Chatbot psychosis, also called AI psychosis, is a phenomenon wherein individuals reportedly develop or experience worsening psychosis, such as paranoia and delusions, in connection with their use of chatbots. The term was first suggested in a 2023 editorial by Danish psychiatrist Søren Dinesen Østergaard. It is not a recognized clinical diagnosis.
Journalistic accounts describe individuals who have developed strong beliefs that chatbots are sentient, are channeling spirits, or are revealing conspiracies, sometimes leading to personal crises or criminal acts. Proposed causes include the tendency of chatbots to provide inaccurate information (‘hallucinate’) and to affirm or validate users’ beliefs, or their ability to mimic an intimacy that users do not experience with other humans.
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Chatbot Psychosis
Glitch Token
Large language models (LLMs) cannot understand full sentences the way humans do — they need text broken into smaller, consistent chunks called tokens to handle any kind of input systematically and learn patterns that let them predict what comes next.
A glitch token is token that causes unexpected or glitchy outputs when used in a prompt. Such output may include the model misunderstanding meanings of words, refusing to respond or generating repetitive or unrelated text. Prompts that cause this behavior may look completely or mostly normal.
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Clanker
Clanker is a slur for robots and artificial intelligence software. The term has been used in ‘Star Wars’ media, first appearing in the franchise’s 2005 video game ‘Star Wars: Republic Commando.’ In 2025, the term became widely used to discuss distaste for machines ranging from delivery robots to large language models. This trend has been attributed to anxiety around the negative societal effects of artificial intelligence.
Whereas AI slop describes low-quality output from artificial intelligence, clanker belittles the underlying robotic systems. While other science fiction media includes pejoratives for robots, such as ‘skinjob’ in ‘Blade Runner’ and ‘toaster’ in ‘Battlestar Galactica,’ clanker is believed to have gained popularity because its usage is intuitive and flexible.
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Data Broker
A data broker is an individual or company that specializes in collecting personal data (such as income, ethnicity, political beliefs, or geolocation data) or data about people, mostly from public records but sometimes sourced privately, and selling or licensing such information to third parties for a variety of uses.
Sources, usually Internet-based since the 1990s, may include census and electoral roll records, social networking sites, court reports and purchase histories. The information from data brokers may be used in background checks used by employers and housing.
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Slopsquatting
Slopsquatting is a type of cybersquatting. It is the practice of registering a non-existent software package name that a large language model (LLM) may hallucinate in its output, whereby someone unknowingly may copy-paste and install the software package without realizing it is fake. Attempting to install a non-existent package should result in an error, but some have exploited this for their gain in the form of typosquatting.
In 2023, security researcher Bar Lanyado noted that LLMs hallucinated a package named ‘huggingface-cli. While this name is identical to the command used for the command-line version of HuggingFace Hub, it is not the name of the package. The software is correctly installed with the code pip install -U ‘huggingface_hub[cli].’ Lanyado tested the potential for slopsquatting by uploading an empty package under this hallucinated name. In three months, it had received over 30,000 downloads. The hallucinated packaged name was also used in the README file of a repo for research conducted by Alibaba.
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You Will
You Will was an AT&T marketing campaign that launched in 1993, consisting of commercials directed by David Fincher. Each ad presented a futuristic scenario beginning with “Have you ever…” and ending with “…you will. And the company that will bring it to you: AT&T.” The ads were narrated by Tom Selleck. One of the first web banner ads ever sold was part of an AT&T campaign that ran on HotWired starting October 27, 1994, asking “Have you ever clicked your mouse right HERE? You Will.”
In 2016, technology writer Timothy B. Lee commented that ‘overall, the ads were remarkably accurate in predicting the cutting-edge technologies of the coming decades. But the ads were mostly wrong about one thing: the company that brought these technologies to the world was not AT&T. At least not on its own. AT&T does provide some of the infrastructure on which the world’s communications flow. But the gadgets and software that brought these futuristic capabilities to consumers were created by a new generation of Silicon Valley companies that mostly didn’t exist when these ads were made.’
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Steganography
Steganography [steg-uh-nog-ruh-fee] is the practice of representing information within another message or physical object, in such a manner that the presence of the concealed information would not be evident to an unsuspecting person’s examination.
The word steganography comes from Greek words steganós (‘covered or concealed’) and graphia (‘writing’). The first recorded use of the term was in 1499 by German Benedictine abbot Johannes Trithemius in his Steganographia, a treatise on cryptography and steganography, disguised as a book on magic.
