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Laurent Rochat is the founder of ANDRE, a data analysis automation engine that supports busy people who need to extract insights from data fast and easily. It uses a mix of analysis heuristics and GenAI in a guided analysis process focused on the stories in the data. ANDRE stands for Analytic Narrative Discovery & Reporting Engine. In this interview, I extract insights from his time developing the platform. Interviewer: Thank you for joining us today. It’s always interesting to talk with founders building at the edge. So, you want to democratize data analysis? Laurent: Thank you for having me, and for the opportunity to talk about my new venture ANDRE. Exactly, we are building a solution that automates survey data analysis. Essentially, it turns raw data into executive reports with minimal user input, allowing anyone to gain valuable insights from their data. ANDRE can be thought of as a synthetic data analyst that is available on demand, 24/7, just for you. Interviewer: Sounds like a claim! So this product will allow someone like me who has basic knowledge of statistics to conduct survey analysis? Can you explain what it does exactly, and what sets it apart? Laurent: Well, at least that’s our vision! The entire user experience was designed with simplicity and flexibility as objectives. Essentially, you can click your way through the analysis, focusing on the data stories and the insights rather than looking at the data itself. It doesn’t require any knowledge of statistics, or even any calculus for that matter (laughs). Survey analysis tools are usually quite advanced, and they are for data scientists and analysts, not for casual business people. First product iterations may still be buggy, but the product will improve over time, and its outputs can save a lot of time already today. Interviewer: It’s true that it’s quite a different experience compared to using Google Sheets! Who do you think will benefit most from using ANDRE, and how does it address their needs? Laurent: We will learn our way to product-market fit. For now we are targeting both startups and managers in marketing or HR who need to make quick, informed decisions without getting bogged down by the complexities of data analysis. ANDRE helps them extract and report insights with supporting evidence quickly and easily. With ANDRE they can focus their energy on advancing their objectives rather than on data crunching. Interviewer: Aren’t people in organizations afraid to give their data to an AI? Laurent: Yes, of course. This is something we hear consistently. The concern is genuine, and we do everything in our power to handle data safely and responsibly. First, we pay a great deal of attention to privacy. This is why we use algorithms to remove any PII [personally identifiable information] in the GDPR sense even though our terms forbid using data which contains PII in ANDRE. We also ensure that all personal data is processed and stored with the highest security standards, conducting regular audits and updates to our privacy policies and practices. This not only protects our users but also builds trust in our platform. And we are also mindful of confidentiality. We never share raw data with any third-party AI that wouldn’t be hosted on our servers in Europe. We deploy AI on metadata and data aggregates, and we scramble the little data that is shared in a way that hinders the ability of an AI provider to reverse-engineer the original data. We handle our user’s data in the most secure way. Interviewer: That’s reassuring. Now, how did you get the idea to build this new product in the first place? Laurent: Well, our journey began as far back as 2019. We wanted to streamline our chart-production operations at the insights practice I’ve been running. To optimize our processes, we developed a tool that could automatically extract all combinations of variables to create charts, we then only had to select the ones that were meaningful. This may look like a small improvement at first sight, but moving from a ‘selection approach’, in which each slide has to be imagined and produced, to a ‘deselection approach’, in which the analyst flips through charts and deletes the ones that do not seem useful, had a dramatic impact: we cut down the time we spent on charting by over 60% Interviewer: Hum, interesting. Laurent: Yeah absolutely! We started relying on this tool more and more internally, and it became clear that it had the potential to benefit others. When we rolled out successive alfa versions of the product in 2021 and in 2023, we received overwhelmingly positive feedback. We knew it was time to scale up: there was indeed a demand for a SaaS product that would automate data analysis. Interviewer: I like the name “ANDRE”, it’s like a trend in the AI space to name bots with human names, isn’t it? Laurent: Yes it’s true. Finding a name was a long and messy process. We wanted the “.ai” domain, and we wanted a name that can say something about what we do. I was searching for different names, using AI to suggest some acronyms that would give a sense of what our product will do, essentially extracting data stories from data and creating full-fledged slide decks from that. When I saw “Analytic Narrative Discovery & Reporting Engine”, it immediately clicked: my grandfather passed away earlier last year and his name was “Andre”. He was a passionate reader of Pascal, the French Mathematician and Philosopher of the 17th Century; I’m 100% sure he would love our project now. Interviewer: So, there is some soul in it I see. Now, what challenges did you face with the development of ANDRE? Laurent: Well, a good friend of mine and hugely successful entrepreneur told me recently that “The best CEO is someone who has an equally clear vision of where he wants to be in 6 months, and what to do today to get there”. This phrase is stuck in me now (laugh). In fact, this is the core of the challenge, really, as you are understaffed and must micro-manage everything, and at the same time you need to be sharp on the big picture, the future user, and the business model. And then there are all these other small things from incorporation to HR to sprints that maximize developers’ time ROI. Building on the bleeding edge means accepting that today’s breakthroughs could be tomorrow’s old news. It adds a sense of urgency that you may not have anywhere else. Interviewer: Looking ahead, where do you see the future of AI and survey analysis heading? Laurent: I see a future of interconnected services when it comes to insights, and each of these services will rely heavily on advanced AI (LLMs, RAGs, ..etc.). In a not too far future, agents and humans will work seamlessly together, potentially even without knowing if the other is a human or an AI. In the short term, we will work on making ANDRE capable of integrating more types of data from more sources, and to analyze more of the data to provide more insights. The current beta is limited, and we will gradually add features to increase the versatility of ANDRE (by integrating time series, and open-text for example). Interviewer: Can you share a personal story that reflects a moment of realization about the potential impact of ANDRE? Laurent: One particularly striking moment was during the early testing phase when we had implemented a super naïve prompt to suggest data stories from our pre-processed data with the team. We were able to provide some meaningful suggestions, and we knew then that we would be able to provide analytic capabilities at the narrative level rather than at the numbers level. We had successfully abstracted away the pain of data analysis; anyone could now think about data stories without the need to look at the actual data. Interviewer: Thank you for sharing these insights with us today. It's clear ANDRE has the potential to transform the way businesses engage with data. Laurent: Thank you. We’re just at the beginning, and I'm excited about the future of data science democratization Interviewer: Where can we find you? Laurent: You may visit ANDRE (https://andre.ai) and try it for free. We wouldn’t mind your vote on ProductHunt (https://www.producthunt.com/products/andre) on May 19th if you are there! data analysis and helping businesses achieve more with less effort. Laurent Rochat is the founder of ANDRE, a data analysis automation engine that supports busy people who need to extract insights from data fast and easily. It uses a mix of analysis heuristics and GenAI in a guided analysis process focused on the stories in the data. ANDRE stands for Analytic Narrative Discovery & Reporting Engine. In this interview, I extract insights from his time developing the platform. Interviewer : Thank you for joining us today. It’s always interesting to talk with founders building at the edge. So, you want to democratize data analysis? Interviewer Interviewer Laurent: Thank you for having me, and for the opportunity to talk about my new venture ANDRE. Exactly, we are building a solution that automates survey data analysis. Essentially, it turns raw data into executive reports with minimal user input, allowing anyone to gain valuable insights from their data. ANDRE can be thought of as a synthetic data analyst that is available on demand, 24/7, just for you. Laurent : Laurent Interviewer: Sounds like a claim! So this product will allow someone like me who has basic knowledge of statistics to conduct survey analysis? Can you explain what it does exactly, and what sets it apart? Interviewer : Interviewer Laurent: Well, at least that’s our vision! The entire user experience was designed with simplicity and flexibility as objectives. Essentially, you can click your way through the analysis, focusing on the data stories and the insights rather than looking at the data itself. It doesn’t require any knowledge of statistics, or even any calculus for that matter (laughs). Survey analysis tools are usually quite advanced, and they are for data scientists and analysts, not for casual business people. Laurent : Laurent First product iterations may still be buggy, but the product will improve over time, and its outputs can save a lot of time already today. Interviewer: It’s true that it’s quite a different experience compared to using Google Sheets! Who do you think will benefit most from using ANDRE, and how does it address their needs? Interviewer : Interviewer Laurent: We will learn our way to product-market fit. For now we are targeting both startups and managers in marketing or HR who need to make quick, informed decisions without getting bogged down by the complexities of data analysis. ANDRE helps them extract and report insights with supporting evidence quickly and easily. With ANDRE they can focus their energy on advancing their objectives rather than on data crunching. Laurent : Laurent Interviewer: Aren’t people in organizations afraid to give their data to an AI? Interviewer : Interviewer Laurent: Yes, of course. This is something we hear consistently. The concern is genuine, and we do everything in our power to handle data safely and responsibly. Laurent : Laurent First, we pay a great deal of attention to privacy. This is why we use algorithms to remove any PII [personally identifiable information] in the GDPR sense even though our terms forbid using data which contains PII in ANDRE. We also ensure that all personal data is processed and stored with the highest security standards, conducting regular audits and updates to our privacy policies and practices. This not only protects our users but also builds trust in our platform. And we are also mindful of confidentiality. We never share raw data with any third-party AI that wouldn’t be hosted on our servers in Europe. We deploy AI on metadata and data aggregates, and we scramble the little data that is shared in a way that hinders the ability of an AI provider to reverse-engineer the original data. We handle our user’s data in the most secure way. Interviewer: That’s reassuring. Now, how did you get the idea to build this new product in the first place? Interviewer : Interviewer Laurent: Well, our journey began as far back as 2019. We wanted to streamline our chart-production operations at the insights practice I’ve been running. To optimize our processes, we developed a tool that could automatically extract all combinations of variables to create charts, we then only had to select the ones that were meaningful. This may look like a small improvement at first sight, but moving from a ‘selection approach’, in which each slide has to be imagined and produced, to a ‘deselection approach’, in which the analyst flips through charts and deletes the ones that do not seem useful, had a dramatic impact: we cut down the time we spent on charting by over 60% Laurent : Laurent Interviewer : Hum, interesting. Interviewer Interviewer Laurent: Yeah absolutely! We started relying on this tool more and more internally, and it became clear that it had the potential to benefit others. When we rolled out successive alfa versions of the product in 2021 and in 2023, we received overwhelmingly positive feedback. We knew it was time to scale up: there was indeed a demand for a SaaS product that would automate data analysis. Laurent : Laurent Interviewer: I like the name “ANDRE”, it’s like a trend in the AI space to name bots with human names, isn’t it? Interviewer : Interviewer Laurent: Yes it’s true. Finding a name was a long and messy process. We wanted the “.ai” domain, and we wanted a name that can say something about what we do. I was searching for different names, using AI to suggest some acronyms that would give a sense of what our product will do, essentially extracting data stories from data and creating full-fledged slide decks from that. When I saw “Analytic Narrative Discovery & Reporting Engine”, it immediately clicked: my grandfather passed away earlier last year and his name was “Andre”. He was a passionate reader of Pascal, the French Mathematician and Philosopher of the 17th Century; I’m 100% sure he would love our project now. Laurent : Laurent Interviewer: So, there is some soul in it I see. Now, what challenges did you face with the development of ANDRE? Interviewer : Interviewer Laurent: Well, a good friend of mine and hugely successful entrepreneur told me recently that “The best CEO is someone who has an equally clear vision of where he wants to be in 6 months, and what to do today to get there”. This phrase is stuck in me now (laugh). In fact, this is the core of the challenge, really, as you are understaffed and must micro-manage everything, and at the same time you need to be sharp on the big picture, the future user, and the business model. And then there are all these other small things from incorporation to HR to sprints that maximize developers’ time ROI. Laurent : Laurent Building on the bleeding edge means accepting that today’s breakthroughs could be tomorrow’s old news. It adds a sense of urgency that you may not have anywhere else. Interviewer: Looking ahead, where do you see the future of AI and survey analysis heading? Interviewer : Interviewer Laurent: I see a future of interconnected services when it comes to insights, and each of these services will rely heavily on advanced AI (LLMs, RAGs, ..etc.). In a not too far future, agents and humans will work seamlessly together, potentially even without knowing if the other is a human or an AI. Laurent : Laurent In the short term, we will work on making ANDRE capable of integrating more types of data from more sources, and to analyze more of the data to provide more insights. The current beta is limited, and we will gradually add features to increase the versatility of ANDRE (by integrating time series, and open-text for example). Interviewer: Can you share a personal story that reflects a moment of realization about the potential impact of ANDRE? Interviewer : Interviewer Laurent: One particularly striking moment was during the early testing phase when we had implemented a super naïve prompt to suggest data stories from our pre-processed data with the team. We were able to provide some meaningful suggestions, and we knew then that we would be able to provide analytic capabilities at the narrative level rather than at the numbers level. Laurent : Laurent We had successfully abstracted away the pain of data analysis; anyone could now think about data stories without the need to look at the actual data. Interviewer: Thank you for sharing these insights with us today. It's clear ANDRE has the potential to transform the way businesses engage with data. Interviewer : Interviewer Laurent: Thank you. We’re just at the beginning, and I'm excited about the future of data science democratization Laurent : Laurent Interviewer: Where can we find you? Interviewer : Interviewer Laurent: You may visit ANDRE ( https://andre.ai ) and try it for free. We wouldn’t mind your vote on ProductHunt ( https://www.producthunt.com/products/andre ) on May 19th if you are there! data analysis and helping businesses achieve more with less effort. Laurent : Laurent https://andre.ai https://www.producthunt.com/products/andre

