Reed MidekeBonus #AIIsGoingGreat "Your phone now needs more than 8 GB of RAM to run autocomplete" (and presumably, battery cost somewhat on a par with heavy GPU rendering) https://arstechnica.com/gadgets/2024/03/google-says-the-pixel-8-will-get-its-new-ai-model-but-ram-usage-is-a-concern/
Today's #AIIsGoingGreat (HT @pluralistic https://mastodon.social/@pluralistic@mamot.fr/112196496077034192)
Tired: Typo squatting
Wired: Hallucination squatting
https://www.theregister.com/2024/03/28/ai_bots_hallucinate_software_packages/
Seems like you could put your thumb on scale for which (non existent) libraries show up with #LLM training set poisoning attacks (previously https://mastodon.social/@reedmideke/110850376856613599)
Set up a site that, when it detects known AI scrapers, serves up code or documentation that references a non-existent library, along text associating with whatever kind of code and industry you want to target
OTOH, this would leave much more of trail than just observing bogus ones that show up naturally
In which the gang discovers Amazon Fresh "Just walk out" checkout was powered by Type II #AI https://gizmodo.com/amazon-reportedly-ditches-just-walk-out-grocery-stores-1851381116
"If you think about the major journeys within a [fast food] restaurant that can be AI-powered, we believe it’s endless"
Sir this a fucking Wendy's and people come here to buy a fucking burger, not "take major journeys" https://arstechnica.com/information-technology/2024/04/ai-hype-invades-taco-bell-and-pizza-hut/
Also uh, can't imagine anything that could possibly go wrong with this: "This enhancement would allow team members to ask the [AI chatbot] app questions like "How should I set this oven temperature?" directly instead of asking a human being"
Some scientists theorized that after over 30 years of continuous development, it was physically impossible to make Adobe Reader worse, but once again, Adobe engineers have found a way
I actually kinda wanted to see it summarize the spurious scholar (https://tylervigen.com/spurious-scholar) paper I was reading when it popped up, but… not enough to log in
Today's #AIIsGoingGreat brought to you by #Ivanti: 'Among the details is the company's promise to improve search abilities in Ivanti's security resources and documentation portal, "powered by AI," and an "Interactive Voice Response system" … also "AI-powered"'
Ah yes, hard to think of any better way to fix a pattern of catastrophic security failures than *checks notes* filtering highly technical, security critical information through a hyper-confident BS machine
Today's #AIIsGoingGreat brought to you by the artist formerly known as Twitter https://mashable.com/article/elon-musk-x-twitter-ai-chatbot-grok-fake-news-trending-explore
Here's a helpful #AI chatbot to assist you with thing that requires domain specific knowledge and has significant real-world consequences for errors… oh, by the way, you'll need to already have that same domain specific knowledge to confirm whether the answers are correct or complete BS
Who thinks this is a good idea?🤔
Texas Education Agency talks a lot about the supposed safeguards in the don't-call-it-#AI "automated scoring engine" but no mention of any testing to determine whether it is fit for purpose (they do mention training it on 3K manually scored questions). Maybe they did and it just didn't get mentioned, but seems like a very good #FOIA target
https://www.texastribune.org/2024/04/09/staar-artificial-intelligence-computer-grading-texas/
https://www.texastribune.org/2024/04/09/staar-artificial-intelligence-computer-grading-texas/
OpenAI argues that “factual accuracy in large language models remains an area of active research”
…in the sense that Bigfoot and Nessie remain areas of active research?
https://noyb.eu/en/chatgpt-provides-false-information-about-people-and-openai-cant-correct-it
A+ BLUF from @benjedwards: "Air-gapping GPT-4 model on secure network won't prevent it from potentially making things up"
https://arstechnica.com/information-technology/2024/05/microsoft-launches-ai-chatbot-for-spies/
Oh hey, remember #AdVon, the definitely-not-an-ai-company caught publishing #AI dreck in Sports Illustrated? (previously https://mastodon.social/@reedmideke/111486230567895424)
Futurism has another update, and it's a doozy
https://futurism.com/advon-ai-content
Futurism has another update, and it's a doozy
https://futurism.com/advon-ai-content
Google+ comparison is very apt, but also that opening example really hits the problem I've been yelling about since the #LLM hype cycle started: The fundamental mismatch between a system that randomly makes shit up and the uses it's being hyped for https://www.computerworld.com/article/2117752/google-gemini-ai.html
This, right here: "Erm, right. So you can rely on these systems for information - but then you need to go search somewhere else and see if they’re making something up? In that case, wouldn’t it be faster and more effective to, I don’t know, simply look it up yourself in the first place?"
