down the problem stated into smaller problems (Decomposition), try different approaches (Ideation), choose the best approaches (validation), reject invalid approaches (possibly backtracking) and finally choose the best answer (execution/solving). Reasoning models like OpenAI’s o1, o1-mini, o3-mini, and DeepSeek-R1 are available in the AI Toolkit for VS Code model catalog, Azure AI Foundry model catalog as well as online for free usage (rate-limited) in the Github Marketplace for models. There are some key differences between reasoning models and general-purpose LLMs. These are summarized in the following table. Summary Table Feature Reasoning Models General Purpose LLMs Primary Purpose and Strengths Explicit step-by-step problem solving and logical reasoning General-purpose text generation and understanding Problem-Solving Approach Break down problems into smaller sub-steps and shows intermediate reasoning (“thinking” phase) Show the output directly without showing intermediate steps. Mostly pattern based next token prediction Output Structure Highly structured, with clear delineation between reasoning steps More flexible and conversational, may mix reasoning with other content Training Specifically trained on step-by-step reasoning tasks and formal logic Trained on a diverse corpus of text data with many different writing styles and purposes Usage of Chain-of-Thought Built into the core architecture and training process Can use chain-of-thought prompting but not inherently designed for it. Must specifically ask for this in the prompt. Interpretability and Error Detection Detecting errors is easier due to explicit reasoning steps Black-box nature makes reasoning for output harder to trace Computational Efficiency May require more computing resources due to step-by-step processing, especially at inference time Relatively lower computing requirements at inference time and usually more efficient for direct responses Latency for response May be slower for simple tasks that don't require explicit reasoning May struggle with complex logical problems requiring step-by-step analysis and interpretation. Examples OpenAI o1, o1-mini, o3-mini, DeepSeek-R1 GPT-4o, Llama3.3, Claude Use cases Scientific reasoning, legal analysis, complex problem-solving, AI agents with multi-step decision-making Chatbots, Text summarization, content generation, Q&A, code completion Since we know that reasoning models excel at logical step-by step problem solving, we will give them tasks. We will be using DeepSeek-R1 from the GitHub model marketplace and AI Toolkit for VSCode for this analysis. Task 1 – Solve a logical puzzle We will use a variation of the river crossing problem that has some interesting constraints and needs some level of backtracking which humans excel at. This is the prompt that we will use is Can you solve this logic puzzle and show it as a diagram "A farmer with a wolf, a goat, and a cabbage must cross a river by boat. The boat can carry only the farmer and a single item. If left unattended together, the wolf would eat the goat, or the goat would eat the cabbage. How can they cross the river without anything being eaten?" AI Toolkit Session follows below: User Can you solve this logic puzzle and show it as a diagram "A farmer with a wolf, a goat, and a cabbage must cross a river by boat. The boat can carry only the farmer and a single item. If left unattended together, the wolf would eat the goat, or the goat would eat the cabbage. How can they cross the river without anything being eaten?" DeepSeek-R1 <think> Okay, so the user wants me to solve this logic puzzle about the farmer crossing the river with a wolf, goat, and cabbage. Let me start by recalling the problem. The farmer can only take one item at a time in the boat. If left alone, the wolf eats the goat, and the goat eats the cabbage. The goal is to get everyone across safely. First, I need to break down the constraints. The boat can carry the farmer and one item. So each trip either the farmer goes alone or takes one item. The main issue is the forbidden pairs: wolf and goat can't be left alone, goat and cabbage can't be left alone. So whenever the farmer moves, the remaining items on either bank must not include these pairs. Let me think through the possible steps. Let's consider the initial state: all four (farmer, wolf, goat, cabbage) are on the left bank. The goal is to get all to the right bank. The first thought: if the farmer takes the goat first. Then left bank has wolf and cabbage. They are safe because wolf and cabbage don't interact. So after first trip, farmer and goat are on the right, wolf and cabbage on the left. Then the farmer goes back alone to the left. Now, the right bank has just the goat. Then the farmer can take either the wolf or the cabbage next. Suppose he takes the wolf. Then on the right bank would be wolf and goat. Oh no, that's a problem because the wolf would eat the goat. So that's forbidden. Alternatively, after taking the goat over and returning alone, the farmer could take the cabbage. If he takes the cabbage to the right bank, then left bank has wolf. Right bank has goat and cabbage. But when he takes the cabbage over, the goat is now on the right with the cabbage. If the farmer leaves them to go back, the goat would eat the cabbage. So that's not allowed either. Wait, this seems confusing. Let's track step by step. State 0: All on left (F, W, G, C). Right is empty. Step 1: Farmer takes goat to right. Now left has W, C; right has F, G. That's safe. Then Step 2: Farmer goes back alone to left. Now left has F, W, C; right has G. Step 3: Farmer takes either W or C. Suppose he takes W. Now right has F, W, G. Left has C. But when he takes W, he leaves G and W on the right? Wait, no. When farmer takes W to the right, after step 3, left has C, right has F, W, G. But if he leaves W and G on the right, that's a problem (wolf and goat). Wait, no, the farmer is there too. So actually, if the farmer is present, they can't eat. The problem occurs only when unattended. So when the farmer takes W to the right, he's with W and G on the right. Then he can leave W there and take G back? Wait, but that would complicate things. Wait, let's step through again. After step 2: left is F, W, C; right is G. Step 3: Farmer takes W to right. Left has C. Right has F, W, G. Since farmer is on the right, wolf and goat are not left alone. Then the farmer leaves W on the right, goes back with G. Wait, but if he leaves W on the right, then the right bank has W and G, but farmer is taking G back. Wait, no. If the farmer takes W to the right, then right bank now has W and G. But the farmer is there. So he can take W to the right bank, and then he stays there, but then he can't take G back. Wait, no. Wait, no. Let me correct this. If the farmer is taking the wolf from left to right, starting at left (F, W, C) and right (G). After moving W: Left has C (and no farmer), right has F, W, G. Wait, but left would have C alone, which is safe. Then the farmer is on the right with W and G. Then he has to leave either W or G to go back. But if he leaves W and G on the right, unattended, that's a problem. So he can't leave