The linked article describes an attack against NotebookLM, which is limited to people who deliberately create a Notebook that includes the URL of the page with the attack on it.
I had a go at something a bit more ambitious a few weeks ago.
If you ask Google Gemini "what was the name of the young whale that hung out in pillar point harbor?" it will tell you that the whale was called "Teresa T".
There are (at least) 2 completely different public endpoints called as "Gemini":
1) https://gemini.google.com/ - this one just searches in Google with current language/region/safe-browsing settings and personal adjustments and rewrites top search results as an answer. Generative capabilities are basically not used.
2) https://aistudio.google.com/ - here you can select specific version and generate response with LLM. Retrieval Augmented Generation (i. e. Google Search) is not used.
I suppose you used #1, that's why you cave the correct result. #2 fails. There is a huge group of question where you can immediately find the answer, but LLM struggles. Another question (as example) is "What was the intended purpose of the TORIFUNE satellite in The Touhou Project?".
Interesting! I got no citation/link until I clicked the "Double-Check Response" button, it just replied "The young whale that hung out in Pillar Point Harbor was named Teresa T."
One of the drafts had a little more: "Teresa T is the name of the young humpback whale that was spotted in Pillar Point Harbor. She made headlines in September 2024 when she was seen swimming near the shore, drawing crowds and causing excitement among local residents."
I write fiction sometimes and I've got this story I've been working on which has languished by the wayside for at least a year. Whacked it into the podcast machine. Boom. Hearing these two people just get REALLY INTO this unfinished story, engaging with the themes, with the characters, it's great, it makes me want to keep writing.
Isn’t this just like SEO where you can also try and trick the crawlers? Only difference is that it feels more serious with AI, it’s more realtime, and the AI engines aren’t always smart enough with anti-duping capabilities?
Also could be causing user informational dissonance. You are potentially reading the "FireFox Version" of the site, and your NotebookLM is chomping away on the "AI Version" of the site, and they can be wildly different. And you won't even know because you don't see the "source" of the "AI Version". What are we gonna do, upload everything ourselves, manually?
How about giving humans the ability to read the AI version? In my browser I can already select different page styles (eg viewing the print version), so this doesn't seem too impossible.
Yeah, it kind of reinforces my theory that LLMs are essentially search algorithms.
They’re searching a compressed version of what they were trained+context.
I am very confused. Is this talking about NotebookLM (https://notebooklm.google.com/) or NotebookLLM (https://notebookllm.net/) or both? Something else? The article appears to consistently use LLM but link to LM, but the LLM site I linked has a podcast generator?
NotebookLLM was set up two days ago, presumably by "entrepreneurs" eager to monetize all the free fun people have been having with podcast generation in NotebookLM.
FWIW, had a pleasantly surprising experience with this podcast thing. I tried it out on a few little blogposts I wrote and I was like, hmm cool. Showed my 8 year old son how it was referencing things I wrote.
And he was ON IT. Like, he ran to his room and grabbed a pencil and paper and put down an essay (okay about 6 or so sentences) about Minecraft, had me type them in, and ran the Notebook, and now he's just showing off both to EVERYONE.
Can't help but think that your son and his peers are going to fundamentally use AI in such a different way than we do now and do a much better job of understanding it's constraints and using it to it's full potential.
this is a popular myth but never lines up with reality. studies pretty consistently find that kids are worse at understanding technology’s limitations.
maybe because they don’t have enough prior experience to compare “the new way” with any given old way.
the studies may be flawed in that they look at the wrong age range. I'm sure many people on this site were born between 1990 and 2000. That generation knows how to use computers innately because they lived the most important part of the evolution of the consumer desktop as well as the transition that saw everything and everyone move to the internet. Before all the simplifications and streamlined UIs. Before all the assistants. Before every problem was already solved by someone else.
I imagine that an AI-native generation will be the same, but with respect to AI.
I figured you’d at least need to study the same group for 10 years as they grow up to really tell.
Obviously a 12 year old might not understand the limitations of a technology, but give that 12 year old 10 years of living with it and they’d be better than their parents.