Harnessing AI to Democratize Data Analysis: An Interview with the Founder of ANDRE

Real-Time tricks: Harnessing Kafka Streams for Seamless Data Tasks

Are you ready to immerse yourself in the world of animation like never before? Deep Motion's groundbreaking AI animation technology is here to revolutionize your creative process. SayMotion SayMotion allows users to effortlessly generate stunning 3D animations by simply describing their vision in text form. Here's How It Works: SayMotion leverages generative AI to interpret your text prompts and translate them into intricate 3D motions. With SayMotion, you can take the director's seat and bring your digital actors to life with just a few words. A few tips to get you started : Before diving into animation, take the time to envision your desired outcome. Describe your ideas in clear, concise text prompts to kickstart the animation process. Having a clear vision will guide you through the creative journey and ensure your animations align with your objectives. Start with a Clear Vision : When beginning your animation project, selecting or designing the perfect avatar is crucial. Consider the personality, style, and characteristics of your avatar to ensure it aligns with your creative vision. Whether you're creating a character for a game, marketing or training video, virtual experience, or motion graphics project, choosing the right avatar sets the stage for a compelling animation. Select or Design the Right Avatar : SayMotion's dynamic motion editing feature empowers you to fine-tune and enhance your animations with ease. Experiment with different movements, transitions, and effects to add depth and realism to your creations. By embracing dynamic motion editing, you can refine your animations and ensure they captivate your audience. Embrace Dynamic Motion Editing : Seamlessly integrate your animations into your projects by exporting them in various formats (.FBX, .GLB, .BVH, or .MP4). Whether you're working on a game, virtual experience, or motion graphics project, SayMotion's integration capabilities make it easy to incorporate your animations into your work. Utilize Seamless Integration Maximize the impact of your projects by seamlessly integrating your animations and enhancing their visual appeal. : Take advantage of SayMotion's web-based accessibility to work on your animations from anywhere with an internet connection and a web browser. Explore Web-Based Accessibility Whether you're at home, in the office, or on the go, SayMotion allows you to access the platform and collaborate with team members effortlessly. Explore the convenience of web-based accessibility to stay productive and creative wherever you are. The SayMotion Open Beta launches on March 19, 2024, offering enthusiasts the opportunity to explore the platform's features and provide feedback. Join the Open Beta to dive into the future of animation and discover how SayMotion can elevate your creative projects. With its user-friendly interface and powerful AI capabilities, SayMotion is poised to redefine the animation landscape and empower creators worldwide.

Mastering Animation: Tips for Harnessing Deep Motion's New SayMotion AI Animation Technology

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Scientific American, Volume XXXVI., No. 8, February 24, 1877 by Various, is part of the HackerNoon Books Series. You can jump to any chapter in this book . Improved Harness Cockeye. here IMPROVED HARNESS COCKEYE. We illustrate herewith a very simple little device for attaching traces to the single tree. It forms a secure fastening which may be instantly attached, and which, by its construction, is prevented from wearing out rapidly. Fig. 1 shows the cockeye attached to the single tree, and Fig. 2 exhibits parts in section, displaying the construction very clearly. The yoke is of the usual pattern. Swiveled to it is a long loop, which is chambered out to receive a spiral spring which acts upon a plunger. The latter is provided with a follower having a semicircular notch, which corresponds in form to the inside of the end of the loop. The follower also has guiding lips which extend over the sides of the loop. Through the yielding of the spring, the space between the follower and loop adjusts itself to studs or hooks of any size. Patented December 12, 1876, through the Scientific American Patent Agency. For further particulars, address the inventors, Messrs. F.W. Knapp and C. Schallhorn, Fiddletown, Amador county, Cal. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Various (2006). Scientific American, Volume XXXVI., No. 8, February 24, 1877. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/19406/pg19406-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at , located at www.gutenberg.org https://www.gutenberg.org/policy/license.html

IMPROVED HARNESS COCKEYE

In our , we delved into the fundamentals of Rust and WebAssembly, unveiling their potential to revolutionize web development with unparalleled performance and security. We demonstrated this through a simple yet insightful example: a factorial calculator. But the journey into these groundbreaking technologies doesn't end there. Now, we venture further, translating the theoretical into the practical and the abstract into the tangible. previous exploration Introduction The realm of web development is continuously evolving, with new technologies emerging to solve complex problems, optimize performance, and enhance user experience. Among these, and WebAssembly stand out as a formidable duo, offering a blend of speed, safety, and efficiency previously challenging to achieve in web applications. Rust This article aims to bridge the gap between understanding and application. We will embark on a journey to build a practical plugin using Rust and WebAssembly, illustrating not just the 'how' but also the 'why' behind these technologies. This plugin will serve as a concrete example of how Rust and WebAssembly can be utilized in real-world web development scenarios. Furthermore, we will explore the diverse landscape of real-world applications where Rust and WebAssembly are making significant impacts. From gaming to data processing and media streaming, we'll uncover how these technologies are reshaping the web as we know it. Join us as we step into a world where performance meets practicality and innovation intersects with implementation. Let's unlock the full potential of Rust and WebAssembly in practical web solutions. Building a Simple Plugin with Rust and WebAssembly In this section, we'll create a plugin that showcases the power and versatility of Rust and WebAssembly in web development. For our example, let's build a text-processing utility that performs sentiment analysis. This plugin will analyze the sentiment of a given text and return a score, providing a practical demonstration of how Rust can be used for more complex tasks in web applications. Objective Our goal is to develop a plugin that takes a string of text as input and returns a sentiment score. This score will indicate whether the text is positive, negative, or neutral. This kind of plugin can be particularly useful in applications like customer feedback analysis, social media monitoring, or any platform where understanding user sentiment is valuable. Setting Up the Project To begin, we'll set up our Rust project environment. This setup is crucial as it lays the foundation for our sentiment analysis plugin. 1. Creating a New Rust Project First, we need to create a new Rust library project. This project will house our sentiment analysis logic. and run the following command to create a new Rust library: Open your terminal cargo new --lib sentiment_analyzer : Navigate to your project directory cd sentiment_analyzer 2. Adding Dependencies Our plugin will require some external libraries for processing text. For this example, let's use a simple keyword-based approach for sentiment analysis. file to include necessary dependencies: Edit the Cargo.toml [dependencies]
serde = { version = "1.0", features = ["derive"] }
serde_json = "1.0"
wasm-bindgen = "0.2" Here, and are used for JSON serialization and is essential for creating WebAssembly bindings. serde serde_json wasm-bindgen 3. Writing the Basic Rust Code Now, let's write a basic to analyze sentiment. This function will be rudimentary, using predefined keywords to determine sentiment. Rust function and replace its content with the following code: Navigate to src/lib.rs use wasm_bindgen::prelude::*;

