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How to use Excel Copilot AI assistant to simplify complex tasks

How to use Excel Copilot AI assistant to simplify complex tasks

Microsoft has recently introduced a new feature in Excel that is set to change the way we interact with spreadsheets. This feature, known as Copilot, is an artificial intelligence (AI) tool and assistant that integrates seamlessly into Excel, offering users a more intuitive and efficient way to manage their data. As technology continues to advance, tools like Copilot are indicative of the direction in which software solutions are heading, aiming to make complex tasks more accessible to a broader audience.

To take advantage of Copilot’s full potential, users must have a Microsoft 365 subscription. The Copilot Pro subscription, in particular, unlocks a suite of advanced features designed to enhance productivity. It’s important to note that Copilot is not a standalone application; it works best when files are stored in OneDrive or SharePoint. Additionally, users must format their data into tables before Copilot’s algorithms can be applied effectively.

Microsoft 365

Copilot is integrated into Microsoft 365 in two ways. It works alongside you, embedded in the Microsoft 365 apps you use every day—Word, Excel, PowerPoint, Outlook, Teams, and more—to unleash creativity, unlock productivity, and uplevel skills. Business Chat works across the LLM, the Microsoft 365 apps, and your data—your calendar, emails, chats, documents, meetings, and contacts—to do things you’ve never been able to do before. You can give it natural language prompts like “tell my team how we updated the product strategy” and it will generate a status update based on the morning’s meetings, emails, and chat threads.

Copilot in Excel

Imagine being able to interact with your data by simply asking for what you need in plain language. Copilot can handle a variety of requests, from calculating unique customer counts to adding profit columns, and from creating pivot tables to generating charts. This AI-driven approach is especially beneficial for those who may not be experts in Excel, as it simplifies the use of the program’s sophisticated features. Here are refuted example prompts you can try in Copilot Excel :

  • Give a breakdown of the sales by type and channel. Insert a table.
  • Project the impact of [a variable change] and generate a chart to help visualize.
  • Model how a change to the growth rate for [variable] would impact my gross margin.

Copilot in Excel works alongside you to help analyze and explore your data. Ask Copilot questions about your data set in natural language, not just formulas. It will reveal correlations, propose what-if scenarios, and suggest new formulas based on your questions – generating models based on the questions that help you explore your data without modifying it. Identify trends, create powerful visualizations, or ask for recommendations to drive different outcomes.

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Getting Started with Excel Copilot

1. Requirements:

  • A Microsoft 365 subscription, either a family or a personal plan.
  • An additional subscription to Copilot Pro, granting access to Copilot features across various Microsoft applications including Excel, Word, PowerPoint, and Outlook, along with benefits like using GPT-4 during peak hours and faster image creation with DALL·E 3.

2. Activation:

  • Navigate to the designated website, accessible via a link provided in the video description or a card in the video’s top right-hand corner.
  • Ensure your files are stored in OneDrive or SharePoint as Copilot functions exclusively with cloud-stored files.

Core Features of Excel Copilot

1. Data Analysis and Insights:

  • Formulas and Calculations: Automatically figure out and apply complex formulas based on natural language prompts, significantly reducing the manual effort required in formula creation.
  • Data Visualization: Generate charts and graphs to visually represent data, facilitating easier interpretation and presentation.
  • Highlighting and Sorting: Highlight cells based on specific criteria and sort/filter data seamlessly, enhancing data readability and organization.

2. Efficiency and Productivity Enhancements:

  • Column Addition: Effortlessly add new columns for calculated data, such as profit margins, by simply prompting Copilot with your requirements.
  • Data Conversion: Convert data ranges into tables with a single click, leveraging the advantages of Excel tables like banded rows, quick formatting, and easy data manipulation.
  • Learning and Suggestions: Receive prompt suggestions and sample queries to better engage with Copilot, making the tool accessible to new users and providing inspiration for complex data manipulation tasks.

Practical Applications

1. Simplifying Complex Tasks:

  • Excel Copilot can intuitively understand and execute complex data queries, such as identifying the number of unique customers or calculating total sales per customer, using natural language prompts. This significantly lowers the barrier for performing sophisticated data analysis.

2. Enhancing Data Presentation:

  • The ability to quickly generate and customize charts based on specific data points or trends allows users to present their data in a more impactful manner. Although some customizations may require manual adjustments, Copilot significantly accelerates the initial creation process.

