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Ahora puedes conseguir un bloque de carga amarillo por $5 que combine con tu cable Playdate

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A. también fue observado Reddit Usado este fin de semana, Panic ahora vende pasta amarilla Envío de ladrillos Para ir con el cable amarillo que viene con el Playdate amarillo resaltado. Di amarillo de nuevo. La buena noticia para cualquiera que quiera un juego completo de accesorios a juego es que cuestan sólo $5; la mala noticia es que los costos de envío son casi el doble que el precio más barato, por lo que es difícil justificar la compra por sí solos.

También tenga en cuenta que el adaptador de corriente de 10 W tiene una conexión USB-A, por lo que funcionará con su cable de carga Playdate existente, pero por lo demás está algo retrasado dado el cambio general hacia la conectividad USB-C. Actualmente, Panic solo vende una versión compatible con el enchufe estándar de dos clavijas en Norteamérica y Japón. No hace falta decir que nadie necesidades Esto: nuestros Playdates se han estado cargando bien sin él todavía, pero si ya estás en el sitio Consigue una caja de pizza Ahora que vuelven a estar disponibles, seguramente se volverán locos.

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Combine sus fotografías con su imaginación con las nuevas herramientas de edición de fotografías impulsadas por IA de Midjourney

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El creador de imágenes impulsado por IA de Midjourney agrega nuevas e importantes opciones de edición a su plataforma Anunciar Escrito por el director ejecutivo David Holz en Discord. Podrás editar la foto cargada usando IA generativa, como hasta ahora solo has podido hacer con fotos generadas por IA. En particular, esta será una herramienta basada en la web, que ampliará las funciones exclusivas centradas en Discord de Midjourney.

Aunque las herramientas de edición de fotografías con IA existen desde hace un tiempo, casi siempre se limitan a fotografías creadas con el mismo modelo de IA que realiza la edición. Midjourney le permite editar la imagen que desea editar en lugar de que el formulario realice la creación inicial.

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Samsung is going after Nvidia’s billions with new AI chip — Mach-1 accelerator will combine CPU, GPU and memory to tackle inference tasks but not training

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Samsung is reportedly planning to launch its own AI accelerator chip, the ‘Mach-1’, in a bid to challenge Nvidia‘s dominance in the AI semiconductor market. 

The new chip, which will likely target edge applications with low power consumption requirements, will go into production by the end of this year and make its debut in early 2025, according to the Seoul Economic Daily.

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How to combine Claude 3 and ChatGPT for amazing results

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How to combine Claude 3 and ChatGPT for amazing results

Claude 3 might catch your attention with its ability to write in a way that captivates readers. However, you may find that its potential is somewhat limited because it doesn’t connect to the internet and relies solely on data it was trained on. On the other hand, ChatGPT-4 comes with a wider array of skills. It can not only write but also create images and browse the web for information. But you might feel that its writing style doesn’t quite match what you’re looking for. This guide provides a quick overview of how you can combine both Claude 3 and ChatGPT to create some amazing results in a wide variety of different applications.

This is where Perplexity steps in. It’s a third-party application designed to combine the strengths of Claude 3, GPT-4, and other AI models, such as DALL-E 3. Perplexity offers a comprehensive platform that caters to the diverse needs of content creators like you. One of the most exciting features of Perplexity is its ability to access live data.

Combining Claude 3 and ChatGPT

It can pull the latest information from platforms like YouTube and Reddit, ensuring that the content you create is not only engaging but also up-to-date with current trends and discussions. When it comes to visuals, Perplexity doesn’t disappoint. It uses AI models like DALL-E 3 and Stable Diffusion to help you create images that are as captivating as the stories you tell.

Here are some other articles you may find of interest on the subject of Claude 3 :

Easily use different LLMs Perplexity AI

Perplexity also allows you to personalize the AI’s output. You can train ChatGPT AI models to mimic your unique writing style, making sure that your personal touch is evident in the content produced by the AI. For those who delve into complex subjects, the Focus mode is perfect for deep exploration. If you’re an advanced user who wants more control, the Pro mode offers nuanced options, including the ability to ask follow-up questions and create multiple-choice prompts.