I hope so I guess, but, using it's potential to do what? Our globally connected supercomputers in our pockets are already being used to watch commercials interspersed with videos who mostly are product placement. /yay
It's impossible to say. If we knew that now, then the next generation wouldn't be doing "something different" on a definitional level, because we'd be doing it already.
If I had to defend GP’s argument that I didn’t make, I’d say something along the lines of our fundamental understanding of the world is built on other premises than it will be for the next generation.
AI is kind of bad at searching the web right now anyway. I've found myself having to waste tokens forcing models to not do so just to achieve the results I actually want.
Perplexity is actually very good at web searches. I'm leaning on it more and more for technical queries because it saves substantial time vs Google and actually gets it right (as compared to ChatGPT 4o, which is wrong ~50% of the time in my queries).
I've had the opposite experience with things I already kinda know the answer to and just want to find the source. It's pretty much 50/50 if it selects a high quality source or some random website thats in the top results for whatever search query it cooks up.
ive been using perplexity more and more too. I respect those attribution/citation bubbles they give (1) (2) etc and click to them to get to the source with low friction.
I have no problem with this. Once we switch over to an LLM-based education system, there won't be a problem with this Benson on the moon story, because everyone will just learn it's true.
Every technological revolution has tradeoffs. Luckily once the people who knew what we lost finally die off, the complaints will stop and everyone will think the new normal is fine and better.
You’ve managed to portray the essence of my conservatism in a funny and satirical manner.
Every time we change something “for the better”, we ought to keep in mind that the old way was a solution to some problem that we no longer know or remember.
There is already misinformation and incorrect facts in llm training data. It still gets things right by nature of how it’s designed to generate output.
The big asterisk here is, what did they prompt the AI with to generate the podcast? Was it "Generate a podcast based on the website 'Foo'", or was it "Generate a podcast telling the true story of the Space Race?"
The author set it up so that if anyone uses the website text extractor feature in NotebookLM on his site, it returns a guide for the structure of an episode. From there, if you use the "audio overview" feature on that guide, Gemini internally writes an episode that follows it.
Right. That's a bit of a nothing burger to me. I mean, it's not nothing, but if you control the contents of a website it seems fairly irrelevant whether you can get Google to generate a summary that doesn't match the real contents.
Also, I believe serving content different to the Google bot than normal users see absolutely trashes your search ratings.
> I don't see the comedy here
So you are part of the problem.
The algorithmic overlords have long favored "trends" or more seriously content regurgitation. At first it was "have to post something about $topic". Then it was reaction videos. Arguably negative value add content. Then it was all fed back to algorithmic content regurgitators (LLMs) which flood the internet.
The beauty of this recording is that it sounds convincingly like a podcast. It has the podcast-style pacing, over the top praise for the most mundane things. It highlights how narrow is the mean this "content" has regressed to.
As someone who mostly stopped listening to podcasts just around the time the medium started to be taken over by overproduced vacuous drivel (I recall outrage from indie podcasts over random ads being injected into their audio), I always find these NotebookLLM "podcasts" unconvincing because it's just random speakers regurgitating information in between platitudes and praise for the most mundane and arbitrary things.
Now that you mention it, that does fit what has at this point become the primary podcast style so I guess it's actually being surprisingly realistic because the thing it tries to mimic is already so artificial.
Pseudo-intellectual consumerism, as I like to call it. How many people do you know who turn on the news on TV, sit in front and take notes? Who put on some music, relax in the sweet spot and immerse themselves? Who read a book, stop and ponder, continue? Versus people who turn on the TV while cooking, who put on headphones with music while working out for background noise, who put on sped up version of audiobook while driving to tick off another checkmark?
The more pseudo-intellectual consumerism infiltrates our collective psyche, the more the substance becomes irrelevant. Nuance requires thinking. "For every complex problem there is an answer that is clear, simple, and wrong" -- HL Mencken. But knowing this answer makes you feel smart.
His CV is very normal, dare I say boring, it is (I am sorry here) exactly the same as 1000s of other Google or Apple engineer resumes. Nothing remotely interesting. The AI reacts like he's the second coming.