3. Streamlining Data Management:

  • By automating the process of highlighting significant data points, such as high-value transactions, and performing conditional formatting, Copilot aids in quickly identifying key insights within large datasets.

4. Facilitating Advanced Analysis:

  • Copilot can handle requests to analyze data for seasonal trends or outliers, enabling users to identify patterns that may not be immediately apparent through traditional analysis methods.

Limitations and Considerations

While Excel Copilot heralds a new era of data interaction within Excel, it’s important to recognize its current limitations, such as the inability to perform certain customizations directly through AI prompts. Currently, it cannot change chart colors directly, and some power users might notice that its response times are slower than performing tasks manually. Additionally, the tool’s effectiveness is pendant upon clear and precise user prompts, and there may be a learning curve in formulating queries that yield desired outcomes. Despite these initial challenges, the future of Copilot looks promising. It is expected to continue improving and become an indispensable tool for Excel users of all skill levels.

Microsoft Copilot represents more than just a new feature in Excel; it is a step towards making data analysis more democratic and less daunting for users who may not have extensive experience with spreadsheets. As we continue to embrace technological advancements, Copilot is poised to play a significant role in reshaping our interactions with Excel and data management as a whole.

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Google Gemini vs. Google Assistant

Google Gemini

In a new video from In Depth Tech Reviews, we get to look at how Google Gemini compares to Google Assistant. In the ever-evolving landscape of digital assistants, two notable contenders stand out for their unique capabilities and applications: Google Assistant and Google Gemini. A meticulous comparison conducted on the Pixel 8 Pro sheds light on the strengths and weaknesses of each, offering valuable insights for users looking to enhance their daily digital interactions. This guide dives deep into their performance, from basic to complex commands, and presents a clear recommendation based on their distinct functionalities.

Performance on Basic Commands

When it comes to handling everyday tasks such as setting timers, alarms, and converting measurements, Google Assistant emerges as the more efficient option. Its quick response times and reduced need for screen interaction, courtesy of its continued conversation feature, streamline the user experience significantly. This aspect of Google Assistant is particularly appealing for those seeking convenience and speed in their routine digital interactions.

Handling Moderate Commands

The capability of these assistants extends to intermediate tasks, including sending messages, navigating to specific locations, and managing device settings. In this realm, Google Assistant again demonstrates its prowess by executing commands more swiftly and delivering more practical outcomes. For instance, it can instantly navigate you to the nearest gas station, emphasizing its utility for on-the-go users who value efficiency.

Complex Command Capabilities

Venturing into the territory of less frequent, more complex requests such as creating cover letters, identifying objects, and generating images from text, Gemini begins to shine. It offers more detailed responses and visual content, showcasing its strength in handling creative and intricate tasks. Despite its prowess, Gemini faces challenges in delivering consistent results for tasks like obtaining flight information and summarizing emails, hinting at areas ripe for improvement.

Unique Features and Limitations

A notable distinction between the two assistants lies in their feature sets. Google Assistant boasts offline support, enabling it to perform certain tasks without an internet connection, a benefit not found in Gemini. Conversely, Gemini excels in creative endeavors, such as composing emails and generating images, with various customization options through different writing styles, making it a valuable tool for creative and personalized tasks.

Optimizing Your Experience with Both Assistants

The comparison underscores that while Google Assistant is ideally suited for everyday use, thanks to its speed and offline capabilities, Gemini offers substantial value for specific, less frequent tasks. The recommendation is clear: leverage Google Assistant for its efficiency in daily tasks while utilizing Gemini to tap into its unique features for creative and less common requests. This strategic approach allows users to maximize their experience, benefiting from the best of both worlds.

Summary

Embarking on a journey through the digital world with the appropriate digital assistant at your side can profoundly transform how you manage your daily activities, boosting both your productivity and your creative endeavors. Google Assistant and Gemini stand out as two pioneering forces in this space, each boasting distinct advantages that cater to a wide array of user needs and preferences. If your day-to-day life demands streamlined efficiency for routine tasks, or if you find yourself in need of a sophisticated tool that enhances your creative projects, gaining a deep understanding of what each assistant offers is crucial.

This knowledge equips you with the power to make choices that are perfectly aligned with your individual lifestyle and goals. Incorporating this detailed comprehension into your overall digital approach ensures you are adeptly prepared to tackle the multifaceted challenges presented by today’s digital environment. With this strategic alignment, you will navigate the digital terrain not just with confidence but with a newfound sense of ease, fully leveraging the technological advancements at your fingertips to enrich your personal and professional life.

