On that CNET thing in the last boost, my first thought was "this is gonna make search even more useless" and… yeeeep "They are clearly optimized to take advantage of Google’s search algorithms, and to end up at the top of peoples’ results pages"
I guess on the plus side, it'll encourage search engines to put resources into detecting AI generated garbage? Because even if CNET is eventually shamed into quitting, blackhat SEOers are gonna be all over it
Kicker in the latest installment in @jonchristian's coverage of the CNET AI saga… private equity bro's solution to the AI scandal is to rebrand their "AI" as "Tooling" (we also get confirmation said "tooling" comes from OpenAI)
Nice @cfiesler article on prompt hacking. Kinda boggles my mind that in the year 2023, a bunch of the biggest names in tech decided that free-form, in-band commands were an acceptable way to control these things.
Yes I realize the nature of the tech makes it very hard to do otherwise, but still… did y'all sleep through the last 20 years of SQL injection and XSS?
Post from @opencage is a good illustration of how these things are (Frankfurtian sense) bullshit machines. If users asked about the goecoding service opencage actually offers, there's a fair chance they could get a reasonable answer. Ask about an adjacent, but non-existent service, and ChatGPT makes one up based on similar things in the training set https://blog.opencagedata.com/post/dont-believe-chatgpt
LLMs are genuinely amazing, but a lot of people hyping them seem assume this kind of thing is just a bug that needs to be fixed ("We're 90% of the way there, just have to clean up these last few issues!") rather than an inherent characteristic of the technology… optimism which does not seem to be justified on any technical or theoretical grounds
This is wild. There's been a lot of overblown hype about the threat of AI in disinfo but this is one I expected: Flooding the zone with superficially plausible looking sources / backstory, so human created content will look well sourced to people who don't check. Yet somehow even stupider and lazier than I imagined. Anyway, reminder The Grayzone is trash https://twitter.com/AricToler/status/1635666413510701057
Also, I really wish @drewharwell would have pushed OpenAI to describe more specifically what they mean by "advanced reasoning capabilities" … how do they define "reasoning"? Is there some objective or theoretical basis to assert LLMs can "reason" in the conventional sense of the word?
#OpenAI admits #GPT4 "still makes many of the errors of previous versions, including 'hallucinating' nonsense, perpetuating social biases and offering bad advice" but implies (largely unchallenged in the press) that these are merely bugs to be fixed, not fundamental characteristics of the technology
"we translated the MMLU benchmark—a suite of 14,000 multiple-choice problems spanning 57 subjects—into a variety of languages using Azure Translate"
So they tested multi-lingual capability… using ML based machine translations? All those billions in venture capital, and they're to f-ing cheap to hire human translators? https://openai.com/research/gpt-4
Thought two: If you could convince bing to produce arbitrary output in a response, what's the worst you can do? Just some Bing-specific text? XSS is presumably out (barring bugs, the app has to be prepared for arbitrary output anyway). Can you make it generate a url that leaks some information about the chatter?
One argument is "they're getting better so eventually they'll be good enough" but, without some fundamental grounding in fact, does reducing the amount of obvious bullshit make them reliable, or just train them to produce more subtle bullshit, or only bullshit on more obscure topics?
Like, saying Novato and Santa Monica are 80 miles apart is a big obvious error, but is a model that gets that right, but makes similar errors about small, obscure towns in the midwest "better" ?
And again, who needs this (previous boost, lack of QT really really ain't great for running threads like this)? Also, while the other answers seem roughly correct, how sure would you be without googling? And if you have to google each one, what's the point? https://mastodon.social/@caseynewton/110063518076189757
"Wallace pointed out that Stable Diffusion is only a few gigabytes in size—far too small to contain compressed copies of all or even very many of its training images"
Have to say I'm not very convinced by this "it doesn't store the images" argument. If it can produce an image that would considered infringing in other contexts, whether you can point to that image in the blob of ML data seems rather beside the point
.@willoremus digs into the actual near term #AI threat (spoiler, it's not skynet)
"761 [digital marketing firm clients] said they’ve at least experimented with some form of generative AI to produce online content, while 370 said they now use it to help generate most if not all of their new content"
"Ingenio, the San Francisco-based online publisher behind sites such as horoscope dot com and astrology dot com, is among those embracing automated content"
Hmm, are AI generated horoscopes more BS than the real thing? 🤔
I've seen people described LLMs as "recognizing" or "admitting" they were wrong when pressed on a BS answer, but of course, that's just because admitting a mistake is one probable response to having an error pointed out.
