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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

#47 Building a NotebookLM Clone, Time Series Clustering, Instruction Tuning, and More!
Artificial Intelligence  Latest  Machine Learning

#47 Building a NotebookLM Clone, Time Series Clustering, Instruction Tuning, and More!

Towards AI Editorial Team
1 like
October 31, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! As we wrap up October, we’ve compiled a bunch of diverse resources for you — from the latest developments in generative AI to tips for fine-tuning your LLM …

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TAI #123; Strong Upgrade to Anthropic’s Sonnet and Haiku 3.5, but Where’s Opus?
Artificial Intelligence  Latest  Machine Learning

TAI #123; Strong Upgrade to Anthropic’s Sonnet and Haiku 3.5, but Where’s Opus?

Towards AI Editorial Team
1 like
October 30, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week Anthropic released significant upgrades to its Claude model family with an improved Sonnet 3.5, the first smaller Haiku model in the 3.5 …

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#46 Why Can’t We Just Remove All Bias in AI?
Latest  Machine Learning

#46 Why Can’t We Just Remove All Bias in AI?

Towards AI Editorial Team
2 likes
October 24, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! An interesting ongoing discussion in the community is around bias in AI. Currently, we are very close to releasing the most comprehensive practical LLM Python developer course out …

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TAI #122; LLMs for Enterprise Tasks; Agent Builders or Fully Custom Pipelines?
Artificial Intelligence  Latest  Machine Learning

TAI #122; LLMs for Enterprise Tasks; Agent Builders or Fully Custom Pipelines?

Towards AI Editorial Team
0 like
October 22, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, the focus on customizing LLMs for enterprises gained further momentum with Microsoft’s announcement of Copilot Studio agents, following Salesforce’s launch of AgentForce …

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#45 Is Prompting a Future-Proof Skill?
Artificial Intelligence  Latest  Machine Learning

#45 Is Prompting a Future-Proof Skill?

Towards AI Editorial Team
0 like
October 17, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! Over the past few months, we have discussed the AI engineer’s toolkit for building reliable LLM products multiple times. We believe that combining RAG, prompting, and fine-tuning will …

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TAI #121: Is This the Beginning of AI Starting To Sweep the Nobel Prizes?
Artificial Intelligence  Latest  Machine Learning

TAI #121: Is This the Beginning of AI Starting To Sweep the Nobel Prizes?

Towards AI Editorial Team
2 likes
October 15, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, our attention was on the Nobel prizes, where two prizes were awarded explicitly for AI research for the first time. The Physics …

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#44 Why is Model Distillation the Hottest Trend in AI Right Now?
Artificial Intelligence  Latest  Machine Learning

#44 Why is Model Distillation the Hottest Trend in AI Right Now?

Towards AI Editorial Team
0 like
October 10, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week we discuss the hottest trend in AI: Model Distillation, along with some interesting articles on RAG, Llama 3.2, and Bayesian methods. What’s AI Weekly This week, …

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Building LLMs for Production Gets a Massive Update!
Latest  Machine Learning

Building LLMs for Production Gets a Massive Update!

Towards AI Editorial Team
1 like
October 9, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. We are excited to announce the new and improved version of Building LLMs for Production. The latest version of the book offers an improved structure, fresher insights, more up-to-date information, and optimized …

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TAI #120; OpenAI DevDay in Focus!
Artificial Intelligence  Latest  Machine Learning

TAI #120; OpenAI DevDay in Focus!

Towards AI Editorial Team
0 like
October 8, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie OpenAI’s 2024 DevDay event came amidst a backdrop of significant changes within the company, including executive departures and new fundraising efforts. Despite the turbulence, …

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#43 MemoRAG, RAG Agent, RAG Fusion, and more!
Artificial Intelligence  Latest  Machine Learning

#43 MemoRAG, RAG Agent, RAG Fusion, and more!

Towards AI Editorial Team
2 likes
October 3, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we are diving into different RAG approaches, programming tips, community discussions, and some fun collaboration opportunities. Dive in and enjoy the read! What’s AI Weekly This …

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TAI #119 New LLM audio capabilities with NotebookLM and ChatGPT Advanced Voice
Artificial Intelligence  Latest  Machine Learning

TAI #119 New LLM audio capabilities with NotebookLM and ChatGPT Advanced Voice

Towards AI Editorial Team
1 like
October 1, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, we were focused on new voice capabilities for LLMs with Google’s recently released NotebookLM’s audio features and OpenAI’s move to roll out …

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#42 Teaching AI to “Think”, Fine-Tuning to SQL, Encoder-only models, and more!
Artificial Intelligence  Latest  Machine Learning

#42 Teaching AI to “Think”, Fine-Tuning to SQL, Encoder-only models, and more!

Towards AI Editorial Team
0 like
September 26, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This is another resource-heavy issue with articles focusing on everything from early AI architectures to the latest developments in AI reasoning abilities. Enjoy the read! What’s AI Weekly …

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A Practical Approach to Using Web Data for AI and LLMs
Artificial Intelligence  Latest  Machine Learning

A Practical Approach to Using Web Data for AI and LLMs

Towards AI Editorial Team
1 like
September 26, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. As businesses and researchers work to advance AI models and LLMs, the demand for high-quality, diverse, and ethically sourced web data is growing rapidly. If you’re working on AI applications or building …

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TAI #118: Open source LLMs progress with Qwen 2.5 and Pixtral 12B
Artificial Intelligence  Latest  Machine Learning

TAI #118: Open source LLMs progress with Qwen 2.5 and Pixtral 12B

Towards AI Editorial Team
2 likes
September 24, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, several new strong open-source LLM models were released. Following OpenAI’s huge LLM progress with its o1 “reasoning” model family last week, it …

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#41 OpenAI’s “innovation,” LLM Quantization, Feature Selection, and more!
Latest  Machine Learning

#41 OpenAI’s “innovation,” LLM Quantization, Feature Selection, and more!

Towards AI Editorial Team
1 like
September 19, 2024

Author(s): Towards AI Editorial Team Originally published on Towards AI. Good morning, AI enthusiasts! This week, we are sharing lots of resources covering some developments in the AI landscape. Today’s articles cover everything from the speed issues with Open AI’s new model …

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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'); -->