them. Thus, the farmer needs to take something with him. Wait, so step 3 alternatives: after step 2 (left has F, W, C; right has G), farmer takes cabbage to the right: Left becomes W (and no farmer), right has F, C, G. But then when he takes C to the right, the right bank would have C and G, which would be a problem if left unattended. Because farmer is on the right, so they are attended. Then he leaves C there, takes G back to left. But that seems steps going back and forth. This is getting a bit tangled. Let's try outlining possible valid moves. The key insight here is that the goat is the only item that can't be left with either wolf or cabbage. So the farmer must ensure that whenever the goat is on a bank without the farmer, there are no other dangerous items there. So, the strategy that typically works is: Take goat over first. Return alone. Take either wolf or cabbage over. Bring goat back. Take the other item (cabbage or wolf) over. Return alone. Take goat over again. Let me check this. Step-by-Step: Start: All on left (F, W, G, C) Take G to right. State: Left: W, C; Right: F, G. Safe, because Left has W and C (no conflict). Farmer returns to left alone. State: F, W, C | G. Farmer takes W to right. State: Left: C; Right: F, W, G. But on the right, when the farmer leaves W there, does he take G back? No. Wait, after bringing W to right, the farmer would have to leave something. If he takes W to the right and leaves it there while he goes back, then right has W and G. The farmer is on the way back, so they are left alone. That's a problem because wolf and goat would be together. Therefore, this is invalid. Hence, step 3 taking W leads to a problem. Ah, so to avoid that, after step 2, instead of taking W, the farmer should take C. Alternative Step 3: After returning, take C to right. Take C to right. State: Left: F, W; Right: G, C. But when he takes C to right, the farmer leaves left bank as W. Which is safe, just wolf alone. Right bank has F, C, G. But when he leaves C and G on the right (since farmer is there, they are safe). Wait, the farmer is present, so they don't eat. So he can leave them, then go back. So step 4: return alone. State: Left: F, W; Right: C, G. Wait, no. Let me track correctly: After Step 1: left: W, C; right: F, G. Step 2: return to left alone. Now left: F, W, C; right: G. Step 3: take C to right. After moving, left: W; farmer is taking C to right. So left becomes W and farmer is moving to right, so left has W alone (which is safe). Right now has F, G, C. But upon arrival, farmer is with G and C. So they are safe. Step 4: farmer returns to left alone. Now left: F, W; right: G, C. But on the left, F and W are there, which is okay. On right, G and C are unattended – that's a problem! Goat would eat cabbage. Wait, even though the farmer has left, he's on left now. So the right bank has G and C without the farmer. So that violates the conditions. So this path would result in the goat eating the cabbage. Hence invalid. Therefore, taking the cabbage on step 3 leads to a problem when returning. Therefore, neither taking W nor taking C works here. Hmm. So alternative approach: after step 2, when the farmer is on the left with W and C, instead of taking C or W, he needs to take the goat back. Wait, but that seems to reverse step 1. That can't help. Wait, maybe the key is that after taking the goat over first, then the farmer must bring it back later to avoid leaving dangerous pairs. Let's try a different sequence: Take goat to right. Left: W, C; Right: F, G. Return alone to left. Left: F, W, C; Right: G. Take wolf to right. Left: C; Right: F, W, G. But as before, after this, farmer is on right with W and G. If he leaves W there and takes G back, then right has W alone, which is okay. So: Take goat back to left. Left: F, C, G; Right: W. Now left has C, G, F; right has W. Then take cabbage to right. Left: G; Right: F, W, C. Then return alone to left. Take goat to right. Now all are on right. Done. This seems to work. Let's verify each step: Take G over. Left: W, C (safe); Right: F, G. Return alone. Left: F, W, C; Right: G. Take W over. Left: C (safe). Right: F, W, G. Farmer is present, so W and G safe. Take G back. Left: F, G, C; Right: W (safe). Wait, on left, when farmer takes G back, left now has G and C with farmer. So when he arrives, left has F, G, C; right has W. But then when he leaves again, left would have G and C, which would be a problem (goat eats cabbage). Wait, no. After step 4, after taking G back, the state is: Left: F, G, C (farmer is there); Right: W. Then the farmer leaves to take C over: Step 5: Take C over. Left: G (alone on left? Wait, no. Wait, if farmer takes C to right, he leaves G on left. Wait, no. Let's see: After step 4: farmer is on left with G, having brought G back from the right. So left has F, C, G; right has W. Then, step 5: farmer takes C to right. So left becomes F, G on left? Wait no: starting from: Left: F, C, G; Right: W. When farmer takes C to right, farmer and C move to right. Left becomes G alone, but without the farmer. That's bad because goat alone on left but nothing else. So it's safe. Wait, goat alone is okay. Goat on left alone is harmless. So after step 5, right has F, C, W. Left has G. But the farmer is on the right. Then step 6: farmer returns alone to left. Left: F, G; Right: W, C. Step 7: Take G to right. Now all on right: F, G, W, C. Done. But let's check at each step: Step 1: left (W, C), right (F, G) - safe. Step 2: left (F, W, C), right (G). Farmer is on left. Step 3: take W to right. Left has C (safe). Right has F, W, G. Farmer there. Step 4: take G back. Left: F, G, C (farmer there). Right: W. So now right has W alone, safe. Step 5: take C to right. Left: G alone (safe). Right: F, W, C. Farmer there. Step 6: return alone. Left: G (farmer on right). So G alone on left is safe. Wait no, after step 6: farmer returns to left, now left has F, G; right has W, C. Farmer is on left with G, right has W and C (separately, so no problem). Safe. Step 7: take G to right. Now all on right. Done. Yes, that works. So the steps are: Farmer and Goat → right. Farmer ← left. Farmer and Wolf → right. Farmer and Goat ← left. Farmer and Cabbage → right. Farmer ← left. Farmer and Goat → right. Each step maintains safety on both banks. Hence the solution is this sequence. Then, to represent it as a diagram, perhaps using a flowchart showing each state with left and right banks, connected by arrows indicating the steps. </think> To solve the puzzle, follow these steps systematically, ensuring that no dangerous pairs are left unattended: Cross with Goat: Farmer takes the Goat to the right bank. Left: Wolf, Cabbage | Right: Farmer, Goat Return Alone: Farmer returns to the left bank alone. Left: Farmer, Wolf, Cabbage | Right: Goat Cross with Wolf: Farmer takes the Wolf to the right bank. Left: Cabbage | Right: Farmer, Wolf, Goat Return with Goat: Farmer brings the Goat back to the left bank. Left: Farmer, Goat, Cabbage | Right: Wolf Cross with Cabbage: Farmer takes the Cabbage to the right bank. Left: Goat | Right: Farmer, Wolf, Cabbage Return Alone: Farmer returns to the left bank alone. Left: Farmer, Goat | Right: Wolf, Cabbage Final Trip with Goat: Farmer takes the Goat to the right bank. Left: (empty) | Right: Farmer, Wolf, Goat, Cabbage Diagram (simplified as a flowchart): <>Plain text Start: F, W, G, C | [Left] → [Right] (empty) Take G ➔ [W, C] | [F, G] Return ↵ [F, W, C] | [G] Take W ➔ [C] | [F, W, G] Take G ↵ [F, G, C] | [W] Take C ➔ [G] | [F, W, C] Return ↵ [F, G] | [W, C] Take G ➔ [ ] | [F, W, G, C] All cross safely! 