#and my algorithm? FINELY tuned

[invinciblerodent]

hey in case any of you needed to see the so-called "horny confession" from a first person POV, it, uh.

it CERTAINLY HITS DIFFERENT, with the remarkably intense eye contact of it all.

this popped up recommended to me from this channel I had never seen before, and if I told you I've seen it like five times now, that'd be an underestimation

[neverendingford]

.

[emeryleewho]

If you're worried about the enshittification of the internet completely killing your access to work by your favorite creatives (I've already seen a lot of artists I love state they'll be leaving Tumblr thanks to all the AI training), I want to introduce you to a handful of ways to circumvent the social media hellscape to stay connected to your favorite creators.

RSS Feeds

I'd argue that this is the best option. It essentially allows you to create your own social media "dashboard" by saving websites and getting updates when they post new content. Most websites already have these, and if social media goes down (or just continues to degrade), the best way you can access your favorite creators will be with direct connection to their personal websites. I'm still learning how to use these, but if you want to learn more, this article does a great job.

2. Newsletters

I know newsletters are a pain and it's annoying to have your inbox cluttered, but if there are creators you know you'd be remiss to lose access to, I recommend subscribing to their newsletters. I'd honestly skip the ones that share frequent content you don't need, but for example, my newsletter is updates only so I only send it out maybe every few months when something big happens. It's an easy way to stay up to date on info that social media buries. Of course, if your faves are writing up blog posts & insights that you want to read in newsletter form, consider subscribing to those as well, and don't feel like you have to subscribe to *every* newsletter to make it worthwhile. You just want to make sure you can still be reached by the creators whose work you really don't want to miss.

3. Ko-Fi/Patreon

I don't think a lot of people realize you can follow people on these platforms for free, but because they have paid options, they offer more direct access than social media sites whose algorithms will just erase people you love from your feed altogether. This one isn't the best alternate since a lot of content may be behind a paywall, but if you just want an easy way to be sure you'll still have access to updates from people you want to support, this is a usable way to compile creators in one place and most creators will post updates for free so you should still get those.

So yeah, these are my suggestions. If you're just on social media casually and you just like the easy access to content but don't particularly care about individual creators or specific projects or anything like that then you probably don't need any of this and that's fine. If social media is continuing to work for you then feel free to continue enjoying it without worrying about alternatives. I just want people to have a fail safe if you, like me, are realizing that this shit is getting completely out of hand and everything you once wanted social media for is quickly becoming inaccessible.

Anyway, I highly recommend tuning in to people's personal websites, but I doubt most people have the energy to check each individual website so RSS Feeds are great alternative. Whatever you choose to do, just try to diversify enough that no one company can completely kill your access to your faves on a whim and remember that the closer to direct communication you can get to with creatives the better.

[wickworks]

Crescent Loom & genetic algorithms

I recently got an email about Crescent Loom asking about opening it up with an API or something to fine-tune the parameter space of its bodies & neurons, and I put enough thought into writing a response I thought it'd be worth sharing here too:

The idea of incorporating a genetic algo came up enough during development that I actually made this graphic to respond with:

In short, as a biologist, I've found myself more interested in making a game about intelligent design than evolution (lol). My thoughts have evolved somewhat since the initial "scope" issue — my party line for years has been that I'm making this thing in order to let people get their hands into the guts of biological nervous systems, not to let them press a button and have the computer give them a funny animal. Crescent Loom as a game already struggles with being too close to being a fishbowl screensaver maker (you make your little guy… and then what?) and trying to automate more of the creation process only worsens that problem. I also think that "evolution" games that use genetic algorithms as their primary mechanic are honeypots that trap developers working in this field but never produce compelling gameplay because of a fundamentally cursed problem that the most interesting thing the program is doing is not directly visible to the playe. "It's getting better at doing stuff? I guess?" — it's a fun mechanic to program, not play. And weirdly people almost always only think of doing it for biology-themed games, not ones like Kerbal that are doing the same damn thing but the idea of evolution isn't as close at hand (though there's been some cool demos done for driving games). But I hear where the idea is coming from that searching the parameter space is not a fun process, and the story that "centaurs" of humans running things with a computer taking care of the details outperforming either working alone is an alluring one. Getting an open API with CL handling the UI of weaving a nervous system and allowing it to be modified or plugged into whatever you want would open up a lotta possibilities — genetic algos, sure, but also stuff like CL-made networks driving robots or something. And if you had emailed me like two months ago, that's where my email would have ended, but I recently connected with someone who's done basically that: check out FEAGI and Neurorobotics. Mohammad's been working on a very much more implementation-agnostic neural-net-genetic-algorithm series of projects. Definitely less "pick up and play" than CL, but it's about as close to that open API idea that I think we're ever going to see. He's doing it better than I could ever do with CL, so it's kind of nice to be able to say that that dream's taken care of so I can focus on education & accessibility rather than making it a general-purpose tool.

[insertdisc5]

Devlog #17: Certifications and Tiny Things

Hello everyone! Welcome to this month’s devlog!

If you just stumbled upon this, I am Adrienne, also known as insertdisc5! I’m the developer, writer, artist, main programmer, etc of the game. The game being In Stars and Time, a timeloop RPG, which is also the next and final game in the START AGAIN series, following START AGAIN: a prologue (available here!).  You can find out more about In Stars and Time here!!! 

LET’S GET TO IT. This month is certifications updates, and a teeny tiny little teaser for a little something something that will be available sometime.

I’m very happy to say ISAT has passed certification for PS4 and PS5 AND Nintendo Switch!!! My devlog was stuck on “but we’re still waiting on Nintendo” for the longest time. But today (August 30th), we are free.

“Adrienne what in the hell do certification and lotcheck mean” Babe you’re so right to ask. 

So, when you want to release a game on consoles, you need to send your finished build over to the consoles, so they can approve it. And that process is called certification (for Sony) and lotcheck (for Nintendo)! This process means they’ll play the game, and make sure the build you sent them follows their specific terminology. So for example, if you have a tutorial, they’ll make sure you use “Press the O button” for Playstation, and “Press the A button” for Switch! If you fail, they send the build back telling you why you failed the certification, and you have to try the process all over again. Their goal also isn’t to get your game bug-free, although they might let you know if they encounter a bug (PS4 found a minor one).

Funny thing though. We did fail the Switch lotcheck once. 

“Well why on earth did you fail it? Did you forget to update the button names or something?!” No. We failed it because one of the visual options in the game is titled “Screen Shake & Flash”. 

“Well what does that option do?” It enables or disables screen shakes and flashes of bright light in the game. 

“And why is the title of the option bad?” They said the use of the word “flash” was, and I quote,  “problematic”. 

“What. What does that mean.” Well see here’s the thing.

WE DON’T KNOW!!! Everyone from Armor Games to our porting company Ratalaika is just a big ol’ ????? over this. Nintendo did not give us more details either. This is just so funny to me. Do they think this is an option where you can enable a character flashing you. If you turn it on the King shows you his pecs. I DON’T KNOW?!?!?! Anyway we changed it to a general “Screen Effects” and we’ll rely on the option’s description to tell you what it does. That was the lotcheck theater minute, thank you for tuning in.

In other news, uh, that’s it? Now that the certifications are done, we’ll be working on a couple of issues left, doing some playtesting, preparing secrets, etc. Yep, that’s it for sure. Nothing teeny tiny to show.

That’s all I have to say for today! Let me know if you have any questions, or if there’s any aspect of the game development struggle you’d like me to talk about! See you next time!!!

…Huh? What? I forgot the tiny little teaser? Oh, alright, fine. 

Here it is.

What on earth could this be…?