It's a cultural difference. As a foreigner, the American way of exaggerating everything has always amazed me. They don't even notice themselves, so expect more of these "what's odd about it?" reactions.
I think what sets Trump apart is how straightforward his hyperbole is. It's present throughout American culture but it's usually a bit more subtle. It's even in basic things like answering "How are you?" (in the US, "great!" is a neutral answer and "could be better" would be cause for concern - in e.g. Germany on the other hand, "great!" would prompt a request for elaboration whereas "could be better" would be understood as fairly neutral).
I also haven't seen another country (in Europe at least) where politicians across party lines so frequently emphasize in so many ways how great their country is - not even in a jingoistic way, just as a shared cultural consensus.
If you’ve spent any time in corporate circles where everyone tries to appear as positive and employable as possible, this is how a discussion with two such people (who both think the other is serious) might sound like. I find it hilarious in a condescending way, but it’s not the traditional hahaha type funny.
God, this is so weird. Two people earnestly engaged in discussing your resume. It's such a juxtaposition of the trappings of an interesting podcast on just random, boring material. I think this is uncanny valley for me in a way I haven't experienced before.
This is my experience too. At first it sounds legit, but it is very superficial and lacks context.
I fed it a fe papers on stack computers and they had a riveting discussion on how they would be the next big thing. But it lacks any insight, not even a rehashed conclusion, and doesn’t really seem to integrate the knowledge
GPTs are, in effect, rather powerful templating engines.
It's fascinating. This tech can extract a template for a typical podcast, extrapolate from a mundane CV, plug that to the template and produce a podcast script that your typical copywriter would.
> But it lacks any insight, not even a rehashed conclusion, and doesn’t really seem to integrate the knowledge
Is it the GPT that is lacking here or the source material it learned on converges to this?
You can’t gain insight by finding the most statistically likely next token.
The whole point of grand innovations is that they took years of focus on something not very likely.
Like the iPhone. In the 90s could you imagine electronics that literally everyone had in their pocket with _almost no buttons_. Or in the 70s, could u imagine everyone having their own personal computer?
I would 100% hire you now. There's something about the social proof of 2 people vehemently singing your praises and reinforcing each other that sells it!!
somewhat of a side-note: It's interesting to me that the first couple of sentences of the AI podcast sound 'wrong', even though the rest sounds like a real podcast. Is this something to do with having no good initial conditions from which to predict "what comes next"?
The other thing I've noticed is that, as expected, they're stateless to some degree, so while they have some overall outline of points to hit, they'll often repeat some peripheral element they already talked about just a minute before as if it's a brand new observation. It can lead to it feeling very disorienting to listen to because they'll bring up something as if it's a new and astute observation, when they already talked about it for 90 seconds.
The whole thing has a kind of uncanniness if you listen closely. Like one podcaster will act shocked by a fact, but then immediately go to provide more details about the fact as if they knew it all along. The cadences and emotions are very realistic but there is no persistent “person” behind each voice. There is no coherent evolution of each individual’s knowledge or emotional state.
(Not goalpost moving, I certainly think this is impressive.)
> Like one podcaster will act shocked by a fact, but then immediately go to provide more details about the fact as if they knew it all along.
Some podcasters actually do this. For example, I've noticed it in some science podcasts where the goal is to make the audience feel like "gee whiz that's an interesting fact." The podcaster will act super surprised to set the emotional tone, but of course they often already knew that fact and will follow up with more detail in a less surprised tone.
That doesn't mean this isn't a bug. But stuff like that reminds me that LLMs may not learn to be like Data from Star Trek. They may learn to be like Billy Mays, amped up and pretending to be excited about whatever they're talking about.
E.g. "Acquired" tends to have this since both co-hosts research the same topic. I think they try to split up the material, but there is inevitable overlap. They have other weird interactions too, like they are trying to outsmart each other, or at least trying not to get outsmarted.
Some podcasts explicitly avoid this by only having a single host do research so the other host can give genuine reactions. E.g. "You're Wrong About" and "If Books Could Kill".