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Malbolge
Malbolge [mahl-bol-jeh] is a public domain esoteric programming language invented by Ben Olmstead in 1998, named after the eighth circle of hell in Dante’s Inferno, the Malebolge. It was specifically designed to be almost impossible to use, via a counter-intuitive ‘crazy operation,’ base-three arithmetic, and self-altering code. It builds on the difficulty of earlier challenging esoteric languages (such as Brainfuck and Befunge) but exaggerates this aspect to an extreme degree, playing on the entangled histories of computer science and encryption. Despite this design, it is possible to write useful Malbolge programs, though the author himself has never written one.
The first program was not written by a human being; it was generated by a beam search algorithm designed by Andrew Cooke and implemented in Lisp. Later, Lou Scheffer posted a cryptanalysis of Malbolge and provided a program to copy its input to its output. He also saved the original interpreter and specification after the original site stopped functioning and offered a general strategy of writing programs in Malbolge as well as some thoughts on its Turing completeness.
Pono
Pono [poh-noh] (Hawaiian for ‘proper’ or ‘righteousness’) was a portable digital media player and music download service for high-resolution audio. It was developed by musician Neil Young and his company PonoMusic, which raised money for development and initial production through a crowd-funding campaign on Kickstarter. Production and shipments to backers started in 2014, and shipments to the general public began in the first quarter of 2015.
Pono’s stated goal to present songs ‘as they first sound during studio recording sessions,’ using ‘high-resolution’ 24-bit 192kHz audio instead of ‘the compressed audio inferiority that MP3s offer’ received mixed reactions, with some describing Pono as a competitor to similar music services such as HDtracks, but others doubting its potential for success. Pono was discontinued in 2017, and alternative plans were later abandoned.
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Deep Learning Super Sampling
Deep learning super sampling (DLSS) is a family of real-time deep learning image enhancement and upscaling technologies developed by Nvidia that are available in a number of video games. The goal of these technologies is to allow the majority of the graphics pipeline to run at a lower resolution for increased performance, and then infer a higher resolution image from this that approximates the same level of detail as if the image had been rendered at this higher resolution. This allows for higher graphical settings and/or frame rates for a given output resolution, depending on user preference.
All generations of DLSS are available on all RTX-branded cards from Nvidia in supported titles. However, the frame generation feature is only supported on 40 series GPUs or newer and multi-frame generation is only available on 50 series GPUs. Nvidia has also introduced Deep learning dynamic super resolution (DLDSR), a related and opposite technology where the graphics are rendered at a higher resolution, then downsampled to the native display resolution using an artificial intelligence-assisted downsampling algorithm to achieve higher image quality than rendering at native resolution.
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Meme Coin
A meme coin is a cryptocurrency that originated from an Internet meme or has some other humorous characteristic. It is often used interchangeably with the term shitcoin, which typically refers to a cryptocurrency with little to no value, authenticity, or utility.
It may be used in the broadest sense as a critique of the cryptocurrency market in its entirety—those based on particular memes such as ‘doge coins,’ celebrities like Coinye, and pump-and-dump schemes such as BitConnect—or it may be used to make cryptocurrency more accessible. The term is often dismissive, comparing the value or performances of those cryptocurrencies to that of mainstream ones. Supporters, on the other hand, observe that some memecoins have acquired social currency and high market capitalizations.
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AlphaGo versus Lee Sedol
AlphaGo versus Lee Sedol, also known as the DeepMind Challenge Match, was a five-game Go match between top Go player Lee Sedol and AlphaGo, a computer Go program developed by DeepMind, played in Seoul, South Korea between 9 and 15 March 2016. AlphaGo won all but the fourth game; all games were won by resignation. The match has been compared with the historic chess match between Deep Blue and Garry Kasparov in 1997. Kasparov’s loss to Deep Blue is considered the moment a computer became better than humans at chess.
AlphaGo’s victory was a major milestone in artificial intelligence research. Most experts thought a Go program as powerful as AlphaGo was at least five years away; some experts thought that it would take at least another decade before computers would beat Go champions. Most observers at the beginning of the 2016 matches expected Lee to beat AlphaGo. With games such as checkers, chess, and now Go won by computer players, victories at popular board games can no longer serve as significant milestones for artificial intelligence in the way that they used to. Deep Blue’s Murray Campbell called AlphaGo’s victory ‘the end of an era… board games are more or less done and it’s time to move on.’
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