Another area where Perplexity shines is in its ability to analyze large files with precision. This is particularly useful for creators who handle big data sets and require accurate insights. However, it’s important to note that within Perplexity, Claude 3’s Opus model might have certain restrictions that could affect how well it performs.

Understanding Claude 3 and ChatGPT

When combining Claude 3 and ChatGPT GPT-4 to enhance your results, it’s essential to first understand the strengths and limitations of each model. Claude 3, like ChatGPT GPT-4, is a powerful language model developed for various tasks, including conversation, content creation, and information retrieval. However, each has unique characteristics and capabilities that, when used together, can complement and enhance overall performance.

Claude 3:

  • Strengths: Designed to have a unique writing style and can be fine-tuned for specific content creation tasks, potentially offering a fresh perspective or alternative style of response.
  • Limitations: May lack web access for real-time information updates and cannot generate images directly within the model.

GPT-4 (ChatGPT):

  • Strengths: Has access to a vast amount of information up to its last training cut-off in 2023, can perform real-time web searches (when enabled), and supports image generation through integration with DALL-E.
  • Limitations: The default writing style may not be to everyone’s liking, and it might require more complex prompts to produce highly customized content.

How to get the most from Claude 3 and ChatGPT

1. Define Your Objective

  • Clearly identify what you want to achieve with your query or content creation effort. This could range from generating creative content to seeking specific information or creating images.

2. Initial Prompting

  • For Claude 3: Begin with a prompt that leverages Claude 3’s unique writing style or specific strengths. This is particularly useful for creative writing or content that benefits from a fresh perspective.
  • For GPT-4: Use GPT-4 for tasks requiring up-to-date information, detailed explanations, or when image generation is needed.

3. Refine and Combine Outputs

  • Use the output from Claude 3 as a base for content that requires a unique style. For additional facts, updates, or image generation, pass this content through GPT-4 with a specific request to enhance the content with up-to-date information or visuals.

4. Leverage Specific Features

  • For Research and Detailed Information: Use GPT-4’s ability to perform web searches (if available) or access its vast database for comprehensive information.
  • For Creative Enhancements: Use Claude 3 to fine-tune the style or approach the subject matter from a unique angle. This is also where you might rewrite GPT-4 outputs to better match your preferred tone or style.

5. Integration with Other Tools

  • Consider using additional platforms like Perplexity.ai, which offer integrated access to multiple models (including GPT-4 and Claude 3) and features such as image generation, web search, and specialized tools (e.g., academic research, YouTube search). This can streamline the process and offer a more cohesive workflow.

6. Continuous Improvement

  • Iteratively refine your prompts and the integration process based on the results you receive. This may involve adjusting the complexity of your prompts, how you combine the outputs of both models, or exploring different features of the integrative platforms.

The integration of AI tools like Claude 3 and ChatGPT-4 through platforms such as Perplexity represents a significant stride forward in the realm of content creation. By combining the capabilities of these models and introducing new features, Perplexity showcases the potential of AI to enhance the creative process. Whether you’re a writer, a researcher, or a visual artist, the expanding AI landscape is equipped to support your projects with unmatched precision and adaptability.

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New ChatGPT mentions lets you combine multiple custom GPTs

GPT mentions a new way to combine custom GPTs into a single conversation

OpenAI has recently introduced an exciting update for ChatGPT subscribers that is poised to significantly improve the way they work with artificial intelligence and specifically OpenAI’s custom GPT Store and AI models. This update allows users to interact with multiple GPT models at once during a single chat session by simply calling them again, once you’ve use them once by typing the @ symbol  into your chat. This means that users can now access a variety of GPTs they have previously used, all in one place, without having to switch between different sessions or platforms.

For those who rely on AI for their projects, this development is a big step forward. It promises to make it much easier to manage various tasks, such as creating images with DALL-E, summarizing research papers, or converting content into different formats like PDFs or PowerPoint presentations. Users can now generate images, turn them into different file types, and even create presentations with integrated narratives, all within the same chat environment. This integration is designed to make project management more efficient and productive.

