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Apple Safari Technology Preview 208 se lanzó con JavaScript, Web API y otras correcciones

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manzana Safari Technology Preview 208 ha sido lanzado para Impermeable Jueves. Es la última actualización de la versión beta de Safari en macOS para desarrolladores, donde las próximas tecnologías web se introducen por primera vez con fines de prueba antes de su lanzamiento general en el navegador web de la empresa. Según Apple, Safari Technology Preview 208 ofrece soluciones para problemas relacionados con CSS, Javascript, renderizado, Web API y WebRTC, así como otras mejoras del sistema.

Vista previa de la tecnología Safari 208: novedades

En su emisión NotasApple dice que Safari Technology Preview 208 está disponible para dispositivos que ejecutan macOS Sonoma y macOS Sequoia. Resuelve un problema con la apariencia del control deslizante al cambiar la combinación de colores. La actualización también corrige un problema de WebRTC con la búsqueda por voz que no vuelve a solicitar el permiso de la cámara o el micrófono y garantiza que el navegador los retenga en instancias de navegación del mismo origen.

Se ha informado que las versiones anteriores de Safari Technology Preview manejan mal el procesamiento de los mapas de origen. La última actualización del navegador de Apple soluciona estos problemas, según el registro de cambios. También contiene una solución para un problema que provocaba que no se aplicara el cambio de tamaño al contenido generado.

Además de las correcciones de errores, Apple dice que Safari Technology Preview 208 introduce nuevas características como soporte para Iterator Helpers, implementación conveniente de instrucciones SIMD para la selección de rutas, soporte para bloqueadores de contenido de URL a menos y soporte alternativo para attr().

En particular, Safari Technology Preview no requiere que los usuarios tengan una cuenta de desarrollador de Apple. Puede ejecutarse junto con el navegador Safari estándar en dispositivos macOS. 208 se puede descargar a través de la opción de actualización de software yendo al archivo Preferencias del sistema En Mac.

La última actualización se basa en el lanzamiento de Safari Technology Preview 207 lanzado a principios de este mes, y trae correcciones de errores para Carga, Redes, Extensiones web e Inspector web, así como otras mejoras de rendimiento del sistema.

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Anthropic presenta una nueva herramienta de análisis en Claude que puede escribir y ejecutar código JavaScript

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antrópico presentó el jueves una nueva herramienta para su chatbot nativo de inteligencia artificial (IA). Esta característica, denominada herramienta de análisis, proporciona un entorno de pruebas de codificación para un modelo de IA en el que puede escribir y ejecutar código JavaScript. Si bien el modelo de IA puede generar código desde el principio, la nueva capacidad le permite realizar análisis de datos más profundos, matemáticas complejas y múltiples iteraciones. La empresa de inteligencia artificial afirma que, a pesar de realizar muchas operaciones, Claude podrá generar información en tiempo real. La función está actualmente disponible en versión preliminar.

en la sala de redacción correoLa empresa de IA detalló la nueva característica. La herramienta de análisis esencialmente proporciona un entorno de prueba donde el modelo de IA ahora puede ejecutar el código escrito y mostrar el resultado. Esta característica es interesante porque permite esto claudio Inteligencia artificial para obtener datos de archivos como hojas de cálculo y PDF, analizar los datos, escribir el código requerido y compartir información en tiempo real.

Esto es similar a Devin AI de Cognitive Labs, que se lanzó en marzo y puede manejar tareas de programación de un extremo a otro y crear aplicaciones y otro software. Para Claude, la innovación aquí es la incorporación del entorno de prueba, que permite al chatbot de IA ejecutar código y verlo funcionar en tiempo real. Como resultado, si el código contiene fallos y errores, Claude también puede corregirlos en iteraciones sucesivas sin requerir más aportaciones por parte del usuario.

Anthropic destacó que la herramienta de análisis se basa en las sofisticadas habilidades de codificación y datos de Cloud 3.5 Sonnet. Con esto, el chatbot puede realizar problemas matemáticos complejos, análisis profundos de datos y probar múltiples ideas para encontrar la mejor manera de crear el resultado deseado.

Anthropic destacó cómo la herramienta puede ayudar a varios equipos empresariales y dijo que los gerentes de producto pueden cargar datos de participación del cliente en Claude, y que el chatbot impulsado por inteligencia artificial puede crear rápidamente prioridades de planificación y desarrollo. Los equipos de marketing también pueden beneficiarse de esta herramienta, ya que la IA puede encontrar lagunas en las interacciones con los clientes en diferentes canales y sugerir formas de mejorar las conversiones del embudo.

Para utilizar la nueva función, los usuarios pueden iniciar sesión en Claude AI, hacer clic en su nombre en la esquina inferior izquierda y buscar la opción “Vista previa de la función”. La herramienta de análisis estará disponible allí.