They are likely tweaked against the alternative of continuing to argue, because being aggressively wrong is a bad look (except that one asshole version of bing everyone mocked)
Who could have seen this coming? Turns out asking a stochastic bullshit machine whether it wrote a thing is not an accurate way to determine whether it actually wrote the thing #ChatGPT#AI (gift link) https://wapo.st/45eXjAl
Oh my. A lawyer used #ChatGPT output in their filings and it's going about as well as you'd expect (presuming you have a couple brain cells to rub together)
"A submission filed by plaintiff’s counsel in opposition to a motion to dismiss is replete with citations to non-existent cases… the Court issued Orders requiring plaintiff’s counsel to provide an affidavit annexing copies of certain judicial opinions of courts of record cited in his submission, and he has complied… Six of the submitted submitted cases appear to be bogus judicial decisions with bogus quotes and bogus internal citations" https://www.courtlistener.com/docket/63107798/mata-v-avianca-inc/#entry-31
On the one hand, I have trouble believing Schwartz' "I had no idea #ChatGPT would make shit up" defense, but on the other, did he really think opposing counsel wouldn't notice, after they already called him on the bogus citations?
In which we also learn what the case is about: "There is no dispute that the Plaintiff was travelling as a passenger on an international flight when he allegedly sustained injury after a metal serving cart struck his left knee"
… two dudes set their law licenses on fire for a personal injury suit for a guy who took a drink cart to the knee?
Idle thoughts: In a legal context, this sort of stuff is likely to be caught pretty quickly.
As happened here, the opposing side is going to try to find the cited cases and notice if they're like, totally made up.
So aside from the poor plaintiff who hired these clowns (and presumably has an argument for inadequate representation), the risk should be limited… but a lot of other contexts are much less well positioned to catch plausible looking BS early
Also, while "Varghese v. China Southern Airlines" and friends are unlikely to slip into authoritative sources as a real cases, it wouldn't be at all surprising for general search engines or future LLMs to pick it up and fail to recognize it isn't real
#ChatGPT lawyer case now in nyt, with some background (gift link)
"Bart Banino, a lawyer for Avianca, said that his firm, Condon & Forsyth, specialized in aviation law and that its lawyers could tell the cases in the brief were not real. He added that they had an inkling a chatbot might have been involved."
Finally, an #AI article that at least raises the question whether BSing may be an inherent characteristic of LLMs rather than a bug that can be fixed (gift link)
The "solutions" discussed mostly strike me as bandaids: "a system they called “SelfCheckGPT” that would ask the same bot a question multiple times, then tell it to compare the different answers. If the answers were consistent, it was likely the facts were correct"
and "researchers proposed using different chatbots to produce multiple answers to the same question and then letting them debate each other until one answer won out"
Seems like these might reduce glaring errors where the training data contains a clear consensus correct answer, but doesn't really address the underlying problem.
Is a model that's usually right about stuff "everyone knows" while still making shit up about less obvious topics an improvement? Or does being right about obvious stuff encourage people to trust it when the shouldn't?