Combine custom GPTs into a single conversation

To take advantage of a specific GPT’s capabilities, users must have had a prior interaction with it. This ensures that the AI tools are tailored to the user’s individual needs and preferences, which helps optimize performance for the tasks at hand. It’s a personalized approach that aims to deliver a more efficient experience.

While this feature is a significant advancement, it’s important to acknowledge that there may be some initial limitations and errors. As with any new technology, some imperfections are to be expected at the outset. OpenAI is aware of this and is committed to making continuous improvements. The goal is to achieve better integration and a smoother user experience over time.

ChatGPT mentions

ChatGPT Mentions  has been recently rolled out by OpenAI enhance user interaction with its ChatGPT AI model by enabling the integration of multiple custom GPTs within a single chat session. ChatGPT Mentions is currently in beta and exclusive to certain paid users.

The core functionality of GPT Mentions lies in its ability to allow users to “@ mention” different GPT models directly within their text prompts. This mechanism is akin to calling upon a specific expert to handle a particular aspect of a conversation or task. It opens up a realm of possibilities for specialized behavior, from workflow automation to managing complex, routine tasks using AI, all within the flow of a single conversation.

Initially, GPT Mentions is available only to users with a paid subscription, such as ChatGPT Plus, Teams, or Enterprise accounts. This exclusivity underscores the feature’s potential to cater to professional and advanced personal use cases, where the integration of specialized GPT models can significantly enhance productivity and interaction quality.

How to Use ChatGPT Mentions

  1. Accessing GPT Mentions: Begin by typing “@” in the chat prompt window of ChatGPT. This action triggers the interface to display a list of available GPTs. The list ranges from recently used and pinned GPTs to an option for creating a new custom GPT.
  2. Selecting a GPT: Browse through the list or use the search function to find the specific GPT you wish to engage. Once identified, click on the GPT’s name to select it. This selection is confirmed by a notification such as “Talking to [name of GPT]” appearing above the chat window.
  3. Engaging with the GPT: After selection, you can proceed to type your prompt as you normally would. The specified GPT will now respond to your prompt, utilizing its unique capabilities or specialized knowledge base. This process can be repeated with different GPTs within the same conversation, allowing for a dynamic and multi-faceted interaction.

Considerations and Limitations

  • Availability: As of the initial rollout, the feature is not accessible to all users. Its availability is limited to those with certain paid subscriptions, with plans for broader access following an official announcement.
  • Account Requirements: Usage of custom GPTs through GPT Mentions requires a subscription to ChatGPT Plus, Teams, or Enterprise accounts.
  • Customization and Integration: The feature’s potential for customization and integration with external software positions ChatGPT as a highly versatile tool for both personal and professional applications.

OpenAI encourages ChatGPT Plus, Team and Enterprise members to try out this new feature and share their feedback. User input is vital for refining the technology and guiding its future direction. As a member, you have the opportunity to be at the forefront of AI interaction and play a role in the development of these tools.

The introduction of multi-GPT interaction is a significant milestone for ChatGPT Plus users. It’s designed to simplify complex tasks and open up new possibilities for creativity and productivity. OpenAI is dedicated to enhancing this feature and expanding its capabilities. Users are invited to explore the new potential that multi-GPT interactions offer and to take part in the next level of digital communication.

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How to combine and fully automate custom GPT AI models

How to automate and combine different custom GPT

With the launch of the highly anticipated OpenAI custom GPT store happening later this month you might be wondering how you can fully automate these custom AI models. Removing the need for you to sit in front of your computer and manually type in actions to each custom GPT manually. Luckily there are plenty of automation platforms already available such as Make, Zapier and others that allow you to easily create autonomous workflows without the need to know anything about coding. Simply connect different applications and custom GPT models together to create your perfect activity workflow removing the mundane tasks from your life. Allowing you to concentrate on the more important aspects.

