Netail, a technology that enables retailers to auto-identify competitors across the internet and track their assortments, availability and optimize prices in real time, announced the closing of $5 Million in seed funding. The round was co-led by Magarac Venture Partners (MVP), which provides early-stage venture capital to dynamic entrepreneurs and successful technology companies throughout the Midwest, and Dr. Andrew Ng's AI Fund. Other investors include HKSTP Ventures. Consumer behavior has changed dramatically, and the majority of purchase decisions are now made online via search, marketplaces and social media. With retailers struggling to adapt, Netail's AI technology is designed to help them succeed by attracting, converting and retaining customers in these increasingly competitive digital arenas.

Identified as the key for further enhancing competitiveness and workforce reinforcement, AI has the potential to be included in various operation processes. One such field, AI in visual inspection – with computer vision and machine learning on the rise – has been becoming more popular thanks to the engagement of top players across industries. In the recent online sharing, experts from FPT Corporation, FPT Software, Landing AI, and Schaeffler discussed their visions for the future of'AI in Real-time Quality Inspection'. All parties emphasised on the use of data-centric approach to shorten AI training duration in machine learning and addressed critical issues faced by brownfields factories. Until just recently, factory owners were equipped with rule-based vision inspection, which required IT experts to write pages of rules for the algorithm to detect product defects.

He is an experienced engineer, programmer, and entrepreneur specializing in the integration of machine vision, robotics, and other automation technologies, with an extensive career in the industry. He was the founder, owner, and principal engineer for two successful vision systems integration firms. Prior to joining Landing AI he was Principal Vision Systems Architect with Integro Technologies, responsible for application evaluation and design of complex automated imaging solutions for inspection, metrology, and robotic guidance. Previously, he had served as Staff Engineer for Intelligent Robotics/Machine Vision at FANUC America Corporation. Mr. Dechow is a recipient of the A3 Automated Imaging Achievement Award honoring industry leaders for outstanding career contributions in industrial and/or scientific imaging.

As enterprises increasingly try to put their data to work using artificial intelligence and machine learning, the landscape of vendors and open source projects can be daunting. As FirstMark partner Matt Turck has written, in 2021 the industry saw a "rapid emergence of a whole new generation of data and ML startups," and in 2022, this trend looks set to continue. AI/ML is so hot, in fact, that even with a recession looming CIOs remain loath to cut spending on AI/ML projects. So where will enterprises spend that money? To help you navigate the sometimes bewildering array of AI/ML options out there, I talked with data science professionals to get their picks on the most innovative companies in AI/ML.

British-born Andrew Ng has had a rich career in the technology industry as Co-Founder and Head of Google Brain, former Chief Scientist at Baidu and Co-Founder of Coursera. At Baidu, Ng built the company's artificial intelligence (AI) sector into a team of several people. In an interview with Lex Fridman, Ng shared where his passion for the industry started: " Growing up in Hong Kong and Singapore, I started learning to code when I was five or six years old. At that time I was learning the BASIC programming language and they would take these folks and they'll tell you type this program into your computer." "So I typed out programs on my computer and as the result of all the typing, I would get to play these very simple, shoot them up games that I had implemented on my little computer. So I thought it was fascinating as a young kid that I could write this code. I was really just copying code from a book into my computer to then play these cool little video games. Another moment for me was when I was a teenager and my father was a doctor was reading about expert systems and about neural networks. So he got me to read some of these books and I thought it was really cool that you could write a computer that started to exhibit intelligence." he continued.

Manufacturers are making strides toward Industry 4.0, a movement to tie a company's factory floor technology with the internet of things, business and operation systems, supply chain and aftermarket technology, and scores of equipment. That includes vision inspection systems, which are increasingly going high-tech with the addition of machine learning, artificial intelligence (AI) algorithms that can be trained to catch small blemishes and disfigurements. The information returned from AI inspection systems is part of the massive operating information that can sense, analyze, and respond to changing company conditions. The resulting data is used to streamline operations and improve efficiency, which lead to massive savings – the premise of Industry 4.0. AI in computer vision is no stranger to manufacturing Industry 4.0 or to a number of other markets, such as biomedical and consumer goods.

At Google Brain, Andrew Ng became famous for showing how deep learning … Later, he founded Coursera, where his machine learning courses have …

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - August 3. Join AI and data leaders for insightful talks and exciting networking opportunities. Did you ever feel you've had enough of your current line of work and wanted to shift gears? If you have, you're definitely not alone. Besides taking part in the Great Resignation, however, there are also less radical approaches, like the one Andrew Ng is taking. Ng, among the most prominent figures in AI, is founder of LandingAI and DeepLearning.AI, co-chairman and cofounder of Coursera, and adjunct professor at Stanford University.

It's no coincidence that deep learning became popular in the AI community following the rise of big data, since neural networks require huge amounts of data to train. But organizations with much smaller data sets can benefit from pre-trained neural networks, especially if they follow the premise of data-centric AI, Andrew Ng said this week at the Nvidia GPU Technology Conference. Ng, a prominent AI researcher and a Datanami 2022 Person to Watch, is at the forefront of the data-centric AI movement, which is aimed at helping millions of smaller organizations leverage the promise of AI. "We know that in consumer software companies, you may have a billion users [in] a giant data set. But when you go to other industries, the sizes are often much smaller," Ng said during his Nvidia GTC session, titled "The Data-centric AI Movement." "From where I'm sitting, I think AI–machine learning, deep learning–has transformed the consumer software Internet. But in many other industries, I think it's frankly not yet there."

Did you miss a session at the Data Summit? Did you ever feel you've had enough of your current line of work and wanted to shift gears? If you have, you're definitely not alone. Besides taking part in the Great Resignation, however, there are also less radical approaches, like the one Andrew Ng is taking. Ng, among the most prominent figures in AI, is founder of LandingAI and DeepLearning.AI, co-chairman and cofounder of Coursera, and adjunct professor at Stanford University.