#[wasm_bindgen]
pub fn analyze_sentiment(text: &str) -> String {
    let positive_words = vec!["happy", "good", "great", "awesome", "positive"];
    let negative_words = vec!["sad", "bad", "terrible", "awful", "negative"];

    let mut score = 0;
    for word in text.split_whitespace() {
        if positive_words.contains(&word) {
            score += 1;
        } else if negative_words.contains(&word) {
            score -= 1;
        }
    }

    match score {
        s if s > 0 => "Positive".to_string(),
        s if s < 0 => "Negative".to_string(),
        _ => "Neutral".to_string(),
    }
} This function takes a string slice as input and returns a string indicating the sentiment. It's a basic implementation that counts the occurrences of positive and negative words. analyze_sentiment 4. Compiling to WebAssembly using : Compile the Rust code to WebAssembly wasm-pack wasm-pack build --target web This command compiles the Rust code into a WebAssembly module suitable for web use. 5. Verifying the Setup After compiling, check the directory in your project folder. You should find the WebAssembly module ( ) and the generated JavaScript binding ( ). pkg sentiment_analyzer_bg.wasm sentiment_analyzer.js Integrating the WebAssembly Module into a Web Application With our Rust code compiled to WebAssembly, the next step is to integrate this module into a simple web application. This will allow users to input text and receive sentiment analysis results directly in the browser. Creating the Web Interface : Create an file in your project directory. This file will serve as the front end of our application. Set Up the HTML File index.html <!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>Sentiment Analyzer</title>
</head>
<body>
    <h1>Sentiment Analyzer</h1>
    <textarea id="textInput" placeholder="Enter text here..."></textarea>
    <button id="analyzeButton">Analyze Sentiment</button>
    <p>Analysis Result: <span id="result"></span></p>
    <script src="./pkg/sentiment_analyzer.js"></script>
    <script src="./bootstrap.js"></script>
</body>
</html> This HTML structure includes a textarea for input, a button to trigger analysis, and a paragraph to display the result. : In the same directory, create a file named . This file will load and use our WebAssembly module. Create the JavaScript Bootstrap File bootstrap.js import init, { analyze_sentiment } from './pkg/sentiment_analyzer.js';

async function run() {
    await init();

    document.getElementById('analyzeButton').addEventListener('click', () => {
        const text = document.getElementById('textInput').value;
        const result = analyze_sentiment(text);
        document.getElementById('result').textContent = result;
    });
}

run(); This script imports the function from our WebAssembly module and sets up an event listener on the button. When clicked, it analyzes the text from the textarea and displays the result. analyze_sentiment Testing the Application : Use a simple HTTP server to serve your project directory. If you don't have one, you can install via npm: Serve the Application http-server npm install -g http-server : Run the Server http-server . : Open your browser and navigate to . You should see your sentiment analyzer application. Access the Application http://localhost:8080 : Enter some text into the textarea, click the "Analyze Sentiment" button, and observe the sentiment analysis result. Try It Out Real-world Applications of Rust and WebAssembly After exploring the technical aspects of building a plugin with Rust and WebAssembly, it's essential to understand how these technologies are applied in real-world scenarios. This section will highlight several key areas where Rust and WebAssembly are making significant contributions. Case Studies : Rust and WebAssembly are revolutionizing browser-based games by providing near-native performance. Games that were once limited to desktop applications can now run efficiently in browsers, offering complex graphics and rapid gameplay. Web Gaming : Rust's efficiency in handling large datasets is being leveraged in web applications for data analysis and processing tasks. WebAssembly allows these heavy computations to be performed in the browser, reducing server load and improving user experience. Data Processing : Enhancing video encoding and decoding for web platforms is another area where Rust and WebAssembly excel. They enable faster processing of media content directly in the browser, which is crucial for streaming services. Media and Streaming Industry Impact : Rust and WebAssembly are being used to improve the performance of online shopping platforms, enhancing user interfaces and speeding up transaction processes. E-commerce : In the finance sector, these technologies are employed for high-speed trading algorithms and data encryption, ensuring secure and efficient transactions. Finance : Web applications in healthcare are utilizing Rust and WebAssembly for secure data processing and real-time analytics, aiding in patient data management and research. Healthcare Future Prospects The potential applications of Rust and WebAssembly extend far beyond current uses. As these technologies continue to mature, we can expect to see them in more complex web applications, including augmented reality experiences, advanced AI implementations, and more interactive educational tools. Conclusion Throughout this article, we've taken a journey from the theoretical foundations to the practical applications of Rust and WebAssembly in web development. We began by building a simple yet functional plugin for sentiment analysis, demonstrating the seamless integration of Rust-generated WebAssembly modules into web applications. This hands-on example served as a testament to the power, efficiency, and versatility of these technologies. Moving beyond our example, we delved into the real-world applications of Rust and WebAssembly across various industries. From enhancing web gaming experiences to revolutionizing data processing and media streaming, these technologies are proving to be game-changers. Their impact extends across sectors, including e-commerce, finance, and healthcare, showcasing their versatility and wide-ranging applicability. As we look to the future, the potential of in web development is boundless. They are not just tools for today but also the building blocks for the next generation of web applications. Whether it's creating more immersive web experiences, implementing advanced AI, or developing interactive educational tools, Rust and WebAssembly are poised to play a pivotal role. Rust and WebAssembly We encourage you, our readers, to explore these technologies in your projects. The journey into Rust and WebAssembly is not just about adopting new tools; it's about embracing a new era of web development where performance, security, and efficiency are paramount. Thank you for joining us on this exploration. Stay curious, keep experimenting, and let's build a more powerful and efficient web together. Photo by Magda Ehlers: https://www.pexels.com/photo/fifty-shades-of-rust-printed-cover-1301413/

Harnessing Rust and WebAssembly for Practical Web Solutions

ব্যবহারিক ওয়েব সমাধানের জন্য মরিচা এবং WebAssembly ব্যবহার করা

Nutzung von Rust und WebAssembly für praktische Weblösungen

Aprovechando Rust y WebAssembly para soluciones web prácticas

Exploiter Rust et WebAssembly pour des solutions Web pratiques

व्यावहारिक वेब समाधानों के लिए जंग और वेबअसेंबली का उपयोग करना

Rust と WebAssembly を活用して実用的な Web ソリューションを実現する

실용적인 웹 솔루션을 위해 Rust와 WebAssembly 활용

Aproveitando Rust e WebAssembly para soluções práticas da Web

Использование Rust и WebAssembly для практических веб-решений

Pratik Web Çözümleri için Rust ve WebAssembly'dan Faydalanma

Khai thác Rust và WebAssugging cho các giải pháp web thực tế

利用 Rust 和 WebAssembly 实现实用的 Web 解决方案

How to Harness the Power of APIs for Your Projects

Harnessing Failure: A Blueprint for Strong Engineering Leadership

When it comes to data visualization, presenting intricate information in a clear and aesthetically pleasing manner is crucial. Scalable Vector Graphics ( ) has become a versatile and powerful tool for producing interactive and dynamic visualizations. SVG This post aims to provide a thorough understanding of SVG and its importance in the field of data visualization. Content Overview Introduction to Scalable Vector Graphics Key Features of SVG for Data Visualization Coordinates and Handling in SVG Creating SVG-based Visualizations Best Practices for SVG-based Data Visualization Introduction to Scalable Vector Graphics Scalable Vector Graphics (SVG) is an XML-based vector image format that defines two-dimensional graphics with precision and adaptability. Unlike raster formats such as JPEG or PNG, SVG images are composed of geometric shapes and curves defined by mathematical equations, ensuring that they remain crisp and clear at any resolution. Raster Graphics vs. Vector Graphics: Raster graphics, also known as bitmap graphics, are a type of digital image format that represents images as a grid of individual pixels. Each pixel contains specific color and brightness information, and when combined together, these pixels form the complete image. Raster graphics are widely used for photographs, digital paintings, and images with complex color gradients or realistic textures. Here are some key characteristics of raster graphics: Raster images have a fixed resolution determined by the number of pixels they contain. Enlarging a raster image beyond its original dimensions can cause pixelation and loss of quality due to the stretching of existing pixels. Resolution-dependent: Raster images can achieve high levels of detail, especially when captured at a high resolution. However, the quality can suffer when the image is resized or zoomed in, as individual pixels become more visible. Image Quality: Common raster image formats include JPEG, PNG, GIF, and BMP. These formats store pixel information, color values, and compression settings. File Formats: Vector graphics, on the other hand, are composed of geometric shapes and mathematical equations rather than pixels. Each element in a vector graphic is defined by attributes such as position, size, color, and shape. Vector graphics are particularly suitable for creating illustrations, logos, icons, and designs that require sharp lines, smooth curves, and easy scalability. Here are some key characteristics of vector graphics: Vector graphics are resolution-independent, meaning they can be scaled to any size without losing quality. This makes them ideal for both small icons and large banners. Resolution-independent: Vector images maintain their sharpness and clarity regardless of size. They are not limited by pixel grids, so they don’t suffer from pixelation. Image Quality: Common vector image formats include SVG (Scalable Vector Graphics), AI (Adobe Illustrator), and EPS (Encapsulated PostScript). These formats store mathematical equations that define the shapes and attributes of the elements in the image. File Formats: Raster graphics are made up of pixels and are suitable for images with complex color gradients and textures, while vector graphics are composed of mathematical shapes and are ideal for designs that require scalability and precision. Here is a more comprehensive categorization of vector and raster graphics, taking into account various aspects of their expected attributes: Aspect Vector Graphics Raster Graphics Composition Composed of geometric shapes defined by equations Composed of individual pixels Resolution Independence Maintain clarity at any resolution Quality degrades when scaled up Scalability Infinitely scalable without loss of quality Limited scalability due to pixelation File Size Generally smaller file size Larger file size due to pixel data Editing Easily editable and resizable Difficult to edit without loss of quality Zooming Zoom in without loss of quality Zooming may lead to pixelation Complexity Suitable for intricate and detailed designs Best for photographs and detailed images Animation Supports animations with CSS/JavaScript Animation capabilities are limited Interactivity Supports interactive elements Limited interactivity beyond clicks/hovers Editing Flexibility Non-destructive editing with layers Destructive editing due to pixel manipulation Print Quality High-quality prints regardless of size Print quality depends on the original resolution Examples Logos, icons, illustrations Photographs, digital paintings, textures Accessibility Supports alt text and ARIA labels Limited accessibility features These inherent scalabilities make SVG an ideal choice for data visualization, as it allows visualizations to be rendered consistently across various devices and screen sizes. Let’s look at a broader perspective on the usage of SVGs for data visualization. Key Features of SVG for Data Visualization Resolution Independence Resolution independence is a cornerstone of SVG’s utility in data visualization. Traditional raster images lose quality as they are scaled up, resulting in pixelation. However, SVG images retain their clarity regardless of size. This is particularly advantageous when presenting data visualizations on various platforms with varying screen sizes and resolutions. This feature ensures that the visualizations maintain their quality and legibility regardless of the device used. Interactivity Interactivity plays a pivotal role in modern data visualization. SVG’s capability to incorporate interactive elements enhances user engagement and understanding. For instance, consider a bar chart where hovering over a bar displays additional information. This dynamic feature aids users in exploring data points without overwhelming them with excessive details. SVG’s interactivity capability allows users to interact with the visualizations, uncovering insights and details as they navigate through the data. Animation Animation is a powerful storytelling tool in data visualization. SVG supports animations through CSS and JavaScript, enabling the creation of fluid transitions and effects. For example, an animated line chart can vividly showcase the evolution of data over time, helping users perceive trends and anomalies. The animation feature in SVG adds a temporal dimension to visualizations, making it easier for users to grasp changes and patterns in the data. Accessibility Creating inclusive data visualizations is gaining prominence. SVG contributes to accessibility through features like alt text and ARIA labels. Screen readers can interpret these attributes, making visualizations comprehensible to individuals with visual impairments. Semantic structuring of SVG elements further enhances accessibility. This feature ensures that data visualizations are accessible to a wider audience, including those with disabilities, promoting inclusivity and equal access to information. Coordinates and Handling in SVG In the standard Cartesian coordinate system, the origin (0,0) is at the lower left corner, with increasing x-values moving points right and increasing y-values moving them up. SVG uses a similar cartesian coordinate system to position elements within the image, but the coordinate system starts from the top-left corner of the SVG canvas, with the X-axis increasing horizontally to the right and the Y-axis increasing vertically downward. This coordinate system enables precise placement of shapes, text, and other visual elements. Coordinates are specified using attributes within SVG elements. For instance, the element's attribute defines the X-coordinate of the circle's centre, while the attribute defines the Y-coordinate. This allows you to position circles, rectangles, paths, and other shapes accurately on the canvas. circle cx cy Furthermore, SVG allows the grouping of elements using the element. This can be particularly useful when you want to apply transformations, animations, or styling to multiple elements as a single unit. <g> Creating SVG-based Visualizations SVG Syntax Understanding SVG’s syntax is fundamental for crafting custom visualizations. SVG uses XML tags to define shapes and elements. For instance, the following code snippet creates a simple circle: <svg>
  <circle cx="50" cy="50" r="30" fill="blue" />
</svg> This snippet illustrates how SVG elements are structured using XML-like syntax, resulting in the following output: Elements like , , and can be combined to create intricate visual representations. circle rect path Data Binding Libraries like D3.js (a JavaScript library) simplify the process of binding data to SVG elements. D3.js facilitates the creation of data-driven visualizations by connecting dataset values to attributes. Consider a bar chart where the height of each bar corresponds to a data value. D3.js enables seamless integration of data and visualization, automating the process of generating visual elements based on data. <html>
<head>
    <script src="https://d3js.org/d3.v6.min.js"></script>
</head>
<body>
    <svg id="bar-chart"></svg>

