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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

TAI #113; Sakana’s AI Scientist — Are LLM Agents Ready To Assist AI Research?
Artificial Intelligence  Latest  Machine Learning

TAI #113; Sakana’s AI Scientist — Are LLM Agents Ready To Assist AI Research?

Towards AI Editorial Team
1 like
August 20, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, xAI joined the growing crowd of broadly GPT-4 class models, which now includes models from OpenAI, Anthropic, Deepmind, xAI, Meta, Mistral, and …

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Face Detection in Python using YOLO: A Practical Guide
Computer Vision  Latest  Machine Learning

Face Detection in Python using YOLO: A Practical Guide

Davide Nardini
0 like
August 17, 2024

Author(s): Davide Nardini Originally published on Towards AI. Impressive Face Detection in just one Python line of code using YOLO and Ultralytics. This member-only story is on us. Upgrade to access all of Medium. This tutorial introduces you to YOLO, one of …

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#36 A Framework for Building Scalable AI Products, Best AI Tools for Marketers, ML Library, and more!
Artificial Intelligence  Latest  Machine Learning

#36 A Framework for Building Scalable AI Products, Best AI Tools for Marketers, ML Library, and more!

Towards AI Editorial Team
1 like
August 15, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we have curated an interesting mix of resources around using AI for businesses, building AI products, and understanding AI models, along with exciting collaboration opportunities. What’s …

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TAI 112; Agent Capabilities Advancing; METR Eval and Inference Compute Scaling
Artificial Intelligence  Latest  Machine Learning

TAI 112; Agent Capabilities Advancing; METR Eval and Inference Compute Scaling

Towards AI Editorial Team
1 like
August 13, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week saw fewer major announcements in AI, but there were still some notable developments. New open-source models were released, including Qwen 2 Math …

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Taylor Series in AI.
Artificial Intelligence  Latest  Machine Learning

Taylor Series in AI.

ifttt-user
1 like
August 8, 2024

Author(s): Surya Maddula Originally published on Towards AI. P.S. Read thru this article a bit slowly, word by word; you’ll thank me later 😉 — — — — Let’s see what the Taylor Series is and how it relates to its applications …

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The Best Practices of RAG
Latest  Machine Learning

The Best Practices of RAG

ifttt-user
2 likes
August 8, 2024

Author(s): Florian June Originally published on Towards AI. Typical RAG Process, Best Practices for Each Module, and Comprehensive Evaluation The process of RAG is complex, with numerous components. How can we determine the existing RAG methods and their optimal combinations to identify …

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Building a Productized AI Chatbot for Credit Card Business
Latest  Machine Learning

Building a Productized AI Chatbot for Credit Card Business

ifttt-user
1 like
August 8, 2024

Author(s): Shenggang Li Originally published on Towards AI. Streamlined Integration of Mixed Tech in AI ChatbotPhoto by Chris Appano on Unsplash Imagine you’re a customer with an urgent question about your credit card. You call customer support, but the wait time is …

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Can Mixture of Experts (MoE) Models Push GenAI to the Next Level?
Artificial Intelligence  Computer Vision  Latest  Machine Learning

Can Mixture of Experts (MoE) Models Push GenAI to the Next Level?

ifttt-user
1 like
August 8, 2024

Author(s): Nick Minaie, PhD Originally published on Towards AI. Can Mixture of Experts (MoE) Models Push GenAI to the Next Level? Having worked in the AI/ML field for many years, I vividly recall the early days of GenAI when creating even simple …

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#35 Advanced prompting techniques are a myth…it’s all about good communication!
Artificial Intelligence  Latest  Machine Learning

#35 Advanced prompting techniques are a myth…it’s all about good communication!

ifttt-user
1 like
August 8, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, don’t skip to your favorite sections (we know you guys do that); we have some fun bonuses for you, especially if you are in the ‘learning …

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Google’s Gemma2-2B, A Compression Marvel
Artificial Intelligence  Data Science  Latest  Machine Learning

Google’s Gemma2-2B, A Compression Marvel

ifttt-user
1 like
August 8, 2024

Author(s): Ignacio de Gregorio Originally published on Towards AI. How to Build a Small TitanSource: Generated by author using GPT-4o Google has reached a new milestone in AI by training a 2 billion parameter model, absolutely minute in today’s terms, that surpasses …

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TensorFlow vs. PyTorch: What’s Better for a Deep Learning Project?
Data Science  Latest  Machine Learning

TensorFlow vs. PyTorch: What’s Better for a Deep Learning Project?

ifttt-user
0 like
August 8, 2024

Author(s): Eashan Mahajan Originally published on Towards AI. Photo by Marius Masalar on Unsplash Deep learning. A subset of machine learning utilizing multilayered neural networks, otherwise known as deep neural networks. Allowing society to simulate the decision-making prowess the human brain possesses, …

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Beyond LLMs: Compounds Systems, Agents, and Whole AI Products
Data Science  Latest  Machine Learning

Beyond LLMs: Compounds Systems, Agents, and Whole AI Products

ifttt-user
1 like
August 8, 2024

Author(s): Adel Zaalouk Originally published on Towards AI. A Framework for Building Great AI Products Introduction The other day, I found myself reflecting on a classic concept that I was taught in business school, Maslow’s hierarchy of needs, a simple but powerful …

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Why Polars Destroy Pandas in All Possible Ways for Data Scientists?
Data Science  Latest  Machine Learning

Why Polars Destroy Pandas in All Possible Ways for Data Scientists?

ifttt-user
0 like
August 8, 2024

Author(s): Lazar Gugleta Originally published on Towards AI. One of the first Data Science libraries, Pandas, has been improving the lives of many developers across the globe, but Polars shows it is time to move on. Pandas needs no introduction, but this …

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From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams
Data Science  Latest  Machine Learning

From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams

ifttt-user
0 like
August 7, 2024

Author(s): Gift Ojeabulu Originally published on Towards AI. From Solo Notebooks to Collaborative Powerhouse: VS Code Extensions for Data Science and ML Teams Photo by Parabol | The Agile Meeting Toolbox on Unsplash In this article, we will explore the essential VS …

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Building Intelligent Agents from Scratch: A Journey into LLM-Powered Autonomy
Latest  Machine Learning

Building Intelligent Agents from Scratch: A Journey into LLM-Powered Autonomy

ifttt-user
0 like
August 6, 2024

Author(s): Anoop Maurya Originally published on Towards AI. Photo by Rock'n Roll Monkey on Unsplash In recent years, the advent of large language models (LLMs) has revolutionized the field of artificial intelligence, making it possible for machines to understand and generate human-like …

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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'); -->