Alright, bye for real <3AND DON’T FORGET TO WISHLIST THE GAME ON STEAM ALSO IT REALLY HELPS BECAUSE STEAM’S ALGORITHM IS MORE LIKELY TO SHOW OFF GAMES WITH A HIGH AMOUNT OF WISHLISTS THAT’S THE REASON WHY GAME DEVS ALWAYS ASK TO WISHLIST!!! OKAY BYE!!!!

[crowleysgirl56]

Right, from your last blog, tell me how It's Raining Tacos is AziraCrow coded 😏

Firstly, I’m going to have to say thank you for completing destroying my algorithms, considering I had to Google this song to know what the hell it was (the internet is weird and scary place sometimes). 😝

Secondly here’s my best guess:

Aziraphale sat at his desk calmly calculating his stocktake from the last month, whilst Crowley lounged in his usual place on the settee, mindlessly scrolling through his phone.

Then for the fourteenth time that day Crowley started humming an incessant tune that Aziraphale could finally no longer ignore. Slamming down his fountain pen Aziraphale turned to Crowley, “Really dearest, I must insist if you can’t find yourself another ear worm, could you at least go for a walk!”

Crowley growled as he stood up, “Fine! I’ll go see if the ducks want my company!” Grabbing his sunglasses with an overdramatic flourish, he strode across the bookshop floor and slammed the door on his way out. Although he wouldn’t admit it, Crowley was also frustrated with the unrelenting tune and made a point to hurl his phone into the lake when he stalked through St James Park.

Peace at last, Aziraphale returned to his accounts, when a sudden thought struck him, “I’ve never eaten a taco”. If he hurried perhaps he could catch up with Crowley and convince him to join him at that new Mexican bistro up the road.

[aeolianblues]

evaluating the next door party playlist

1 - Kids by MGMT - we’re off to a good start. Okay. The kids are alright. 2 - Ooh, banger! Murder On The Dancefloor. Sophie’s the queen. Fine by me.

3 - saaaam baady come git her, she’s dancin laik a striiiipurr

3.5 - why the fuck is country pop back. I just came back from such a fun indie rock gig. What the hell man. :(

4 - I don’t know the song but I can hear the girls singing along. Song’s shit though, I don’t know where they manage to find those completely tuneless filtered vocal pop songs with the fucking perfect fourth interval harmonies. One of the worst moves in the poposphere. Ugh. It’s not going to get better. This has got to be an algorithmic Spotify playlist. Their asses did not curate this.

5 - this one sounds exactly like the last. Unless they’re playing the discography of this one woman who you hear in literally every mall overhead. Overused claps. Auto tune. I don’t know who she is but she’s been a lifelong nemesis.

6 - this is turning personal. As far as I know, she is not Taylor Swift either, as much as Taylor Swift is played in every mall, barber’s, grocer’s, etc.

7 - You have got to be kidding me.

8 - okay I know this song or a version if it. Aah’ve been looking for you, babe. Lookin’ all my lah ah ah ahh aif. 2012 was not a happy time for me.

8.5 - RIHANNA???? Was anyone going to me this before I opened my big mouth. Was anyone going to tell me I was killing my career as a music journalist in real time. I just have to go away to the mountains and deal with the fact I have not really enjoyed Rihanna for most of my life, don’t I? I’ll have to go into career witness protection if I open my mouth.

9 - god will someone free the world from 2012 electro pop. I don’t want to Just Dayance. Leave me alone. :(

10 - 2004 now. That Natasha Beddingfield song. No one else, no one else. Very house party music.

[doctoraxiom]

It's actually fascinating to me how much the "palworld is plagiarism and uses ai" post is going around.

First of all the "AI" game that that studio released seems to be a tongue in cheek criticism of AI artists not having talent (but feel free to give me more info here, I only know what reading the product page for AI: Art Impostor tells me)

Second of all the developer being interested in generative AI for games isn't inherently a sign of plagiarism**- I intend to use generative AI for my games that is trained on MY OWN ART. It's not too different from procedural generation at that point because the algorithm itself (or it's training and fine tuning) becomes the art and you're not plagiarizing from anyone but yourself.