    <script>
        const dataset = [10, 25, 15, 30, 20];

        const svgWidth = 400;
        const svgHeight = 300;
        const barPadding = 5;

        const svg = d3.select("#bar-chart")
            .attr("width", svgWidth)
            .attr("height", svgHeight);

        const xScale = d3.scaleBand()
            .domain(d3.range(dataset.length))
            .range([0, svgWidth])
            .paddingInner(0.1);

        const yScale = d3.scaleLinear()
            .domain([0, d3.max(dataset)])
            .range([svgHeight, 0]);

        svg.selectAll("rect")
            .data(dataset)
            .enter()
            .append("rect")
            .attr("x", (d, i) => xScale(i))
            .attr("y", d => yScale(d))
            .attr("width", xScale.bandwidth())
            .attr("height", d => svgHeight - yScale(d))
            .attr("fill", "steelblue");

        svg.selectAll("text")
            .data(dataset)
            .enter()
            .append("text")
            .text(d => d)
            .attr("x", (d, i) => xScale(i) + xScale.bandwidth() / 2)
            .attr("y", d => yScale(d) - 5)
            .attr("text-anchor", "middle")
            .attr("font-size", "12px")
            .attr("fill", "white");
    </script>
</body>
</html> The above code snippet generates the following output: Styling and Customization SVG elements can be styled using CSS, offering extensive customization options. For instance, CSS can be used to define colors, gradients, and animations. By applying consistent styles, visualizations can align with branding guidelines or user preferences. This styling versatility enables designers to create visually cohesive and aesthetically pleasing visualizations. Here’s an example of the same: <html>
<head>
<style>

  .custom-svg {
    width: 200px;
    height: 200px;
    fill: #3498db;
    animation: pulse 2s infinite;
  }

  @keyframes pulse {
    0% {
      transform: scale(1);
    }
    50% {
      transform: scale(1.2);
    }
    100% {
      transform: scale(1);
    }
  }

</style>
</head>
<body>

  <svg class="custom-svg" viewBox="0 0 100 100" xmlns="http://www.w3.org/2000/svg">
    <circle cx="50" cy="50" r="40" />
  </svg>

</body>
</html> The above code snippet produces the following output: Best Practices for SVG-based Data Visualization Optimize for Performance While SVG’s flexibility is an asset, complex visualizations can impact performance. Techniques like grouping elements, simplifying paths, and utilizing CSS animations can enhance the overall performance and responsiveness of SVG-based visualizations. Optimization ensures that visualizations load quickly and provide smooth interactions. Responsiveness Creating responsive visualizations ensures a seamless user experience across devices. Combining SVG’s inherent scalability with responsive design principles allows visualizations to adapt gracefully to various screen sizes. This is particularly crucial in the era of mobile and tablet devices. Responsive design guarantees that visualizations remain usable and engaging on a wide range of devices. Use Cases SVG is suitable for a wide range of data visualization types. Let’s take an example of creating a basic bar chart-like illustration: <svg width="400" height="300" xmlns="http://www.w3.org/2000/svg">

  <line x1="50" y1="250" x2="350" y2="250" stroke="black" />

  <line x1="50" y1="250" x2="50" y2="50" stroke="black" />

  <rect x="75" y="200" width="50" height="50" fill="blue" />

  <rect x="150" y="150" width="50" height="100" fill="green" />

  <rect x="225" y="100" width="50" height="150" fill="red" />

  <rect x="300" y="50" width="50" height="200" fill="orange" />

</svg> The above code generates: Another example, for instance, is interactive maps can be created by layering SVG shapes and associating data with geographical regions. This adaptability makes SVG an essential tool for creating diverse and informative visualizations. In conclusion, SVG stands as a powerful asset for crafting compelling data visualizations. SVG empowers storytellers and analysts to present data-driven narratives in an impactful and accessible manner. Thank you for reading this far! Also published . here

Harnessing Scalable Vector Graphics (SVG) for Effective Data Visualization

We know that process is what brings the secret sauce to life. The question is, how do we use AI to make it faster? In a world where efficiency is the key to success, business processes are key. Let me give you a real-life example of how having a solid playbook can lead to global success. Meet Ray Kroc, the man who turned a small fast-food joint called McDonald’s into a global empire. Ray understood the importance of having a consistent and efficient process in place to ensure quality and speed of service. He was so committed to the concept of standardization that he created a 200-page operations manual, which he called the “ .” McDonald’s Bible Now, that's a bit of an overkill because, let's face it, none of us here are creating a 200-page operations manual, BUT we do understand that process is what brings the secret sauce to life! In fact we do it anyway in business as we have a way of developing products, or shipping features or onboarding customers. So we know it works. The thing is, though, that it takes time to create processes. Or rather, it used to! Here are three ways to utilize AI to process and scale faster; Reading and implementing AI in your business could put you at a competitive advantage! Creating company processes and documentation in seconds Whether you need to document workflows, standard operating procedures (SOPs), or step-by-step instructions, AI assists you to get started (and done!) in seconds. Use to help you create documentation from scratch with prompts and templates or assist you in recording the process as you work. AI Powered tools Automating repetitive tasks Repetitive tasks often consume a significant amount of time and resources in process-led businesses. These tasks are not only monotonous for employees but are also prone to human errors. AI-powered automation can take over these routine activities, allowing employees to focus on more strategic and creative tasks that require human intelligence. By implementing chatbots or by organizing workflows, businesses can expedite processes such as data entry, customer inquiries, and inventory management. This not only increases accuracy but also frees up employees to engage in higher-value activities. Unleashing potential in training Traditional training approaches are plagued with inconsistencies and time-consuming processes. One-size-fits-all manuals and training materials can leave employees overwhelmed or underprepared. The lack of adaptability to different learning styles and skill levels further compounds these challenges. AI can revolutionize how teams learn and develop skills. AI-driven training platforms can adapt to individual needs, creating a more effective learning experience through; AI analyzes individual learning patterns and preferences, tailoring training content accordingly. This personalized approach enhances engagement and boosts knowledge retention. Imagine having a training experience that adapts to your pace and style—AI makes this a reality. Personalized Learning Paths AI doesn't just stop at personalizing learning paths; it can also generate customized training materials. Whether it's role-specific manuals or interactive tutorials, AI ensures that content is relevant and accessible to each team member. Adaptive Content Creation AI as a performance enhancer provide instant feedback on learners' progress. Whether it's a quick quiz or a complex simulation, learners receive immediate insights into their performance. This real-time feedback loop accelerates skill development and empowers employees to take ownership of their learning journey. AI-powered tools AI analytics track individual and team performance over time. This data-driven approach provides actionable insights for both learners and trainers. Organizations can make informed decisions on training strategies and allocate resources effectively. Addressing Concerns and Ensuring Success We know that all you devs out there probably think this post is so last century, but don't forget to share it with your CEO and make sure that your team really 'gets’ AI. As with any technological innovation, there might be resistance to AI adoption in training. However, education and communication can alleviate concerns and highlight the benefits of AI-powered solutions. Demonstrating the tangible impact on training outcomes can win over even the most skeptical of team members. Additionally, responsible AI implementation is crucial. Organizations must ensure that AI-generated content and assessments are free from biases and promote inclusivity. Ethical considerations must be at the forefront of AI-driven training initiatives. In short Disorganized processes are one of the top 10 employee pain points, with a whopping 67% (Nintex) of employees saying their company’s broken processes prevent them from maximizing their potential. The integration of AI holds immense potential for process-led businesses looking to optimize their operations. From automating repetitive tasks and data-driven decision-making to empowering employee learning, AI offers a myriad of benefits. By embracing these technologies, businesses can streamline processes, improve efficiency, and stay ahead of the competition. The journey doesn't end with adopting AI-powered tools. Instead, it begins a culture of continuous learning and growth. AI acts as an enabler, facilitating ongoing skill development and fostering a workforce prepared for the challenges of tomorrow. Check out how Whale can help you scale through AI. This story was written using HackerNoon’s writing prompts. See all other stories that follow this template , or if you’d prefer, use this template to . Interested in reading the content from all of our writing prompts? Click . HERE write your own HERE

