The biggest tech story of the year is shaping up around the seemingly sudden arrival of AI chatbots into mainstream attention: piggybacking off last year's viral reception to text-to-image generators like DALL-E 2, the launch of OpenAI's ChatGPT in November has since spurred not only widespread media coverage and netizen adoption, but also an industry-wide arms race. Whatever polite corporate doffing made to AI's thicket of ethical ramifications over the past few decades disintegrated nearly overnight in favor of Silicon Valley's primal fear of competition, and we now live in a society where Microsoft's newly AI-powered Bing ("Sydney," to her friends), Google's Bard, Meta's LLaMA, and Snapchat's My AI (which at least allows you the dignity of naming your chatbot yourself) seem poised to transform us all. The AI future feels nigh, if not terribly optimistic. In an era where major breakthroughs in tech render either inscrutable--admit it, you still don't know what a blockchain is, do you?--or We're kind of used to it already: After spending the greater part of Web 2.0 accepting the sleight of hand that invisible, algorithmic forces exert on our day-to-day, the consumer-friendly AI-powered machinations of driverless cars and actually efficient task assistants and decent predictive-text features has become a foregone conclusion.

AI is no longer confined to small circles of developers and enthusiasts. Data analysis and machine learning services, like Google Colab and Microsoft's Azure OpenAI Service's various models, make it easier than ever to include a larger circle of employees in AI development by enabling anyone to write and share code for projects. Enterprises must appropriately train business users on what AI is and how AI can apply to everyday tasks to utilize the technology effectively. Arpit Mehra, practice director at analyst firm Everest Group, recommends enterprises use decentralized governance models to enable data and technology learning strategies. Arun Chandrasekaran, distinguished vice president and analyst at Gartner, also recommended that companies prioritize investments in specialized and domain-specific intelligent applications that focus on training in areas like customer engagement, customer service and talent acquisition.

The graph represents a network of 1,072 Twitter users whose recent tweets contained "iiot bigdata", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 3/9/2023 5:00:36 PM. The network was obtained from Twitter on Friday, 10 March 2023 at 12:02 UTC. The tweets in the network were tweeted over the 1827-day, 0-hour, 27-minute period from Friday, 09 March 2018 at 00:30 UTC to Friday, 10 March 2023 at 00:58 UTC. There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above. The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

Are ChatGPT and generative AI a blessing or a curse for security teams? While artificial intelligence (AI)'s ability to generate malicious code and phishing emails presents new challenges for organizations, it's also opened the door to a range of defensive use cases, from threat detection and remediation guidance, to securing Kubernetes and cloud environments. Recently, VentureBeat reached out to some of PWC's top analysts, who shared their thoughts on how generative AI and tools like ChatGPT will impact the threat landscape and what use cases will emerge for defenders. Follow VentureBeat's ongoing generative AI coverage Overall, the analysts were optimistic that defensive use cases will rise to combat malicious uses of AI over the long term. Below is an edited transcript of their responses.

The biggest difference between Google Bard and ChatGPT is that, as of this writing, Bard knows about ChatGPT but ChatGPT is blissfully unaware of Bard. But I can play around with ChatGPT, while Google Bard is still out of reach for most of us. Both ChatGPT and Google Bard are AI chatbots. The simplest version of this technology already exists on your smartphone - you type "Good," and your phone predicts that the next word you might want to use is "morning." ChatGPT was originally developed by OpenAI and then invested in by Microsoft for an eye-watering $10 billion (in addition to an earlier $1 billion investment).

The general public discovered the existence of OpenAI's GPT-3.5 language model with the publication of ChatGPTChatGPT late last November. The next version, GPT-4, was expected for this year, but the launch is now said to be imminent. At a German conference AI in focus around Artificial Intelligence, Andreas Braun, CTO of MicrosoftMicrosoft Germany, said GPT-4 is expected to be announced in the coming days. The announcement should logically fall during Microsoft's conference on the future of work with AI (Future of Work with AI) scheduled for Thursday, March 16 at 5 p.m. French time. He did not specify whether Microsoft or OpenAI will make the announcement.

Following Microsoft, DuckDuckGo is now tapping OpenAI's ChatGPT technology to streamline its search engine. DuckAssist is a free feature that can pop up when you make a query on the DuckDuckGo search engine. By tapping AI algorithms, DuckAssist can offer a concise answer to your query at the top of the search page, removing the need to scroll through search results and visit a third-party website to find the answer. The approach could kill off traditional search results, like Microsoft is starting to do with the ChatGPT-powered Bing. But for now, DuckAssist's scope has been confined to only citing content from encyclopedia sites Wikipedia and Brittanica.

ChatGPT might well be the most famous, and potentially valuable, algorithm of the moment, but the artificial intelligence techniques used by OpenAI to provide its smarts are neither unique nor secret. Competing projects and open-source clones may soon make ChatGPT-style bots available for anyone to copy and reuse. Stability AI, a startup that has already developed and open-sourced advanced image-generation technology, is working on an open competitor to ChatGPT. "We are a few months from release," says Emad Mostaque, Stability's CEO. A number of competing startups, including Anthropic, Cohere, and AI21, are working on proprietary chatbots similar to OpenAI's bot.

With the continuous improvement of artificial intelligence (AI), expert research shows that AI has the power to double yearly economic growth rates by 2035 and completely revolutionize how humans work, create and communicate. However, the advent of AI engines like DALL·E 2, Midjourney and Point-E have left many creators worried that AI will leave humans with no creative outlet. The good news is that this is not the case. AI has advanced enough in its communication skills to even fill the role of a close companion or dynamic, interactive acquaintance. Programs like Journey AI and Replika have intriguing tag lines like "AI devoted to you" and "the AI companion who cares."

Groundbreaking large language model research from OpenAI, Google, Amazon, and others have transformed expectations of machine-generated software. But how do these AI assistants measure up against regular expressions--a workhorse technology for developers used to describe, find, and manipulate patterns in text. Regular Expression Puzzles and AI Coding Assistants is the story of two competitors. On one side is David Mertz, an expert programmer and the author of the Web's most popular Regex tutorial. On the other are the AI powerhouse coding assistants, GitHub Copilot and OpenAI ChatGPT.