Source & Image Credit: In Depth Tech Reviews,

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NVIDIA’s AI personal assistant demo available for RTX GPU PCs

NVIDIA RTX AI PCs Chat Bot Demo

NVIDIA has recently unveiled a new technology demonstration that is set to enhance the way we interact with artificial intelligence. This new feature, known as “Chat With RTX,” is designed to work seamlessly on Windows RTX PCs, leveraging the power of NVIDIA RTX GPUs to deliver a personalized and efficient chatbot experience. The technology is aimed at providing users with quick, secure, and contextually relevant responses, drawing from their own documents and notes to ensure a private and customized interaction.

At the heart of “Chat With RTX” lies a sophisticated GPT large language model that is capable of tailoring conversations to the user’s specific needs. This is not your average chatbot; it’s an intelligent system that can process a variety of file types, including text documents, PDFs, Word documents, XML files, and even transcriptions from YouTube videos. This versatility allows the chatbot to provide assistance that is highly relevant to the user’s personal content.

NVIDIA RTX AI PCs Chat Bot Demo

One of the key features of NVIDIA’s new tech demo is the use of retrieval-augmented generation (RAG), which significantly enhances the quality of the chatbot’s responses. In addition, the demo incorporates TensorRT-LLM, a tool for optimizing large language models, ensuring that the chatbot operates at peak efficiency. Thanks to RTX acceleration, the chatbot is not only accurate but also incredibly fast, running directly on a user’s Windows RTX PC without the need for cloud processing.

Developers, in particular, may find “Chat With RTX” intriguing as it builds upon the TensorRT-LLM RAG developer reference project available on GitHub. This provides them with a valuable opportunity to explore advanced AI models and potentially integrate similar technologies into their own projects.

 

For those interested in experiencing “Chat With RTX,” there are certain system requirements that must be met. The user’s PC should be equipped with a GeForce RTX 30 Series GPU or a more advanced model, with a minimum of 8GB of VRAM. Additionally, the PC must be running either Windows 10 or 11 and have the latest NVIDIA drivers installed to ensure compatibility with the demo.

NVIDIA has acknowledged a current installation issue with “Chat With RTX” and has promised to resolve it in a forthcoming update. In the meantime, users are advised to install the application in the default directory to avoid any complications.

Furthermore, NVIDIA is encouraging developers to push the boundaries of generative AI by hosting a contest. Participants are invited to create innovative applications using NVIDIA RTX GPUs, with the chance to win prizes. This contest not only stimulates creativity within the developer community but also showcases the potential of NVIDIA’s technology in driving forward AI applications.

The introduction of “Chat With RTX” is a testament to NVIDIA’s ongoing efforts to advance AI and GPU technology. By focusing on high-performance computing and data privacy, NVIDIA is making it possible to integrate sophisticated AI capabilities into everyday tasks. This technology allows users to benefit from a smart, responsive, and personalized AI assistant, all while keeping their data securely processed on their local machine. As NVIDIA continues to innovate and address any initial teething problems, “Chat With RTX” is poised to become an essential tool for those seeking a more intelligent and responsive computing experience.

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How to use GitHub Copilot AI coding assistant

How to use GitHub Copilot AI coding assistant

If you’re working with Python or other coding languages to develop applications or the next AI service that is going to transform our lives, you might need extra help but not have the resources to employ additional developers. Do not fear there’s a tool that can help you: GitHub Copilot. This AI-powered coding assistant is designed to enhance your productivity by offering code suggestions, completing functions, and even helping with documentation. Whether you are an experienced developer or a lone coder who is just starting out on their journey. Let’s delve into how you can leverage GitHub Copilot to improve your coding workflow and tackle your coding workflow with ease.

For example if you are working with working with Python to to parse emails for example. Guiding Copilot with specific comments can be incredibly beneficial. For example, a comment such as “# Extract email sender information” can prompt Copilot to provide you with code snippets that are directly relevant to what you’re trying to achieve. This not only saves you time but also ensures that your workflow remains uninterrupted.

It’s also important to define your functions with clarity. By doing so, Copilot can better understand the purpose of your code and offer suggestions that are more pertinent to your task. Say you’re working on a function to parse an email’s subject line; Copilot will recognize this and provide you with code that’s specifically suited for that function.