🚣✨ Token used: 3278 (11693 characters) Conclusion As you can see it has arrived at the right answer, and you can see it taking the following steps Reformulating the problem as a set of constraints Adding symbols for each of the interacting entities. Then it takes a series of steps to see if they satisfy the constraints and discards ones that do not. Then it layers each of these steps to build an efficient solution based on backtracking and trial-and-error. Finally, once it has a probable answer, it crosschecks again on the constraints and draws the diagram as we instructed it (with symbols for each). A nice touch is that it has also shown the answer in human readable text before to make it easy to follow. Task 2 – Explain obfuscated code Another scenario that we can often face in our lives as programmers is stumbling across a piece of code in our codebase that does something clever but alas, it has no documentation. Sounds familiar? Let's see how DeepSeek-R1 can tackle this task. This is the prompt we will use What does this program do? What language is it in? And what are such programs called? s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" AI toolkit Session transcript follows: User What does this program do? What language is it in? and what are such programs called? s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" DeepSeek-R1 <think> Okay, so I need to figure out what this program does, what language it's written in, and what such programs are called. Let me start by looking closely at the code. First, the code starts with s='s=\47%s\47;printf "$s" "$s"'; followed by printf "$s" "$s". Hmm, the initial part is assigning a string to variable s. The string seems to have some escape characters. The \47 is probably an octal escape in some programming language. Since 47 in octal is 39 in decimal, which is the ASCII code for a single quote ('). So s='s=\47%s\47;printf "$s" "$s"' would actually translate to s='s='%s';printf "$s" "$s"'. Wait, let me check that. So the single quote in the string is escaped using \47, which would allow the string to include a single quote without closing the string prematurely. So the value of s is a string that starts with 's=' followed by a single quote (from \47), then %s, then another single quote (again \47), followed by ;printf "$s" "$s". Then, the next part is printf "$s" "$s". So they're using printf with the format string stored in s and the argument is the same s variable. Let's think step by step. Let's substitute s into the printf command. The s variable is: 's=\47%s\47;printf "$s" "$s"'. When printf is executed, the format string is s, which includes a %s placeholder. The arguments passed to printf are "$s", so the first %s in the format string is replaced by the value of s. Wait, but in the first line, the code is written as s='s=\47%s\47;printf "$s" "$s"'; which when interpreted would need to handle the single quotes correctly. Let me parse this. The assignment is s='...' where the content inside the single quotes includes \47, which as I thought is a single quote. So the actual value of s when assigned is: s='s='%s';printf "$s" "$s"'. Wait, maybe not. Let me think again. The original assignment is s='s=\47%s\47;printf "$s" "$s"'; So inside the single-quoted string, \47 is an escape sequence. But in some shells like Bash, inside single quotes, escapes are not processed unless the single quote is closed. Wait, but the code is using printf, which is a shell command, suggesting maybe this is a shell script? But in the shell, single quotes don't allow escaping, except for the single quote itself by using '''. Wait, but maybe the code is in a different language where \47 represents a single quote. For example, in C, octal escapes are allowed in strings. Wait, but the code uses printf with "$s" as the format and "$s" as the argument. Let me try to simulate this. Let's suppose s has the value: s='s=\47%s\47;printf "$s" "$s"'. Then, when the printf is executed: printf "$s" "$s". So substituting variables, the format string is the value of s, which is 's=\47%s\47;printf "$s" "$s"'. Then, the first argument is also s. So the %s in the format will be replaced by the value of the first argument, which is s. Wait, but the substitution happens inside the format string. Let me try writing it out. Let's say s is the string 's=\47%s\47;printf "$s" "$s"'. Then, when we do printf "$s" "$s", the %s in the format string will be replaced by the argument "$s". So the output would be the format string with %s replaced by s's value. Let's compute that. Replacing the %s with the value of s gives: s='\47 followed by the value of s (which includes \47%s\47) followed by \47'; then ;printf "$s" "$s". Hmm, that's getting a bit tangled. Maybe this program is a quine? A quine is a program that outputs its own source code. So perhaps this code, when run, generates its own source as output. Let's test this idea. Let's see what the output would be. The initial value of s is s='s=\47%s\47;printf "$s" "$s"'. Then printf is called with the format string being s and the argument being s. So substituting, the format string is 's=\47%s\47;printf "$s" "$s"', and the %s will be replaced with the same string. Let's do that: replacing %s with the value of s (i.e., the string 's=\47%s\47;printf "$s" "$s"') into the format string. So the result would be s='\47's=\47%s\47;printf "$s" "$s"'' followed by ;printf "$s" "$s". Wait, no. Let me actually plug in the substitution. The original s is: s=\47%s\47;printf "$s" "$s" So when we replace the %s in the format with the s itself, the line becomes s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" Wait, but wait. Let me process this step by step. Let me consider what happens when the printf command runs. The first printf is given the format string in variable s, which is 's=\47%s\47;printf "$s" "$s"' (the outer single quotes in the assignment are part of the shell syntax, but the actual content is s=\47%s\47;printf "$s" "$s"). Wait, no. Let's clarify: in shell scripting, when you assign s='some string', the variable s holds 'some string' without the single quotes. Wait, no. Wait in shell scripting, variable assignments like s='value' assign s the literal 'value', with the quotes used to delimit the string but not part of the value. So in this code, s is assigned the string s=\47%s\47;printf "$s" "$s" where \47 is a literal \ followed by 47, but when interpreted inside a shell, what's the actual value? Wait, but shell does not interpret octal escapes in normal strings unless using certain commands like echo with flags. Oh, but here they're using printf, which does interpret backslash escapes. Wait, but variable assignment in shell doesn't process escapes unless in certain contexts. So if s is assigned