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Why JavaScript developers are switching to Rust in 2024 and why not

Why JavaScript developers are switching to Rust in 2024

It is becoming apparent that developers who typically work with JavaScript are now turning their attention to Rust, a programming language that stands out for its efficiency and safety. Rust is unique because it doesn’t have a runtime environment and requires that code be compiled before it can be executed. This language has won the hearts of many, as evidenced by its top ranking in the StackOverflow survey for several years. Its growing presence in the JavaScript community is noteworthy, with developers using Rust to boost the performance of various tools and frameworks. This article delves into the key aspects of Rust that are attracting JavaScript developers and provides guidance for those who are eager to learn this robust language.

Rust offers several features that are particularly appealing to JavaScript developers. First and foremost, Rust is a compiled language, which is a stark contrast to JavaScript’s interpreted nature. This means that Rust code must be transformed into a standalone program before it can be run, which contributes to its remarkable speed and efficiency. Another standout feature is Rust’s approach to memory management. It employs a distinctive ownership model that enforces strict rules, effectively preventing common issues such as memory leaks and data races that plague other languages.

JavaScript developers learning Rust

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When it comes to working with functions, Rust allows developers to use references and borrowing. This means you can use values in functions without giving away their ownership, promoting safer code reuse and improved concurrency. Additionally, Rust enforces that variables are immutable by default. Once a value is set, it cannot be altered unless explicitly declared as mutable, which helps to reduce unintended consequences in your code.

Rust

  • Primary Use: Systems programming, including web assembly, embedded systems, and performance-critical applications.
  • Language Type: A compiled, statically-typed language.
  • Execution Environment: Compiled to machine code, it runs directly on operating systems or embedded systems.
  • Syntax and Learning Curve: Has a steeper learning curve due to its strict type system and ownership model.
  • Static Typing: Strong and static typing ensures many types of errors are caught at compile time.
  • Concurrency Model: Employs a unique ownership model for safe concurrency without data races.
  • Ecosystem and Community: Growing ecosystem, with a focus on safety and performance; not as vast as JavaScript’s.
  • Performance: Offers high performance, on par with C and C++, due to its low-level control and lack of garbage collection.
  • Memory Management: Manual memory management, guided by its ownership model, which ensures memory safety without a garbage collector.

Rust also comes with its own package manager, Cargo, which offers functionalities akin to NPM but with added features that streamline dependency management and project compilation. Furthermore, Rust is both a statically and strongly typed language, which means that it performs type checking at compile time. This eliminates ambiguous types like ‘any’ or ‘null’, allowing developers to catch errors early in the development process. Lastly, Rust provides robust error handling capabilities, distinguishing between recoverable and unrecoverable errors and offering comprehensive tools to manage them effectively.

For JavaScript developers ready to embark on their Rust learning journey, there are several structured resources available. The Rust Book is an in-depth guide that includes interactive elements and projects, providing a thorough understanding of Rust’s principles. The Official Rust Course is another resource that focuses on syntax and can be accessed through your terminal or browser, catering to different learning styles. Rust by Example is a practical way to learn Rust through documented examples, reinforcing knowledge with real-world scenarios. Lastly, the Standard Library Documentation offers detailed descriptions and examples of Rust’s standard library, expanding your understanding and skill set.

JavaScript

  • Primary Use: Primarily used for web development, both on client-side (front-end) and server-side (with Node.js).
  • Language Type: A high-level, interpreted scripting language.
  • Execution Environment: Runs in web browsers and on servers (using Node.js).
  • Syntax and Ease of Use: Known for its flexible and forgiving syntax, making it accessible for beginners.
  • Dynamic Typing: Uses dynamic typing, which can lead to runtime errors but offers flexibility in development.
  • Concurrency Model: Event-driven and non-blocking I/O model, particularly effective for web servers and interactive web applications.
  • Ecosystem and Community: Has a vast ecosystem with numerous libraries and frameworks (like React, Angular, Vue.js).
  • Performance: Generally slower than compiled languages; performance depends on the JavaScript engine (like V8 in Chrome).
  • Memory Management: Automated garbage collection.

The versatility of Rust is evident in the wide range of applications it can be used for. Developers can create full-stack websites using frameworks like Yew or Rocket, or develop command-line tools with the help of Clap. Rust even makes its way into game development, with engines like Amethyst providing the tools necessary to create games.