Imagine a world where your daily tasks are handled automatically, where your productivity soars as repetitive work is done without your constant attention. This is the promise of integrating a custom Generative Pre-trained Transformer (GPT) with Zapier, a powerful tool that can take your workflow to new heights of efficiency. This article will guide you through the steps to make this integration a reality, turning your custom GPT into an indispensable ally in your work routine.

In today’s fast-paced work environment, the ability to streamline operations and reduce manual labor is more important than ever. A custom GPT, also known as your “Script Assistant,” can be the answer to this need. By automating routine tasks, you can minimize errors and free up time to concentrate on more strategic work that requires your unique expertise.

Automate custom GPT AI models

To begin, you’ll need to develop a custom GPT tailored to your specific needs. This involves programming it with the knowledge and commands that are relevant to your tasks. Once you have your custom GPT ready, the next step is to integrate it with Zapier, a versatile platform that connects over 6,000 apps, allowing for a wide range of automation possibilities.

Here are some other articles you may find of interest on the subject of automations using the Zapier platform:

Zapier acts as the hub of your automation setup. It’s the bridge that connects your custom GPTs with other applications you use daily, such as Google Docs and email services. This connectivity is what turns your “Script Assistant” into a dynamic force that can handle tasks with precision and speed.

Setting up automations in Zapier is a straightforward process. For example, you can automate the transfer of data from your custom GPT to Google Docs. This ensures that scripts and documents are organized and stored systematically. Additionally, you can set up notifications to keep your team informed when new content is generated, ready for review, or published.

However, it’s not enough to just set up these automations. You must ensure they work as intended. Testing your setup is a critical step to confirm that your custom GPT and Zapier actions are functioning together harmoniously. While these tools are powerful, they may still encounter issues, especially since they could be in development stages. But don’t worry, there’s a robust community of users and experts ready to help you troubleshoot any problems that arise.

By integrating a custom GPT with Zapier, you’re not just automating tasks; you’re reshaping the way you work. This integration allows you to create a “Script Assistant,” link it with essential apps, and set up automations that enhance your workflow. With this system in place, you’re well-equipped to tackle the challenges of automation and stay ahead in a competitive landscape.

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Combine Gemini Pro AI with LangChain to create a mini RAG sys

Combine Gemini Pro AI with LangChain to create a mini RAG system

In the rapidly evolving world of language processing, the integration of advanced tools like Gemini Pro with LangChain is a significant step forward for those looking to enhance their language model capabilities. This guide is crafted for individuals with a semi-technical background who are eager to explore the synergy between these two powerful platforms. With your Google AI studio API key at hand and recently made available by Google for its new Gemini AI.  We will explore a process that will take your language models to new heights.

LangChain is a robust and versatile toolkit for building advanced applications that leverage the capabilities of language models. It focuses on enhancing context awareness and reasoning abilities, backed by a suite of libraries, templates, and tools, making it a valuable resource for a wide array of applications.

LangChain represents a sophisticated framework aimed at developing applications powered by language models, with a strong emphasis on creating systems that are both context-aware and capable of reasoning. This functionality allows these applications to connect with various sources of context, such as prompt instructions, examples, and specific content. This connection enables the language model to ground its responses in the provided context, enhancing the relevance and accuracy of its output.

The framework is underpinned by several critical components. The LangChain Libraries, available in Python and JavaScript, form the core, offering interfaces and integrations for a multitude of components. These libraries facilitate the creation of chains and agents by providing a basic runtime for combining these elements. Moreover, they include out-of-the-box implementations that are ready for use in diverse applications.

Accompanying these libraries are the LangChain Templates, which constitute a collection of reference architectures. These templates are designed for easy deployment and cater to a broad spectrum of tasks, thereby offering developers a solid starting point for their specific application needs. Another integral part of the framework is LangServe, a library that enables the deployment of LangChain chains as a REST API. This feature allows for the creation of web services that enable other applications to interact with LangChain-based systems over the internet using standard web protocols.