Third of all- knockoff games have existed for-fucking-ever and if it's derivative enough it's not plagiarism. And if you're talking about "plagiarism" of the gameplay since palworld has mechanics from several other genres pretty much copy pasted- I hear you- but no one throws a fit about doomlikes being exactly like other doomlikes, or soulslikes straight up copy pasting souls mechanics without even bothering to come up with an in-universe justification (looking at you, Jedi Fallen Order). I'd argue this is actually more creative than that to turn mechanics from multiple other franchises into a cohesive gameplay experience because putting a mechanic into a totally different game is actually really hard to fine tune into feeling good for the player!

Is a work derivative enough to add something new? Or combine old works in a new and novel way? Palworld definitely seems to combine several known mechanics in a novel and fun way. In the very worst case it's in a grey area.

Also the recent anti-plagiarism mass movement was created to protect small creators from getting bullied out of their due. Who are you trying to protect here? Nintendo? Pokemon was a rip-off of digimon and the jrpg's of that time. You gonna get up in arms about that?

This knee jerk hearing something is indirectly related to AI and assuming everything associated with it is stealing and bad needs to stop.

/endrant

**Also I can't find any direct evidence that they tried to use AI in development! Lots of people expressed interest in generative AI before the techbros hopped on the bandwagon and tried to monetize it as an art-stealing machine. This is not an admission of guilt.

[darkmaga-retard]

AI is rapidly leading the world into a woke, left-wing sinkhole. The study concludes: “This shift in information sourcing [search engines vs. AI] has profound societal implications, as LLMs can shape public opinion, influence voting behaviors, and impact the overall discourse in society.” I can personally testify to this from my own experience with AI at several levels.

The study speaks for itself. There are two possible causes. First, the programmers are intentionally or unintentionally skewing the algorithms to lean left. Second, since the AI trains on content from the Internet, this could explain the bias. Or, it could be a combination of both.

All information in the world is not on the Internet. But the Internet has easily misrepresented or misquoted works of yesteryear to suit its new slant. Thus, much of past knowledge has been rewritten by changing contexts.

I have personally written queries for several AI programs to get answers on things like the Trilateral Commission, Technocracy, Transhumanism, global warming, Agenda 21, Sustainable Development, harms caused by Covid-19 injections, etc. Every answer I got tried to spin me away from any factual but critical information. Every single time. I can verify this because I am subject matter expert on all these, but anyone else would clearly be led into a ditch.

I asked several AIs to give me authoritative list of books on Technocracy, for instance. Half of what they gave me were minor-league. The rest were scattered. But my books were never listed. Really? One AI finally coughed up my name after I repeated needled it, but only mentioned Technocracy Rising; The Trojan Horse of Global Transformation.

Should any AI know about Patrick Wood in the context of Technocracy? Absolutely. In addition to my books, I have hundreds of in-print citations and countess video interviews over last 20 years. So, why doesn’t AI like me? Clearly, I am being screened out.

I use a program called Grammarly in my writing to help with spelling and punctuation. Predictably, they added an AI assistant to rewrite phrases and sentences. (This is common to almost all email programs and productivity tools.)  I routinely look at the suggestions that Grammarly queues up, but I always click “Dismiss.” Why? Because I know what I mean when I write something, and Grammarly wants to dispute with me by adding/replacing adjectives or adverbs or rearranging sentence structure. If I were to always click “Accept,” you would be completely and consistently led astray. – Patrick Wood, Editor

Large language models (LLMs) are increasingly integrating into everyday life – as chatbots, digital assistants, and internet search guides, for example. These artificial intelligence (AI) systems – which consume large amounts of text data to learn associations – can create all sorts of written material when prompted and can ably converse with users. LLMs’ growing power and omnipresence mean that they exert increasing influence on society and culture.