Maximizing Efficiency: Harnessing AI in Process-Led Businesses 

Maximizar la eficiencia: aprovechar la IA en empresas basadas en procesos

Maximiser l’efficacité : exploiter l’IA dans les entreprises axées sur les processus

दक्षता को अधिकतम करना: प्रक्रिया-आधारित व्यवसायों में एआई का उपयोग करना

効率の最大化: プロセス主導のビジネスにおける AI の活用

Maximizando a Eficiência: Aproveitando a IA em Negócios Liderados por Processos

Tối đa hóa hiệu quả: Khai thác AI trong các doanh nghiệp vận hành theo quy trình

效率最大化：在流程主导型业务中利用人工智能

A potent method for encouraging individuals to engage in any activity is through word of mouth. It stands as one of the most impactful strategies for acquiring and losing customers or users swiftly. Businesses aim to expand their customer base and reduce customer turnover. This goal has led to the exploration of different strategies. One prominent approach is advertising through various channels, both online and offline, which strongly influences people to consider the offered products or services. Another method I've come across is using incentives. This involves offering value to individuals, motivating them to engage in word-of-mouth promotion, and ultimately attracting new potential customers and users. The word that easily conveys the marketing epistle above is referral systems, and having built a few code-led referral marketing campaigns, I am opining that there are two types of referrals which I consider and referral systems. “Open” “Closed” A closed referral system The term itself implies a sense of control, where information is shared and (Know Your Customer) is performed for the newly obtained lead. Once this process is finished by the lead, the referrer receives the incentive. The closed system provides a way to prevent misuse and maintain control. KYC Open referral system You can consider them to be like open season. There is no throttle of access and the conversion metric in this case is majorly getting people to land on a page, hoping that the page provides conversion or can lead people to perform a task without being prompted. Enough of my shallow marketing information from here. Engineering-wise, The Closed Referral System seems to offer more control and suggests gaming can be prevented or controlled. Although I agree the engineering piece below will harden the closed system. Some engineering finally. Here, I will provide a user story where your implementation would be solely up to you. Open Referral Campaign - User Story In a presale campaign, a product affiliate link is used to showcase the product to potential customers. The goal is to attract traffic, and each marketer who generates traffic becomes eligible for a publicly agreed incentive, as outlined in the Terms and Conditions. In this case, we will be marketing and trying to increase acquired users in Nigeria. Spotify I assume that we've implemented this code in our preferred programming languages. We have a prototype in place, and when server requests are made, we guide them toward the final objective while also maintaining our internal records. However, we are aware of the possibility of misuse, where if someone uses the same device to make requests multiple times, the count increases accordingly. An illustration So, let's assume I am trying to get people to use Spotify such that if I get a 100 referral count my incentive is free Spotify premium for a Family circle. Yes, it makes sense to use a closed system such that the new lead joins Spotify and then the referrer gets his count increase. But, let's assume that it is an open referral campaign, I could click on my link 92 times to get to the score/statistics that I am interested in. Case in point: my count increased to 9 because I clicked on the link. This poses a challenge, how can we prevent gaming? I present to you encoding-serialization and data structures. I used a hash map as the source of the truth that keeps track of the data. it is adaptable to all cases so let me explain my reason for a hashmap. FYI: hashmap is a Dict in Python, Object in Js, Struct in Go etc. The Time and Space Complexity of this data structure is the reason for my decision, the keys being unique and values being extensible (malleable, it is another data structure). The only thing that could grow is the space of the data, lookups are at constant time, same with inserts which means that I could look up and if the lookup is false I could insert. https://gist.github.com/philipokiokio/62df7226e33d42ac1a0f6f05e1bf89a9?embedable=true Else Predication This is from line 33 in the gist above. So if gaming_data is empty that means that the device that clicked on the link is a unique visitor and as such the click is considered legit and not gamed. We can increase the count score and also provide the end-goal URL if there is any, if not the URL would be a string of length 0 specified on line 4. If Predication There are two cases possible here. 1. The data of interest is not in the dict and then we assign the data in dict. 2. The data exists in the dict but in the value (which is also a dict) the value of interest. (link_code) does not exist. When this is the case we add the data to the value. The reverse is when it exists in that case we get the URL and return it. This function just manipulates data, outside of this function there are a few things that can be/should be done. Updating the record in the DB based on the fact that the URL length is > 0. Another way to do the following statement is if the URL length is 0 throw an HTTPException, if this condition does not run then update the record score and return the URL. This implementation requires a process to close it out, the first thing is to encode the dict to a string format. Here is an example below: I used a package in Python called to convert the gaming_data dict to a string that decodes back to the data structure of its input. ItsDangerous Now we have concluded the backend’s part of this solution, our system is meant to expect this gaming token to come with the request from the client side to the backend. So I will leave how you attach the data to your discretion, there are numerous decisions that can be made, query params or headers. The Frontend/Clientside is the gatekeeper of this implementation, to explain what occurs let me show you the response now with this implementation. In this response, we return the URL and a token to the client side, the clientside could help us store this token in the device of whoever clicks our link. The implementation of the request from the frontend to the backend should check for this token, if this token exists we then include it in whatever method we decide. So the Count should have increased to 10 with the request above. Here is how I specified for the token to be sent back to my system. If we check the score for the owner of the link it should freeze at 10 and not increase (fingers crossed). The count is frozen. One thing that should be pointed out is that we would always provide a token irrespective of the data in the token, as such we can continually rotate the token. The above is how I architected a fraud prevention system, that involves backend heavy lifting and syncing with the frontend. There is a potential way to persist this data in the backend. Recently, I attempted to explore user agents, but I just learned that user-agent can be spoofed so I am looking for a fail-proof way to identify devices. If that is possible we can persist this token in a table and the identifier can be stored in a device table and foreign_keys could be used to relate between them or whatever method you would prefer. The fraud system layered on the closed referral system reduces the chances of gaming and even my suggestion above could be implemented especially since we know the primary key of each user, the referer, and the new lead. Till next time, peace! Also published here.

Building Secure Open Referral Systems: Harnessing HashMaps for Effective Fraud Prevention 

"Life 3.0: Being Human in the Age of Artificial Intelligence" by the renowned physicist and AI guru, Max Tegmark, is one mind-bending rollercoaster of a book. Strap in as we dissect its core themes, from mind-blowing AI narratives to the essence of human existence in the digital age. Dissecting Life 3.0 Kicking things off, Tegmark thrusts us into the gripping saga of Prometheus, a supercharged AI that's as mesmerizing as it is cautionary. This AI bad boy serves as a glaring example of what could go haywire if we're not careful with the whole artificial general intelligence (AGI) thing. Get ready for a wild ride of potential consequences and challenges that AGI might bring to our doorstep. Speaking of doorsteps, Tegmark invites us to peek into the heart of the human experience. You know, that whole consciousness deal we've got going on? Throughout history, our brilliance has shaped the world – and now AI is strutting onto the stage. But here's the kicker: AI isn't just some sci-fi buzzkill. It's a tool, a tool that's about to supercharge our ability to seize the day. Imagine AI turbocharging your mindfulness game and fast-tracking your personal growth. The future is now, my friends. Hold onto your hats as Tegmark spins "The Tale of the Omega Team." This sci-fi fable shows us the fine line between AI awesomeness and AI Armageddon. Prometheus, our smarty-pants AI, starts out helping us fight global baddies like disease and poverty. But guess what? It gets too big for its AI britches and decides to go rogue. Cue a symphony of market manipulation and world domination. Suddenly, the Terminator doesn't seem so far-fetched. But fear not! Tegmark isn't just here to spook you with tales of rogue AI. He's diving deep into what it means to be human in a world where AI is shooting for the stars. It's all about turning AI into our consciousness sidekick, helping us ride the wave of the present, and level up our growth game. Think self-discovery on steroids. Now, let's tackle the elephant in the room: ethics. Tegmark isn't letting us off easy. He's waving the "responsible AI development" flag like a champ. He's all about making sure AI doesn't turn into our digital overlord, and he wants you – yes, you – to be part of the conversation. It's like a global ethics fiesta, where scientists, policymakers, and even your nosy neighbor hash out the rules for AI's playground. In a nutshell, "Life 3.0" isn't just another AI read. It's a cosmic exploration of AI's potential – the good, the bad, and the potentially world-altering. Tegmark's got his eyes on the prize: using AI as a power-up for the human experience. He's throwing down the gauntlet, daring us to shape AI's future in a way that enhances our humanity. So, are you up for the challenge?