The framework includes LangSmith, a comprehensive developer platform. LangSmith provides an array of tools for debugging, testing, evaluating, and monitoring chains built on any language model framework. Its design ensures seamless integration with LangChain, streamlining the development process for developers.

To kick things off, you’ll need to install the LangChain Google gen AI package. This is a straightforward task: simply download the package and follow the installation instructions carefully. Once installed, it’s crucial to configure your environment to integrate the Gemini Pro language model. Proper configuration ensures that LangChain and Gemini Pro work seamlessly together, setting the stage for a successful partnership.

After setting up Gemini Pro with LangChain, you can start to build basic chains. These are sequences of language tasks that Gemini Pro will execute in order. Additionally, you’ll be introduced to creating a mini Retrieval-Augmented Generation (RAG) system. This system enhances Gemini Pro’s output by incorporating relevant information from external sources, which significantly improves the intelligence of your language model.

Combining Gemini Pro and LangChain

The guide below by Sam Witteveen takes you through the development of Program-Aided Language (PAL) chains. These chains allow for more complex interactions and tasks. With Gemini Pro, you’ll learn how to construct these advanced PAL chains, which expand the possibilities of what you can accomplish with language processing.

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LangChain isn’t limited to text; it can handle multimodal inputs, such as images. This part of the guide will show you how to process these different types of inputs, thus widening the functionality of your language model through Gemini Pro’s versatile nature.

A critical aspect of using Google AI studio is the management of API keys. This guide will walk you through obtaining and setting up these keys. Having the correct access is essential to take full advantage of the features that Gemini Pro and LangChain have to offer.

Finally, the guide will demonstrate the practical applications of your integrated system. Whether you’re using Gemini Pro alone or in conjunction with other models in the Gemini series, the applications are vast. Your LangChain projects, ranging from language translation to content creation, will benefit greatly from the advanced capabilities of Gemini Pro.

By following this guide and tutorial kindly created by Sam Witteveen , you will have a robust system that leverages the strengths of Gemini Pro within LangChain. You’ll be equipped to develop basic chains, mini RAG systems, PAL chains, and manage multimodal inputs. With all the necessary packages and API keys in place, you’re set to undertake sophisticated language processing projects. The details and code jump over to the official GitHub repository.

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Combine OpenAI Assistant API and Zapier for no-code automations

How to combine OpenAI Assistant API and Zapier for no code automation

Thanks to the explosion of AI it is now possible to create artificial intelligence assistants to help with those mundane tasks enabling you to concentrate on more important areas of your business or personal life. If you would like to learn how you can combine the OpenAI Assistant API and Zapier together to create no code automations this guide will provide an excellent starting point.

Imagine being able to quickly set up a virtual assistant to sort out customer questions, manage your schedule, or organize your emails. Thanks to the ability to combine Assistance API from OpenAI and the Zapier online automation service you can now quickly create low code automations to help you accomplish a wide variety of different tasks. Perhaps you would like to add a virtual assistant into your current systems, that can boost your productivity and let you concentrate on the bigger picture.

Your virtual assistant can be designed to remember past interactions. This means it doesn’t just do tasks; it gets better at them by using information from before. This leads to more tailored and effective results. For instance, it can remember what a customer bought in the past or suggest a useful next step. Your assistant is set up to work with a deep understanding of what’s needed.

Building automated workflows using Assistant API and Zapier

The power behind the Assistance API is advanced AI, including the latest models like OpenAI’s GPT-3.5 and GPT-4. This allows your assistant to deal with large amounts of data accurately. For example, if you have a detailed PDF on climate change, your assistant can quickly go through it and pull out the important points, saving you a lot of time and effort. The API’s skills also include pulling out information from different places and understanding various coding languages. This is great for both people who know how to code and those who don’t, making it a helpful tool for everyone.

Here are some other articles you may find of interest on OpenAI’s new Assistant API and GPTs.

Personalization is at the heart of the Assistance API. You can shape your virtual assistant to meet your specific needs, making sure that interactions are as natural and effective as possible. This level of customization means that in the future, your virtual assistant might respond in a way that’s hard to tell apart from a human coworker.