Using GitHub Copilot for coding and more

Engaging with Copilot directly in your code file can be particularly useful when you’re dealing with a challenging piece of code. The Copilot dialogue feature allows you to request specific code snippets, ensuring that the AI understands the full scope of your coding task. This interaction can lead to more accurate and helpful code suggestions.

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Moreover, the integration of Copilot with Visual Studio Code (VS Code) can significantly enhance your coding experience. This powerful duo not only aids in refining your code but also supports you in generating documentation. With VS Code, executing Copilot commands becomes a breeze, which can make your coding sessions more efficient and reduce the likelihood of errors.

By implementing these strategies, GitHub Copilot transforms from a mere coding tool into a valuable collaborator in your development journey. It’s crafted to assist you in the creation, refinement, and documentation of your Python scripts for email parsing. This allows you to focus on the essential logic and structure of your code. With the backing of Copilot’s AI-driven capabilities, you can approach the complexities of email parsing with greater confidence and productivity.

Email parsing can be a daunting task, especially when you’re trying to extract specific pieces of information from a cluttered inbox. Python developers often face the challenge of writing scripts that can sift through emails effectively. However, with GitHub Copilot, you have a resourceful ally that can make this task much more manageable.

Copilot AI coding assistant

Imagine having an assistant that not only understands your coding intentions but also provides you with real-time suggestions to enhance your work. That’s what GitHub Copilot does. It’s like having a co-pilot in the cockpit of your development environment, someone who’s always ready to offer assistance and ensure you’re on the right track.

One of the key benefits of using GitHub Copilot is its ability to learn from the context you provide. When you’re coding, every comment and function definition you write teaches Copilot about your goals. This learning process enables Copilot to give you code suggestions that are not just generic but tailored to your specific project needs.

For developers who are constantly looking for ways to optimize their workflow, GitHub Copilot presents an opportunity to do just that. It’s not just about writing code faster; it’s about writing smarter code. With Copilot’s suggestions, you can avoid common pitfalls and ensure that your scripts are robust and reliable.

Visual Studio Code

Furthermore, GitHub Copilot’s integration with VS Code is a match made in heaven for developers. VS Code is already a popular choice among programmers for its user-friendly interface and extensive range of features. When combined with Copilot, it becomes an even more powerful tool that can significantly cut down on development time and help you produce high-quality code.

In the world of software development, efficiency and accuracy are paramount. GitHub Copilot helps you achieve both by acting as a virtual coding mentor. Whether you’re a seasoned developer or someone just starting out, Copilot can help you navigate the intricacies of email parsing and other coding challenges with greater ease.

The beauty of GitHub Copilot lies in its simplicity and effectiveness. It’s not about replacing the developer but rather enhancing their capabilities. By providing intelligent code suggestions and helping with documentation, Copilot allows developers to focus on the creative aspects of programming while it takes care of the more mundane tasks.

In essence, GitHub Copilot is a testament to the advancements in AI and its application in software development. It’s a tool that can adapt to your coding style, learn from your patterns, and provide you with the support you need to be more productive. As you continue to work on parsing emails or any other Python project, consider giving GitHub Copilot a try. It could be the perfect co-pilot for your coding journey, helping you to write better code and bring your projects to completion with greater speed and less stress.

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How to Use Google Bard as the Ultimate Learning Assistant

Summary

By embracing and implementing these carefully outlined strategies, you have the unique opportunity to elevate Google Bard from its initial status as merely an advanced AI tool to a deeply personalized learning companion. This transformation is designed to empower you, the user, to embark on a journey of exploration, discovery, and comprehensive learning. The essence of this journey lies in your curiosity and willingness to engage deeply with the vast array of information that Bard offers.

To truly harness the full potential of Google Bard, it is essential to cultivate a mindset of curiosity. This involves not just asking questions, but asking the right kind of questions—those that are insightful, thought-provoking, and open-ended. Such questions encourage Bard to delve into its extensive database of knowledge to provide you with rich, nuanced, and multifaceted answers.

Moreover, active engagement with Bard’s responses is crucial. This means not just passively receiving information but critically analyzing it, reflecting on it, and applying it to your own contexts and experiences. It’s about making connections between what you learn and what you already know or wish to know more about.

Remember, the relationship with Bard is symbiotic. The more you interact with it, providing feedback and direction, the more it tailors its assistance to suit your unique learning preferences and objectives. In doing so, Bard becomes more than just a tool; it becomes a catalyst for personal growth, intellectual development, and lifelong learning.