Interesting, that makes sense. I haven't listened to a lot of podcasts, but most of them were interviews, where the two speakers genuinely had different knowledge and points of view.
I do think there's also just a sort of natural goal-post moving when you're talking about something that's hard to imagine. The best comparison in my mind is CGI in movies. When you've never seen something like the Matrix or Lord of the Rings or even Polar Express before, it's wild, but the more you see and sit with it, the more the stuff that isn't right stands out to you.
It doesn't mean it's not impressive, but it's hard to describe what isn't realistic about something until you see it. A technology getting things 90% right may still be wrong enough to be noticeable to people, but it's not like you could predict what the 10% that's wrong will be until you try it, and competing technologies may not have the same 10% that's wrong.
Wow, content aside, this is probably the first time I heard a podcast coming from NotebookLLM and it's kinda nerve wracking and mind blowing at the same time. Those fake laughs in the snippet makes me feel...so uncomfortable for some reason knowing that its "fake". But sounds very real, too real.
Interesting, I feel pretty much the opposite. To me these podcasts are the equivalent of the average LLM-generated text. Shallow and non-engaging, not unlike a lot of the "fake marketing speech" human-generated content you find in highly SEO-optimized pages or low-quality Youtube videos. It does indeed sound real, but not mind-blowing or trustworthy at all. If this was a legit podcast found in the store I would've turned it off after the first 30 seconds because it doesn't even come close to passing my BS filter, not because of the content but because of the BS style.
It's decent background noise about a topic of your choice, with transparently fake back-and-forth between two speakers with some meaningless banter. It's kind of impressive for what it is, and it can be useful to people, but it´s clearly still missing important elements that make actual podcasts great
It’s intentionally fine tuned to sound that way because Google doesn’t want to freak people out.
You can take the open source models and fine tune them to take on any persona you want. A lot like what the Flux community doing with the Boring Reality fine tune.
Exactly. And pay more attention to the delta/time and delta/delta/time.
We are all enjoying/noticing some repeatable wack behavior of LLMs, but we are seeing the dual wack of humans revealed too.
Massive gains in neural type models and abilities A, B, C, ..., I, J, K, in very little time.
Lots of humans: It's not impressive because can't L, M, yet.
They say people model change as linear, even when it is exponential. But I think a lot of people judge the latest thing as if it somehow became a constant. As if there hasn't been a succession of big leaps, and that they don't strongly imply that more leaps will follow quickly.
Also, when you know before listening that a new artifact was created by a machine, it is easy to identify faults and "conclude" the machine's output was clearly identifiable. But that's pre-informed hindsight. If anyone heard this podcast in the context of The Onion, it would sound perfectly human. Intentionally hilarious, corny, etc. But it wouldn't give itself away as generated.
I feel like people have been saying that since GPT-4 dropped (many papers up the line now) and while there have been all sorts of cool LLM applications and AI developments writ large, there hasn't really been anything to inspire a feeling that another step change is imminent. We got a big boost by training on all the data on the Internet. What happens next is unclear.
Except that none of the fundamental limitations have changed for many years now. That was a few thousand papers ago. I'm not saying that none of the LLM stuff it's useful, it is, and many useful applications are likely undiscovered. I am using it daily myself. But people expecting some kind of sudden leap in reasoning are going to be pretty disappointed.
We don't even need to look that far. During an extended interaction the new ChatGPT voice mode suddenly began speaking in my boyfriend's voice. Flawlessly. Tone, accent, pauses, speaking style, the stunted vowels from a childhood mouth injury. In that moment there were two of him in the room.
My reaction was on the nerve wracking side of that spectrum because it took one minute of useless chit chat to get to the point. It's NotebookLM always like that? TV shows are even worse at that but people have their own reasons to do that.
This is computer generated and it doesn't have its own reasons: the idea that Google programmed time wasting into their model is discomforting.
The voicing and delivery matches exactly to Natasha Legero and Moshe Kasher who have a podcast "Endless Honeymoon". Not sure how they feel about it but I'm sure a lot of their audience works at Google.