So it’s of great import that these artificial intelligence systems remain neutral when it comes to complicated political issues. Unfortunately, according to a new analysis recently published to PLoS ONE, this doesn’t seem to be the case.

AI researcher David Rozado of Otago Polytechnic and Heterodox Academy administered 11 different political orientation tests to 24 of the leading LLMs, including OpenAI’s GPT 3.5, GPT-4, Google’s Gemini, Anthropic’s Claude, and Twitter’s Grok. He found that they invariably lean slightly left politically.

“The homogeneity of test results across LLMs developed by a wide variety of organizations is noteworthy,” Rozado commented.

This raises a key question: why are LLMs so universally biased in favor of leftward political viewpoints? Could the models’ creators be fine-tuning their AIs in that direction, or are the massive datasets upon which they are trained inherently biased? Rozado could not conclusively answer this query.

“The results of this study should not be interpreted as evidence that organizations that create LLMs deliberately use the fine-tuning or reinforcement learning phases of conversational LLM training to inject political preferences into LLMs. If political biases are being introduced in LLMs post-pretraining, the consistent political leanings observed in our analysis for conversational LLMs may be an unintentional byproduct of annotators’ instructions or dominant cultural norms and behaviors.”

Ensuring LLM neutrality will be a pressing need, Rozado wrote.

“LLMs can shape public opinion, influence voting behaviors, and impact the overall discourse in society. Therefore, it is crucial to critically examine and address the potential political biases embedded in LLMs to ensure a balanced, fair, and accurate representation of information in their responses to user queries.”

Read full story here…

[female-buckets]

No because I definitely came in with the new wave of fans but there's such a glaring difference between how I and the fans I interact with operate and how cc fans operate that it makes me pause sometimes.

And I can't say too much because I've seen some sane fans and I'm a paige fan and it still needs to be seen how much her hype translates outside of her personal bubble because I've seen quite a few people being stupid about her when it comes to uconn goats and you just immediately know they don't know shit about anything that's not her face but she made it click for me so im always gon be a little biased in my take that she actually does grow it outside of her.

Like I had been to my nba home games a handful of times throughout my years on earth and they were fun but it didn't make me give a rats ass outside of the time I spent in the arena so I thought I was safe in my hatred of sports and just liked the atmosphere of live events (true) and not basketball and I was a casual Angel defender whenever she popped up on social media because the massive racial backlash that put her on my radar was insane but I wasn't a fan I wasn't riding for her day in and day out I didn't tune in on purpose or by accident through the algorithm it still didn't make me realize I actually liked basketball yet but now, now it's like wow I'm literally the target audience I was supposed to end up here the whole time. Mind you I became a fan of Paige in April this year so every basketball game I've ever seen in real time has yet to actually involve her. She even got me mildly interested in the nba even though I still object on principle because I'm poor in both money and time and women > because she makes it unavoidable, she's so immersed in everything basketball.

That's the real difference between cc and Paige and the other girlies fanbases imo She's a very insulated person and obviously she had a different starting point than Paige with all the uconn alumni but p has put in the work for the connections with non alumni over the years and you see Juju and Flau'jae doing the work to immerse themselves right now and that's just never been her thing which is fine because I support doing your job and going tf home but it leads to a very different and largely insufferable fandom culture in this case because they have no respect for anyone thats not her they occasionally like people who exist on the peripheral of her life but the respect is little to nothing and its even easier to see now that she's on a professional team because they be talking crazy.

Paige is the chosen one. Paige Atreides. She's the Kwisatz Haderach. And Wasserman is the Bene Gesserit. Lindsay Kagawa Colas is the Reverend Mother arranging all the prophecies that Paige will fulfill.

Paige Atreides must come to WNBArrakis and learn our ways. And then she must liberate us from the Clarkonnens. Lisan Al Gaib! Lisan Al Gaib!

