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Landing AI Secures m on Series A for MLOps Platform
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Landing AI Secures $57m on Series A for MLOps Platform

Towards AI Team
2 likes
November 8, 2021
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Last Updated on November 8, 2021 by Editorial Team

Author(s): Towards AI Team

Source: Landing AI

AI Rolls Up Its Sleeves in Legacy Industries with Landing AI’s MLOps Platform

PALO ALTO, Calif., Nov. 8, 2021 — Landing AI, which provides tools that make building and deploying AI systems in manufacturing faster and easier than ever, today announced Series A funding of $57 million led by McRock Capital, the first investment firm focused exclusively on the Industrial IoT.

In addition, New York-based global private equity and venture capital firm Insight Partners, Taiwania Capital, Canada Pension Plan Investment Board (CPP Investments), Intel Capital, Samsung Catalyst Fund, Far Eastern Group’s DRIVE Catalyst, Walsin Lihwa, and AI Fund all participated in the round.

“Landing AI will unleash the power of the Industrial IoT one company, one factory, and one manufacturing line at a time.”

Landing AI, led by artificial intelligence visionary, Andrew Ng, developed LandingLens™, a fast, easy-to-use enterprise MLOps platform. It applies AI and deep learning to help manufacturers solve visual inspection problems, find product defects more reliably, and generate business value.

Landing AI sees the next era of AI as one in which all companies access the benefits of AI — not just consumer internet companies like Google and Facebook — but legacy industries such as manufacturing, healthcare, and agriculture. To do that, Landing AI says industries should adopt a new, data-centric approach to building AI that ensures that the data conveys what they need the AI to learn. Using data-centric AI technology, the application of AI will no longer depend on big data but on the data the entities actually have, which is often limited.

“You don’t always need big data to win with AI. You need good data that teaches the AI what you want it to learn,” said Ng, Founder & CEO of Landing AI. “AI built for 50 million data points doesn’t work when you only have 50 data points. By bringing machine learning to everyone regardless of the size of their data set, the next era of AI will have a real-world impact on all industries.”

Source: Landing AI

The data-centric approach of Landing AI is also vital to making LandingLens fast and easy to use. The process of engineering the data, instead of the AI software, gives an efficient way for manufacturers to teach an AI model what to do. Domain experts can now build an AI system and take it to production, not just AI experts. For example, rather than writing pages of code to train a neural network, a domain expert can do it with a few mouse clicks. This no code/low code data-centric platform enables new users to build advanced AI models in less than a day. Vision inspection projects that used to take over a year can be executed in just weeks using LandingLens.

“Landing AI will unleash the power of the Industrial IoT one company, one factory, and one manufacturing line at a time,” said Scott MacDonald, Co-Founder and Managing Partner of McRock Capital. “We partner with relentless entrepreneurs, like Andrew, who bring transformative digital technologies to large industrial markets.” As part of the financing, MacDonald has joined the Landing AI Board of Directors.

“Digital modernization of manufacturing is rapidly growing and is expected to reach $300 billion by 2023,” said George Mathew, Managing Director at Insight Partners. “The opportunity and need for Landing AI is only exploding. It will unlock the untapped segment of targeted machine vision projects addressing quality, efficiency and output. We’re looking forward to playing a role in the next phase of Landing AI’s exciting journey.”

Landing AI is on a strong growth trajectory, and customers are reaping the benefits. “Partnering with Landing AI can improve the reliability and efficiency of our quality inspection process, which is important to our company’s growth. Using cutting-edge deep learning tools like LandingLens enables our team to move faster and focus on developing and commercializing our next-generation batteries,” said Tim Holme, Co-founder & CTO, QuantumScape.

The new investment will be used to accelerate product innovation and grow engineering and operations teams within Landing AI, including engineering, product, sales, and marketing. To join the Landing AI team, please go to https://landing.ai/careers/, and to schedule a demo of LandingLens, please click here.

Source: Landing AI

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} 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(`#${articleId} .entry-content`); //replaces the "linktext" in achor tag with the keyword that will be searched and replaced let newLink = anchorTag.replace('linktext', keyword); //regular expression to search keyword var re = new RegExp('(' + keyword + ')', 'g'); //this replaces the keywords in h3 h4 and p tags content with achor tag content.innerHTML = content.innerHTML.replace(re, newLink); } function articleFilter(keyword, anchorTag) { //gets all the articles var articles = document.querySelectorAll('article'); //if its zero or less then there are no articles if (articles.length > 0) { for (let x = 0; x < articles.length; x++) { //articles to skip is an array in which there are ids of articles which should not get effected //if the current article's id is also in that array then do not call search and replace with its data if (!articleIdsToSkip.includes(articles[x].id)) { //search and replace is called on articles which should get effected searchAndReplace(keyword, anchorTag, articles[x].id, key); 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mlclinks = document.querySelectorAll(`#${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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