Grindr Goes'AI-First' as It Strives to Be an'Everything App for the Gay Guy' After controlling shareholders failed to take Grindr private and controversies over data and the banning of the phrase "No Zionists," Grindr's CEO opens up about AI, privacy, and big expansion plans. Every Grindr user is unique. South Koreans prefer open relationships. The highest percentage of self-proclaimed "daddies" call the US home, and Switzerland is overrun with twinks. Delivered by annual trend report Grindr Unwrapped, those critical insights offer the type of information that will help usher the company into its "AI-first" era where it's "the everything app for the gay guy," CEO George Arison tells WIRED. Grindr was the first to leverage geo-location tech when it burst onto the scene in 2009. Arison arrived at the company in 2022 from the world of automotive ecommerce.

Brands said it is bringing an "AI-first" mentality to fast food. FAST-FOOD INNOVATIONS: Yum! Brands, the operator of KFC, Pizza Hut, Taco Bell and The Habit Burger Grill restaurants, is embracing technology with plans for "AI-powered" fast food, according to a Wall Street Journal report. Companies will be making the move toward AI to power their restaurants. CREATIVE INFRINGEMENT: Katy Perry and Miranda Lambert are just some of the more than over 200 names who have signed a letter speaking out for musicians' rights as artificial intelligence continues to expand its reach. POWER SURGE: Global energy demand is projected to surge in coming years amid the growth of artificial intelligence, which requires massive amounts of electricity.

Welcome to AI book reviews, a series of posts that explore the latest literature on artificial intelligence. Artificial intelligence has become a buzzword in the tech industry. Companies are eager to present themselves as "AI-first" and use the terms "AI," "machine learning," and "deep learning" abundantly in their web and marketing copy. What are the effects of the current hype surrounding AI? Is it just misleading consumers and end-users or is it also affecting investors and regulators?

MONTREAL and VANCOUVER, British Columbia, July 08, 2021 (GLOBE NEWSWIRE) -- Rithmik Solutions, whose mission is building the world's most advanced and reliable analytics for mobile mining equipment, today announced the closing of a US$1.2M investment led by Chrysalix Venture Capital and joined by Fonds Ecofuel. The funding will accelerate the commercialization of the company's flagship product, Rithmik Asset Health Analyzer (AHA), which has been in development for the past three years and is currently undergoing real-time onsite trials in Alberta, Quebec and Zambia. Rithmik AHA applies a multi-tiered machine learning approach to increase mobile equipment uptime while reducing maintenance costs and lowering greenhouse gas emissions. Mining companies typically spend anywhere from 20%-50% of their annual operating budgets on equipment maintenance, and lost production from unplanned downtime has an even bigger financial impact. "We were impressed by the Rithmik team's deep technical experience in the space of mobile mining equipment data, across equipment types and OEM brands, and that experience has strongly resonated with their early customers," said Alicia Lenis, Vice President at Chrysalix Venture Capital, an industrial innovation fund.

If an operating model defines how an organization positions people, process, and technology to deliver customer value, then companies with an AI-first operating model are those that prioritize the use of AI to weave more intelligence and automation into the firm's products, processes, and experiences. Data gathered from 100 global CIOs at the Metis Strategy Digital Symposium in July 2020 personifies the trend toward AI-first operating models: 66% of CIOs stated that they have teams focused on identifying AI use cases, conducting pilots and scaling those cases that improve outcomes. Of the CIOs who do not currently have resources focused on this, roughly 60% indicated it is on their roadmap. In our work with Fortune 500 companies, we have identified common characteristics among organizations that successfully navigate the shift to AI-first. Below are a series of smart first steps digital leaders can take to initiate, accelerate, or course correct their AI transformation.

Those that implement AI and Machine Learning project learn quickly that machine learning projects are not application development projects. Much of the value of machine learning projects rest in the models, training data, and configuration information that guides how the model is applied to the specific machine learning problem. The application code is mostly a means to implement the machine learning algorithms and "operationalize" the machine learning model in a production environment. That's not to say that application code is not necessary -- after all, the computer needs some way to operationalize the machine learning model -- but focusing a machine learning project on the application code is missing the big picture. If you want to be AI-first for your project, you need to have a data-first perspective.

Artificial intelligence (AI) is giving customer experience a shot in the arm. Organizations are increasingly adopting conversational chatbots for providing customer service. Airports around the world are investing in mobile androids that help travelers with directions. Hotels are experimenting with voice-assisted in-room controls.1 A Microsoft social chatbot in China, "Xaiolce," already has over 200 million users, with 600,000 calls made in the first ten months since its launch.

Convenience drives consumers' choices of channels and devices. I don't care how many market research stats you can find about consumers' use of branches, mobile devices, or voice-enabled technology, you will never sway my belief that consumers will use whatever channel or device is most convenient for them at the moment they want or need to interact. A Statista study found that only one in five bank customers have "warmed up" to conversing with chatbots, while another study from NewVoiceMedia revealed that just 13% of consumers prefer their customer service queries to be handled by a chatbot. Why in the world would you be "AI-first" when your customers are anything but? Technology isn't a panacea for ineffective business processes, practices, or policies.

The past year was one of change for the digital experience. Thanks to the rising availability of machine learning, contextual experiences are finding their footing in every industry, the use of personal content is giving new vigor to ecommerce, and vendors are evolving their classic content management systems (CMS) into more powerful digital experience platforms (DXP). This transformation is just starting. Like every other year, 2018 will be about moving forward with (and, for the first-movers, ahead of) the demands of the digital world. Here's a look at what I believe will be the five biggest developments in digital experience in 2018.

Google has plunged high towards its'AI-first' dream. The tech giant has attempted to develop a Text-to-speech system that has exactly human-like articulation. This AI system is called "Tacotron 2" that has the ability to give an AI-generated computer speech in a human-voice. Google researchers mentioned in the blog post that the new procedure does not utitilise complex linguistic and acoustic features as input. In place of it, they developed human-like speech from text using neural networks trained using only speech examples and corresponding text transcript. Google's CEO Sundar Pichai announced that the company will be shifting its focus from mobile-first to AI-first at the Google I/O 2017 developers conference.