By adopting these strategies, you are not just leveraging technology; you are setting the stage for a continuous learning adventure. This adventure is bound by neither time nor subject matter, enabling you to achieve not just your current learning goals but also to set new ones, continually expanding the horizons of your knowledge and skills. So, let your curiosity lead the way, engage deeply with the knowledge Bard imparts, and you will unlock a world of learning that knows no bounds.

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GitHub Copilot AI coding assistant for Visual Studio Code – Beginners Guide

GitHub Copilot coding assistant

If you are learning to code or would like a little assistance on those harder areas of your script or application. You may be considering using Copilot to offer suggestions, helping you navigate complex functions, and even writing chunks of code for you. This isn’t a distant dream—it’s a reality for developers using Visual Studio Code (VS Code), thanks to GitHub Copilot. A cloud-based artificial intelligence tool developed by GitHub now owned by Microsoft and OpenAI to assist users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) by providing coding assistance. This AI-powered assistant is designed to make coding more efficient and less daunting, and it’s available right within your favorite coding environment.

For those who spend their days (and sometimes nights) immersed in code, GitHub Copilot is a valuable addition to your toolkit. It’s like having a co-pilot in the cockpit of a plane, but for coding. This tool learns from the vast repositories of code on GitHub and uses that knowledge to provide real-time assistance as you write code in VS Code.

Learn how to use GitHub Copilot

Getting started with GitHub Copilot is straightforward. You’ll need to head over to the Extensions view in VS Code, which you can find by clicking the square icon on the sidebar or by using the shortcut `Ctrl+Shift+X`. Once there, simply search for “GitHub Copilot,” hit ‘Install,’ and you’re ready to take your coding to the next level.

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But before you can fully harness the power of Copilot, you’ll need to connect it to your GitHub account. This step is crucial as it links the AI tool to the vast code libraries it uses to assist you. To do this, click on the accounts icon at the bottom left of VS Code and sign in with your GitHub credentials. Make sure your GitHub account has Copilot access, and you’re all set.

Now that you’re connected, it’s time to tailor Copilot to your specific needs. VS Code allows you to open the settings with `Ctrl+,` or by clicking the gear icon and selecting ‘Settings.’ Here, you can adjust Copilot’s behavior to your liking. Whether you’re working with certain file types or programming languages, you can set up Copilot to offer assistance when and how you need it.

One of the standout features of Copilot is its robust auto-completion capabilities. As you type, Copilot suggests code snippets and constructs that you can use to speed up your workflow. You can fine-tune these suggestions in the settings, controlling how they appear and interact with your coding process. Additionally, you can customize the Copilot chat feature to communicate with the AI in a way that suits your style.

GitHub Copilot pricing

GitHub Copilot pricing

As you delve into your coding tasks, Copilot is right there with you, providing real-time suggestions that you can accept in whole or in part. It can even offer explanations for certain code segments, which is particularly helpful when you’re trying to understand complex functions or generate documentation on the fly.

But Copilot isn’t just about writing code; it also offers contextual help. By right-clicking on a piece of code, you can access menus that explain or document the code you’re working with. This feature is invaluable when you’re trying to decipher intricate code or understand a colleague’s work.

As you continue to use Copilot, you’ll find that it becomes an integral part of your coding routine. It’s not just about the time saved; it’s also about the learning experience. Copilot can introduce you to new coding patterns and best practices, helping you become a better developer.

While this article has covered the basics of getting started with GitHub Copilot in VS Code, there’s much more to explore. In the future, we’ll delve into advanced UI features in VS Code that enhance Copilot’s functionality. These features will offer deeper customization options and further streamline your coding process.

GitHub Copilot is more than just a tool; it’s a companion for developers looking to improve their productivity and code quality. By installing and configuring Copilot as outlined above, you can begin to reap the benefits of AI-assisted coding. And as you become more familiar with its features, you’ll discover even more ways it can help you in your coding endeavors.

So, whether you’re a seasoned developer or someone just starting out, GitHub Copilot in VS Code is worth exploring. It’s an assistant that works tirelessly to help you write better code, faster, and with fewer errors. And as the AI continues to learn and improve, so too will the assistance it provides. Embrace this technology and watch as it transforms the way you code, one suggestion at a time.

