Separately, in February French grocery chain Carrefour produced its first-ever video made with ChatGPT answering FAQs. The 30-second video has a robot speaking in French and answering common questions from customers like "how to eat better and cheaper via its website." Carrefour's Chief E-commerce Officer Elodie Perthuisot wrote in a LinkedIn post that Carrefour Carrefour's "data and innovation teams are currently working on the use cases of ChatGPT, and generative AI in general." Analysts and grocery tech executives that Modern Retail spoke with said while all types of retailers are excited about using ChatGPT, grocers have compelling reasons to jump into this head first, for a few reasons. For starters, grocers have among the most diverse customer base.

Afif Khoury, CEO and Co-Founder of SOCi, believes that AI will greatly improve the customer experience for both digital marketers and end customers. He believes that customers' expectations are likely to change regarding how they interact with products like SOCi's, and that this will impact the company's product strategy. Khoury believes that generative AI will help SOCi get enterprises' jobs done better than previous approaches by providing more accurate and timely information to customers. SOCi, a leading marketing platform for multi-location brands, announced today a fundraise of $120 million to develop a transformative line of AI-based marketing products and grow into new markets.

Feature Generative AI poses interesting challenges for academic publishers tackling fraud in science papers as the technology shows the potential to fool human peer review. Describe an image for DALL-E, Stable Diffusion, and Midjourney, and they'll generate one in seconds. These text-to-picture systems have rapidly improved over the past few years, and what initially began as a research prototype, producing benign and wonderfully bizarre illustrations of baby daikon radishes walking dogs in 2021, has since morphed into commercial software, built by billion-dollar companies, capable of generating increasingly realistic images. These AI models can produce lifelike pictures of human faces, objects, and scenes, and it's a matter of time before they get good at creating convincing scientific images and data, too. Text-to-image models are now widely accessible, pretty cheap to use, and they could help dodgy scientists forge results and publish sham research more easily.

If you haven't heard of ChatGPT, the uncanny new AI-driven chatbot from San Francisco-based OpenAI, here is a quick primer on everything you need to know about the controversial new program. ChatGPT is an artificial intelligence tool that allows a user to generate original text. You can ask it questions, give it creative prompts, and use it to generate a whole bunch of different stuff--from poems, to songs, to essays, to short stories. ChatGPT was created by OpenAI and launched in November of last year. Partially founded by Elon Musk, OpenAI is an organization that is dedicated to the research and development of artificial intelligence.

Generative AI is an umbrella term for any kind of automated process that uses algorithms to produce, manipulate, or synthesize data, often in the form of images or human-readable text. It's called generative because the AI creates something that didn't previously exist. That's what makes it different from discriminative AI, which draws distinctions between different kinds of input. To say it differently, discriminative AI tries to answer a question like "Is this image a drawing of a rabbit or a lion?" whereas generative AI responds to prompts like "Draw me a picture of a lion and a rabbit sitting next to each other." This article introduces you to generative AI and its uses with popular models like ChatGPT and DALL-E.

Generative artificial intelligence tools like ChatGPT are changing the way that companies and salespeople are communicating with customers for the better, said Clara Shih, CEO of Salesforce's Service Cloud business. "You look at how salespeople work today, and most of them, they dread writing sales emails; they'd much rather be out there with customers," Shih said on CNBC's "Squawk Box" on Thursday. "So they can offload those tasks that are more mundane … they want to focus on engaging with the customer and problem solving." Shih drew a clear line between how generative AI can be utilized by the general person compared to business clients and enterprise users: "We're not talking about writing funny poems, we're talking about writing sales emails and customer service responses that agents can send to get back to customers faster." Earlier this week, Salesforce launched what it called the first generative AI CRM technology, Einstein GPT.

Open-source technologies have had a profound impact on the world of AI and machine learning, enabling developers, data scientists, and organizations to collaborate, innovate, and build better AI solutions. As large AI models like GPT-3.5 and DALL-E become more prevalent, organizations are also exploring ways to leverage existing open-source models and tools without needing to put a tremendous amount of effort into building them from scratch. Microsoft Azure AI is leading this effort by working closely with GitHub and data science communities, and providing organizations with access to a rich set of open-source technologies for building and deploying cutting-edge AI solutions. At Azure Open Source Day, we highlighted Microsoft's commitment to open source and how to build intelligent apps faster and with more flexibility using the latest open-source technologies that are available in Azure AI. Recent advancements in AI propelled the rise of large foundation models that are trained on a vast quantity of data and can be easily adapted to a wide variety of applications across various industries.

OpenAI just announced pricing for businesses seeking to integrate its ChatGPT service into their own products, and it looks an awful lot like a 90 percent off sale. It all starts with OpenAI, a former nonprofit that's now gunning for riches as lustily as any Silicon Valley unicorn. The company has built a dazzling array of products, including the DALL-E image generator and the renowned ChatGPT service. ChatGPT is powered by a system known as a large language model (or LLM), and it's one of several LLM lines that OpenAI sells commercially. Buyers of LLM output are mostly companies that integrate language-related services like chat, composition, summarization, software generation, online search, sentiment analysis, and much more into their websites, services, and products.

As the search AI chatbot shindigs -- like Microsoft's Bing bot debut and Google's Bard launch -- wind down for now, who knew the hottest, trendiest party in generative AI would be … business productivity apps? After years of being relegated to nerdy, wallflower AI status while self-driving cars, robot dogs and the future of the AI-powered metaverse got the spotlight, generative AI's email-writing, blog-producing, copy-powering abilities are suddenly popular. And top companies from startups to Big Tech are developing tools to gain admittance to the generative AI bash. Follow VentureBeat's ongoing generative AI coverage Arriving fashionably late to this generative AI soiree is San Francisco-based Grammarly. The digital writing assistant with a browser extension is far from a newbie to the AI space, but today the company announced its GPT-powered, chatbot-style GrammarlyGo. The new offering will start rolling out to its 30 million daily customers in beta in early April, as well as 50,000 teams in Grammarly Business.

Generative AI's two-edged sword - more information made available. Well before the birth of the internet, I had become an infomaniac. I devoured tech magazines and books on tech to try and stay up to date on current trends and issues related to my job as a tech analyst. I am also a techie at heart, and my first tech-related job in 1975 was semiconductor-related. I would also go to specialized tech user groups and mini-conferences as my interest in tech evolved and helped me when I joined Creative Strategies in 1982 as their first PC analyst.