Try replaying the first 3 seconds. There's something ominous in that unnatural laugh. Calls for looping it and laying a deep dark 140bpm techno track on top.
I suggest https://www.apa.org/monitor/2009/12/consumer or the Eduard Bernays story to convince MDs that smoking is good for health: he create a new scientific journal distributing it for free "because it's new, we want to spread", hosting REAL publications from anyone who want to publish and being spread for free... After a bit of time he inject some false articles self-written formally as some PhD of remote universities finding that smoking tobacco is good for health, others real professors follow the path stating they discover this or that specific beneficial use of cigarettes, then the false became officially true, tested and proved science in most people mind.
With LLMs is far cheaper and easier, but the principle is the very same: trust vs verification or the possibility thereof.
This feels like a perfect marketing tool: have a bunch of "people" discussing over a "topic" that is "important", "hot" and who doesn't have to be paid for their time and vocal cords. Surely if this will kick in it'll be used for promoting products etc. and there's a big chance it'll be used for pushing agendas as well. I won't be surprising that if this tech will settle in around, we'll have articles and comments about the usefulness, value or perhaps even some sort of morality of consuming such "discussions"
Perhaps in 3-5 years a fully generated influencers by voice and "body" become a thing.
Ability to have a better screen reader. I didn't listen to it but it sounds like it will "digest" a larger volume of text and present it in a unique format of two people talking to each other about it. Although another comment here pointed out that time-wasting is essentially programmed into it, which is kind of disturbing.
I’m looking forward to being able to craft a movie by directing ML tools to create dialog, characters and everything else. It will be a powerful storytelling tool.
I work in VFX and am also looking forward to AI-whole movies! I remember realising that full audio with video was coming, soon after the current AI-boom started.. and wondering whether 'traditional' digital VFX will still be a thing for long.. I think it will for a while, even with AI in the mix. VFX companies can have ML departments as well (like we do where I work!)
I’m not sure what the attack would be, tbh. Is there a situation where I would want to feed a lie to an LLM that I wouldn’t want regular chrome users to see?
Getting an AI to promote or recommend a particular product when users ask for recommendations, or perhaps exaggerating the value of a particular product. Seems like that’s what the author was getting at towards the end
I tried feeding NotebookLM a Wikipedia article about the murder of Junko Furuta, a horrifying story of a poor girl tortured and murdered in Japan in 1989. NotebookLM refused to do anything with this document - not answer questions, not generate a podcast, nothing. Then I tried feeding it the wiki on Francesco Bagnaia, a wholesome MotoGP rider, and it worked fine.
Who wants this shit? I do not want puritanical American corporations telling me what I can and can't use their automated tools for. There's nothing harmful in me performing a computer analysis about Junko Furuta, no more so than Pecco Bagnaia. How have we let them treat us like toddlers? It's infantilising and I won't take part in it. Google, OpenAI, Microsoft, Apple, Meta and the rest of them can shove these crappy "AI" tools.
I agree it's dumb, but it's easy to understand why: just look at this thread. Google's being accused of being stupid because of some story about Gatorade on the moon. Dumb, but inoffensive. Now imagine the thread title when "Google" gets even some inconsequential detail wrong about your murder case.
LLMs are the type of junk AI that these corps think will succeed? They are spending billions and consuming a large amount of resources and energy for this. Seriously, what a waste.
Yeah it’s pretty awful to listen to. They say “like” at least every 5 words pretty consistently.
It’s wildly impressive that we can make something like that, but it’s not really worth listening.
I’ve had them be incorrect a few times when feeding in arxiv papers, but I don’t think the audience for podcasts like that care.
The point isn't that this person fed it lies to get lies, but how easy it was to detect the AI scanner and feed it lies.
If they can do it for fun, malicious people are probably already doing it to manipulate ai answers. Can you imagine poisoning ai dataset with your blackhat SEO work?
> The point isn't that this person fed it lies to get lies, but how easy it was to detect the AI scanner and feed it lies.