By using Zapier’s automation service to add a virtual assistant to your workflow, you’re not just making your current tasks easier; you’re at the forefront of AI and automation and no coding knowledge is required. Enabling anyone to start automating processes, analyzing data, and creating personalized interactions using the latest AI models and technologies.

No-code automations

Combining the OpenAI Assistant API with Zapier’s online automation services can significantly enhance workflow automations. Here’s a step-by-step analysis of the benefits:

  • Automation of Complex Tasks: The OpenAI Assistant API can process and understand natural language inputs, enabling it to handle complex tasks that involve data interpretation, content generation, and decision making. Integrating this with Zapier allows these capabilities to be applied across a wide range of applications and services that Zapier supports.
  • Increased Efficiency: By automating tasks, businesses and individuals can save time and resources. Routine tasks such as data entry, content creation, and information retrieval can be streamlined. The combination of OpenAI’s AI capabilities with Zapier’s extensive integration options makes the automation process more efficient and adaptable to different needs.
  • Custom Workflow Creation: Zapier excels in connecting different web applications and automating workflows between them. By adding the OpenAI Assistant API into this mix, users can create more sophisticated workflows that include AI-driven analysis, content generation, and decision-making processes.
  • Enhanced Data Processing: The OpenAI Assistant can analyze large volumes of text, extract key information, summarize content, and even generate reports. When this is combined with Zapier’s ability to move data between different platforms, it enhances the overall data processing and management capabilities of a workflow.
  • Scalability and Flexibility: As businesses grow, their needs change. The combination of the OpenAI Assistant and Zapier allows for scalable and flexible automation solutions. Users can start with simple automations and gradually incorporate more complex AI-driven tasks as required.
  • Accessibility and User-Friendliness: Zapier’s user-friendly interface makes it accessible to non-technical users. When combined with the OpenAI Assistant, it allows a broader range of users to develop AI-enhanced automation workflows without needing extensive programming knowledge.
  • Innovative Applications: The integration opens up possibilities for innovative applications in various fields like marketing, customer service, data analysis, and more. For example, generating automated responses to customer queries, creating dynamic content for marketing, or analyzing customer feedback for insights.

Combining the OpenAI Assistant API with Zapier’s automation capabilities can lead to more efficient, flexible, and innovative workflows. It enables both technical and non-technical users to harness the power of AI in their daily tasks and processes.

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How to combine GPT-4 Turbo with Google web browsing

How to combine GPT-4 Turbo with Google web browsing using the Assistants API

Being able to combine the power of OpenAI’s latest GPT-4 Turbo AI model and Google web browsing using the Assistants API opens up a wide variety of new applications that can take your business, SaaS or ideas to the next level. Search engines, like Google, have become the gatekeepers of vast amounts of data, and AI is the key to unlocking the most relevant and personalized results. Let’s explore the sophisticated technologies that are enhancing the way we search for information, making it a more intuitive and efficient experience.

When you type a query into a search bar, you expect more than just a list of links. You want answers that are tailored to your needs and preferences. This is where AI modeling comes into play. By integrating advanced AI, such as OpenAI’s GPT-4 Turbo, search engines can interpret your queries with a deeper understanding. This means that the results you get are not just related to your question, but they also take into account the context of your search.

Browsing the web with GPT-4 Turbo

The backbone of this seamless integration lies in Application Programming Interfaces (APIs), like the Google Search API. These APIs allow the AI model to quickly process your questions and fetch the most relevant search results. Alongside APIs, web scraping tools, such as Beautiful Soup, are used to gather data from the web pages that appear in your search results. This combination ensures that the information you receive is both up-to-date and comprehensive.

But how does it all start? With your questions. The AI system takes your queries and optimizes them for the search engine, ensuring that the essence of what you’re asking for is captured. Then, it retrieves URLs from the search results, diving into the web’s vast pool of information. The real magic happens in how the AI presents the information to you. Whether you prefer quick bullet points or a detailed JSON format for integrating data, the AI adapts to your needs. It can even add a touch of creativity to the responses, making the process of finding information more engaging.