Google's current #AIIsGoingGreat moment really checks all the bad #AI boxes. Starting with the dismissive "examples we've seen are generally very uncommon queries and aren’t representative of most people’s experiences" - Sure *sometimes* the answers are complete BS and possibly dangerous, but what about the times they aren't? Checkmate, Luddites!
And as always, they insist they are fixing it: "We conducted extensive testing before launching this new experience and will use these isolated examples as we continue to refine our systems overall" - with *zero* indication they have a technical or even theoretical path to solving the general problem that #LLMs don't have any concept of truth
And then, the whole thing is made worse by positioning it as a replacement for search, in the top spot with google branding. The "eat rocks" article ranks high in the regular organic search results the same query, but users have a lot more clues that it was a joke
Why am I so sure #AI companies have no serious technical or theoretical solution to the underlying problem that #LLMs have no concept of truth? The fact their approach so far is manually band-aiding results that go viral or put them in legal jeopardy is a pretty big hint! https://www.theverge.com/2024/5/24/24164119/google-ai-overview-mistakes-search-race-openai
👉 "Gary Marcus, an AI expert and an emeritus professor of neural science at New York University, told The Verge that a lot of AI companies are “selling dreams” that this tech will go from 80 percent correct to 100 percent. Achieving the initial 80 percent is relatively straightforward since it involves approximating a large amount of human data, Marcus said, but the final 20 percent is extremely challenging. In fact, Marcus thinks that last 20 percent might be the hardest thing of all"
What they're doing now seems like selling a calculator, and when a screenshot of it saying 2+2=5 goes viral on social media, they add a statement like "if x=2 and y=2 return 4" at the top of the program and say "see, we fixed it!"
Straight from Google CEO Sundar Pichai's mouth: 'these "hallucinations" are an "inherent feature" of AI large language models (LLM), which is what drives AI Overviews, and this feature "is still an unsolved problem"'
but they're gonna keep band-aiding until it's good, promise! ""Are we making progress? Yes, we are … We have definitely made progress when we look at metrics on factuality year on year. We are all making it better, but it’s not solved""
Just occurred to me Mitchell and Webb predicted our current pizza-gluing, gasoline spaghetti #AIIsGoingGreat moment 16 years ago https://www.youtube.com/watch?v=B_m17HK97M8
Mitchell & Webb: Cheesoid
Today's #AIIsGoingGreat - Meta's chatbot helpfully "confirms" a scammers number is a legitimate facebook support number
(of course, #LLMs just predict likely sequences of text, and for a question like this, "yes" is one of the high probability answers. There's no indication any of the companies hyping LLMs as a source of information have any serious solution for this kind of thing)
https://www.cbc.ca/news/canada/manitoba/facebook-customer-support-scam-1.7219581
Kyle Orland hammers on my off-repeated complaint (https://mastodon.social/@reedmideke/110063208987793683) that filtering your information through an #LLM *removes* useful context: "When Google's AI Overview synthesizes a new summary of the web's top results, on the other hand, all of this personal reliability and relevance context is lost. The Reddit troll gets mixed in with the serious cooking expert"
https://arstechnica.com/ai/2024/06/googles-ai-overviews-misunderstand-why-people-use-google/
On the same note, today's #AIIsGoingGreat courtesy of @ppossej, observing Microsoft copilot helpfully "summarizing" a phishing email. Even leaving aside obvious problem here, what exactly is supposed to be the value having an already short email filtered through spicy autocomplete? https://mastodon.social/@[email protected]ocial/112555512126646188
I initially dismissed today's #AIIsGoingGreat (HT @zhuowei) as a joke, but no* : "aiBIOS leverages an LLM to integrate AI capabilities into Insyde Software’s flagship firmware solution, InsydeH2O® UEFI BIOS. It provides the ability to interpret the PC user’s request, analyze their specific hardware, and parse through the LLM’s extensive knowledge base of BIOS and computer terminology to make the appropriate changes to the BIOS Setup"
* not an intentional one, anyway
https://www.insyde.com/press_news/press-releases/insyde%C2%AE-software-brings-higher-intelligence-pcs-aibios%E2%84%A2-technology-be
* not an intentional one, anyway
https://www.insyde.com/press_news/press-releases/insyde%C2%AE-software-brings-higher-intelligence-pcs-aibios%E2%84%A2-technology-be
Today's #AIIsGoingGreat features Zoom CEO Eric Yuan blazed out of his mind on his own supply: "Today for this session, ideally, I do not need to join. I can send a digital version of myself to join so I can go to the beach. Or I do not need to check my emails; the digital version of myself can read most of the emails. Maybe one or two emails will tell me, “Eric, it’s hard for the digital version to reply. Can you do that?”"
