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Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Publication

Building a Ready-to-Use Multi-Agent GenAI Chatbot on AWS for Streamlined Production Incident Response
Latest  Machine Learning

Building a Ready-to-Use Multi-Agent GenAI Chatbot on AWS for Streamlined Production Incident Response

Asif Foysal Meem
1 like
April 17, 2025

Author(s): Asif Foysal Meem Originally published on Towards AI. This is part 2 of a step-by-step exploration of AWS Bedrock’s built-in features and multi-agent orchestration to streamline on-call incident triage — You’ll only need one coffee to triage prod incidents once you’ve …

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Using CrewAI to Build Agentic Systems
Artificial Intelligence  Latest  Machine Learning

Using CrewAI to Build Agentic Systems

Igor Novikov
0 like
April 16, 2025

Author(s): Igor Novikov Originally published on Towards AI. Image by the author Crew AI is one of the most popular agentic AI frameworks out there. I’ve reviewed Autogen by Microsoft before, and it turned out to be quite buggy. This one is …

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From Data Points to Decision Boundaries: A Hands-On Guide to Predictive Maintenance using PCA
Latest  Machine Learning

From Data Points to Decision Boundaries: A Hands-On Guide to Predictive Maintenance using PCA

Luis Ramirez
1 like
April 16, 2025

Author(s): Luis Ramirez Originally published on Towards AI. For industrial equipment the default approach is preventive maintenance, which involves servicing equipment on a fixed schedule, such as monthly or semi-annually. While better than reactive maintenance (fixing equipment after failure), this one-size-fits-all strategy …

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Introduction: The Silent Sidekicks You Didn’t Notice
Latest  Machine Learning

Introduction: The Silent Sidekicks You Didn’t Notice

Harshit Kandoi
0 like
April 16, 2025

Author(s): Harshit Kandoi Originally published on Towards AI. Yesterday, an AI agent reminded me to water my plants, flagged a train route to Vrindavan, and sorted my inbox — all while I was stuck in a meeting. I didn’t ask for any …

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Future of the Job Market — Impact of AI on Various Roles in 2025
Artificial Intelligence  Latest  Machine Learning

Future of the Job Market — Impact of AI on Various Roles in 2025

Nishtha Nagar
0 like
April 16, 2025

Author(s): Nishtha Nagar Originally published on Towards AI. The job market in 2025 is undergoing a fundamental shift, influenced heavily by the rapid adoption of artificial intelligence (AI). As AI technologies, particularly generative AI, become more integrated into workplace systems, their impact …

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DeepSeek-V3 Part 2: DeepSeekMoE
Latest  Machine Learning

DeepSeek-V3 Part 2: DeepSeekMoE

Nehdiii
0 like
April 16, 2025

Author(s): Nehdiii Originally published on Towards AI. This article marks the second entry in our DeepSeek-V3 series, focusing on a pivotal architectural breakthrough in the DeepSeek models [1, 2, 3]: DeepSeekMoE [4]. Vegapunk №02 One Piece Character Generated with ChatGPT In this …

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Data-Driven LLM Evaluation with Statistical Testing
Latest  Machine Learning

Data-Driven LLM Evaluation with Statistical Testing

Robert Martin-Short
1 like
April 16, 2025

Author(s): Robert Martin-Short Originally published on Towards AI. Helping iterative projects move in the right direction.ChatGPT’s interpretation of “A quirky robot evaluates a statistical test”. This is not the first example I’ve seen of 3-armed robot images generated by AI … Image …

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How I Made an AI Film: River of Inheritance
Latest  Machine Learning

How I Made an AI Film: River of Inheritance

Sophia Banton
0 like
April 15, 2025

Author(s): Sophia Banton Originally published on Towards AI. How I Made an AI Film: River of Inheritance Scene from River of Inheritance:Created using Google ImageFX and animated with Runway Gen-3 Alpha Turbo. This scene established the film’s outdoor setting and recurring focus …

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Improving Zero-Shot Quality with Verb Injection
Latest  Machine Learning

Improving Zero-Shot Quality with Verb Injection

Mikhail Simin
1 like
April 15, 2025

Author(s): Mikhail Simin Originally published on Towards AI. Teaching Language Models Complex New Verbs Fine-tuning large language models (LLMs) has become the default method for tailoring AI systems to specific tasks, yet it often comes with significant drawbacks: high computational costs, brittleness …