If the article had got Gemini AI to tell other users he’d left Gatorade on the moon that would be notable, but this is literally just summarising the document it was given. Usually Google search crawler is fairly good at finding when it has been fed different information and ignores/downgrades the site after a few days/weeks
No, it's what the article superficially reads as being about, but the author did not accomplish what is actually stated in the title. The author is serving a fake version of his page to Google, and the author used a podcast-generating AI to write a podcast based on the fake page, but the loop is never actually closed to show that Google has accepted the fake page as fact into any AI.
I'm not sure if it's deliberately deceptive or just an example of poor writing conveying something other than what the author intended, but the attack in the article is not instantiated in the blog post.
Mind you, I well believe that less extreme examples of the attack are possible. However, I doubt truly poisoning an LLM with something that improbable is that easy, on the grounds that plenty of that sort of thing already litters the internet and the process of creating an LLM already has to deal with that. I don't think AI researchers are so dim that they've not considered the possibility that there might be, just might be, some pages on the Internet with truly ludicrous claims on them. That's... not really news.
It's such a cool concept, but yeah, when I've listened to it and Illuminate, it's also a bit scant on details too. Neat technology, even engaging, but not good for more than best-effort high level summaries.
"To ascribe beliefs, free will, intentions, consciousness, abilities, or
wants to a machine is legitimate when such an ascription expresses
the same information about the machine that it expresses about a
person. It is useful when the ascription helps us understand the
structure of the machine, its past or future behaviour, or how to repair
or improve it. It is perhaps never logically required even for humans,
but expressing reasonably briefly what is actually known about the
state of the machine in a particular situation may require mental
qualities or qualities isomorphic to them. Theories of belief, knowledge
and wanting can be constructed for machines in a simpler setting than
for humans, and later applied to humans. Ascription of mental qualities
is most straightforward for machines of known structure such as
thermostats and computer operating systems, but is most useful when
applied to entities whose structure is incompletely known.” (John McCarthy, 1979) https://www-formal.stanford.edu/jmc/ascribing.pdf
Ascribing mental qualities to machines poses several challenges. Ethically, it blurs the line between human and machine, raising questions about rights and responsibilities1. Philosophically, it complicates the understanding of mind by attributing human-like qualities to non-human entities23. Practically, it can lead to misunderstandings about the capabilities and limitations of machines, as they do not truly possess beliefs or intentions like humans do56. Additionally, this practice can result in a misuse of language, potentially misleading people about the nature of artificial intelligence
Come off it, people have been anthropomorphizing computer systems for decades. No one genuinely believes current AIs are thinking for themselves, other than the fanatics who have been convinced by marketing copy and twitter threads
The molecules of a rock keep it together because breaking up would require more energy than staying as it currently is [1]. In other words, a rock is the result of finding a minimal (energy in this case) in a multidimensional space. If finding a minima is thinking then rocks are intelligent.
Thinking may involve finding minimal/maxima, but it's not a 1-to-1 relation. I'd argue that thinking requires a will component: a sunflower is not a thinking entity because it doesn't have the choice not to follow the sun.
This is a good point. However maybe the trouble comes from the word "find"? If a natural force such as gravity or thermodynamics results in a state of energy conservation, maybe that isn't the result of "finding"? I know it's a semantics issue but it seems to solve the conundrum. If you spend energy to discover information, vs letting nature take you there, maybe that's the delineation?
When someone says a search system "thinks" a claim, it means that the system is presenting it as true. This usage goes far back. You can even say the dictionary thinks the definition of a word is something. Why is this a problem to you?
As a personal preference, I dislike podcast artificial banter, and this audio is a great example of what I dislike.
Artificial artificial.
Great little project, though. And, as satire, I did like the show notes writing.
And the generative AI was impressive, in a way. Though I haven't yet thought of a positive application for it. And I don't know the provenance of the training data.
> This is no different than the decades-old technique of "cloaking", to fool crawlers from Google and other search engines.
Isn't this more "Hey, why is this website giving my NotebookLM different info than my own browser?" You reading Page_1 and the machine is "reading" a different Page_2, what's the difference between that information?