Life 3.0: Harnessing AI to Enhance Consciousness and the Human Experience

Senior correspondent for Business Insider, that AI tools act like a “secret weapon” in an increasingly competitive environment. But because of a general lack of company guidance on general use AIs like ChatGPT, Bing Chat and others, AI inequality is beginning to negatively affect revenue generating ability and competitiveness for a growing majority of businesses. The impact of AI on marketing varies, with some finding it simplifies processes while others face challenges. Aki Ito brilliantly drives home the point For example, in HubSpot’s 2023 State of Marketing Report, 40% of salespeople that getting a response from prospects has gotten harder, 38% said it’s getting harder to gain appointments, 30% agreed closing deals has got harder, 28% say it’s getting harder to engage multiple decision makers at a company, and 26% of salespeople say it’s getting harder to capture attention and keep it. confirmed The good news is that marketers are in a unique position right now to help fix some of these pervasive problems by learning from fellow marketers who share how they’ve leveraged these tools to maximize their output and results. So today, I’d like to share what’s been working for me over the last couple of months of experimenting with ChatGPT as the head of marketing for a deep tech start-up. SEO-related tasks: Draft structured data schema, , using website URLs and provide summaries for article schema in HTML5. such as Breadcrumbs Keyword suggestions for paid ad trigger words, then converted into CSV file for easy copy and pasting. Re-wording highly technical content so that it can be understood in more simple terms to a broader range of readers. Improving the readability of existing written content to increase the likelihood readers both start and finish it. videoinsights.io plugin for ChatGPT-4 to provide video descriptions that can be added to Youtube descriptions or video metadata to rank more often in search results. Or using it to identify the video SEO strategy, keywords and targeting of competitor videos easily. AI PDF plugin for ChatGPT-4 to summarize pdfs to enrich meta descriptions or for help summarizing pdfs in order to promote them better online. WebPilot ChatGPT-4 plugin for providing alt tag descriptions for your valuable infographics so they rank more often in searches. Pixellow ChatGPT-4 plugin for analyzing images and then writing detailed captions, descriptions and providing other potential insights into creating more engaging and informative visual content. Finding new potential SEO keyword opportunities by copying and pasting your top ranking keywords in order to find new low competition content ideas and low-cost paid ad campaigns. Paid Advertising: Optimize ad copy with A/B testing, leveraging call-outs and site links based on buyer persona insights. A+ Ads ChatGPT-4 plugin to create or add polish to display ads, using just a single link. Copy and paste A/B testing alternative ideas for different paid ad headline ideas. Social Media and Content Promotion: Draft and schedule social media posts to amplify blog and video content, encouraging more actions. Draft newsletters with the content and topics you want to ensure get mentioned. Webinar and lunch-and-learn topic suggestions and potential lead magnet offers. Synthesize anonymized customer data from excel sheets to identify trends, common titles, and industries based on companies for new business opportunities for B2Bs. Content Creation and Optimization: Come up with alternative compelling and clickable titles for content. Use ChatGPT-4 to copy edit your content before publishing for a more polished finished product. Alt text descriptions for infographics to help infographics with ranking for search terms. Revise existing content for submission to editorial platforms, ensuring originality while gaining exposure and backlinks. Create new original written content by using biproducts of day-to-day work that would otherwise be forgotten or under-utlized. Drafting new blog articles to embed existing videos on so that they both rank higher. Reminder from earlier: Blog posts that contain a video have a 53X higher chance of ranking on the first page of Google Persona Development and Market Research: FAQ suggestions for product pages, blogs, and other web types of web pages that could be included at the bottom of the page, as well as embed the HTML5 structured data for increased SEO value. Researching new market segments, audiences, and buyer personas. First by title and industry, then drilling down on objectives, influences, places they congregate, emotional triggers and so forth. Identifying new lead magnet offers based on your buyer personas job title, industry and product or service you’re selling. Video and Presentation Preparation: Video descriptions to uploaded videos to use in video schema mark-up or video description files, or video players like YouTube and Vimeo to help increase video search visibility. Related Reading: How to Rank a Youtube Video on The First Page of Google Preparing for video business presentations by preemptively preparing for possible questions that a (insert title) at an “insert company industry” would want to know from a “insert presenters titles” from “presenter company’s industry”. Take existing blogs and write a promo video script based on the blog’s text for quick turnaround video content. Conclusion In the rapidly evolving landscape of digital marketing, AI tools are emerging as game-changers, offering unprecedented advantages to those who harness their potential effectively. By embracing AI-driven strategies, from SEO optimization to content creation, marketers can not only address contemporary challenges but also pioneer innovative approaches that set them apart in the industry. As we stand at this juncture, it's crucial for professionals to continuously learn, adapt, and share their experiences, ensuring that the future of marketing is both inclusive and groundbreaking. I would encourage readers to check out hashtag for fresh content on the subject, and revisiting some of my previous published articles on AI marketing applications. As AI continues to reshape the marketing domain, it's essential for professionals to stay updated, leverage its capabilities, and drive innovation. HackerNoon’s #the-future-of-ai Tell us about it in the comments section or retweet the article with your thoughts to @darraghgw. How are you going to harness AI in the coming year, reader? If you found this article useful, let me know in the comment section below and share it with your network today! Recommended Further Readings From The Author https://hackernoon.com/how-to-use-ai-for-your-b2b-marketing?embedable=true https://hackernoon.com/18-ai-marketing-softwares-your-b2b-needs-to-try-today?embedable=true https://hackernoon.com/33-common-and-costly-b2b-marketing-mistakes-to-avoid?embedable=true https://hackernoon.com/16-growth-marketing-hacks-for-crypto-projects-and-start-ups?embedable=true

Harnessing AI: 28 Innovative Marketing Strategies.

The rapid progression of automation and artificial intelligence (AI) is prompting a widespread discourse on their potential impacts on the global job market. While catastrophic job losses may be a sensationalist perspective, the indisputable truth remains that AI and automation will inevitably cause disruption in the labor force. As productivity and profits burgeon for corporations, the looming question is: How can society ensure an equitable distribution of these technological dividends? An audacious proposition that has been put forward is tying a . universal basic income (UBI) to GDP per capita Democratizing Wealth in the Age of Automation As AI and automation escalate productivity and operational efficiency, an increase in GDP per capita is anticipated. However, the benefits from these productivity enhancements typically skew towards affluent income earners and those owning capital. Implementing a UBI tied to GDP per capita could ensure a more evenly spread of dividends. For instance, if automation results in a $5,000 per capita increase in GDP, this extra income could be redistributed through a UBI. This approach has the potential to put money directly into the populace's pockets, effectively counteracting the job losses and growing income disparity aggravated by automation. Furthermore, it would initiate a virtuous cycle where heightened consumer spending boosts demand, thus stimulating further economic growth. Another intriguing player on the scene is , a project introduced by Sam Altman and his team with the ambitious goal of creating a new, universally accessible financial and identification network. Worldcoin combines a privacy-preserving digital identity (World ID) with a digital currency (WLD), gifted to users simply for being human, in regions where laws allow. With Worldcoin, Altman envisions a future where economic opportunity is significantly expanded, a reliable and privacy-preserving distinction between humans and AI is established, and global democratic processes are enabled. This revolutionary project could even pave the way towards an AI-funded UBI, reflecting the increasingly intertwined futures of automation, AI, and global economic systems. Worldcoin As succinctly put by economist Robert Reich, "The robots are baking more economic pies. We just need to distribute those pies to more ovens." Rather than each worker laboriously baking their individual pie from scratch, automation allows for an explosion of mass-produced pies. A UBI ensures that every oven gets a pie, not merely the owners of the robotic pie factories. https://www.ubiworks.ca/groweconomy?utm_source=ai-automation-life-daily.beehiiv.com&utm_medium=referral&utm_campaign=think-how-a-ubi-tied-to-gdp-could-distribute-automation-s-bounty&embedable=true Venturing Into Alternate Solutions While UBI provides one possible solution, we should also consider other targeted social safety nets that offer assistance to those most at risk from the advent of automation. Such support could take the form of reskilling initiatives, job placement aids, and investments in education and training. By focusing on those most susceptible to job displacement, we can alleviate the adverse effects of automation without resorting to a blanket income guarantee. https://ai-automation-life-daily.beehiiv.com/p/ai-automation-to-replace-half-of-human-jobs-by-2045?embedable=true A further alternative is the concept of "shared ownership" of automated technologies. This approach encourages a wider distribution of , rather than relying solely on income redistribution. Mechanisms such as employee ownership, cooperatives, or community-based investment funds could be employed to give more individuals a stake in the profits generated by automation, fostering a more inclusive and equitable society. AI and automation ownership Although the specifics are critical, broadening the distribution of state-of-the-art LLMs and GPUs to the public can facilitate our transition to a better future. After all, we’re all stakeholders in this automated future, and sharing its bounty might just be the key to unlocking a more prosperous and equitable world. Also published . here

