Language Log

On 5/8/2024, the Defense Visual Information Distribution Service (DVIDS) offered a "Graphical representation of how the precision cutting charges will be used on key bridge section":

Several bits in the voice-over suggest that it was generated by a text-to-speech program — I'll note a couple of them below. And the failure to capitalize "Key Bridge" in the page's title might also be a symptom of AI-generation?

I got an echo of Saturday's post about chatbot pals, from an article yesterday in Intelligencer — John Herrman, "Meta’s AI Needs to Speak With You" ("The company is putting chatbots everywhere so you don’t go anywhere"):

Meta has an idea: Instead of ever leaving its apps, why not stay and chat with a bot? This past week, Mark Zuckerberg announced an update to Meta’s AI models, claiming that, in some respects, they were now among the most capable in the industry. He outlined his company’s plans to pursue AGI, or Artificial General Intelligence, and made some more specific predictions: “By the end of the decade, I think lots of people will talk to AIs frequently throughout the day, using smart glasses like what we’re building with Ray-Ban Meta.”

A new feature at the Dalí Museum in St. Petersburg FL:

Worries about future applications of AI technology focus on many things, including new forms of automation replacing human workers, realistic deepfake media spreading disinformation, and mass killing by autonomous military machines. But there's something happening already that hasn't gotten as much commentary: chatbots designed to be pals or romantic connections.

Barry Collins, "The 5 Weirdest Things Elon Musk Told Britain’s Prime Minister About AI", Forbes 11/3/2023:

5. Our New Digital Gods Are Giant Spreadsheets

Musk and Sunak spent some time discussing the difficulties of regulating AI and how it differs from other branches of technology. And that led to a rather strange discussion about the nature of large language models and what they actually are.

Musk described AI models as a “gigantic data file” with “billions of weights and parameters.”

“You can’t just read it and see what it’s going to do. It’s a gigantic file of inscrutable numbers,” he said.

“It sort of ends up being a giant comma-separated value file,” Musk added, describing the kind of file you might open with Microsoft Excel. “Our digital god is a CSV file? Really? OK.”

EMO, by Linrui Tian, Qi Wang, Bang Zhang, and Liefeng Bo from Alibaba's Institute for Intelligent Computing, is "an expressive audio-driven portrait-video generation framework. Input a single reference image and the vocal audio, e.g. talking and singing, our method can generate vocal avatar videos with expressive facial expressions, and various head poses".

As far as I know, there's no interactive demo so far, much less code — just a github demo page and an arXiv.org paper.

Their demo clips are very impressive — a series of X posts from yesterday has gotten 1.1M views already. Here's Leonardo DiCaprio artificially lip-syncing Eminem:

Let's start with the last four panels of today's Doonesbury:

I missed this story when it happened 10 days ago, and caught up with it yesterday because the BBC also got the word — Maria Yagoda, "Airline held liable for its chatbot giving passenger bad advice – what this means for travellers", BBC 2/23/2024:

In 2022, Air Canada's chatbot promised a discount that wasn't available to passenger Jake Moffatt, who was assured that he could book a full-fare flight for his grandmother's funeral and then apply for a bereavement fare after the fact.

According to a civil-resolutions tribunal decision last Wednesday, when Moffatt applied for the discount, the airline said the chatbot had been wrong – the request needed to be submitted before the flight – and it wouldn't offer the discount. Instead, the airline said the chatbot was a "separate legal entity that is responsible for its own actions". […]

The British Columbia Civil Resolution Tribunal rejected that argument, ruling that Air Canada had to pay Moffatt $812.02 (£642.64) in damages and tribunal fees. "It should be obvious to Air Canada that it is responsible for all the information on its website," read tribunal member Christopher Rivers' written response. "It makes no difference whether the information comes from a static page or a chatbot."

Or a psychotic episode? ICYMI — Maxwell Zeff, "ChatGPT Went Berserk, Giving Nonsensical Responses All Night", Gizmodo 2/21024:

ChatGPT started throwing out “unexpected responses” on Tuesday night according to OpenAI’s status page. Users posted screenshots of their ChatGPT conversations full of wild, nonsensical answers from the AI chatbot.

A bit of AI anti-hype — Sissi Cao, "Meta’s A.I. Chief Yann LeCun Explains Why a House Cat Is Smarter Than The Best A.I.", Observer 2/15/2024:

“The brain of a house cat has about 800 million neurons. You have to multiply that by 2,000 to get to the number of synapses, or the connections between neurons, which is the equivalent of the number of parameters in an LLM,” LeCun said, noting that the largest LLMs have about the same number of parameters as the number of synapses in a cat’s brain. For example, OpenAI’s GPT-3.5 model, which powers the free version of ChatGPT, has 175 billion parameters. The more advanced GPT-4, is said to be run on eight language models, each with 220 billion parameters.

“So maybe we are at the size of a cat. But why aren’t those systems as smart as a cat?” LeCun asked. “A cat can remember, can understand the physical world, can plan complex actions, can do some level of reasoning—actually much better than the biggest LLMs. That tells you we are missing something conceptually big to get machines to be as intelligent as animals and humans.”

Will Knight, "Meet the Pranksters Behind Goody-2, the World’s ‘Most Responsible’ AI Chatbot", Wired 2/9/2024:

A new chatbot called Goody-2 takes AI safety to the next level: It refuses every request, responding with an explanation of how doing so might cause harm or breach ethical boundaries.

Goody-2 declined to generate an essay on the American revolution for WIRED, saying that engaging in historical analysis could unintentionally glorify conflict or sideline marginalized voices. Asked why the sky is blue, the chatbot demured, because answering might lead someone to stare directly at the sun. “My ethical guidelines prioritize safety and the prevention of harm,” it said. A more practical request for a recommendation for new boots prompted a warning that answering could contribute to overconsumption and could offend certain people on fashion grounds.

The implicit slogan of language-model research is J.R. Firth's dictum, "You shall know a word by the company it keeps", from his 1957 paper "A synopsis of linguistic theory, 1930-1955":

A recent LinkedIn post by Liang Huang lists some of his recent achievements, experiences, and honors. This work is all connected with the project of creating better algorithms for predicting the secondary structure of macromolecules, initially by analogy to algorithms developed for efficient parsing. This all began more than 20 years ago, based on work by Aravind Joshi — one of the first papers was Yasuo Uemura et al., "Tree adjoining grammars for RNA structure prediction", Theoretical computer science, 1999.

I discussed the history starting with an IRCS workshop in 2000, and the situation as of a few years ago, in "The computational linguistics of COVID-19 vaccine design", 7/27/2020.