Name: Towards AI
Legal Name: Towards AI, Inc.
Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world.
Phone Number: +1-650-246-9381
Email: pub@towardsai.net
228 Park Avenue SouthNew York,
NY10003United States
Name: Towards AI
Legal Name: Towards AI, Inc.
Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication.
Founders:
Roberto Iriondo,
Website,
Job Title: Co-founder and Advisor
Works for: Towards AI, Inc.
Follow Roberto:
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Towards AI Profile,
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Roberto Iriondo, Generative AI Lab,
Generative AI LabDenis Piffaretti,
Job Title: Co-founder
Works for: Towards AI, Inc.Louie Peters,
Job Title: Co-founder
Works for: Towards AI, Inc.Louis-François Bouchard,
Job Title: Co-founder
Works for: Towards AI, Inc.
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Areas Served: Worldwide
Alternate Name: Towards AI, Inc.
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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 = [
/*
' ' +
'
Towards AI has published Building LLMs for Production—our 470+ page guide to mastering LLMs with practical projects and expert insights!
' +
'' +
'' +
'' +
'
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