as s='s=\47%s\47;printf ...', then \47 is literally a backslash followed by 4 and 7, not as an octal escape. Hmm, that complicates things. So in that case, when the printf is executed, the format string would have \47 which printf would interpret as octal 47 (if the format string is processed with printf's escape handling). Wait, but the shell's printf command processes the escapes in the format string. Wait, the shell's printf uses the format string and replaces escape sequences in it if they are present. But in this code, the format string is stored in $s, which is being passed as the first argument to printf, and the second argument is $s. Let's take an example. Let's say s is the string 's=\47%s\47;printf "$s" "$s"'. Then, when you run printf "$s" "$s", the first argument (the format) is "s=\47%s\47;printf "$s" "$s"" and the second argument is the same string. So the %s in the format will be replaced by the second argument. Wait, but the format has \47 which, when interpreted by printf, is octal 47, which is a single quote. So in the format string, s=\47%s\47 becomes s='%s' after replacing \47 with '. Then the %s is replaced by the argument, which is the original s value. Wait, this is getting a bit confusing. Maybe I should write down the actual evaluation step by step. Let me try to reproduce the program and see what the output is. The program is: s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" Assuming this is a shell script (Bash, perhaps), let's parse this. The first part assigns the variable s to the string 's=\47%s\47;printf "$s" "$s"'. Then, the printf command is executed with the format string "$s" and the argument "$s". So, expanding variables, the printf command becomes: printf 's=\47%s\47;printf "$s" "$s"' "$s" So the format string is 's=\47%s\47;printf "$s" "$s"' with %s, and the argument is the value of s (same string). Now, when printf processes the format string, it replaces the %s with the argument. But the format string includes \47, which in the printf command is interpreted as an octal escape for the character with octal value 47, which is 39 in decimal, which is ASCII for '. Therefore, \47 becomes ', so the format string would be 's='%s';printf "$s" "$s"'. So substituting the argument (which is s='s=\47%s\47;printf "$s" "$s"') into the %s: s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" Wait, but substituting the value of s into the format, which is now 's=%s' with the %s being replaced by s, which includes the same string. Wait, this seems like a quine, where the program generates its own source code. When you run the printf command, it replaces %s with the original s variable, but within a structure that reconstructs the original program. Let me try creating the output step by step. The original code is: s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" The printf command is: printf "s=\47%s\47;printf "$s" "$s"" "$s" Because the $s in the format is replaced by the variable s. Wait, but variables inside single quotes are not expanded. Wait, no, in the assignment, the string is in single quotes, so variables inside aren't expanded. Then in the printf "$s" "$s", the $s are in double quotes, so they get expanded. Wait, but the first line is s='s=\47%s\47;printf "$s" "$s"'; Then, the second command is printf "$s" "$s". Because $s is in double quotes, the shell will replace $s with its value, which is 's=\47%s\47;printf "$s" "$s"'. Wait, but not exactly, because in the assignment, the variable s is assigned the literal string between the single quotes. Let's clarify with an example: suppose s is assigned to the literal characters s=\47%s\47;printf "$s" "$s". Because the assignment is s='...', so the single quotes around the value when assigning mean that everything inside is literal, so \47 is just three characters: backslash, 4, 7. But when you use printf "$s" "$s", the shell first substitutes the $s variables. So the first argument to printf is the value of s: s=\47%s\47;printf "$s" "$s". Then the second argument is the same. The printf command now has a format string where %s is present. Also, in the format string, there are \47 sequences. But when the shell's printf processes the format string, it will interpret backslash escapes. So the \47 in the format string, as parsed by printf, represents an octal escape code for the single quote. So let me reconstruct the formatted output: The format string after substitution is "s=\47%s\47;printf "$s" "$s"" (wait, not exactly, because variables inside double quotes are expanded, but inside the format string here it's the literal s value). Maybe I need to consider that when the line is parsed, the printf command receives the expanded variables. Wait, step by step: Original code: s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" The first part assigns s to the string "s=\47%s\47;printf "$s" "$s"" (but with the $s inside the string being literal because of the single quotes). So after assignment, the variable s contains the literal characters: s=\47%s\47;printf "$s" "$s" Now, the printf command is executed as printf "$s" "$s". The shell replaces $s with its value, so the command becomes: printf 's=\47%s\47;printf "$s" "$s"' 's=\47%s\47;printf "$s" "$s"' Notice that the first argument is the format string: 's=\47%s\47;printf "$s" "$s"' But when printf processes this format string, it replaces the \47 with the octal value 47, which is a single quote. So the format string becomes: s='%s';printf "$s" "$s" Then, the %s is replaced with the second argument: 's=\47%s\47;printf "$s" "$s"' So the resulting output is: s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" Which is exactly the original code. Therefore, this program outputs its own source code. Therefore, it's a quine. Now, regarding the language: this uses printf, which is a shell command. The syntax of variable assignment and the use of quotes indicates that it's a shell script. The initial assignment uses single quotes to define the variable s, then uses printf in a way that constructs the output by embedding the variable's content. Therefore, this code is written in a shell scripting language, probably Bash or similar. Such programs that produce their own source code as output are called quines. So putting this all together: the program is a quine written in a shell scripting language (like Bash) that prints its own source code when executed. </think> The program is a quine, which is a program that outputs its own source code when executed. It is written in shell script (specifically compatible with Bourne shell or Bash). Here's how it works: Variable Assignment: The string s='s=\47%s\47;printf "$s" "$s"' assigns the variable s with a format string containing \47 (an octal escape for the single quote '). The %s acts as a placeholder for string substitution. Print Command: The printf "$s" "$s" uses the value of s as both the format string and the argument. The shell expands $s, replacing %s with the original value of s and interpreting \47 as '. Self-Referential Output: When executed, the program constructs its identical source code by substituting %s with the escaped version of s, reproducing the original