  • Compiled Language Without Runtime: Rust requires code compilation into an executable, differing from JavaScript’s interpreted nature. This contributes to Rust’s efficiency and performance.
  • Memory Management through Ownership: Rust’s ownership model enforces rules to prevent memory management errors, a contrast to JavaScript’s automated garbage collection.
  • References and Borrowing: Rust uses references and borrowing for function values without transferring ownership, promoting safer code reuse, unlike JavaScript’s more flexible approach to variable referencing and manipulation.
  • Immutable Variables by Default: In Rust, variables are immutable by default, with mutability being a choice. This contrasts with JavaScript’s flexible variable assignment and mutability.
  • Cargo vs. NPM: Rust’s package manager, Cargo, includes additional functionalities compared to JavaScript’s NPM, streamlining dependency management and project compilation.
  • Static and Strong Typing: Rust’s statically and strongly typed system, with enforced types at compile time, stands in contrast to JavaScript’s dynamic typing. Rust’s approach eliminates ambiguous types like ‘any’ or ‘null’.
  • Error Handling: Rust categorizes errors as either recoverable or unrecoverable, with tools to address all possible errors, unlike JavaScript’s less structured error handling.
  • Applications of Rust: The reference text highlights Rust’s applications in full-stack website development (using frameworks like Yew or Rocket), command-line tools (with Clap), and game development (with Amethyst). This shows Rust’s versatility beyond JavaScript’s traditional domain of web development.
  • Emphasis on Clarity and Strong Typing: Rust’s explicitness and strong typing are advantageous for writing clear and error-free code, a departure from JavaScript’s more flexible and forgiving nature.

For those who are accustomed to JavaScript, exploring the world of Rust can significantly enhance your coding practices. The language’s emphasis on clarity and strong typing leads to the creation of code that is both more understandable and reliable. By familiarizing yourself with the core features of Rust and following the suggested learning path, you can tap into the potential of Rust to improve your programming abilities and contribute to cutting-edge projects.

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Build a custom AI chatbot with JavaScript in just two hours

learn how to use JavaScript to build a ChatGPT AI chatbot trained with custom data

If you would like to build a custom chatbot using JavaScript, you might be interested to know that Ania Kubów an expert in coding has created a new tutorial that takes you through a project to build a full stack ChatGPT AI chatbot trained on your data. Imagine the possibilities when you combine the power of AI with the efficiency of inventory management. You’re about to dive into a project that will not only streamline how businesses handle their stock but also transform the way they interact with data.

This guide will walk you through the steps of creating an AI chatbot that can sift through CSV file data and tap into the wealth of information available on the internet. By using TypeScript for the chatbot’s framework and integrating OpenAI’s natural language processing capabilities, you’ll create a tool that’s both smart and easy to talk to.

Let’s start by setting up your development environment. This is where you’ll lay the groundwork for your project. You’ll need to install some key software, like Node.js, which will support both TypeScript and Python. You’ll also set up your development tools and generate an API key. This key is crucial—it’s like a secret handshake that lets your chatbot access and update your database securely.

Now, let’s talk about TypeScript. It’s a supercharged version of JavaScript that makes your code more reliable and easier to maintain, thanks to its strong typing and object-oriented features. You’ll begin by building the core of your AI chatbot with TypeScript, focusing on how it will interact with users and process their queries.

Building and AI chatbot using JavaScript

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Your chatbot needs to be quick and sharp when searching through large datasets. That’s where SingleStore’s vector search comes in. You’ll learn how to integrate vector embeddings into your database, which will allow your chatbot to find similar products quickly by using a similarity score. This is a game-changer for inventory management because it means your chatbot can make fast and accurate product suggestions.

For your chatbot to really understand and respond to users naturally, you’ll harness the power of OpenAI’s natural language processing technologies. By using OpenAI’s GPT models, your chatbot will be able to generate responses that make sense in the context of the conversation, pulling information from your CSV files to do so.

While TypeScript is great for building the chatbot’s structure, you’ll use Python scripting for managing the database. Python is perfect for creating tables, filling them with data, and running complex queries. This strategic use of both TypeScript and Python ensures that you’re using the best tool for each job.

Of course, a chatbot isn’t much without a user interface (UI). You’ll design a UI that’s not only nice to look at but also easy to use. This will make the user’s experience with your chatbot smooth and enjoyable. At the same time, you’ll work on integrating your chatbot with a backend server. This server will handle user inputs and make sure all parts of your chatbot work together flawlessly.

By the end of this guide, you’ll have a sophisticated AI chatbot that’s perfectly tuned for managing inventory. You’ll have hands-on experience with TypeScript, SingleStore vector search, OpenAI’s natural language processing, and Python database scripting. Your chatbot will be a pro at navigating CSV data and using internet resources to become a comprehensive inventory management tool.

This journey will equip you with the skills to build advanced, intelligent systems that can enhance business operations. You’re not just creating a chatbot; you’re crafting a smarter way for businesses to work, and enhancing your skills which you can resell to those in need. Taking advantage of the explosion in AI technologies over the recent 12 months and assisting those businesses looking to integrate AI, ChatGPT and custom AI models into workflows.

