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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!

Category: Machine Learning

LAI #66: Information Theory for People in a Hurry
Artificial Intelligence  Latest  Machine Learning

LAI #66: Information Theory for People in a Hurry

Towards AI Editorial Team
1 like
March 13, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, I’m heading to San Jose, CA, for Nvidia GTC, happening from March 17 to 21. I’ll attend many discussions and am excited to meet some of …

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WHAT IS MCP BY ANTHROPIC?(MODEL CONTEXT PROTOCOL)
Data Science  Latest  Machine Learning

WHAT IS MCP BY ANTHROPIC?(MODEL CONTEXT PROTOCOL)

Adarsh Menon
0 like
March 12, 2025

Author(s): Adarsh Menon Originally published on Towards AI. while learning about MCP, I was initially perplexed regarding its functionality; my confusion deepened while examining the architecture. When I say “architecture is pretty complicated,” I mean the following:- SOURCE: https://modelcontextprotocol.io/introduction Motivation By Anthropic …

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FactoryBERT: An AI That Understands Manufacturing
Data Science  Latest  Machine Learning

FactoryBERT: An AI That Understands Manufacturing

Saif Ali Kheraj
0 like
March 12, 2025

Author(s): Saif Ali Kheraj Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. https://www.freepik.com/free-photos-vectors/manufacturing-process Factories have their own way of talking. If you’ve ever been inside one, you might hear things like: “OEE is …

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🔎 Decoding LLM Pipeline — Step 1: Input Processing & Tokenization
Artificial Intelligence  Latest  Machine Learning

🔎 Decoding LLM Pipeline — Step 1: Input Processing & Tokenization

Ecem Karaman
1 like
March 12, 2025

Author(s): Ecem Karaman Originally published on Towards AI. 🔎 Decoding LLM Pipeline — Step 1: Input Processing & Tokenization 🔹 From Raw Text to Model-Ready Input In my previous post, I laid out the 8-step LLM pipeline, decoding how large language models …

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Meta to Launch Its Own In-House AI Chip
Artificial Intelligence  Latest  Machine Learning

Meta to Launch Its Own In-House AI Chip

Get The Gist
1 like
March 12, 2025

Author(s): Get The Gist Originally published on Towards AI. Plus: Microsoft Introduces Interactive Ads for Copilot Users This member-only story is on us. Upgrade to access all of Medium. Welcome to Get The Gist, where every weekday we share an easy-to-read summary …

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I Built an AI Money Coach in Python — Here’s How You Can Too (Step-by-Step Guide!)
Artificial Intelligence  Data Science  Latest  Machine Learning

I Built an AI Money Coach in Python — Here’s How You Can Too (Step-by-Step Guide!)

Mukundan Sankar
0 like
March 11, 2025

Author(s): Mukundan Sankar Originally published on Towards AI. Want to manage your money better? Learn how to build an AI-powered financial coach in just a few steps. This member-only story is on us. Upgrade to access all of Medium. Image generated using …

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ChatGPT Now Works Natively in Xcode and VS Code
Artificial Intelligence  Latest  Machine Learning

ChatGPT Now Works Natively in Xcode and VS Code

Get The Gist
1 like
March 11, 2025

Author(s): Get The Gist Originally published on Towards AI. Plus: Apple Delays Advanced Siri Features Until 2026 This member-only story is on us. Upgrade to access all of Medium. Welcome to Get The Gist, where every weekday we share an easy-to-read summary …

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TAI #143: New Scaling Laws Incoming? Ilya’s SSI Raises at bn, Manus Takes AI Agents Mainstream
Artificial Intelligence  Latest  Machine Learning

TAI #143: New Scaling Laws Incoming? Ilya’s SSI Raises at $30bn, Manus Takes AI Agents Mainstream

Towards AI Editorial Team
0 like
March 11, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie As Ilya Sutskever’s Safe SuperIntelligence (SSI) secures another $2bn round at a hefty $30bn valuation, speculation has grown around what he is working on …

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Exploring and Exploiting the Racetrack
Latest  Machine Learning

Exploring and Exploiting the Racetrack

Denny Loevlie
1 like
March 11, 2025

Author(s): Denny Loevlie Originally published on Towards AI. Solving Sutton and Bartos racetrack problem using Reinforcement Learning. This member-only story is on us. Upgrade to access all of Medium. (Image by Author) This post covers a solution and extension to the racetrack …

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The Data Scientist’s New Assistant: An Ultimate Guide to Google’s Gemini Data Science Agent
Data Analysis  Data Science  Latest  Machine Learning

The Data Scientist’s New Assistant: An Ultimate Guide to Google’s Gemini Data Science Agent

Krishan Walia
1 like
March 11, 2025

Author(s): Krishan Walia Originally published on Towards AI. Let’s find to what extent your data science work is automated! This member-only story is on us. Upgrade to access all of Medium. Not a member?Feel free to access the full article here. The …

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NN#12 — Neural Networks Decoded: Concepts Over Code
Artificial Intelligence  Latest  Machine Learning

NN#12 — Neural Networks Decoded: Concepts Over Code

RSD Studio.ai
1 like
March 11, 2025

Author(s): RSD Studio.ai Originally published on Towards AI. Visualizing and Understanding CNNs: The Hidden Machinery of Computer VisionCredits: PrettyStock This member-only story is on us. Upgrade to access all of Medium. We have seen in previous article, how limitations of ANN in …

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Understanding Reinforcement Learning and Multi-Agent Systems: A Beginner’s Guide to MARL (Part 1)
Latest  Machine Learning

Understanding Reinforcement Learning and Multi-Agent Systems: A Beginner’s Guide to MARL (Part 1)

Arthur Kakande
1 like
March 11, 2025

Author(s): Arthur Kakande Originally published on Towards AI. Photo by Hyundai Motor Group on Unsplash When we learn from labeled data, we call it supervised learning. When we learn by grouping similar items, we call it clustering. When we learn by observing …

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Future-Proof Your Marketing: Applied AI and Prompt Engineering for Homo Sapiens
Artificial Intelligence  Latest  Machine Learning

Future-Proof Your Marketing: Applied AI and Prompt Engineering for Homo Sapiens

Jason Dobbs
0 like
March 10, 2025

Author(s): Jason Dobbs Originally published on Towards AI. Image by Jason Dobbs This member-only story is on us. Upgrade to access all of Medium. Despite constant reassurances that AI is here to empower us rather than replace us, the reality is that …

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LlamaIndex vs. LangChain vs. Hugging Face smolagent: A Comprehensive Comparison
Latest  Machine Learning

LlamaIndex vs. LangChain vs. Hugging Face smolagent: A Comprehensive Comparison

Can Demir
1 like
March 10, 2025

Author(s): Can Demir Originally published on Towards AI. Introduction Large Language Models (LLMs) have opened up a new world of possibilities, powering everything from advanced chatbots to autonomous AI agents. However, to unlock their full potential, you often need robust frameworks that …

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Month in 4 Papers (February 2025)
Latest  Machine Learning

Month in 4 Papers (February 2025)

Ala Falaki, PhD
0 like
March 10, 2025

Author(s): Ala Falaki, PhD Originally published on Towards AI. This member-only story is on us. Upgrade to access all of Medium. Exploring how caching strategies, context length, uncertainty estimation, and conceptual representations are reshaping knowledge retrieval in language models. This series of …

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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 = { '': '', '': '', '
': '
' + ctaLinks + '
', }; 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'); -->