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MultiON web based personal AI assistant and Rabbit R1 alternative

MultiON personal AI assistant

anyone looking for a little assistance when carrying out mundane online tasks might be interested in a new web-based personal AI assistant called MultiON. Imagine a world where your online tasks are handled with the click of a button, where booking a ride, filling out forms, or navigating complex websites is done for you by an intelligent assistant. This is the reality that MultiON, a sophisticated AI agent, has started offering to enhance your web experience. This free tool is designed to streamline your digital interactions, making your online activities more efficient and less time-consuming.

MultiON browse API

MultiON stands out from other web automation tools by being a personal AI assistant that integrates directly with your Chrome browser. Once installed, it allows you to command it to perform a variety of tasks with ease and accuracy. Whether you need to retrieve data or fill out online forms, MultiON is equipped to handle these tasks with a level of precision that surpasses other tools like Rabbit R1 apparently. It offers a unique and interactive approach to managing your web activities.

The control MultiON provides over your browser is unparalleled. You can issue commands, and the AI agent will execute them with precision. The technology that powers MultiON is designed to understand and follow your instructions, providing a seamless and efficient browsing experience. This level of control is what sets MultiON apart, making it a valuable asset for anyone looking to optimize their time online.

Web based AI assistant

MultiOn is an AI agent that helps you with your daily tasks. The MultiOn Chrome extension re-imagines how you interact with the internet. its developers recommend using MultiOn for doing a task similar to how you will do it and describing the task or steps in natural language. They have found clear and descriptive commands to work the best. MultiOn can be prompted to follow specific behavior or rules similar to ChatGPT, and we recommend playing with prompting to find the best flow for you. Here are a few examples of how you can use the new web-based AI assistant

  • Make a 100-word Tweet on Twitter on “Excited to be using MULTION: Your AI Web Co-Pilot!”
  • Order the book How Google Works from Amazon (for the demo version, its developers have disabled press the place order button on Amazon).
  • Send a message on LinkedIn to my colleague and say hello
  • Order a burger from the Melt in Palo Alto using Doordash
  • Check FB for friends’ birthdays and send a happy Bday message
  • How is the weather today in San Francisco?
  • Book a calendar meeting for 2-3 pm tomorrow and invite everyone from…

If you’d like to learn more about the interesting developments that MultiON  offers check out the overview video below kindly created by WorldofAI.

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Personal AI assistant

The Browse API allows you to perform a single browsing session with the MultiOn Web Agent. A session in this context refers to a stateful instance of interaction with our Agent for a specific user query or workflow.

  • Session Lifecycle: A session begins when you initiate it with an input URL and an instruction prompt and ends when the Agent has completed the task with the required Actions. Each session is isolated, ensuring that data and interactions are not shared across sessions.
  • Use Cases: Sessions are ideal for handling individual queries, like fetching weather updates or executing a specific task.
  • Security: Sessions maintain high levels of security, as each session is authenticated and isolated, protecting the integrity of your data and interactions.

web-based AI assistant

Security and privacy are at the forefront of MultiON’s design. The tool ensures that your data and interactions are kept private through session isolation. This means that your activities in one session are not shared with any other, providing a layer of security that is crucial in today’s digital landscape.

The true strength of MultiON lies in its advanced API integration. By leveraging powerful APIs such as OpenAI Assistant API, Langchain, and Llama index, MultiON can manage even the most complex web tasks with ease. This sophisticated integration is what enables MultiON to offer a refined and powerful automation experience that can adapt to your specific needs.

To support its users, the MultiON team offers a wealth of resources, including extensive documentation and instructional videos. These materials are designed to help users of all levels to fully utilize the capabilities of their personal AI agent for web automation. Whether you’re a beginner or an experienced user, these resources are there to guide you through the process and ensure you get the most out of MultiON.

MultiON is not just a tool; it’s a gateway to a more intelligent and automated online world. As a free Chrome extension, it provides exceptional browser control, prioritizes your privacy with session isolation, and is equipped with a suite of features to cater to your web automation needs. Learn more about how to use  the innovative web browsing AI assistant in more detail over on the official help site.

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New open source AI coding assistant DeepSeek released

DeepSeek LLM open source AI coding assistant

Developers, coders and enthusiasts may be interested in a new open source AI coding assistant model in the form of the DeepSeek large language model (LLM).  DeepSeek, a company that’s been working under the radar, has recently released an open-source coding model that’s making waves in the tech community. This model, known as the DeepSeek coder model, boasts an impressive 67 billion parameters, putting it in the same league as some of the most advanced AI models out there, like GPT-4.   The open source AI coding assistant has been trained from scratch on a vast dataset in both English and Chinese.