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Using JavaScript to build your AI SaaS business

Using JavaScript to build your AI SaaS business

In today’s tech world, JavaScript is everywhere and is mainly used to make websites more interactive. Meanwhile, Artificial Intelligence (AI) has moved beyond just being a topic in science fiction. It’s now a big deal in many different fields. You’ll be pleased to know that combining JavaScript and AI can be a great way to create a successful online subscription-based service, also known as a SaaS business.

Why JavaScript?

JavaScript, initially a client-side language, has evolved considerably. With the advent of Node.js, it’s now omnipresent, running on the client as well as the server side. This means you can use a single language throughout your stack, enhancing consistency and streamlining development.

The JavaScript ecosystem is brimming with libraries, frameworks, and tools that can expedite the development process. For instance, TensorFlow.js allows you to bring machine learning capabilities right into the browser. JavaScript developers are abundant, which often leads to competitive pricing when hiring. Moreover, the open-source nature of many JavaScript tools can significantly reduce initial costs.

AI SaaS business

AI algorithms can process vast datasets to make real-time decisions. In a SaaS context, this capability can be employed for customer segmentation, predictive analytics, and automated customer service. Machine learning models can tailor user experiences based on historical data and behavior patterns. A more personalized service often translates to higher user retention rates. AI can adapt to growing or fluctuating workloads, adjusting algorithms and resource allocation as needed. This dynamic nature is crucial for a SaaS model where scalability can make or break the business.

In addition to JavaScript, CSS and HTML are integral for front-end development. While these languages are easier to learn and primarily used for designing the user interface, their role should not be underestimated. A well-designed and user-friendly interface can significantly enhance the user experience, making the SaaS product more appealing to potential customers.

Data handling is another critical aspect of coding for SaaS applications. Efficient data handling can improve the performance of the application and enhance the user experience. JavaScript excels in this area, allowing for efficient data manipulation and exchange with other software, including payloads and exos calls.

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Combining both AI and JavaScript

To enhance your experience, it’s essential to select the appropriate frameworks and libraries that align with your goals. For example, if you’re aiming to integrate chatbot functionality into your SaaS platform, you might want to look into libraries like Botpress or Rasa that specialize in conversational AI. The right tools can not only make your development process smoother but also provide a more polished end result, elevating user satisfaction and engagement. So, don’t just pick the first library or framework that comes up in a Google search; take the time to evaluate your options and choose those that best align with what you’re trying to achieve.

Before diving into AI algorithms, you need a robust data pipeline. JavaScript libraries like Pandas-js can be used for data manipulation and preparation. Once your data is ready, you can train your AI models. Tools like TensorFlow.js can be used not just for model training but also for inference right within the browser. This allows for a more interactive and responsive user experience. After the model is trained, the next step is to integrate it into your SaaS platform. Make sure to conduct thorough testing to ensure the model’s accuracy and reliability. JavaScript’s rich testing frameworks like Mocha or Jest can be beneficial here.

Server-side

On the server-side, Node.js, a JavaScript runtime built on Chrome’s V8 JavaScript engine, is a popular choice for back-end development. It allows developers to write server-side scripts in JavaScript, enabling the development of dynamic web pages before they are sent to the user’s web browser. This makes Node.js particularly useful for creating complex, data-intensive, real-time applications that run across distributed devices, a common requirement for AI integrated SaaS products.

Key Considerations

  • Security: AI models can be vulnerable to various attacks. Therefore, always adhere to best practices when it comes to securing your JavaScript code as well as your AI model.
  • Performance: Machine learning models can be resource-intensive. Optimize your JavaScript code to ensure that the user experience is not compromised.
  • Compliance: Be sure to adhere to regulations like GDPR when collecting and processing data.
  • Scalability: As your user base grows, both your JavaScript code and your AI models should be designed to scale efficiently.

Getting started

  1. Define the Problem: Clearly identify what you aim to solve with AI.
  2. Select Tools and Libraries: Choose appropriate JavaScript libraries and AI frameworks.
  3. Data Preparation: Collect and prepare the data for training.
  4. Train the Model: Use the chosen framework for training.
  5. Deploy and Iterate: Once deployed, continuously update the model based on performance and feedback.

JavaScript’s versatility, widespread use, and compatibility with AI platforms make it a fantastic tool for building a web-based AI integrated SaaS product. Coupled with its role in front-end and back-end development, data handling, and integration with other platforms, it is clear that mastering JavaScript is a crucial step towards successfully building and launching an AI integrated SaaS product. Whether you’re a seasoned developer or just starting your coding journey, investing time and effort into learning JavaScript will undoubtedly pay off in the long run.

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