What if, in the end, we are done in not by intercontinental ballistic missiles or climate change, not by microscopic pathogens or a mountain-size meteor, but by … text? Simple, plain, unadorned text, but in quantities so immense as to be all but unimaginable--a tsunami of text swept into a self-perpetuating cataract of content that makes it functionally impossible to reliably communicate in any digital setting? Our relationship to the written word is fundamentally changing. So-called generative artificial intelligence has gone mainstream through programs like ChatGPT, which use large language models, or LLMs, to statistically predict the next letter or word in a sequence, yielding sentences and paragraphs that mimic the content of whatever documents they are trained on. They have brought something like autocomplete to the entirety of the internet.

Do you know who Russell Westbrook is? If not, allow me to give you a rundown of this basketball star's outstanding background. Let's start by discussing his accomplishments. Westbrook has been selected to the NBA All-Star team nine times and has twice been voted the game's MVP. Additionally, he has earned spots on both the All-NBA First Team and the All-NBA Second Team five times each.

Are you a basketball fan? If so, you've undoubtedly heard of Joel Embiid, the talented center for the Philadelphia 76ers. Let's begin with his successes on the court. Embiid was chosen to the All-NBA Third Team and the All-Defensive Second Team in just his fifth season in the NBA. Additionally, he participated in his third consecutive All-Star game and was selected to the All-NBA Third Team for a second time in a row.

This article was featured in One Great Story, New York's reading recommendation newsletter. Sign up here to get it nightly. But before Microsoft's Bing started cranking out creepy love letters; before Meta's Galactica spewed racist rants; before ChatGPT began writing such perfectly decent college essays that some professors said, "Screw it, I'll just stop grading"; and before tech reporters sprinted to claw back claims that AI was the future of search, maybe the future of everything else, too, Emily M. Bender co-wrote the octopus paper. Bender is a computational linguist at the University of Washington. She published the paper in 2020 with fellow computational linguist Alexander Koller. The goal was to illustrate what large language models, or LLMs -- the technology behind chatbots like ChatGPT -- can and cannot do. Say that A and B, both fluent speakers of English, are independently stranded on two uninhabited islands. They soon discover that previous visitors to these islands have ...

The cybersecurity firm Darktrace has warned that since the release of ChatGPT it has seen an increase in criminals using artificial intelligence to create more sophisticated scams to con employees and hack into businesses. The Cambridge-based company, which reported a 92% drop in operating profits in the half year to the end of December, said AI was further enabling "hacktivist" cyber-attacks using ransomware to extort money from businesses. The company said it had seen the emergence of more convincing and complex scams by hackers since the launch of the hugely popular Microsoft-backed AI tool ChatGPT last November. "Darktrace has found that while the number of email attacks across its own customer base remained steady since ChatGPT's release, those that rely on tricking victims into clicking malicious links have declined while linguistic complexity, including text volume, punctuation and sentence length among others, have increased," the company said. "This indicates that cybercriminals may be redirecting their focus to crafting more sophisticated social engineering scams that exploit user trust." However, Darktrace said that the phenomenon had not yet resulted in a new wave of cybercriminals emerging, merely changing the tactics of the existing cohort.

The story so far: Most of the discussion of ChatGPT I'm seeing from even very smart, tech-savvy people is just not good. In articles and podcasts, people are talking about this chatbot in unhelpful ways. And by "unhelpful ways," I don't just mean that they're anthropomorphizing (though they are doing that). Rather, what I mean is that they're not working with a practical, productive understanding of what the bot's main parts are and how they fit together. To put it another way, there are some can-opener problems manifesting in the ChatGPT conversation, and lowering the quality of The Discourse. To be clear, I do not know everything I'd like to know about this topic. That said, I'm certainly far enough along that I can help others who are a few steps behind.

The humble broadcast-radio host, whether a disc jockey or interviewer or reporter, has been going through it for decades now. The 1996 Telecommunications Act fueled the consolidation of local stations, decimating their staffs. The explosion of online radio, music and video streaming, and podcasting have upended ratings for shows on public airwaves. Funding for public radio is notoriously unreliable. On top of all that, your local DJ was already on the losing end of the artificial-intelligence revolution. Before the A.I. hype from last year, and even before the COVID recession demolished media ad markets, broadcast networks were gutting on-air talent at the both the national and collegiate level to trim budgets and automate programming: syndicating well-known shows and brands, prerecording and prearranging late-night broadcasts, training a roboticized voice to fill in the space when needed.

On Monday, a group of AI researchers from Google and the Technical University of Berlin unveiled PaLM-E, a multimodal embodied visual-language model (VLM) with 562 billion parameters that integrates vision and language for robotic control. They claim it is the largest VLM ever developed and that it can perform a variety of tasks without the need for retraining. According to Google, when given a high-level command, such as "bring me the rice chips from the drawer," PaLM-E can generate a plan of action for a mobile robot platform with an arm (developed by Google Robotics) and execute the actions by itself. PaLM-E does this by analyzing data from the robot's camera without needing a pre-processed scene representation. This eliminates the need for a human to pre-process or annotate the data and allows for more autonomous robotic control.

We've only had a couple of years of GPT growing to a mass scale; a few months ago, an AI-generated image won an art contest, and now generative conversations, videos, and deepfakes are running rampant across the internet. I believe this is a pivotal moment in history, as some of the crazy tech we've seen in movies is making its way into a scope of possibility. Our world is quickly becoming one in which we're chatting with AI bots on Instagram and Snapchat, worried over AI text detectors, and asking Siri to generate a gluten-free version of your favorite recipe. You've probably already heard about ChatGPT's incredible growth to one million users in just five days. Microsoft released an all-new Bing, featuring a helpful (and sometimes inaccurate) chatbot that is rumored to be powered by GPT-4, the next generation of the popular large language model (LLM) GPT-3.

Within four days of ChatGPT's launch, Habib used the chatbot to build QuickVid AI, which automates much of the creative process involved in generating ideas for YouTube videos. Creators input details about the topic of their video and what kind of category they'd like it to sit in, then QuickVid interrogates ChatGPT to create a script. Other generative AI tools then voice the script and create visuals. Tens of thousands of users used it daily--but Habib had been using unofficial access points to ChatGPT, which limited how much he could promote the service and meant he couldn't officially charge for it. That changed on March 1, when OpenAI announced the release of API access to ChatGPT and Whisper, a speech recognition AI the company has developed.