code. Language: Shell script (Bash/Bourne-like shell). Program Type: Quine. Output: <>Plain text s='s=\47%s\47;printf "$s" "$s"';printf "$s" "$s" This matches the original code, confirming it's a quine. Token used: 3376 (12922 characters) Conclusion So, as you can see from the example above, the model followed a series of logical steps to arrive at the answer It examines the code, simulates some parts of the code to figure out what it does At the same time, it also sees certain functions such as print and single quotes and guesses that the language is bash scripting It then simulates the entire program and realizes that code output is same as the generating code. It knows from its world knowledge and training that such programs are called quines. Armed with all this information, it validates the entire chain of thought to be sure of its answer and then finally formulates and prints the answer. Task 3 – Solve an optimization problem with constraints In everyday life, we often must solve problems when we have budgets and cost constraints or want to maximize revenue or profit or any other such numerical target. We might have metrics to measure them and might guess some relationships between different variables. For example, when we have a set marketing budget and different channels such as online ads, Linkedin/X posts and emails to send to prospective attendees, how do we distribute this budget between different channels with slightly different audiences and efficacy of reach and signs ups (say for an online seminar or a conference). Let us look at a similar problem but in the manufacturing domain. This is the prompt that we will give. I want to sell a certain number of items (children's toys) in order to maximize my profit. Market research tells me that if I set the price at $1.50, I will be able to sell 5000 items, and for every 10 cents I lower the price below $1.50 I will be able to sell another 1000 items. Suppose that my manufacturing setup costs ( “start-up costs” ) total $2000, and the manufacturing cost per item ( “marginal cost” ) is $0.50. Find the price to set per item and the number of items that I need to sell in order to maximize my profit and also determine the maximum profit I can get. AI Toolkit Session follows: User I want to sell a certain number of items (children's toys) in order to maximize my profit. Market research tells me that if I set the price at $1.50, I will be able to sell 5000 items, and for every 10 cents I lower the price below $1.50 I will be able to sell another 1000 items. Suppose that my manufacturing setup costs ( “start-up costs” ) total $2000, and the manufacturing cost per item ( “marginal cost” ) is $0.50. Find the price to set per item and the number of items that I need to sell in order to maximize my profit and also determine the maximum profit I can get. Deepseek-R1 <think> Okay, let's try to figure out how to maximize the profit for selling these children's toys. Hmm, so the problem gives me some information about price, quantity sold, start-up costs, and marginal cost. I need to model this mathematically and then find the optimal price and quantity. Let's break it down step by step. First, the initial price is $1.50, and at that price, they can sell 5000 items. Then, for every 10 cents they lower the price below $1.50, they can sell an additional 1000 items. So, the price decrease affects the quantity sold. I need to model the relationship between price and quantity sold. Let me denote the number of times they lower the price by 10 cents as x. So, if x = 0, the price is $1.50, and quantity sold is 5000. If x = 1, the price is $1.40, and quantity sold is 5000 + 1000*1 = 6000. If x = 2, price is $1.30, quantity is 7000, and so on. So, in general, if they lower the price x times, the price becomes: Price = 1.50 - 0.10x dollars. And the quantity sold becomes: Quantity = 5000 + 1000x items. But x has to be a non-negative integer, right? Wait, or can x be any non-negative real number? The problem says "for every 10 cents I lower the price below $1.50 I will be able to sell another 1000 items." So, is the 10 cent decrease a discrete step or can we consider a continuous decrease? Hmm, the problem doesn't specify that we have to keep the price in multiples of 10 cents. Maybe it's continuous. But the phrasing is "for every 10 cents," which suggests that each 10 cent decrease gives an additional 1000 items. But maybe we can model it as a linear relationship. Let me check. If the price drops by 10 cents, quantity increases by 1000. So, per 1 cent decrease, quantity increases by 100 items? Wait, 10 cents correspond to 1000 items, so 1 cent decrease would correspond to 1000/10 = 100 items per cent. So, we can model the quantity sold as a linear function of the price decrease. Let me define the price p as a variable, then express the quantity sold in terms of p. Alternatively, if we consider p in dollars, the relationship is: when p decreases by $0.10, quantity increases by 1000. So, if we let p = 1.50 - 0.10x, then quantity q = 5000 + 1000x. Solving for x in terms of p: x = (1.50 - p)/0.10. Then plug into q: q = 5000 + 1000*(1.50 - p)/0.10. Let me compute that. q = 5000 + 1000*(1.50 - p)/0.10 = 5000 + 1000*( (1.50 - p) / 0.10 ). Let's compute the coefficient: 1000 / 0.10 = 10,000. So, q = 5000 + 10,000*(1.50 - p) = 5000 + 15,000 - 10,000p = 20,000 - 10,000p. Wait, that seems like a linear demand function where q = 20,000 - 10,000p. Let me check that. When p = 1.50, q = 20,000 - 10,000*(1.50) = 20,000 - 15,000 = 5000, which matches. If p decreases by $0.10 to 1.40, then q = 20,000 - 10,000*(1.40) = 20,000 - 14,000 = 6,000, which is 5000 + 1000. So that works. Therefore, the quantity sold is a linear function of price: q = 20,000 - 10,000p. So, we can model this as a linear demand curve. Alternatively, maybe they want us to model x as a continuous variable, so that x can take any non-negative real value, meaning that the price can be any value below $1.50, not necessarily in increments of 10 cents, and the quantity sold would adjust accordingly. So, if you lower the price by 5 cents, then you can sell 500 more items. But does the problem allow that? The market research says "for every 10 cents I lower the price below $1.50 I will be able to sell another 1000 items." So, it's a rate: 10 cents decrease => 1000 items more. So, that is $0.10 decrease corresponds to 1000 items increase. Therefore, the slope of the demand curve is dq/dp = -1000 / 0.10 = -10,000. So, the demand function is linear with slope -10,000. So, starting from p = 1.50, q = 5000. So, the equation is q = -10,000(p - 1.50) + 5000 = -10,000p + 15,000 + 5000 = 20,000 - 10,000p, which is the same as before. So, yes, continuous. Therefore, the quantity sold as a function of price is q(p) = 20,000 - 10,000p. Alternatively, we can write p as a function of q. Let's solve for p: q = 20,000 - 10,000p => 10,000p = 20,000 - q => p = (20,000 - q)/10,000 => p = 2 - q/10,000. So, the inverse demand function is p = 2 - q/10,000. Okay, so total revenue R is pq. So, R = pq = (2 - q/10,000)*q = 2q - q²/10,000. Total cost C consists of fixed costs (start-up costs) of $2000 and variable costs