"I truly hate reading email every morning, and ideally, my AI version for myself reads most of the emails. We are not there yet"
OK, points for recognizing we're "not there yet", in roughly the same sense the legend of Icarus foresaw intercontinental jet travel but was "not there yet"
Actually interesting thing in that Eric Yuan interview "every day, I personally spend a lot of time on talking with our customer’s prospects. Guess what? First question they all always ask me now is “What’s your AI strategy? What do you do to embrace AI?…”"
- even if exaggerated, seems like a good indicator of how deeply C-suite types have bought into the hype, which in turn means they all need an "AI strategy" no matter how ludicrous
- even if exaggerated, seems like a good indicator of how deeply C-suite types have bought into the hype, which in turn means they all need an "AI strategy" no matter how ludicrous
and the thing is, in terms of their personal incentives, they're probably not wrong. The analysts and shareholders and trade press want the new shiny thing, and if their current business gets caught on the wrong side of the bubble, they keep whatever bonuses they got in the interim and it probably won't hurt their future career prospects much
Bonus #AIIsGoingGreat from NYT with a deep look at (now defunct) skeevy news out BNN Breaking: "employees were asked to put articles from other news sites into the [#LLM] tool so that it could paraphrase them, and then to manually “validate” the results by checking them for errors… Employees did not want their bylines on stories generated purely by A.I., but Mr. Chahal insisted on this. Soon, the tool randomly assigned their names to stories"
https://www.nytimes.com/2024/06/06/technology/bnn-breaking-ai-generated-news.html?u2g=i&unlocked_article_code=1.x00.zn0r.s2tFDDFWR0fo&smid=url-share
#GiftArticle #GiftLink #BNN
https://www.nytimes.com/2024/06/06/technology/bnn-breaking-ai-generated-news.html?u2g=i&unlocked_article_code=1.x00.zn0r.s2tFDDFWR0fo&smid=url-share
#GiftArticle #GiftLink #BNN
#BNN founder Gurbaksh Chahal seems to be an all-around charming fellow "In 2013, he attacked his girlfriend at the time, and was accused of hitting and kicking her more than 100 times, generating significant media attention because it was recorded by a video camera he had installed in the bedroom … After an arrest involving another domestic violence incident with a different partner in 2016, he served six months in jail"
Some might argue that making the #AI acronym do double duty with "Apple Intelligence" is a recipe for confusion, but after all the hype I find it refreshingly honest to position the product as "about as smart as a piece of fruit"
That "#ChatGPT is bullshit" paper I boosted earlier does a nice job of laying out why the "hallucination" terminology is harmful "what occurs in the case of an #LLM delivering false utterances is not an unusual or deviant form of the process it usually goes through… The very same process occurs when its outputs happen to be true"
https://link.springer.com/article/10.1007/s10676-024-09775-5
ChatGPT is bullshit - Ethics and Information Technology
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
The authors rightly object to "confabulation" for similar reasons "This term also suggests that there is something exceptional occurring when the LLM makes a false utterance, i.e., that in these occasions - and only these occasions - it “fills in” a gap in memory with something false. This too is misleading. Even when the ChatGPT does give us correct answers, its process is one of predicting the next token"
They are far from the first to make the connection between #LLMs and Frankfurtian bullshit, but humor aside, they do make a compelling case that the terminology matters https://link.springer.com/article/10.1007/s10676-024-09775-5#Sec12
ChatGPT is bullshit - Ethics and Information Technology
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (On Bullshit, Princeton, 2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
"Calling their mistakes ‘hallucinations’ isn’t harmless: it lends itself to the confusion that the machines are in some way misperceiving but are nonetheless trying to convey something that they believe or have perceived. This, as we’ve argued, is the wrong metaphor. The machines are not trying to communicate something they believe or perceive. Their inaccuracy is not due to misperception or hallucination … they are not trying to convey information at all. They are bullshitting"
Medea Vanamonde🏳️⚧️ ♀@reedmideke Racters gonna Racter