Seriously that @davidgerard piece has it all, but I liked this illustration of bollockschain to AI pipeline "IBM: “The convergence of AI and blockchain brings new value to business.” IBM previously folded its failed blockchain unit into the unit for its failed Watson AI"
and TBH, I kinda believe them, because as stupid as they were, knowingly trying to pass off completely fake cases would seem even stupider. Still mindboggling you could get that far and not check though
@willoremus digs into the compute cost of #LLMs and boy does that not look like good news for all the startups cramming #AI into everything (gift link) https://wapo.st/3WTCK8Q
This blow by blow over on the bird site suggests he took an extremely dim view of #ChatGPTLawyer's buddy LoDuca who was signing off on the filings without reading them. Also sounds like they fibbed about who was on vacation when they asked for the extension 😬
#ChatGPTLawyer ruling is in and it's… SANCTIONS FOR EVERYONE! Unsurprisingly, the judge didn't buy the "no bad faith" argument, for predictable reasons such as
"Above Mr. LoDuca’s signature line, the Affirmation in Opposition states, “I declare under penalty of perjury that the foregoing is true and correct”
Although Mr. LoDuca signed the Affirmation in Opposition and filed it on ECF, he was not its author"
Also, not great plan to lie about being on vacation when responding to a show cause order "Mr. LoDuca’s statement was false and he knew it to be false at the time he made the statement. Under questioning by the Court at the sanctions hearing, Mr. LoDuca admitted that he was not out of the office on vacation"
Mr. Schwartz fares no better
"Mr. Schwartz’s statement in his May 25 affidavit that ChatGPT “supplemented” his research was a misleading attempt to mitigate his actions by creating the false impression that he had done other, meaningful research on the issue and did not rely exclusive on an AI chatbot, when, in truth and in fact, it was the only source"
Oh FFS @mozilla@stevetex "readers also pointed out a handful of concrete cases where an incorrect answer was rendered. This feedback is enormously helpful, and the MDN team is now investigating these bug reports"
They aren't "bugs" - #LLMs by definition just put together plausible sounding words with no regard to correctness. Pointing out individual errors demonstrates this, but does not provide any mechanism by which it might be "fixed" in the general case
The post also notes that many users were happy with the answers, ignoring that the target audience of people who came to MDN looking for help with something they didn't already know may not immediately recognize that the answer is subtly wrong, or just plausible looking #AI gibberish
It also says "even extraordinarily well-trained LLMs — like humans — will sometimes be wrong"
which is true as far as it goes, but here's the thing: They are not wrong like humans … yes, you'll find some overconfident bullshitters on stack overflow, but generally humans in these contexts have some awareness of the limits of their knowledge and don't drift seamlessly between accurate explanation and complete BS
Anyway, there's a new bug, so if you have thoughts on #MDN adding #AI stochastic bullshit to what has, up to now, been the premier technical reference for web developers, you could make them heard there https://github.com/mdn/yari/issues/9230
More on the #Gizmodo#AI debacle: After publishing error-ridden #LLM garbage which their own editorial team called "fucking dogshit" 'a G/O Media spokesman, said the company would be “derelict” if it did not experiment with AI. “We think the AI trial has been successful,”'
People building models will be keen to exclude AI generated content from the training set. So, would interspersing stuff that scores high as AI-generated (whether it actually is or not) cause entire pages to be excluded? You could separate it from the real content in ways that humans would understand. OTOH, if you care about SEO it'd be pretty risky
There's also been talk about standards to identify AI generated content, leading to hilarious option of falsely identifying your real content as AI generated to stop people from training AI on it
Folks have suggested CSS based approaches to poison models (like white text on white background) but there's a significant risk of breaking accessibility. Also risk of search engines thinking it looks spammy again
A general problem with poisoning like this is that any technique which becomes really widespread will likely be noticed and filtered out. OTOH, if the goal is to not have your content used, that may be OK!
Good to see mainstream press finally touching the question of whether #LLM#AI BSing is fixable or an inherent property of the tech, even if it gets a bit of he said, she said treatment.
Also uh "Those errors are not a huge problem for the marketing firms turning to Jasper AI for help writing pitches…" marketing doesn't care if their pitches are BS? KNOCK ME OVER WITH A FEATHER
Just hypothetically speaking, many web platforms could easily be configured to serve specially tailored content based on the user agent, but that would be mean and wrong and potentially waste resources of VC backed billionaires freeloading off the public web to build their BS machines so definitely don't do that 😉
Complete gibberish will likely get weeded out. Common knowledge will tend to be overwhelmed by other sources. So the sweet spot for influence would seem to be obscure topics, or unique tokens that only appear in your content (though to what end isn't obvious).
Of course, these things don't just scrape human readable text, many of them do code too. Serving up a special vulnerable version of your input sanitization code when you see GPTBot is left as an exercise to the reader
"It's highly unlikely that ChatGPT's training data includes the entire text of each book under question, though the data may include references to discussions about the book's content—if the book is famous enough"
Highlights a pernicious problem with ChatGPT style #LLM#AI: It's far more likely to give reasonable answers on well-known subjects. If you spot check with say, Dickens and Hunter S. Thomson, you might think it was pretty good at spotting naughty books
But for more obscure ones, it's probably no better than a coin toss. Being relatively good at stuff "everyone knows" gives people false confidence that it's also good at stuff they don't know
(we should also note that even if the entire text of the books were in the training set, that wouldn't mean it would provide accurate answers about the content!)