Building apps with GPTs web browsing functionality

Other articles we have written that you may find of interest on the subject of coding with AI models, ChatGPT and Copilot :

Conversion of user queries into optimized search queries

Let’s consider a practical example. Say you’re looking to find out the latest on Sam Altman’s role at OpenAI. The AI system doesn’t just give you the latest news; it organizes it in a way that’s easy to digest. Or perhaps you’re curious about who won the Las Vegas F1 Grand Prix. The AI quickly scans the web for the latest results, keeping you updated as events happen.

The integration of AI with search engines is revolutionizing how we access information. By leveraging cutting-edge technologies like GPT-4 Turbo, the Google Search API, and web scraping tools such as Beautiful Soup, the system provides search results that are not only optimized and current but also customized to your preferences. As you journey through the vast information superhighway, AI stands as a powerful companion, delivering the knowledge you seek with unprecedented efficiency.

The potent power of GPTs and web browsing

This advanced integration of AI into search engines is not just about getting answers; it’s about getting the right answers quickly and in a way that resonates with you. It’s about having a digital assistant that understands not just the words you type, but the intent behind them. With these AI-enhanced search capabilities, the world’s information is at your fingertips, ready to be accessed and utilized in ways that were once unimaginable.

Combining ChatGPT with web browsing capabilities for creating custom Software as a Service (SaaS) applications and enhancing business services and websites offers several powerful advantages:

  • Access to Real-Time Information: ChatGPT, when integrated with web browsing, can access and retrieve the most current data from the web. This is crucial for businesses that rely on up-to-date information, such as market trends, news updates, or regulatory changes.
  • Enhanced User Experience: ChatGPT can provide interactive and personalized experiences for users. By combining this with web browsing, the interaction becomes even more relevant and engaging, as it can pull in live data or additional context from the web to enhance the conversation.
  • Automated Research and Data Gathering: For SaaS applications, especially those involving data analysis, market research, or competitive intelligence, the ability to automatically gather and process information from the web is invaluable. This reduces manual effort and increases efficiency.
  • Dynamic Content Generation: Businesses can use ChatGPT to generate content dynamically for websites or applications. When combined with web browsing, this content can be tailored to current events, user preferences, or specific queries, keeping the content fresh and relevant.
  • Customer Support and Engagement: ChatGPT can provide immediate, 24/7 customer support. By integrating web browsing, it can pull specific information, such as FAQs, product details, or policy information, directly from the business’s website or other relevant sources, offering more accurate and helpful responses.
  • Scalability and Cost-Efficiency: Automating tasks like customer service, data gathering, and content creation with ChatGPT and web browsing can significantly reduce costs and allow for easy scaling as the business grows.
  • Informed Decision Making: For business analytics and decision support systems, combining ChatGPT’s ability to reason and explain with real-time data from the web can lead to more informed and timely decisions.
  • Personalization and Targeting: SaaS applications can use this combination to better understand user needs and preferences, customizing services and content accordingly, which enhances user satisfaction and engagement.
  • Continuous Learning and Improvement: As ChatGPT interacts with users and web content, it can learn from these interactions, leading to continuous improvement in its responses and recommendations.
  • Seamless Integration with Existing Systems: ChatGPT can be integrated with existing business systems and workflows, enhancing them with web browsing capabilities without the need for major overhauls or disruptions.

As we continue to rely on the internet for knowledge, entertainment, and communication, the importance of efficient search capabilities cannot be overstated. The AI-driven search is a testament to the incredible progress we’ve made in technology, and it’s a glimpse into a future where our interactions with machines are more natural and productive.

The implications of this technology are vast. For businesses, it means being able to provide customers with instant, accurate information. For researchers, it streamlines the process of sifting through endless data to find relevant studies and data. For the everyday user, it simplifies the quest for knowledge, whether it’s for learning a new skill, keeping up with current events, or just satisfying a curious mind.