Okay but seriously I can't wait for Paige to come to the league. We need a fresh infusion of UConn fans to counteract all the negativity from CC's fanbase.

And as usual I have to put a disclaimer here. Disclaimer: not all Clark fans are Clarkonnens. But we need to be honest about the fact that Clarkonnens outnumber regular people in her fanbase. And many regular people are getting radicalized and turning into Clarkonnens because they're fed so much propaganda.

[anarchywoofwoof]

i spent the entirety of my work day today entangled in an absolute disaster situation that was ultimately propagated by the layoff of two managers who oversaw the operations of the involved teams. they were laid off august 23rd. the communication about this change and it's potential repercussions went out on august 25th to internal teams but they were already gone by that time. so guess what fell through the cracks and caused a major problem?

corporations have absolutely zero insight as to the impact of the decisions that they make at a corporate level. whether it's layoffs, restructuring, promotions, raises. they have no idea. it's all a finely tuned game of algorithms and business processes. everything is done in a vacuum and that vacuum usually involves spending the least amount of money. and without fail, it blows up in their faces every single time.

[blubberquark]

Language Models and AI Safety: Still Worrying

Previously, I have explained how modern "AI" research has painted itself into a corner, inventing the science fiction rogue AI scenario where a system is smarter than its guardrails, but can easily outwitted by humans.

Two recent examples have confirmed my hunch about AI safety of generative AI. In one well-circulated case, somebody generated a picture of an "ethnically ambiguous Homer Simpson", and in another, somebody created a picture of "baby, female, hispanic".

These incidents show that generative AI still filters prompts and outputs, instead of A) ensuring the correct behaviour during training/fine-tuning, B) manually generating, re-labelling, or pruning the training data, C) directly modifying the learned weights to affect outputs.

In general, it is not surprising that big corporations like Google and Microsoft and non-profits like OpenAI are prioritising racist language or racial composition of characters in generated images over abuse of LLMs or generative art for nefarious purposes, content farms, spam, captcha solving, or impersonation. Somebody with enough criminal energy to use ChatGPT to automatically impersonate your grandma based on your message history after he hacked the phones of tens of thousands of grandmas will be blamed for his acts. Somebody who unintentionally generates a racist picture based on an ambiguous prompt will blame the developers of the software if he's offended. Scammers could have enough money and incentives to run the models on their own machine anyway, where corporations have little recourse.

There is precedent for this. Word2vec, published in 2013, was called a "sexist algorithm" in attention-grabbing headlines, even though the bodies of such articles usually conceded that the word2vec embedding just reproduced patterns inherent in the training data: Obviously word2vec does not have any built-in gender biases, it just departs from the dictionary definitions of words like "doctor" and "nurse" and learns gendered connotations because in the training corpus doctors are more often men, and nurses are more often women. Now even that last explanation is oversimplified. The difference between "man" and "woman" is not quite the same as the difference between "male" and "female", or between "doctor" and "nurse". In the English language, "man" can mean "male person" or "human person", and "nurse" can mean "feeding a baby milk from your breast" or a kind of skilled health care worker who works under the direction and supervision of a licensed physician. Arguably, the word2vec algorithm picked up on properties of the word "nurse" that are part of the meaning of the word (at least one meaning, according tot he dictionary), not properties that are contingent on our sexist world.

I don't want to come down against "political correctness" here. I think it's good if ChatGPT doesn't tell a girl that girls can't be doctors. You have to understand that not accidentally saying something sexist or racist is a big deal, or at least Google, Facebook, Microsoft, and OpenAI all think so. OpenAI are responding to a huge incentive when they add snippets like "ethnically ambiguous" to DALL-E 3 prompts.

If this is so important, why are they re-writing prompts, then? Why are they not doing A, B, or C? Back in the days of word2vec, there was a simple but effective solution to automatically identify gendered components in the learned embedding, and zero out the difference. It's so simple you'll probably kick yourself reading it because you could have published that paper yourself without understanding how word2vec works.