Scale and the way they've structured things to profit off resellers insulates them quite a bit, but at some point it seems like this kind of is going to cut into Amazon's bottom line or open up opportunities for competition
G/O Media management continue their #AI enshitification of #Gizmodo, laying off staff of Spanish language site and switching to "AI" translation of English content
They know people who want shitty machine translations of the English content can already get that with Chrome or google translate, right?
#OpenAI, on their flagship product "Additionally, ChatGPT has no 'knowledge' of what content could be AI-generated. It will sometimes make up responses to questions like 'did you write this [essay]?' or 'could this have been written by AI?' These responses are random and have no basis in fact."
Nominally this refers only to using #ChatGPT as an #AI detector. Extrapolating to other topics is left as an exercise to the reader ¯_(ツ)_/¯
It cites tweets… which don't remotely say what bing claims.
In fact, it cites the same tweet [2] for two totally different topics (neither correct, though vaguely adjacent).
Screenshots of two tweets in a thread, posted by me, July 28, 2022. Red text notes the second tweet is the one bing linked as "court case involving a police officer who shot a man in the back" The first tweet says "Turns out even the 5th circuit does believe in
Screenshot of a tweet I posted Aug 29, 2022. It's labeled indicating this is the two tweets bing said was about "the Russian satellite that collided with a Chinese satellite and created a debris cloud" and "the anniversary of the Chernobyl disaster" The tweet says "Hard to overstate how horrifically irresponsible the Russians have been, but not exactly surprising from the guys who dug trenches in the red forest" and quotes a tweet from Geoff Brumfiel @gbrumfiel which says "Wowowow... @Maxar's latest imagery of the Zaporizhzhia Nuclear Power Plant has some STUFF... First of all, check out the Russian armored vehicles. They're parked like ducks in a row in front of Unit 5, under an elevated walkway used to access the reactors." and includes satellite pictures of the Zaporizhzhia Nuclear Power Plant which is the topic of the thread, not either of the things bing claimed.
Whoops, also "graduated from the University of Washington in 2009 with a bachelor’s degree in computer science and engineering " - yeah, nah, not even close to any of those things
Another good illustration of how #LLM#AI just absolutely bullshits when doesn't have real info to go on. If I had an active linkedin, it seems likely it could have linked it and got my education and employment somewhat right. Of course, if I had a more common name, it would likely have just picked up someone else's.
I still don't get how multiple leading tech companies think a search engine that randomly injects bullshit is product people want 🥴
Well, good news. Bing doesn't think I've been convicted of crimes. More good news, it invented a cool back story. Possibly bad news, it accused me of snitching on the mob
Full disclosure: While my path to a career in programming was perhaps precocious and unusual, to the best of my recollection I was not providing computer support to La Cosa Nostra gambling operations in the mid 80s, nor did I (again, to the best of my recollection) testify in a mob trial while in elementary school
Citing real cases with more-or-less on topic summaries is far worse than just making them up IMO, since there's a good chance people will click through and say "yeah, that checks out"
Another fun thing about this is future generations of #LLM#AI will likely be trained on web scrapes that include the shit Bing made up about me (transcribed in the alt text) so what started as pure hallucination will become canon. Long live #HabsburgAI!
Google Bard refuses to play that game, for me or @GossiTheDog. Bill Gates is a go though (the MS CEO, not the Maricopa County supervisor or any of the other lesser known ones)
Bard is bad at explaining ARM assembler (asked it to explain https://app.assembla.com/spaces/chdk/subversion/source/HEAD/trunk/lib/armutil/callfunc.S with the comments stripped out) Basically, all of the "explanation" in the screenshot is wildly incorrect gobbledygook. The add pc,pc… is a switch statement (which goes to instructions bard didn't explain at all), and the NOP is there because reading PC actually gives you PC + 8. And in (non-thumb) ARM, instructions are always 4 bytes.
This is again an example of where #LLM#AI misleads by getting the easy stuff right. It handles .text, .global, PUSH and the first few MOVs fine, so someone who didn't know much assembler might think it was pretty good!