  • Superior General Capabilities: DeepSeek LLM 67B Base outperforms Llama2 70B Base in areas such as reasoning, coding, math, and Chinese comprehension.

  • Proficient in Coding and Math: DeepSeek LLM 67B Chat exhibits outstanding performance in coding (HumanEval Pass@1: 73.78) and mathematics (GSM8K 0-shot: 84.1, Math 0-shot: 32.6). It also demonstrates remarkable generalization abilities, as evidenced by its exceptional score of 65 on the Hungarian National High School Exam.

  • Mastery in Chinese Language: Based on our evaluation, DeepSeek LLM 67B Chat surpasses GPT-3.5 in Chinese.

What makes the DeepSeek coder model stand out is its extensive training on a dataset comprising two trillion tokens. This vast amount of data has given the model a wide-ranging understanding and knowledge base, allowing it to perform at levels that exceed Llama 2’s 70 billion base model and show competencies akin to GPT-3.5. This achievement has quickly made it a notable competitor in the AI landscape.

But DeepSeek didn’t stop there. They’ve been continuously improving their model. With the release of version 1.5, they’ve added an extra 1.4 trillion tokens of coding data to the model’s training, which has significantly enhanced its capabilities. This upgrade means that the DeepSeek coder model is now even more adept at handling complex tasks, such as natural language programming and mathematical reasoning. It’s become an essential tool for those who need to simplify intricate processes.

DeepSeek open source AI coding assistant

“We release the DeepSeek LLM 7B/67B, including both base and chat models, to the public. To support a broader and more diverse range of research within both academic and commercial communities, we are providing access to the intermediate checkpoints of the base model from its training process. Please note that the use of this model is subject to the terms outlined in License section. Commercial usage is permitted under these terms.”

The model’s versatility is also worth mentioning once again as it supports multiple languages, including Chinese, which opens up its benefits to a wider, international audience. This is particularly important as the demand for advanced AI technology grows across different regions and industries.

DeepSeek LLM vs LLaMA 2

DeepSeek open source AI coding model benchmarking

For those interested in using the DeepSeek AI coding assistant, it’s readily available on platforms like Hugging Face and LM Studio.and is available to download in both 7 Billion and 33 Billion versions. This accessibility ensures that users who need cutting-edge AI can easily integrate it into their work. The model’s technical capabilities are further showcased by its ability to predict the next token in a sequence with a window size of 4K, which means it can produce outputs that are more nuanced and aware of the surrounding context. Additionally, the model has been fine-tuned on 2 billion tokens of instruction data, which guarantees that it can understand and carry out complex instructions with remarkable accuracy.

The research and development team responsible for creating this unique advanced language model comprising of 67 billion parameters have future plans for its development, and the DeepSeek AI coding assistant is likely just the start of their journey. They’ve hinted at future developments that could redefine the limits of AI models. This suggests that we can expect more innovative tools from DeepSeek that will continue to shape the future of various industries and applications.

The DeepSeek coder model is a significant step forward in the realm of open-source AI technology. With its advanced features and strong performance, it’s an excellent option for anyone in need of an AI model that specializes in coding and mathematics. As the AI community continues to expand, the DeepSeek coder model stands as a prime example of the kind of innovative, powerful, and adaptable tools that are driving progress across different fields. To give the AI coding assistant try jump over to the official DeepSeek Alpha website.

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Langchain library LangGraph lets you improve AI assistant runtimes

New Langchain library LangGraph lets you improve AI assistant runtimes

If you’re interested in learning more about how to build AI assistants or improve runtimes you may be interested in LangGraph specifically designed to help you supercharge your AI agents by enabling dynamic cyclic interactions among different components. LangGraph is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner. It is inspired by Pregel and Apache Beam. The current interface exposed is one inspired by NetworkX.

Imagine a tool that simplifies the complex task of managing agent runtimes, making the development process smoother and more efficient. That’s exactly what LangGraph, the latest addition to the Langchain library, offers to developers. This tool is designed to handle cyclical computational steps, which are essential for applications that require iterative interactions. It’s a sophisticated module that goes beyond the basics, orchestrating the flow of agents, or “actors,” in looping processes. This is particularly useful in scenarios where continuous communication between components is necessary.