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Multimodal Autonomous AI Agents: Enhancing Web Interactions Through Tree Search
Artificial Intelligence  Latest  Machine Learning

Multimodal Autonomous AI Agents: Enhancing Web Interactions Through Tree Search

Kapardhi kannekanti
1 like
April 15, 2025

Author(s): Kapardhi kannekanti Originally published on Towards AI. I’ve been thinking a lot about AI agents lately, those systems that can actually do things for us online instead of just answering questions. Last week, Professor Ruslan Salakhutdinov from CMU gave a Lecture …

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Streaming with Pydantic AI
Latest  Machine Learning

Streaming with Pydantic AI

Barrett Studdard
0 like
April 15, 2025

Author(s): Barrett Studdard Originally published on Towards AI. Building a pattern around LLM streamingCredit Volodymyr Hryshchenko on Unsplash In my prior article on building a DAX LLM, I utilized base API calls to stream data from Anthropic. In this article, we’ll look …

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TAI #148: New API Models from OpenAI (4.1) & xAI (grok-3); Exploring Deep Research’s Scaling Laws
Artificial Intelligence  Latest  Machine Learning

TAI #148: New API Models from OpenAI (4.1) & xAI (grok-3); Exploring Deep Research’s Scaling Laws

Towards AI Editorial Team
1 like
April 15, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, AI developers got their hands on several significant new model options. Adding to the new Llama 4 model options last week, OpenAI …

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Traditional RAG vs Graph RAG
Artificial Intelligence  Data Science  Latest  Machine Learning

Traditional RAG vs Graph RAG

Kalash Vasaniya
1 like
April 15, 2025

Author(s): Kalash Vasaniya Originally published on Towards AI. Why Graph RAG Outperforms Classical Retrieval: A Smarter Path to Context-Rich AnswersSource: From https://x.com/akshay_pachaar If you’re not a member but want to read this article, see this friend link here. Graph RAG is next-level …

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I Was About to Order Taco Bell Again. Instead, I Built an AI That Talks Me Down
Artificial Intelligence  Latest  Machine Learning

I Was About to Order Taco Bell Again. Instead, I Built an AI That Talks Me Down

Mukundan Sankar
1 like
April 15, 2025

Author(s): Mukundan Sankar Originally published on Towards AI. How I stopped craving with code and started reflecting with GPT-4A smartphone user browsing a pizza delivery app at night while a laptop nearby displays an AI-powered cravings journal. The pizza image is visible …

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GPT-4.1, Mini, and Nano
Data Science  Latest  Machine Learning

GPT-4.1, Mini, and Nano

Naveen Krishnan
0 like
April 14, 2025

Author(s): Naveen Krishnan Originally published on Towards AI. Image Source—unsplash.com The GPT-4.1 model series release through Azure AI Foundry represents a major step forward in AI capabilities. The model series provides multiple options that suit different application requirements, from complex reasoning to …