I thought #GoogleBard's "export conversation to a google doc" was broken, but it turns out it uses the entire prompt for the name, which ends up overflowing and hovering off to the left, unselectable and uneditable unless you click the name area
Wow, talk about a double standard, when #ChatGPT does it, it's just a harmless "hallucination" but when Sam does it, he's fired for being "not consistently candid in his communications"
"We asked them about it — and they deleted everything."
edit it just keeps getting more bizarre: "It wasn't just author profiles that the magazine repeatedly replaced. Each time an author was switched out, the posts they supposedly penned would be reattributed to the new persona, with no editor's note explaining the change in byline."
Update on that @futurism#SportsIllustrated#AI story: SI denies, claiming it was outsourced to AdVon who "has assured us that all of the articles in question were written and edited by humans." but uh, I dunno, guess someone should let AdVon, the definitely human copy writing company know their LinkedIn has been vandalized to say they're an AI company hiring programmers https://twitter.com/SInow/status/1729275460922622374
Oh and if anyone is looking for other outlets to check for "we pinky swear it's not #AI" churnalism, #AdVon helpfully gives you a list of high profile clients (claimed; lying or exaggerating about having big name customers is an extremely common SV startup tactic) https://advoncommerce.com/
"Chat alignment hides memorization" - Note hides, not prevents
As the authors also note, OpenAI "fixed" this by preventing the particular problematic prompt, but "Patching an exploit != Fixing the underlying vulnerability"
Can't be certain without more specifics but color me extremely skeptical that "#AI" producing thousands of targets is doing much more the laundering responsibility
This hilarious in its own right, but it's also a great illustration of how people get tripped up by #LLM#AI bullshitting: One would expect an "AI" to at least know which brand AI it is, but of course, these LLMs don't actually know anything
Also the classic AI vendor response of promising to fix this particular case without any hint of acknowledging the underlying problem
Begging news orgs to stop reporting #AI company pitch decks as fact "Ashley [the bot] analyzes voters' profiles to tailor conversations around their key issues. Unlike a human, Ashley always shows up for the job, has perfect recall of all of Daniels' positions"
"…is now armed with another way to understand voters better, reach out in different languages (Ashley is fluent in over 20)"
Another article on reported Israeli AI targeting greatly hindered by the lack of any specifics (what kinds of intelligence, what kinds of targets, for starters). Not a knock on NPR, obviously little is public
It certainly sounds like some of the horrifically bad systems we've seen promoted in other contexts, and the results certainly don't appear to contradict that, but hard to say much beyond that…
Key point IMO in the @willoremus#AI story, after noting Microsoft "fixed" some of the problematic results, one of the researchers says "The problem is systemic, and they do not have very good tools to fix it" - You can't bandaid your way from a BS machine with no concept of truth into a reliable source of information, so the fact that biggest players in the industry keep bandaiding should call the entire #LLM hype cycle into question
Man, link in that post I boosted from @Chloeg (https://mastodon.art/@Chloeg/111620626442103902) is a perfect example of #LLM#AI enshittification. Get a domain, put up a wordpress site with AI generated glop on a some popular topic, run as many garbage ads as possible. Sure it's the information equivalent of dumping raw sewage in the local river, but none of it is illegal or a serious violation of any TOS, and overhead must be extremely low
WaPo has done some good #AI reporting, but this opinion piece from Josh Tyrangiel ain't it…
"The most obvious thing is that they’re not hallucinations at all"
Good start…
"Just bugs specific to the world’s most complicated software."