of $0.50 per item. So, total cost is C = 2000 + 0.50q. Therefore, profit π is total revenue minus total cost: π = R - C = (2q - q²/10,000) - (2000 + 0.50q) = 2q - q²/10,000 - 2000 - 0.50q Simplify: π = (2q - 0.50q) - q²/10,000 - 2000 = 1.50q - q²/10,000 - 2000. So, profit as a function of quantity q is π(q) = - (q²)/10,000 + 1.50q - 2000. To maximize profit, we need to find the value of q that maximizes π(q). Since this is a quadratic function with a negative coefficient on q², it opens downward, so the maximum is at the vertex. The vertex of a quadratic function ax² + bx + c is at x = -b/(2a). Here, a = -1/10,000 and b = 1.50. Therefore, the quantity that maximizes profit is: q = -b/(2a) = -1.50 / (2*(-1/10,000)) = -1.50 / (-2/10,000) = (1.50 * 10,000)/2 = (15,000)/2 = 7,500. So, the profit-maximizing quantity is 7,500 items. Then, the corresponding price can be found from the inverse demand function p = 2 - q/10,000 = 2 - 7,500/10,000 = 2 - 0.75 = $1.25 per item. Let me verify that. So, at q = 7500, p = $1.25. Then, total revenue R = p*q = 1.25 * 7500 = $9,375. Total cost C = 2000 + 0.50*7500 = 2000 + 3750 = $5,750. Profit π = 9,375 - 5,750 = $3,625. Is this the maximum profit? Let's check another point. Suppose q = 7000. Then, p = 2 - 7000/10,000 = 2 - 0.7 = $1.30. Revenue = 1.30 * 7000 = $9,100. Cost = 2000 + 0.50*7000 = 2000 + 3500 = $5,500. Profit = 9,100 - 5,500 = $3,600, which is less than $3,625. Similarly, q = 8000, which would be p = 2 - 8000/10,000 = 2 - 0.8 = $1.20. Revenue = 1.20 * 8000 = $9,600. Cost = 2000 + 0.50*8000 = 2000 + 4000 = $6,000. Profit = 9,600 - 6,000 = $3,600, again less than $3,625. So, 7500 seems to be the maximum. Alternatively, since we derived this using calculus (vertex of parabola), it's correct. But just to check. Alternatively, if we take derivative of π(q) with respect to q: dπ/dq = 1.50 - 2q/10,000. Set derivative equal to zero: 1.50 - (2q)/10,000 = 0 => (2q)/10,000 = 1.50 => q = (1.50 * 10,000)/2 = 7,500. So, same result. Wait, but in the original problem, they mention that for every 10 cents decrease, you can sell another 1000 items. So, starting at $1.50 with 5000 items. Then, decreasing by 10 cents increments gives 1000 more each time. So, how does it work at 7500 items? That would be an increase of 2500 items from the original 5000. Since each 10 cents decrease gives 1000 more, 2500 would be 2.5 times 10 cents. So, decrease price by 25 cents? Wait, but in the model we had, q = 20,000 - 10,000p. So, if p is $1.25, which is a $0.25 decrease from $1.50, then yes, (1.50 - 1.25)/0.10 = 2.5, so x=2.5. Then, quantity sold is 5000 + 1000*2.5 = 7500. So, even though x is 2.5, which is not an integer, the problem didn't specify that the price has to be in 10-cent increments, so allowing x to be a real number. So, in reality, you could set the price at $1.25, even though it's a 25-cent decrease, which is 2.5 times 10 cents. So, the model allows for continuous variables, which is fine. So, the conclusion is that the optimal price is $1.25 per item, selling 7500 items, resulting in a maximum profit of $3,625. Wait, let me just confirm profit calculation once again: Revenue: 7500 * 1.25 = 7500 * 1 + 7500 * 0.25 = 7500 + 1875 = 9375. Cost: 2000 + 7500 * 0.50 = 2000 + 3750 = 5750. Profit: 9375 - 5750 = 3625. Yes, that's $3,625. So, all checks out. So, the answer is price of $1.25, quantity of 7500, profit of $3,625. Final Answer The optimal price is \boxed{1.25} dollars per item, the number of items to sell is \boxed{7500}, and the maximum profit is \boxed{3625} dollars. </think> To determine the optimal price, quantity, and maximum profit for selling children's toys, we start by modeling the relationship between price and quantity sold. The market research indicates that for every $0.10 decrease in price below $1.50, the quantity sold increases by 1000 items. This results in a linear demand function. Demand Function: The price ( p ) and quantity ( q ) are related by the equation: [ q = 20,000 - 10,000p ] Solving for ( p ) gives the inverse demand function: [ p = 2 - \frac{q}{10,000} ] Profit Function: Total revenue ( R ) is given by ( R = p \times q ): [ R = \left(2 - \frac{q}{10,000}\right) q = 2q - \frac{q^2}{10,000} ] Total cost ( C ) includes fixed costs of $2000 and variable costs of $0.50 per item: [ C = 2000 + 0.50q ] Profit ( \pi ) is total revenue minus total cost: [ \pi = \left(2q - \frac{q^2}{10,000}\right) - (2000 + 0.50q) = 1.50q - \frac{q^2}{10,000} - 2000 ] Maximizing Profit: The profit function is a quadratic equation, and the maximum profit occurs at the vertex. For the quadratic equation ( \pi(q) = -\frac{q^2}{10,000} + 1.50q - 2000 ), the vertex is found at: [ q = -\frac{b}{2a} = -\frac{1.50}{2 \left(-\frac{1}{10,000}\right)} = \frac{1.50 \times 10,000}{2} = 7,500 ] Substituting ( q = 7,500 ) into the inverse demand function gives the optimal price: [ p = 2 - \frac{7,500}{10,000} = 2 - 0.75 = 1.25 ] Calculating Maximum Profit: Total revenue at ( q = 7,500 ) and ( p = 1.25 ): [ R = 1.25 \times 7,500 = 9,375 ] Total cost: [ C = 2000 + 0.50 \times 7,500 = 2000 + 3750 = 5,750 ] Maximum profit: [ \pi = 9,375 - 5,750 = 3,625 ] Final Answer The optimal price is \boxed{1.25} dollars per item, the number of items to sell is \boxed{7500}, and the maximum profit is \boxed{3625} dollars. Token used: 3399 (10017 characters) Conclusion As you can see the various steps logically laid out where the model uses its knowledge of the worlds (profits = sales - cost), generates an algebraic function to link the behavior of various variables and then uses calculus to maximize the profit function to arrive at the right price and quantity for maximum profit. Resources Reasoning models on OpenAI - https://platform.openai.com/docs/guides/reasoning Bring your own models on AI Toolkit - using Ollama and API keys Building Retrieval Augmented Generation on VSCode & AI Toolkit1.2KViews0likes0CommentsWhy Every JavaScript Developer Should Try TypeScript
Introduction "Why did the JavaScript developer break up with TypeScript?" "Because they couldn’t handle the commitment!" As a student entrepreneur, you're constantly juggling coursework, projects, and maybe even a startup idea. You don’t have time to debug mysterious JavaScript errors at 2 AM. That's where TypeScript comes in helping you write cleaner, more reliable code so you can focus on building, not debugging. In this post, I’ll show you why TypeScript is a must-have skill for any student developer and how it can set your projects up for success. Overview of TypeScript JavaScript, the world's most-used programming language, powers cross-platform applications but wasn't designed for large-scale projects. It lacks some features needed for managing extensive codebases, making it challenging for IDEs. TypeScript overcomes these limitations while preserving JavaScript’s versatility, ensuring code runs seamlessly across platforms, browsers, and hosts. What is TypeScript? TypeScript is an open-source, strongly typed superset of JavaScript that compiles down to regular JavaScript. Created by Microsoft, it introduces static typing, interfaces, and modern JavaScript features, making it a favorite for