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`; } else { console.error('Element with id="subscribe" not found within the page with class "home".'); } } }); // Remove duplicate text from articles /* Backup: 09/11/24 function removeDuplicateText() { const elements = document.querySelectorAll('h1, h2, h3, h4, h5, strong'); // Select the desired elements const seenTexts = new Set(); // A set to keep track of seen texts const tagCounters = {}; // Object to track instances of each tag elements.forEach(el => { const tagName = el.tagName.toLowerCase(); // Get the tag name (e.g., 'h1', 'h2', etc.) // Initialize a counter for each tag if not already done if (!tagCounters[tagName]) { tagCounters[tagName] = 0; } // Only process the first 10 elements of each tag type if (tagCounters[tagName] >= 2) { return; // Skip if the number of elements exceeds 10 } const text = el.textContent.trim(); // Get the text content const words = text.split(/\s+/); // Split the text into words if (words.length >= 4) { // Ensure at least 4 words const significantPart = words.slice(0, 5).join(' '); // Get first 5 words for matching // Check if the text (not the tag) has been seen before if (seenTexts.has(significantPart)) { // console.log('Duplicate found, removing:', el); // Log duplicate el.remove(); // Remove duplicate element } else { seenTexts.add(significantPart); // Add the text to the set } } tagCounters[tagName]++; // Increment the counter for this tag }); } removeDuplicateText(); */ // Remove duplicate text from articles function removeDuplicateText() { const elements = document.querySelectorAll('h1, h2, h3, h4, h5, strong'); // Select the desired elements const seenTexts = new Set(); // A set to keep track of seen texts const tagCounters = {}; // Object to track instances of each tag // List of classes to be excluded const excludedClasses = ['medium-author', 'post-widget-title']; elements.forEach(el => { // Skip elements with any of the excluded classes if (excludedClasses.some(cls => el.classList.contains(cls))) { return; // Skip this element if it has any of the excluded classes } const tagName = el.tagName.toLowerCase(); // Get the tag name (e.g., 'h1', 'h2', etc.) // Initialize a counter for each tag if not already done if (!tagCounters[tagName]) { tagCounters[tagName] = 0; } // Only process the first 10 elements of each tag type if (tagCounters[tagName] >= 10) { return; // Skip if the number of elements exceeds 10 } const text = el.textContent.trim(); // Get the text content const words = text.split(/\s+/); // Split the text into words if (words.length >= 4) { // Ensure at least 4 words const significantPart = words.slice(0, 5).join(' '); // Get first 5 words for matching // Check if the text (not the tag) has been seen before if (seenTexts.has(significantPart)) { // console.log('Duplicate found, removing:', el); // Log duplicate el.remove(); // Remove duplicate element } else { seenTexts.add(significantPart); // Add the text to the set } } tagCounters[tagName]++; // Increment the counter for this tag }); } removeDuplicateText(); //Remove unnecessary text in blog excerpts document.querySelectorAll('.blog p').forEach(function(paragraph) { // Replace the unwanted text pattern for each paragraph paragraph.innerHTML = paragraph.innerHTML .replace(/Author\(s\): [\w\s]+ Originally published on Towards AI\.?/g, '') // Removes 'Author(s): XYZ Originally published on Towards AI' .replace(/This member-only story is on us\. Upgrade to access all of Medium\./g, ''); // Removes 'This member-only story...' }); //Load ionic icons and cache them if ('localStorage' in window && window['localStorage'] !== null) { const cssLink = 'https://code.ionicframework.com/ionicons/2.0.1/css/ionicons.min.css'; const storedCss = localStorage.getItem('ionicons'); if (storedCss) { loadCSS(storedCss); } else { fetch(cssLink).then(response => response.text()).then(css => { localStorage.setItem('ionicons', css); loadCSS(css); }); } } function loadCSS(css) { const style = document.createElement('style'); style.innerHTML = css; document.head.appendChild(style); } //Remove elements from imported content automatically function removeStrongFromHeadings() { const elements = document.querySelectorAll('h1, h2, h3, h4, h5, h6, span'); elements.forEach(el => { const strongTags = el.querySelectorAll('strong'); strongTags.forEach(strongTag => { while (strongTag.firstChild) { strongTag.parentNode.insertBefore(strongTag.firstChild, strongTag); } strongTag.remove(); }); }); } removeStrongFromHeadings(); "use strict"; window.onload = () => { /* //This is an object for each category of subjects and in that there are kewords and link to the keywods let keywordsAndLinks = { //you can add more categories and define their keywords and add a link ds: { keywords: [ //you can add more keywords here they are detected and replaced with achor tag automatically 'data science', 'Data science', 'Data Science', 'data Science', 'DATA SCIENCE', ], //we will replace the linktext with the keyword later on in the code //you can easily change links for each category here //(include class="ml-link" and linktext) link: 'linktext', }, ml: { keywords: [ //Add more keywords 'machine learning', 'Machine learning', 'Machine Learning', 'machine Learning', 'MACHINE LEARNING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ai: { keywords: [ 'artificial intelligence', 'Artificial