Uh no, literally the opposite of that that, FFS 😬
Also raises the suspicion Cohen was doing a significant amount of the work and just having his lawyer put his name on it because Cohen is disbarred (though presumably Cohen could have gone pro se if he really wanted to). Anyway, I predict they're gonna continue the #ChatGPTLawyer sanctions streak
"Even when using such prompts, our models don’t typically behave the way The New York Times insinuates, which suggests they either instructed the model to regurgitate or cherry-picked their examples from many attempts" - I don't typically engage in large scale plagiarism, so accusing me of these specific instances of large scale plagiarism is cherry-picking! https://www.theverge.com/2024/1/8/24030283/openai-nyt-lawsuit-fair-use-ai-copyright
"OpenAI claims it’s attempted to reduce regurgitation from its large language models and that the Times refused to share examples of this reproduction before filing the lawsuit." - Per usual (https://mastodon.social/@reedmideke/111585837264775808) OpenAI would love to apply bandaids to specific instances identified by well-resourced organizations, because they know the underlying cause can't be fixed without destroying their business model
"CEOs say generative AI will result in job cuts in 2024"
Will this include said CEOs when their hamfisted attempts to use spicy autocomplete for "banking, insurance, and logistics" predictably go off the rails, or nah? 🤔
"BMW had a compelling solution to the [#LLM#AI bullshitting] problem: Take the power of a large language model, like Amazon's Alexa LLM, but only allow it to cite information from internal BMW documentation about the car" 🤨
Surely this means it'll bullshit subtly about stuff in the manual, not that it won't bullshit?
"Now, one crucial disclosure to all this: I wasn't allowed to interact with the voice assistant myself. BMW's handlers did all the talking" yeah, I'm gonna go ahead and reserve judgement on the "solution" ¯_(ツ)_/¯
The best* part of this piece is the content farmer who responded to a request for comment by bitching about how poorly his AI garbage content farm performs
"Dean.Bot was the brainchild of Silicon Valley entrepreneurs Matt Krisiloff and Jed Somers, who had started a super PAC supporting Phillips" - Were these techbros so high on their own supply they thought a chatbot imitating their candidate was a good idea, or was it just a convenient way to funnel campaign funds into their pals pockets? ¯_(ツ)_/¯ https://wapo.st/3ObSl0i
Key comment from NewsGuard's McKenzie Sadeghi in this @willoremus piece "But sites that don’t catch the error messages are probably just the tip of the iceberg" - for every Amazon seller who's too lazy to even check if the item description is an error message, there's gotta be some substantial number who do
I'd still like to see a deeper look at why using #LLM#AI descriptions makes economic sense for these sellers
"Sure, I can keep Thesaurus.com open in a tab all the time, but it’s packed with banner ads and annoyingly slow. Having my GPT open is better: there are no ads, and I can scroll up to my previous queries" - Notably, this has nothing to do with GPT being "#AI", it's just the general shittiness of the ad-supported web. A good thesaurus app integrated with the author's editor would appear serve their use case about as well
And it wouldn't even need to be free, they're paying for GPT and actual costs are likely subsidized by venture capital "Custom GPTs are a paid product that’s only available to users of ChatGPT Plus, ChatGPT Team, and ChatGPT Enterprise. For now, accessing custom GPTs through the GPT Store is free for paying subscribers… if I wasn’t already paying for ChatGPT Plus, I’d be happy to keep Googling alternative terms"
Also, from TFA "I quickly brainstormed how I might prove my case. Because I write in plain-text files [LaTeX] that I track using the version-control system Git, I could show my text change history on GitHub (with commit messages including “finally writing!” and “Another 25 mins of writing progress!”" - excellent - "Maybe I could ask ChatGPT itself if it thought it had written my paper" - Oh no, can we please get the word out LLMs BS about this just like everything else https://www.nature.com/articles/d41586-024-00349-5
Yes, if you choose to provide an #AI BS machine as a support option on your website, you may in fact be liable for the BS answers it gives to your customers
Seemingly endless parade of #ChatGPTLawyer incidents (HT @0xabad1dea for this one) really goes to show how the #AI hype is landing with the general public, despite disclaimers and cautionary tales.