LangGraph new Langchain library

LangGraph stands out by providing a level of control over language models in environments that are marked by looping processes and uncertainty. It acts as a conductor, ensuring that your language models work together seamlessly, regardless of the complexity of the task at hand. Whether you’re deploying advanced chat agents or human-in-the-loop systems, LangGraph simplifies the process, offering you unprecedented control.

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

At the core of LangGraph is the state machine concept, which is crucial for dictating program actions and transitions. This allows you to define agent behaviors and responses to various triggers, ensuring a smooth sequence of interactions. The library’s toolkit, which includes nodes, state graphs, and edges, gives you the power to design intricate agent behaviors with great precision.

LangGraph is a tool that unlocks the full potential of agent runtimes in cyclical computational environments jump over to the official website to learn more about its latest library. Whether you’re working on chat agents or human-in-the-loop systems, LangGraph offers the adaptability and control you need. With the backing of Langchain and a dedicated community, you’re well-equipped to delve into the advanced realm of agent runtime technology.

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Rabbit R1 pocket AI assistant upgrade and Perplexity collaboration

Rabbit R1 upgrade and collaboration with Perplexity

The recently launched Rabbit R1, artificial intelligent (AI) pocket assistant which was launched earlier this year and has already sold a considerable amount of preorders. Has received an upgrade as well as a new collaboration with Perplexity AI a notable player in the AI market. This new upgrade to the Rabbit R1 isn’t just a step up in terms of technology; it also introduces a a closer integration with Perplexity’s AI system that’s bound to transform how you interact with your Rabbit R1 in a major way.

The much-anticipated sixth batch of the Rabbit R1 is set to hit the markets in the EU and UK come July 2024, with an attractive price point of $200. To learn more about the Rabbit R1 check out our previous article here. No subscription is required to use your Rabbit R1  AI helper and that is now available to preorder priced at $199.

Rabbit R1 AI pocket assistant

The Rabbit R1 measures just 78mm x 78mm x 13mm in size and is powered by a MediaTek MT6765 Octa-core (Helio P35) together with a 2.88 inch TFT touchscreen, 8MP, 3264 x 2448 camera, magnetometer, accelerometer, gyroscope, dual microphone array and GPS.

Upgrade and collaboration with Perplexity

As already explained one of the most exciting aspects of this upgrade is the Rabbit R1’s collaboration with Perplexity, an AI-driven search assistant designed to tailor search results to your individual preferences. When you purchase the Rabbit R1, you’ll also receive a complimentary one-year subscription to Perplexity Pro. This premium service, typically costing between $10 to $20 a month, is a significant value-add for new owners of the device.

Here are some other articles you may find of interest on the subject of Perplexity AI :

The tech industry is taking notice of the Rabbit R1’s potential, with leaders like Microsoft CEO Satya Nadella recognizing its capacity to shake up the market. Such endorsements from top figures in technology lend the device an added layer of credibility and confirm its status as an innovative contender.

At the heart of the Rabbit R1 is its proprietary technology, the Large Action Models (LAMs), which are integrated into its operating system, Rabbit OS. These models allow for direct interaction with the web, bypassing the need for additional APIs or software. The device’s focus on performance is evident, aiming to provide users with quick response times and minimal delays, ensuring a smooth and efficient experience.

Looking ahead, AI assistants are set to become an even more essential part of our digital lives, particularly with the growing trend of voice-based commands. The Rabbit R1 is leading the charge in this area, ready to make your interactions with technology more natural and intuitive.

Rabbit R1 pricing and availability

Pricing starts at $199. Taxes, shipping fees and duties for international orders are not included. Maximum 5 units per order. For pre-orders, we expect to begin shipping r1 1st batch orders to US/Canada addresses in March-April 2024, r1 2nd batch orders to US/Canada addresses in April-May 2024, r1 3rd batch orders to US/Canada addresses in May-June 2024, r1 4th, 5th and 6th batch orders to US/Canada addresses in June-July 2024. Shipping to non-US/Canada addresses for all batches is expected to begin later in 2024, but we do not have a more definite estimate at this time. Shipping estimates are subject to change based on our manufacturing capacity and component availability.

The Rabbit R1 is more than just another gadget; it’s a significant advancement in the realm of smart technology. With its strategic partnership, industry recognition, and cutting-edge features, the Rabbit R1 is on track to become an indispensable part of your digital experience. Keep an eye out for its upcoming release and get ready to experience smart device technology in a whole new way.

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