intelligence', 'Artificial Intelligence', 'artificial Intelligence', 'ARTIFICIAL INTELLIGENCE', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, nl: { keywords: [ 'NLP', 'nlp', 'natural language processing', 'Natural Language Processing', 'NATURAL LANGUAGE PROCESSING', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, des: { keywords: [ 'data engineering services', 'Data Engineering Services', 'DATA ENGINEERING SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, td: { keywords: [ 'training data', 'Training Data', 'training Data', 'TRAINING DATA', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, ias: { keywords: [ 'image annotation services', 'Image annotation services', 'image Annotation services', 'image annotation Services', 'Image Annotation Services', 'IMAGE ANNOTATION SERVICES', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, l: { keywords: [ 'labeling', 'labelling', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, pbp: { keywords: [ 'previous blog posts', 'previous blog post', 'latest', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, mlc: { keywords: [ 'machine learning course', 'machine learning class', ], //Change your article link (include class="ml-link" and linktext) link: 'linktext', }, }; //Articles to skip let articleIdsToSkip = ['post-2651', 'post-3414', 'post-3540']; //keyword with its related achortag is recieved here along with article id function searchAndReplace(keyword, anchorTag, articleId) { //selects the h3 h4 and p tags that are inside of the article let content = document.querySelector(`#${articleId} .entry-content`); //replaces the "linktext" in achor tag with the keyword that will be searched and replaced let newLink = anchorTag.replace('linktext', keyword); //regular expression to search keyword var re = new RegExp('(' + keyword + ')', 'g'); //this replaces the keywords in h3 h4 and p tags content with achor tag content.innerHTML = content.innerHTML.replace(re, newLink); } function articleFilter(keyword, anchorTag) { //gets all the articles var articles = document.querySelectorAll('article'); //if its zero or less then there are no articles if (articles.length > 0) { for (let x = 0; x < articles.length; x++) { //articles to skip is an array in which there are ids of articles which should not get effected //if the current article's id is also in that array then do not call search and replace with its data if (!articleIdsToSkip.includes(articles[x].id)) { //search and replace is called on articles which should get effected searchAndReplace(keyword, anchorTag, articles[x].id, key); } else { console.log( `Cannot replace the keywords in article with id ${articles[x].id}` ); } } } else { console.log('No articles found.'); } } let key; //not part of script, added for (key in keywordsAndLinks) { //key is the object in keywords and links object i.e ds, ml, ai for (let i = 0; i < keywordsAndLinks[key].keywords.length; i++) { //keywordsAndLinks[key].keywords is the array of keywords for key (ds, ml, ai) //keywordsAndLinks[key].keywords[i] is the keyword and keywordsAndLinks[key].link is the link //keyword and link is sent to searchreplace where it is then replaced using regular expression and replace function articleFilter( keywordsAndLinks[key].keywords[i], keywordsAndLinks[key].link ); } } function cleanLinks() { // (making smal functions is for DRY) this function gets the links and only keeps the first 2 and from the rest removes the anchor tag and replaces it with its text function removeLinks(links) { if (links.length > 1) { for (let i = 2; i < links.length; i++) { links[i].outerHTML = links[i].textContent; } } } //arrays which will contain all the achor tags found with the class (ds-link, ml-link, ailink) in each article inserted using search and replace let dslinks; let mllinks; let ailinks; let nllinks; let deslinks; let tdlinks; let iaslinks; let llinks; let pbplinks; let mlclinks; const content = document.querySelectorAll('article'); //all articles content.forEach((c) => { //to skip the articles with specific ids if (!articleIdsToSkip.includes(c.id)) { //getting all the anchor tags in each article one by one dslinks = document.querySelectorAll(`#${c.id} .entry-content a.ds-link`); mllinks = document.querySelectorAll(`#${c.id} .entry-content a.ml-link`); ailinks = document.querySelectorAll(`#${c.id} .entry-content a.ai-link`); nllinks = document.querySelectorAll(`#${c.id} .entry-content a.ntrl-link`); deslinks = document.querySelectorAll(`#${c.id} .entry-content a.des-link`); tdlinks = document.querySelectorAll(`#${c.id} .entry-content a.td-link`); iaslinks = document.querySelectorAll(`#${c.id} .entry-content a.ias-link`); mlclinks = document.querySelectorAll(`#${c.id} .entry-content a.mlc-link`); llinks = document.querySelectorAll(`#${c.id} .entry-content a.l-link`); pbplinks = document.querySelectorAll(`#${c.id} .entry-content a.pbp-link`); //sending the anchor tags list of each article one by one to remove extra anchor tags removeLinks(dslinks); removeLinks(mllinks); removeLinks(ailinks); removeLinks(nllinks); removeLinks(deslinks); removeLinks(tdlinks); removeLinks(iaslinks); removeLinks(mlclinks); removeLinks(llinks); removeLinks(pbplinks); } }); } //To remove extra achor tags of each category (ds, ml, ai) and only have 2 of each category per article cleanLinks(); */ //Recommended Articles var ctaLinks = [ /* ' ' + '