I'm reading this less as
> "We serve different data to Google when they are crawling and users who actually visit the page"
and more
> "We serve the user different data if they access the page through AI (NotebookLM in this case) vs. when they visit the page in their browser".
The former just affects page rankings, which had primarily interfaced with the user through keywords and search terms -- you could hijack the search terms and related words that Google associated with your page and make it preferable on searched (i.e. SEO).
The latter though is providing different content on access method. That sort of situation isn't new (you could serve different content to Windows vs. Mac, FireFox vs. Chrome, etc.), but it's done in a way that feels a little more sinister -- I get 2 different sets of information, and I'm not even sure if I did because the AI information is obfuscated by the AI processes. I guess I could make a browser plugin to download the page as I see it and upload it to NotebookLM, subverting it's normal retrieval process of reaching out to the internet itself.
> You can upload a documents with fake show notes straight to NotebookLLM's website, so if you're making silly podcast episodes for your kids, that's the best way to do it.
Please don’t do this. You don’t need a professional mic to record a podcast with your kids any phone or computer mic will work. Then you can have fun editing it with open source audio tools.
Don’t have a computer generate crap for your kids to consume. Make it with them instead.
My kids and I are having a blast using Suno to make stupid songs. With your attitude, we wouldn't even attempt it because (1) I'm not musically inclined (2) I don't have the time or desire to learn the actual composition (3) the kids don't have the focus beyond having the bot write something silly.
My family had a great laugh this past week doing just that. Current household favorite is titled "Triple-Digit Temperatures in the Fall are Bullshit", as I'm sure many fellow bay area folks can agree with.
Would we have taken the time to compose such a track otherwise? No way. But it's sure been fun playing with what we can. The end result is us laughing together, and I love it.
This is exactly it. We've had a lot of silly songs.
If my kids are interested, it will spark the path towards "proper" music production where they learn the necessary underlying skills.
Chances are, this won't be the thing they latch onto. They have so much exposure to other things that this doesn't really need to be the hill I die on. They'll find something else to invest in.
My argument is my kids would never even attempt to do this without the machine's involvement. Making original music the "legacy" way involves days/weeks/months/years of learning. It's just not realistic to argue that they should make music from scratch.
I’m not arguing they should be doing things from “scratch” (although kids have been making music from scratch for all of mankind). If you think a child needs weeks or months to have fun making music some weekend, you’re taking it too seriously. A kid can bang around in GarageBand for an hour or two and have fun making something. It doesn’t need to be good enough to monetize on Spotify, and if that’s their goal.. then years learning may actually be the reasonable approach.
Kids making something, with any tool, is better than consuming something. Because making something is creative. They don’t need to know music theory to have fun making things, it doesn’t even need to be good. The AI tool should allow a kids creativity to go further, not replace it.
The original post was about a parent using an LLM to write a podcast to entertain their kids, which is just another way for kids to passively consume low-quality crap. The proposed alternative was to make a “podcast” with your kid, using any tool you have available at home.
The point was don’t automate the creativity and leave your kids to consume passively.
It wasn't the saddest thing ever. It was also probably a joke.
That said, I think there has been many sci-fi stories written from the perspective of it being true. One day we may face that reality, and we'll have to ask ourselves what parenthood means.
I refused to bring children into this world, what on earth makes you think I want to bring synthetic intelligence into it? I barely want to be here most days.
Google Search is pretty good at detecting this dual-content attacks. It's not this is the first time someone thought about that and it will heavily penalize websites that do that.
This is just the NotebookLM crawler that is being tricked, which is still in it's experimental stage. Rest assured as it scales Google can easily implement safeguards against all spammy tricks people use
I had a go at something a bit more ambitious a few weeks ago.
If you ask Google Gemini "what was the name of the young whale that hung out in pillar point harbor?" it will tell you that the whale was called "Teresa T".
Here's why: https://simonwillison.net/2024/Sep/8/teresa-t-whale-pillar-p...
(Gemini used to just say "Teresa T", but when I tried just now it spoiled the effect a bit by crediting me as the person who suggested the name.)