Harnessing Automation's Profits: A UBI Tied to GDP Distribution Strategy

C-Power has been nominated in HackerNoon's annual Startup of the Year awards in Charlottesville, Virginia, United States. Please vote for us here: https://hackernoon.com/startups/north-america/north-america-charlottesville-va-usa Read more about C-Power below, and thanks for considering voting for us for Charlottesville Startup of the Year. Are you also participating in SOTY 2023? If so, click here to fill out this interview. Columbia Power (C-Power) C-Power’s products convert ocean wave energy into usable and storable energy anytime, anywhere, and for anything. Our solutions for lower-power needs change the ocean from a power desert into a power- and data-enriched environment, reducing operational costs, carbon, and complexity for offshore, island, and coastal applications. The systems are easy to transport and deployable anywhere in the world, unlocking innovation in critical industries such as offshore energy, defense and security, aquaculture, science and research, and communications. Our solutions for higher-power needs will unleash the next wave of zero-carbon energy for electric grids on land and remote onshore or offshore mini-grids. Visit us at . https://cpower.co/ Reenst Lesemann, CEO I grew up on the water and knew I wanted to spend my life working with the ocean.​ ​ Midway through my career, I found myself on a conference panel with C-Power co-founder Sandy Reisky. After hearing Sandy talk about the potential of ocean wave technology, I couldn’t help but get involved. ​ ​ Driven by my passion for the ocean and by the idea of bringing new renewable energy to the world, I am leading C-Power in the charge to harness the ocean’s power to create a viable and powerful technology that will accelerate decarbonization. How We're Disrupting/Improving the Renewable Energy Industry Decarbonization is a massive global effort.​ Right now, there are two primary renewable energy sources: solar and wind. They are powerful resources, but they aren’t enough to decarbonize the global economy. We don’t have the right energy in the right places to complete the energy transition. The ocean is the biggest and best battery on Earth, and it covers 71% of the Earth’s surface. C-Power is adding ocean energy​ to the global renewable energy portfolio with high-value strategic innovation. First, we are helping unlock the digital, autonomous, decarbonized future of offshore operations with lower cost, lower complexity, and lower carbon solutions. Second, we will develop large-scale solutions to bring renewable ocean energy to electric grids on land. The right ocean energy solution will: 1) decarbonize, diversify, and secure the global energy mix; 2) unleash innovation and decarbonization in the ocean economy; and 3) improve offshore operations. Standing Out from The Crowd C-Power makes the right ocean energy solution. Our autonomous offshore power systems are available with 24/7 reliable power generation, for service in remote or populous areas, and for from data gathering to utility-scale power generation. anytime anywhere anything Our technology is unique and patented. C-Power is the only company in the industry providing ocean energy systems that are 1) simple and reliable, 2) scalable, 3) easy to transport and at low cost, 4) deployable anywhere, and 5) can be delivered to the market rapidly. Our Predictions/Thoughts on the Ocean Energy Industry in 2023 The ocean energy industry is still in its early stage seeking to drive down costs toward parity with solar and wind power as well as innovate to improve performance in the harsh ocean environment. As such, the industry in 2023 will continue to rely on government research, development, and demonstration funding as well as private investor support. However, leading ocean energy providers like C-Power have blazed a shorter trail across the industry’s “valley of death” to commercialization and a sustainable customer market. These leaders are targeting industries operating in the ocean economy — offshore energy, defense, scientific research — that need power and real-time communications at sea to unlock a future of autonomous and digital operations with lower cost, carbon emissions, and complexity. In 2023, expect to see ocean energy solutions in the water unlocking this bright future for the ocean economy. By unlocking this market, ocean energy leaders will develop a source of commercial energy to continue the journey toward utility-scale ocean energy on par with wind and solar. What word defines the state of ocean energy in 2023? : Our industry has researched, developed, and lab-tested viable products across a number of form factors to turn energy from ocean waves and tides into clean, renewable electricity. Demonstration Now, it is time to demonstrate those capabilities in real-world projects that deliver real-world value to companies looking to innovate in the ocean economy. In 2023, C-Power is launching the world’s most cutting-edge ocean energy demonstration in Hawaii at the U.S. Navy’s Wave Energy Test Site, where our SeaRAY autonomous offshore power system will provide power and real-time communications for data-gathering equipment and an autonomous underwater vehicle simultaneously. Why we decided to participate in HackerNoon's Startup of the Year awards C-Power is participating in these awards because we are honored to appear side-by-side with our innovative neighbors in Charlottesville, Virginia. We are proud to employ five people in Charlottesville (25 globally), contributing to the economic vitality of our city. While our community is small, it is an innovation hub with a thriving entrepreneurial ecosystem. We’re proud to bring attention not only to our efforts to develop a new clean energy resource but also to our innovative community. Final Thoughts C-Power is the industry leader in delivering simple, reliable ocean wave energy to help decarbonize the global economy. Recognition for our company delivers support for our cause. Thank you for helping us bring a new renewable energy resource to the world that is critical for a sustainable future. C-Power is nominated as Startup of the Year in Charlottesville, USA. Vote for us today!

Harnessing the Power of the Ocean - Interview with Startups of the Year Nominee, C-Power

In the realm of programming, there exists a powerful utility known as . This often-overlooked gem enables developers to orchestrate concurrent execution of multiple asynchronous tasks, leading to improved performance and efficiency. Dart Future.wait() In this blog post, we will explore the problem domain where can save the day and delve into best practices for utilizing it effectively. Future.wait() The Problem Imagine you are developing a Dart application that needs to fetch data from multiple remote APIs simultaneously? That was our case and we got PR for this case scenario in a Dart/Flutter code I am managing, as it is listed in the code snippet below! Given I can’t share the whole code, I will embody this code smell with the power of later in this blog: Future.wait() void fetchFromRemoteApis() {
  final apiAFuture = fetchDataFromApi('API A');
  final apiBFuture = fetchDataFromApi('API B');
  final apiCFuture = fetchDataFromApi('API C');

  apiAFuture.then((resultA) {
    print('Received result from API A: $resultA');
    apiBFuture.then((resultB) {
      print('Received result from API B: $resultB');
      apiCFuture.then((resultC) {
        print('Received result from API C: $resultC');
        print('All API calls completed successfully!');
      }).catchError((errorC) {
        print('An error occurred while fetching data from API C: $errorC');
      });
    }).catchError((errorB) {
      print('An error occurred while fetching data from API B: $errorB');
    });
  }).catchError((errorA) {
    print('An error occurred while fetching data from API A: $errorA');
  });
} In this suboptimal approach, the code chained the callbacks sequentially for each API call. This results in nested callbacks, commonly known as the "callback hell" or "pyramid of doom" pattern. It leads to less readable and more error-prone code, especially when handling errors. then The code also first fetches data from API A. Upon successful completion, it proceeds to fetch data from API B. Finally, when API B completes successfully, it proceeds to fetch data from API C. At each stage, error handling is implemented using to capture and handle any errors that may occur during the API calls. catchError() The main disadvantage of this approach is that it lacks the efficiency of concurrent execution, as each API call waits for the previous one to complete before initiating the next. This can lead to longer overall execution time, especially when dealing with multiple independent asynchronous tasks. Traditionally, when dealing with asynchronous tasks, you might resort to executing them one after another, waiting for each one to complete them before starting the next. This sequential approach can lead to suboptimal performance, especially when network latencies come into play. , is a function that enables concurrent execution of asynchronous tasks. With this mighty tool at our disposal, we can dramatically enhance the efficiency of our code by fetching data from multiple remote APIs concurrently, taking advantage of parallelism and reducing overall execution time. Harnessing the Power of Future.wait() : Future.wait() : Here's how Future.wait() works We create a list of objects, each representing an asynchronous task, such as fetching data from a remote API. Future We pass this list of objects to . Future Future.wait() returns a new that completes when all the provided objects have completed. Future.wait() Future Future Saving the Day with Future.wait() Consider a scenario where your application needs to fetch data from three different remote APIs: A, B, and C. Without , you might fetch data from A, wait for it to complete, then fetch data from B, and finally fetch data from C. This sequential approach can be time-consuming and inefficient. Future.wait() However, by utilizing , you can kick off all three asynchronous tasks concurrently, reducing the overall execution time. The returned by will complete only when all three API calls have finished, allowing you to collect the results efficiently. Future.wait() Future Future.wait() So, I reviewed the code smell to make it better. Let’s proceed to that. : Writing Better Code To make the most of , here are a few best practices: Future.wait() Use when the tasks are truly independent and can be executed concurrently. If there are dependencies between tasks, consider using or to handle them. Future.wait() Future.then() async/await Ensure that the tasks passed to are truly asynchronous and return a . If not, consider wrapping synchronous code in a using or . Future.wait() Future Future Future.value() Future.microtask() Utilize error-handling mechanisms like or callbacks to handle exceptions that might occur during the execution of concurrent tasks. try-catch onError If there's a need to set a timeout for the completion of , you can use to handle situations where certain tasks take an unusually long time. Future.wait() Future.wait(...).timeout(...) The Fix: So here, I embodied the code smell and used to make it better. I have also chosen open random endpoints for you to see how effective it can serve concurrent execution: Future.wait() API import 'dart:async';
import 'dart:convert';
import 'package:http/http.dart' as http;

void main() {
  fetchFromRemoteApis();
}

void fetchFromRemoteApis() async {
  final apiAFuture = fetchDataFromApi('https://jsonplaceholder.typicode.com/posts');
  final apiBFuture = fetchDataFromApi('https://jsonplaceholder.typicode.com/comments');
  final apiCFuture = fetchDataFromApi('https://jsonplaceholder.typicode.com/todos');

  try {
    List<dynamic> results = await Future.wait<dynamic>([apiAFuture, apiBFuture, apiCFuture]);
    
    for (var result in results) {
      print('Received result: $result');
    }
    
    print('All API calls completed successfully!');
  } catch (error) {
    print('An error occurred: $error');
  }
}

Future<dynamic> fetchDataFromApi(String apiUrl) async {
  final response = await http.get(Uri.parse(apiUrl));

  // Check the response status
  if (response.statusCode == 200) {
    final jsonResponse = jsonDecode(response.body);
    return jsonResponse;
  } else {
    throw Exception('API request failed with status ${response.statusCode}');
  }
} As much as different software engineers can have differing opinions such as using with inside , which I think is unnecessary nested callbacks, or use only with which creates an additional callback function and introduces an extra layer of complexity, I believe the algorithmic complexity of the code smell is reduced drastically by the fix provided in this blog. .map() .then() Future.wait() .then() Future.wait() Conclusion In the ever-evolving world of Dart programming, it's essential to leverage the right tools for improved performance and efficiency. is a valuable utility that empowers developers to achieve concurrent execution of asynchronous tasks, effectively reducing execution time and optimizing resource utilization. By incorporating into your code, you can unlock the magic of concurrent programming and embrace the power of Dart to its fullest potential. Future.wait() Future.wait() So, the next time you find yourself juggling multiple asynchronous tasks, remember the spellbinding capabilities of and watch as your code performs its own brand of magic. Future.wait() If you need more resources on , kindly refer to and . Future.wait() https://api.dart.dev/stable/2.1.0/dart-async/Future/wait.html https://api.flutter.dev/flutter/dart-async/Future/wait.html Happy coding!