both small projects and enterprise applications Why Should Student Entrepreneurs Care About TypeScript? TypeScript Saves You Time: You know that feeling when your JavaScript app breaks for no reason just before a hackathon deadline? TypeScript catches errors before your code even runs, so you don’t waste hours debugging. TypeScript Makes Your Code More Professional: If you're building a startup, investors and potential employers will look at your code. TypeScript makes your projects scalable, readable, and industry ready. TypeScript Helps You Learn Faster: As a student, you’re still learning. Typescripts autocomplete and type hints guide you, reducing the number of Google searches you need. For a beginner-friendly introduction to TypeScript, check out this MS Learn module: 🔗 Introduction to TypeScript Setting Up TypeScript in 5 Minutes Prerequisites Knowledge of JavaScript NodeJS Code editor Visual Studio Code Install TypeScript TypeScript is available as a package in the npm registry as typescript. To install the latest version of TypeScript: In the Command Prompt window, enter npm install -g typescript. npm install -g typescript Enter tsc to confirm that TypeScript is installed. If it was successfully installed, this command should show a list of compiler commands and options. Create a new TypeScript file Create a new folder in your desktop called “demo”, right-click on the folder icon and select open with vs code When vs code opens, click on add file icon and create new file “index.ts” Let’s write a simple function to add two numbers Compile a TypeScript file TypeScript is a strict superset of ECMAScript 2015 (ECMAScript 6 or ES6). All JavaScript code is also TypeScript code, and a TypeScript program can seamlessly consume JavaScript. You can convert a JavaScript file to a TypeScript file just by renaming the extension from .js to .ts. However, not all TypeScript code is JavaScript code. TypeScript adds new syntax to JavaScript, which makes the JavaScript easier to read and implements some features, such as static typing. You transform TypeScript code into JavaScript code by using the TypeScript compiler. You run the TypeScript compiler at the command prompt by using the tsc command. When you run tsc with no parameters, it compiles all the .ts files in the current folder and generates a .js file for each one. To compile our code, open command prompt in vs code and type tsc index.ts Notice that a new JavaScript file has been added, You might need to refresh the Explorer pane to view the file At the Terminal command prompt, enter node index.js. This command runs the JavaScript and displays the result in the console log. And that’s it! 🎉 Core TypeScript Features Every Developer Should Know Static Typing for Safer Code – TypeScript’s static typing prevents runtime errors by catching type mismatches at compile time, making code more reliable. This prevents unintended assignments like: Interfaces for Better Object Structures – Interfaces help define the structure of objects, ensuring consistency and maintainability across a codebase. Enums for Readable Constants – Enums define named constants, making code more readable and reducing the risk of using incorrect values. Generics for Reusable Code – Generics allow you to create flexible, type-safe functions and components that work with multiple data types. Type Assertions for Flexibility – Type assertions let you explicitly specify a value’s type when TypeScript cannot infer it correctly, enhancing type safety in dynamic scenarios. Conclusion: TypeScript is Your Superpower🚀 TypeScript is more than just a superset of JavaScript—it's a game-changer for developers, especially those working on large-scale projects or building career-defining applications. By introducing static typing, interfaces, Enums, generics, and type assertions, TypeScript helps eliminate common JavaScript pitfalls while maintaining flexibility. These features not only enhance code quality and maintainability but also improve collaboration among teams, ensuring that projects scale smoothly. Whether you're a student entrepreneur, a freelancer, or a professional developer, adopting TypeScript early will give you a competitive edge in the industry. Embracing TypeScript means writing safer, cleaner, and more efficient code without sacrificing JavaScript’s versatility. With its powerful developer tools and seamless integration with modern frameworks, TypeScript ensures that your code remains robust and adaptable to changing requirements. As the demand for TypeScript continues to grow, learning and using it in your projects will open new opportunities and set you apart in the ever-evolving world of web development. Read More And do more with Typescript Declare variables in Typescript TypeScript repository on GitHub TypeScript tutorial in Visual Studio Code Build JavaScript applications using TypeScript184Views2likes0CommentsGitHub Copilot Bootcamp Resources
Passos para resgatar o desconto para sua certificação GitHub (Português Brasileiro) Pasos para canjear el descuento para tu certificación de GitHub (Español) Steps to redeem the discount for your GitHub certification (English) 兑换 GitHub 认证折扣的步骤 (Chinese) Passos para resgatar o desconto para sua certificação GitHub Se você deseja consultar o código de desconto compartilhado durante a sessão, por favor, visite a página de inscrição para acessar a gravação: https://aka.ms/GitHubCopilotBootcampBrasil O código do voucher deverá ser inserido manualmente durante o processo de checkout. Abaixo estão os passos para registro e agendamento: Faça login no site de registro do exame e escolha a certificação desejada. Isso o redirecionará para a página de registro. Clique em “Agendar/fazer exame” para prosseguir. Complete o formulário de registro e selecione “Agendar exame” na parte inferior. Esta ação transmitirá seus detalhes de elegibilidade para nosso fornecedor de testes, PSI. Ao enviar o formulário de registro, você será direcionado ao site de testes da PSI para finalizar o agendamento do seu exame. Durante o processo de checkout no site de testes da PSI, você encontrará um campo designado onde poderá inserir o código do voucher para zerar o saldo. Pasos para canjear el descuento para tu certificación de GitHub Si deseas consultar el código de descuento compartido durante la sesión, por favor, visita la página de inscripción para acceder a la grabación: https://aka.ms/GitHubCopilotBootcampLATAM El código del voucher (cupón) se ingresará manualmente durante el proceso de pago. A continuación, se detallan los pasos de registro y para agendar tu examen: Inicia sesión en el sitio de registro del examen y elige la certificación deseada. Esto te redireccionará a la página de registro. Haz clic en "Programar/realizar examen" para continuar. Completa el formulario de registro y selecciona "Programar examen" en la parte inferior. Esta acción transmitirá tus detalles de elegibilidad a nuestro proveedor de pruebas, PSI. Al enviar el formulario de registro, serás dirigido al sitio de pruebas de PSI para finalizar la programación de su examen. Durante el proceso de pago en el sitio de pruebas de PSI, encontrarás un campo designado donde puedes ingresar el código del voucher (cupón) para poner a cero el saldo. Steps to redeem the discount for your GitHub certification If you wish to check the discount code shared during the session, please visit the registration page to access the recording: https://aka.ms/GHCopilot-Bootcamp The voucher code will be entered manually during the checkout process. Below are the registration and scheduling steps: Log into the exam registration site and choose the desired certification. This will redirect you to the registration page. Click on "Schedule/take exam" to proceed. Complete the registration form and select "Schedule exam" at the bottom. This action will transmit your eligibility details to our testing vendor, PSI. Upon submitting the registration form, you'll be directed to the PSI testing site to finalize the scheduling of your exam. During the checkout process on the PSI testing site, you'll encounter a designated field where you can enter the voucher code to zero the balance.5.8KViews1like6CommentsAI Toolkit for VS Code January Update