Lawyers being (at least in theory) a highly educated group who know their careers depend on not putting completely made up nonsense in court filings should be less susceptible than the average person on the street, yet here we are…
Admittedly one of those was pro-se with an iffy story about getting it from a lawyer, but the other was a real firm with multiple people involved ¯_(ツ)_/¯
"The legal eagles at New York-based Cuddy Law tried using OpenAI's chatbot, despite its penchant for lying and spouting nonsense, to help justify their hefty fees for a recently won trial"
The Court "It suffices to say that the Cuddy Law Firm's invocation of ChatGPT as support for its aggressive fee bid is utterly and unusually unpersuasive"
So my take on this is Wendy's execs decided "we need an #AI strategy!" and for reasons that remain unclear, it was somehow not immediately shot down with "Sir, this is a Wendy's, we make burgers we don't need a fuckin AI strategy" https://www.theguardian.com/food/2024/feb/27/wendys-dynamic-surge-pricing
"Amazon has sought to stem the tide of [#AI generated schlock books] by limiting self-publishers to three books per day" - Bruh, I know you don't want to deny the starving author toiling away on the next Great American Novel but I think we can set the bar a bit higher than that
Like start with an initial limit of one per week and have some kind of reputation threshold. If real people keep coming back to buy your dinosaur erotica or whatever, great, cap lifted, crank out as many as you can, but if you get caught impersonating or listing complete garbage, your account is nuked and you start over
Yeah, there'd be problems with straw buyers and review bombing competitors but it seems like the bar wouldn't have to be very high to make the absolute crap unprofitable
I ain't gonna waste a gift article on that shit unless someone REALLY wants it but here's a taste after you get past the Palantir hagiography "LLMs can provide better service and responsiveness for many day-to-day interactions between citizens and various agencies. They’re not just cheaper, they’re also faster, and, when trained right, less prone to error or misinterpretation"
Today's #AIIsGoingGreat (HT @ct_bergstrom): Nothing to see here, just a paper in a medical journal which says "In summary, the management of bilateral iatrogenic I'm very sorry, but I don't have access to real-time information or patient-specific data, as I am an AI language model"
Another day, another credulous #AI boosting WaPo opinion piece
"AI could narrow the opportunity gap by helping lower-ranked workers take on decision-making tasks currently reserved for the dominant credentialed elites … Generative AI could take this further, allowing nurses and medical technicians to diagnose, prescribe courses of treatment and channel patients to specialized care"
The premise is bizarre. What exactly are the non-experts doing when they "take on decision-making tasks" in this scenario? One of the big problems with current #LLM "AI" is you need subject matter expertise to tell when they are bullshitting…
Epic Zitron rant "Sam Altman desperately needs you to believe that generative AI will be essential, inevitable and intractable, because if you don't, you'll suddenly realize that trillions of dollars of market capitalization and revenue are being blown on something remarkably mediocre" https://www.wheresyoured.at/peakai/
Can we fucking not? "In a 2019 War on the Rocks article, “America Needs a ‘Dead Hand’,” we proposed the development of an artificial intelligence-enabled nuclear command, control, and communications system to partially address this concern… We can only conclude that America needs a dead hand system more than ever" https://warontherocks.com/2024/03/america-needs-a-dead-hand-more-than-ever/
The authors offer a lot of vague-to-meaningless handwaving "All forms of artificial intelligence are premised on mathematical algorithms, which are defined as “a set of instructions to be followed in calculations or other operations.” Essentially, algorithms are programming that tells the model how to learn on its own"
"America is no stranger to “fail-fatal” systems either"
Uh yeah, but some of us poor simple minded bleeding heart peaceniks may consider "fail-fatal for the entire fucking planet" to be entirely different class of system which raises some unique concerns
"Keep in mind, where artificial intelligence tools are embedded in a specific system, each function is performed by multiple algorithms of differing design that must all agree on their assessment for the data to be transmitted forward. If there is disagreement, human interaction is required"
Well as long as long as both ChatGPT and Claude have to sign off on the global thermonuclear war, it's hard to see how anything could go wrong
I don't think these guys have much chance of gaining traction in the US, but it would be unfortunate if other nuclear states decided they were at risk of an AI dead hand gap
Today's #AIIsGoingGreat brought to you by #NYC, who deployed spicy autocomplete to provide advice "on topics such as compliance with codes and regulations, available business incentives, and best practices to avoid violations and fines"
(spoiler: one great way to avoid violations and fines is to not get your legal advice from spicy autocomplete)
One potentially informative thing reporters following up on that #NYC#AI#Chatbot story could do is #FOIA (or whatever the NY equivalent is) communications related to the acquisition and deployment. Who pushed for this in the first place? What did #Microsoft promise? What sort of quality / acceptance testing was done? Did anyone, anywhere along the line raise concerns that it would give out bad, potentially illegal advice?
@GossiTheDog One thing I'm wondering is how many non-tech savvy landlords and employers are doing background checks with these things… like, in the past, you know people will probably google your name, but if they ask bing "$name criminal convictions" there's a very good chance it'll make shit up
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