As we look ahead, the potential for AI to further enhance our search experiences is boundless. We can expect even more personalized results, faster response times, and perhaps even predictive search capabilities that anticipate our questions before we even ask them. The integration of AI into search engines is a significant step forward in our digital evolution, making information more accessible and useful for everyone.

So, the next time you find yourself typing a question into a search bar, take a moment to appreciate the complex technology at work behind the scenes. AI is not just changing the way we search; it’s changing the way we interact with the world’s knowledge. It’s a powerful tool that, when used wisely, can help us make more informed decisions, spark new ideas, and continue to push the boundaries of what’s possible.

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Combine Arduino, Raspberry Pi Hats and cameras with the Portenta Hat Carrier

Portenta Hat Carrier combines Arduino with Raspberry Pi Hats and cameras

The official Arduino development team has this week announced the arrival of the new Arduino Pro Portenta Hat Carrier. A carrier board compatible with Raspberry Pi Hats and cameras, offering a significant development in the world of single board computers.

This innovative product, part of the Arduino PRO range of high-performance hardware, is designed to transform the Portenta X8 into an industrial-grade single board computer. Its compatibility also extends to the Portenta H7 and Portenta C33, making it a versatile option for a wide range of applications.

The Portenta Hat Carrier provides easy access to multiple peripherals such as CAN, Ethernet, microSD, and USB. This makes it suitable for both prototyping and scaling up, extending the features of a typical Raspberry Pi Model B. With dedicated JTAG pins for quick debugging and a PWM fan connector for efficient heat management, this carrier board is designed for ease of use and high performance.

On-board camera connector

One of the standout features of the Portenta Hat Carrier is its onboard camera connector, which enables the addition of industrial machine vision solutions. This feature, combined with the ability to control actuators or read analog sensors via 16 additional analog I/Os, makes the carrier board a powerful tool for a variety of applications.

Availability and pricing

The Portenta Hat Carrier is available for €39 or $45 in the Arduino Store and through major distributors. It offers a frictionless Linux prototyping experience and the ability for integrated real-time MCU solutions, making it an affordable and efficient option for those looking to develop advanced commercial solutions.

Arduino Portenta Hat Carrier

“Portena Hat Carrier provides a unique bridge between the Arduino and Raspberry Pi ecosystems, offering professionals a modular platform for prototyping to full-fledged industrial applications,” said Massimo Banzi, Arduino’s co-founder, chairman and CMO. “We are excited to offer a product that answers our customers’ requests and supports an ecosystem we admire.”

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The Portenta Hat Carrier is designed to combine and extend MPU and MCU applications, which is a key benefit of using it. The integration with the Arduino and Raspberry Pi ecosystems also makes it a versatile tool for developers. Its compatibility with a wide range of Raspberry Pi HATs and the ease of debugging and inspecting the CAN lines through dedicated pins further add to its appeal.

The carrier board enables any Portenta module easy expansion to multiple peripherals, including any Raspberry Pi HAT compatible with the Model B 40-pin header, Ethernet, microSD, and USB. It also features an onboard CAN transceiver, an additional 8x analog I/Os, and a PWM fan connector.

Arduino Portenta Hat Carrier board underneath

The Portenta Hat Carrier is suitable for industrial applications ranging from robotic motion controls, intelligent sorting, anomaly detection, vehicle monitoring, and smart sensing. Its wide range of compatible peripherals, easy debugging and inspection capabilities, and additional analog I/Os and a PWM fan connector make it a robust and versatile option for a variety of industrial applications.

The Portenta Hat Carrier is a carrier board that offers a wide range of capabilities, making it a valuable tool for developers and industries alike. Its compatibility with Raspberry Pi Hats and cameras, along with its multiple peripherals and extension of features found in the Raspberry Pi Model B, make it a powerful and versatile addition to the Arduino PRO range. Its affordability and ease of use, combined with its suitability for commercial and industrial applications, make it a compelling choice for those looking to extend their single board computer capabilities.

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