AI Toolkit is a VS Code extension aiming to empower AI engineers in transforming their curiosity into advanced generative AI applications. This toolkit, featuring both local-enabled and cloud-accelerated inner loop capabilities, is set to ease model exploration, prompt engineering, and the creation and evaluation of generative applications. We are pleased to announce the January Update to the toolkit with support for OpenAI's o1 model and enhancements in the Model Playground and Bulk Run features. What's New? January’s update brings several exciting new features to boost your productivity in AI development. Here's a closer look at what's included: Support for OpenAI’s new o1 Model: We've added access to GitHub hosted OpenAI’s latest o1 model. This new model replaces the o1-preview and offers even better performance in handling complex tasks. You can start interacting with the o1 model within VS Code for free by using the latest AI Toolkit update. Chat History Support in Model Playground: We have heard your feedback that tracking past model interactions is crucial. The Model Playground has been updated to include support for chat history. This feature saves chat history as individual files stored entirely on your local machine, ensuring privacy and security. Bulk Run with Prompt Templating: The Bulk Run feature, introduced in the AI Toolkit December release, now supports prompt templating with variables. This allows users to create templates for prompts, insert variables, and run them in bulk. This enhancement simplifies the process of testing multiple scenarios and models. Stay tuned for more updates and enhancements as we continue to innovate and support your journey in AI development. Try out the AI Toolkit for Visual Studio Code, share your thoughts, and file issues and suggest features in our GitHub repo. Thank you for being a part of this journey with us!Microsoft Startup Spotlight Live Series
As a founder, developer, or AI enthusiast, have you ever wondered what AI startups are solving, the technologies they use, or the journeys their founders have taken? How do they tackle challenges and create impactful solutions? These are questions we often ask, and there’s no better way to find answers than by hearing directly from the innovators themselves. I’m excited to introduce the Startup Spotlight Series—a bi-weekly live event hosted on the Microsoft Reactor YouTube channel. This series offers a unique opportunity to: Hear exclusive stories from AI startup founders. See live demonstrations of their technologies. Learn about the latest AI trends and real-world solutions for customers’ challenges 💡 Why Should You Tune In? The Startup Spotlight Series isn’t just another livestream—it’s a unique opportunity designed to provide insights, inspiration, and practical value for a variety of audiences: Startups Founders: Learn from the successes (and struggles) of AI startup leaders. Gain actionable insights into building innovative products, scaling businesses, and navigating challenges. Developers: Dive into the technical details with live product demos and behind-the-scenes discussions. See how their solutions are being built and deployed. Students: Discover the latest AI trends and practical applications. Discover how startups are leveraging AI to create impactful solutions. Whether you're looking for inspiration or considering a future in AI, this series is packed with insights to help you grow. AI Enthusiasts: Stay ahead of the curve by learning how startups are revolutionizing industries. From transformative use cases to the stories behind the technologies, you’ll leave every episode inspired. Have burning questions about AI? Each session includes a live Q&A, where you can ask founders directly about their journeys, challenges, and advice. This is your chance to engage with the people shaping the future of AI! Thursday Jan 30 2025, Startup Spotlight: Activeloop Join us for the second episode of the Startup Spotlight Live Series, a space where AI startups share their journeys, showcasing their innovative technologies and demonstrating live product use cases. In this episode, Gabriela de Queiroz sits down with Davit Buniatyan from Activeloop to explore how they’re leveraging Microsoft to grow, scale, and address real-world challenges. Thursday Feb 13th 2025, Startup Spotlight: Synthesized Join us for the third episode of the Startup Spotlight Live Series, a space where AI startups share their journeys, showcasing their innovative technologies and demonstrating live product use cases. In this episode, Gabriela de Queiroz sits down with Nicolai Baldin from Synthesized to explore how they’re leveraging Microsoft to grow, scale, and address real-world challenges. Thursday Feb 27th 2025, Startup Spotlight: Dataloop Join us for the fourth episode of the Startup Spotlight Live Series, a space where AI startups share their journeys, showcasing their innovative technologies and demonstrating live product use cases. In this episode, Gabriela de Queiroz sits down with Dataloop to explore how they’re leveraging Microsoft to grow, scale, and address real-world challenges. Join Us If you’re as excited about the future of AI as I am, I encourage you to tune in to the Startup Spotlight Series. Episodes air every other Thursday at 10:00 AM Pacific Time on the Microsoft Reactor YouTube channel. Can’t make it live? Don’t worry—episodes will be recorded and available for you to watch later at your convenience at Microsoft Reactor Youtube Sign up now to receive reminders and updates for upcoming episodes: aka.ms/startup-spotlight 🚀' But that's not all... Startups can apply (aka.ms/ss-credits) and get tons of benefits: Up to $150,000 in Azure credits Free access to leading AI models through Azure, including OpenAI's models, Llama 2 from Meta, and more. 1:1 meetings with experts who can help solve immediate business challenges, plus provide technical guidance on the latest in AI. 30+ additional free and discounted tools, tech, and services from Microsoft and our partners including M365, GitHub, LinkedIn Premium and more. 👋 See you there!