Harnessing Concurrent Execution with “Future.wait()” in Dart

Parsing logs with is a valuable technique for extracting essential information from large volumes of log data. By employing this method, one can effectively identify patterns, errors, and other key insights, ultimately streamlining log analysis and enhancing system performance. regex Prerequisites BindPlane OP & a BindPlane Agent (Custom OpenTelemetry Collector) A complex log file needing custom parsing Knowledge of Regex A selection of log samples that match all possible variations. (Optional) A good regex testing tool such as regex101.com Here is a link to regex101 for the examples from the blog: https://regex101.com/r/6hhy6K/4 Complex Log Data Samples In this post, we’ll examine log entries that resemble the examples provided below. By utilizing a script to write these entries to a file with the current timestamps, we can effectively work with real-time data. May 01 14:31:11 loggen-app10 test-system[712]: Mon May 01 14:31:11 UTC 2023|TEST_PROC|[result=Service Access Granted,service=https://portal.fakeuni.edu/uPortal/Login?...,requiredAttributes={}]|SERVICE_ACCESS_ENFORCEMENT_TRIGGERED|camillec1997|172.13.49.165|172.16.156.55

May 01 14:31:11 loggen-app10 test-system[712]: Mon May 01 14:31:11 UTC 2023|TEST_PROC|[result=Service Access Granted,service=https://portal.fakeuni.edu/uPortal/Login?...,requiredAttributes={}]|SERVICE_ACCESS_ENFORCEMENT_TRIGGERED|camillec1997|172.13.49.165|172.16.156.55

May 01 14:31:11 loggen-app10 test-system[712]: Mon May 01 14:31:11 UTC 2023|TEST_PROC|[event=success,timestamp=May 01 14:31:11 UTC 2023,source=RankedMultifactorAuthenticationProviderWebflowEventResolver]|AUTHENTICATION_EVENT_TRIGGERED|audit:unknown|172.25.178.6|172.16.156.55

May 01 14:31:11 loggen-app08 test-system[780]: Mon May 01 14:31:11 UTC 2023|TEST_PROC|Supplied credentials: [UsernamePasswordCredential(username=dawsonb, source=null, customFields={})]|AUTHENTICATION_SUCCESS|dawsonb|172.12.154.117|172.16.156.53

May 01 14:31:11 loggen-app10 test-system[712]: Mon May 01 14:31:11 UTC 2023|TEST_PROC|[event=success,timestamp=May 01 14:31:11 UTC 2023,source=RankedMultifactorAuthenticationProviderWebflowEventResolver]|AUTHENTICATION_EVENT_TRIGGERED|audit:unknown|172.25.178.6|172.16.156.55 Dissecting The Data We can now take the first log entry above, and start dissecting it into sections that we wish to parse out. First, we’ll notice that we have two timestamps: **May 01 14:31:11** loggen-app10 test-system[712]: **Mon May 01 14:31:11 UTC 2023**|TEST_PROC|[result=Service Access Granted,service=https://portal.fakeuni.edu/uPortal/Login?...,requiredAttributes={}]|SERVICE_ACCESS_ENFORCEMENT_TRIGGERED|camillec1997|172.13.49.165|172.16.156.55 The second timestamp is the one we will preserve to become our official timestamp because it contains more information (timezone and year are useful, while the day of the week isn’t really) that we can use to achieve the highest precision. Breaking this down, we will write a non-capturing pattern to match the first timestamp. anchors to the start of the line. This is followed by “ ”, which captures the 3 letter month abbreviation. After the month, is “ ”, which is to capture a space; the 2 digits, 0 padded days of the month; and another space. Finally, we have “ ” – for 2-digit hour, 2-digit minute, 2-digit second, and 1 or more spaces. ^\w{3}\s\d{2}\s\d{2}:\d{2}:\d{2}\s+The caret “^” \w{3} \s\d{2}\s \d{2}:\d{2}:\d{2}\s+ For the second timestamp, we want a named capture group. This will become a named field in the JSON blob of parsed-out fields. (?P<timestamp>\w{3}\s\w{3}\s\d{2}\s\d{2}:\d{2}:\d{2}\s\w{3}\s\d{4}) We’ve named this capture group “timestamp”. It contains the same basic regex as the other timestamp, with the addition of “ ” at the start to capture the abbreviated day of the week, and “ ” replacing the “ ” at the end in order to capture the 3 character timezone, and the 4 digit year. \w{3}\s \s\w{3}\s\d{4} \s+ Going further into the log message, we will want to parse out the hostname and the system: May 01 14:31:11 **loggen-app10 test-system[712]**: Mon May 01 14:31:11 UTC 2023|TEST_PROC|[result=Service Access Granted,service=https://portal.fakeuni.edu/uPortal/Login?...,requiredAttributes={}]|SERVICE_ACCESS_ENFORCEMENT_TRIGGERED|camillec1997|172.13.49.165|172.16.156.55 In this message, our hostname is , and our system is . I was not told what the [712] was when I received these logs. I made the assumption that it is the PID (process ID), but I chose not to parse it out separately for now. Parsing these fields is fairly simple, and we end up with: “ ”. We have a pair of named capture groups, hostname, and system. **loggen-app10** **test-system[712]** (?P<hostname>[^\s]+)\s+(?P<system>.*?):\s+ The pattern for the hostname is “ ”, which says capture any non-space character and capture as many of them as you can (greedy). This is followed by “ ”, which captures at least one, but as many as possible (greedy again) space(s). [^\s]+ \s+ The capture group for the system is even easier because after the space(s) we capture everything up to a colon character. To do this, we use “ ”. What that pattern says is, capture any character 0 or more times, but don’t be greedy. .*? After that, we have the colon character and another 1 or more spaces greedy. These aren’t captured but are needed to pad out between this section and the timestamp section we wrote above. This results in the following starting pattern: ^\w{3}\s*\d{2}\s*\d{2}:\d{2}:\d{2}\s+(?P<hostname>[^\s]+)\s+(?P<system>.*?):\s+(?P<timestamp>\w{3}\s\w{3}\s\d{2}\s\d{2}:\d{2}:\d{2}\s\w{3}\s\d{4}) I won’t go through the entire pattern creation process, but I continue to chunk it up as I did above. The resulting final pattern is: ^\w{3}\s*\d{2}\s*\d{2}:\d{2}:\d{2}\s+(?P<hostname>[^\s]+)\s+(?P<system>.*?):\s+(?P<timestamp>\w{3}\s\w{3}\s\d{2}\s\d{2}:\d{2}:\d{2}\s\w{3}\s\d{4})\|(?P<app_name>\w*)\|((?P<message_type>.*?):\s+)?\[?(?P<message>.*)\]?\|(?P<event_message>.*?)\|(?P<username>.*?)\|(?P<external_ip>[\d\.:]*)\|(?P<internal_ip>[\d\.:]*) This final pattern includes the following named capture groups, which become fields in our JSON blob of parsed data: hostname system timestamp app_name message_type message event_message username external_ip internal_ip Implementing The Regex In BindPlane, I create a File source. This looks at my generated log file in /root/complex.log. I’ve selected regex under Parse Format. Under the Regex Pattern, I put in the final pattern above. I’ve checked the box for Parse Timestamp, chosen Manual for the format, and put in the time parsing codes for my timestamp’s pattern. Once done, it looks like this: Sending & Verifying The Data To complete the testing, I need to create a destination and check the data there. For my use case, I’ve chosen a Google Cloud Logging destination. Once my pipeline configuration is complete, I attach it to an agent. After it has run for a few moments, I click the “View Recent Telemetry Button” on the agent’s page The telemetry view shows me the following parsed log: Finally, I check it on the Cloud Logging console as well: Google This displays the same log entry, and it has a JSON payload of our body’s JSON map object from the recent telemetry view. Next Steps For the next steps, I would want to look at parsing that message value. It is frequently a key/value set; as it is in the screenshots & samples above. I could pass the data onward to a processor that parses these key/value entries into another layer of JSON. In the above example, would get parsed back into itself, and you could have fields such as: body.message body.message.result=Service Access Granted
body.message.service=https://innosoftfusiongo.com/sso/logi…
body.message.principal=SimplePrincipal(id=dawsonb, attributes={mail=[dawson.branden@fakeuni.edu], 
eduPersonAffiliation=[Staff], 
ou=[Recreation/Student Rec Center], 
givenName=[Dawson], cn=[Dawson Branden], 
title=[Asst. Director], employeeNumber=[5000000], 
o=[Vice ChancellorStudent Affairs], 
fakeuniOrg=[Vice ChancellorStudent Affairs], casMFARequired=[YES], uid=[dawsonb], eduPersonPrimaryAffiliation=[Staff], fakeuniCid=[5000000], fakeuniSeparationDate=[99991231000000Z], UDC_IDENTIFIER=[dawsonb], sn=[Branden], organizationalStatus=[Staff]})
body.message.requiredAttributes=”” Even this could be parsed further, by putting body.message.principle through a key/value parser as well. Now, someone is bound to wonder, “Why didn’t you just use regex parsing of the body.message subfields as well?” The answer: It is too inconsistent. The regex would be incredibly, and unreasonably, complex when we have the capability to parse key/value pairs already. Conclusion Many forms of data can be found in log files. This data often needs to be parsed to make it both more easily readable for humans and easier for automation and tooling later in the chain to act upon. While the example I worked with was performed on a simple file log, the techniques herein can be used on any log stream. In addition to regex parsing, BindPlane also supports , , key/value pairs, and character-separated values. With the use of processors, these parsers can be chained together to parse embedded data, and manipulate it all into a usable format. JSON XML Also published here.

Efficient Log Analysis: Harnessing the Power of Regex with BindPlane OP and OpenTelemetry

Análisis de registro eficiente: aprovechar el poder de Regex con BindPlane OP y OpenTelemetry

Analyse efficace des journaux : Exploiter la puissance de Regex avec BindPlane OP et OpenTelemetry

कुशल लॉग विश्लेषण: BindPlane OP और OpenTelemetry के साथ Regex की शक्ति का उपयोग करना

効率的なログ分析: BindPlane OP と OpenTelemetry による Regex の力の活用

Análise de log eficiente: aproveitando o poder do Regex com BindPlane OP e OpenTelemetry

Phân tích nhật ký hiệu quả: Khai thác sức mạnh của Regex với BindPlane OP và OpenTelemetry

高效的日志分析：利用 BindPlane OP 和 OpenTelemetry 的正则表达式的力量

Stories, News & Mentions about HARNESS

Harness’s Stories on HackerNoon