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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!

Author: Towards AI Editorial Team

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
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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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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
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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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LLMs Are “Just” Coding Assistants — But That Still Changes Everything
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LLMs Are “Just” Coding Assistants — But That Still Changes Everything

Towards AI Editorial Team
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March 7, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Understanding the Role of LLMs in Modern Coding: A Guide for Aspiring Developers The rise of large language models (LLMs) has made AI development more accessible than ever. You can generate text, …

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LAI #65 What Happens When You Combine LangGraph, DeepSeek-R1, Function Call, & Agentic RAG
Artificial Intelligence  Latest  Machine Learning

LAI #65 What Happens When You Combine LangGraph, DeepSeek-R1, Function Call, & Agentic RAG

Towards AI Editorial Team
1 like
March 6, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Ever since we launched our ‘From Beginner to Advanced LLM Developer’ course, many of you have asked for a solid Python foundation to get started. Well, it’s here! …

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TAI #142: GPT-4.5 Released — But Can It Stack Up Against Reasoning Models?
Artificial Intelligence  Latest  Machine Learning

TAI #142: GPT-4.5 Released — But Can It Stack Up Against Reasoning Models?

Towards AI Editorial Team
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March 4, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week’s GPT-4.5 release landed with predictable excitement but, perhaps more tellingly, also sparked some debate. Despite being OpenAI’s largest and most expensive model …

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Introducing Our Python Primer for Generative AI
Artificial Intelligence  Latest  Machine Learning

Introducing Our Python Primer for Generative AI

Towards AI Editorial Team
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March 3, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. The First Python Course Designed for AI Development — from scratch! This week, we are excited to announce our most requested course, Python Primer for Generative AI — designed to help you …

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#64 Here’s how you keep up with AI!
Artificial Intelligence  Latest  Machine Learning

#64 Here’s how you keep up with AI!

Towards AI Editorial Team
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February 27, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we’re diving into a challenge many of us face: keeping up with the rapid pace of AI and answering some extremely thought-provoking questions, such as: Is …

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TAI #141: Claude 3.7 Sonnet; Software Dev Focus in Anthropic’s First Thinking Model
Artificial Intelligence  Latest  Machine Learning

TAI #141: Claude 3.7 Sonnet; Software Dev Focus in Anthropic’s First Thinking Model

Towards AI Editorial Team
1 like
February 25, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie Anthropic Claude 3.7 Sonnet reasoning model stole the show this week. This is partly due to how quickly you can test and see the …

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#63: Full of Frameworks: APDTFlow, NSGM, MLFlow, and more!
Artificial Intelligence  Latest  Machine Learning

#63: Full of Frameworks: APDTFlow, NSGM, MLFlow, and more!

Towards AI Editorial Team
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February 20, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we are introducing new frameworks through hands-on guides such as APDTFlow (addresses challenges with time series forecasting), NSGM (addresses variable selection and time-series network modeling), and …

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#62 Will AI Take Your Job?
Artificial Intelligence  Latest  Machine Learning

#62 Will AI Take Your Job?

Towards AI Editorial Team
1 like
February 13, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Yet another week, and reasoning models and Deepseek are still the most talked about in AI. We are joining the bandwagon with this week’s resources focusing on whether …

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TAI #139: LLM Adoption; Anthropic Measures Use Cases. OpenAI API Traffic up 7x in 2024
Artificial Intelligence  Latest  Machine Learning

TAI #139: LLM Adoption; Anthropic Measures Use Cases. OpenAI API Traffic up 7x in 2024

Towards AI Editorial Team
1 like
February 11, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, Google DeepMind expanded access to Gemini 2.0, OpenAI increased transparency in ChatGPT’s reasoning and thinking steps, and Mistral launched its rapid AI …

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#61: Are LLMs Entering the Age of Agents?
Artificial Intelligence  Latest  Machine Learning

#61: Are LLMs Entering the Age of Agents?

Towards AI Editorial Team
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February 6, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Reasoning agents seem to have taken over AI in the last couple of weeks. While it is early, this class of reasoning-powered agents is likely to progress LLM …

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TAI #138: OpenAI’s o3-Mini and Deep Research: A New Era of Reasoning Powered Agents?
Artificial Intelligence  Latest  Machine Learning

TAI #138: OpenAI’s o3-Mini and Deep Research: A New Era of Reasoning Powered Agents?

Towards AI Editorial Team
1 like
February 4, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie We realize that we have been alternating between OpenAI and DeepSeek-focused discussions recently, but this is with good reason, given some very impressive models …

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#60: DeepSeek, CAG, and the Future of AI Reasoning
Artificial Intelligence  Latest  Machine Learning

#60: DeepSeek, CAG, and the Future of AI Reasoning

Towards AI Editorial Team
1 like
January 30, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! The last two weeks in AI have been all about Deepseek-R1. So this week’s issue includes resources and discussions on that, along with emerging techniques such as CAG, …

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TAI #137: DeepSeek r1 Ignites Debate: Efficiency vs. Scale and China vs. US in the AI Race
Artificial Intelligence  Latest  Machine Learning

TAI #137: DeepSeek r1 Ignites Debate: Efficiency vs. Scale and China vs. US in the AI Race

Towards AI Editorial Team
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January 28, 2025

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week’s AI discourse centered on DeepSeek’s r1 release, which sparked a heated debate about its implications for OpenAI, GPUs, and the broader industry. …

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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'); -->