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',*/ ]; var replaceText = { '': '', '': '', '
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', }; Object.keys(replaceText).forEach((txtorig) => { //txtorig is the key in replacetext object const txtnew = replaceText[txtorig]; //txtnew is the value of the key in replacetext object let entryFooter = document.querySelector('article .entry-footer'); if (document.querySelectorAll('.single-post').length > 0) { //console.log('Article found.'); const text = entryFooter.innerHTML; entryFooter.innerHTML = text.replace(txtorig, txtnew); } else { // console.log('Article not found.'); //removing comment 09/04/24 } }); var css = document.createElement('style'); css.type = 'text/css'; css.innerHTML = '.post-tags { display:none !important } .article-cta a { font-size: 18px; }'; document.body.appendChild(css); //Extra //This function adds some accessibility needs to the site. function addAlly() { // In this function JQuery is replaced with vanilla javascript functions const imgCont = document.querySelector('.uw-imgcont'); imgCont.setAttribute('aria-label', 'AI news, latest developments'); imgCont.title = 'AI news, latest developments'; imgCont.rel = 'noopener'; document.querySelector('.page-mobile-menu-logo a').title = 'Towards AI Home'; document.querySelector('a.social-link').rel = 'noopener'; document.querySelector('a.uw-text').rel = 'noopener'; document.querySelector('a.uw-w-branding').rel = 'noopener'; document.querySelector('.blog h2.heading').innerHTML = 'Publication'; const popupSearch = document.querySelector$('a.btn-open-popup-search'); popupSearch.setAttribute('role', 'button'); popupSearch.title = 'Search'; const searchClose = document.querySelector('a.popup-search-close'); searchClose.setAttribute('role', 'button'); searchClose.title = 'Close search page'; // document // .querySelector('a.btn-open-popup-search') // .setAttribute( // 'href', // 'https://medium.com/towards-artificial-intelligence/search' // ); } // Add external attributes to 302 sticky and editorial links function extLink() { // Sticky 302 links, this fuction opens the link we send to Medium on a new tab and adds a "noopener" rel to them var stickyLinks = document.querySelectorAll('.grid-item.sticky a'); for (var i = 0; i < stickyLinks.length; i++) { /* stickyLinks[i].setAttribute('target', '_blank'); stickyLinks[i].setAttribute('rel', 'noopener'); */ } // Editorial 302 links, same here var editLinks = document.querySelectorAll( '.grid-item.category-editorial a' ); for (var i = 0; i < editLinks.length; i++) { editLinks[i].setAttribute('target', '_blank'); editLinks[i].setAttribute('rel', 'noopener'); } } // Add current year to copyright notices document.getElementById( 'js-current-year' ).textContent = new Date().getFullYear(); // Call functions after page load extLink(); //addAlly(); setTimeout(function() { //addAlly(); //ideally we should only need to run it once ↑ }, 5000); }; function closeCookieDialog (){ document.getElementById("cookie-consent").style.display = "none"; return false; } setTimeout ( function () { closeCookieDialog(); }, 15000); console.log(`%c 🚀🚀🚀 ███ █████ ███████ █████████ ███████████ █████████████ ███████████████ ███████ ███████ ███████ ┌───────────────────────────────────────────────────────────────────┐ │ │ │ Towards AI is looking for contributors! │ │ Join us in creating awesome AI content. │ │ Let's build the future of AI together → │ │ https://towardsai.net/contribute │ │ │ └───────────────────────────────────────────────────────────────────┘ `, `background: ; color: #00adff; font-size: large`); //Remove latest category across site document.querySelectorAll('a[rel="category tag"]').forEach(function(el) { if (el.textContent.trim() === 'Latest') { // Remove the two consecutive spaces (  ) if (el.nextSibling && el.nextSibling.nodeValue.includes('\u00A0\u00A0')) { el.nextSibling.nodeValue = ''; // Remove the spaces } el.style.display = 'none'; // Hide the element } }); // Add cross-domain measurement, anonymize IPs 'use strict'; //var ga = gtag; ga('config', 'G-9D3HKKFV1Q', 'auto', { /*'allowLinker': true,*/ 'anonymize_ip': true/*, 'linker': { 'domains': [ 'medium.com/towards-artificial-intelligence', 'datasets.towardsai.net', 'rss.towardsai.net', 'feed.towardsai.net', 'contribute.towardsai.net', 'members.towardsai.net', 'pub.towardsai.net', 'news.towardsai.net' ] } */ }); ga('send', 'pageview'); -->