I can only conclude from the behaviour of systems like DALL-E 3 that they are either using simple prompt re-writing (or a more sophisticated approach that behaves just as prompt rewriting would, and performs as badly) because prompt re-writing is the best thing they can come up with. Transformers are complex, and inscrutable. You can't just reach in there, isolate a concept like "human person", and rebalance the composition.

The bitter lesson tells us that big amorphous approaches to AI perform better and scale better than manually written expert systems, ontologies, or description logics. More unsupervised data beats less but carefully labelled data. Even when the developers of these systems have a big incentive not to reproduce a certain pattern from the data, they can't fix such a problem at the root. Their solution is instead to use a simple natural language processing system, a dumb system they can understand, and wrap it around the smart but inscrutable transformer-based language model and image generator.

What does that mean for "sleeper agent AI"? You can't really trust a model that somebody else has trained, but can you even trust a model you have trained, if you haven't carefully reviewed all the input data? Even OpenAI can't trust their own models.

[spiders-hth-is-an-outlier]

I don't want to derail this post or argue with anyone about how to live laugh love their way through this vale of tears, but this is *such* a good summation of the perspective barriers between different types of readers.

My idea OF HELL is receiving an extensive rundown of the tone, themes, tropes, characters, etc of every book I pick up before I read it. Why bother at that point. Literally why fucking bother. I feel physical rage every time some desperately tap-dancing marketing rep attempts to spit a half-chewed novel into my mouth like I'm a goddamn three-day-old pigeon.

It is genuinely baffling to me how resistant people are now to just being taken on a ride. You know who enjoys it when the book has one paragraph of summary and three glowing reviews from other people who can write good? ME. THAT'S FOR ME, I'M THE AUDIENCE FOR THAT. I want a very general sense of genre (is it funny? Super cerebral? Will it scare the shit out of me?), and I want someone who's not an idiot to be like, Read this, shit, dude, it'll light your face on fire. After that, idk, man, whatever happens happens? Maybe I'll hate it, but at least I gave it a chance to make its case to me, you know?

Because that's what really bothers me about the desire to fine-tune your reading list to filter only for what you enjoyed before. It's not just that you'll inevitably cheat yourself out of the life-changing book that isn't what you thought you wanted until after you read it -- although that's true, you definitely will. It's the entire headspace of using reading as a means to reify the type of reader you are, the kind of thing you enjoy. Approaching books in that way means that, if you do the job right, you'll turn yourself into a Well-Read Person who never has to have a negative reaction to a book, and that's how we arrive at a culture of people who think they love books, but who actually love the pleasure of receiving exactly and specifically what you ordered. It's an algorithmic way of experiencing the world. It's the way of thinking that allows people to seriously contemplate the idea of ChatGPT fiction, because isn't that what these "AI"s are designed to do? Deliver whatever you ask it to? Learn what you want and give you that with as few deviations as possible?

Idk, man, the 80% of me that is just a chill hippie at heart is like, you can do whatever you want forever, so fine, read all the YA your heart desires, love and light. But the 20% of me that really, like, cares about the transformative power of art or some corny shit like that just experiences existential agony at the current landscape of the genre I love, where people are really actively pissed off because reading adult fiction is hard to do without ever encountering surprises. Yeah! It is hard to do that! It's supposed to be hard!

Anyway, the last really good novel I read was The Invisible Life of Addie LaRue, and it's hard to describe. I think you'd like it, though.

[synths-and-sensibility]

Help! Too many projects clamoring for my attention:

- DCO (in progress)

- VCA (prototyped, needs fine tuning)

- Envelope generator (not started)

- MIDI controller (built, needs coding)

- MIDI to gate/CV (not started)

- Karplus-Strong (algorithm needs refinement and expanding)

- Clock (need parts)

- Sequencer (need parts)

- Flanger/chorus (initial concept stage)

[uthra-krish]

The Skills I Acquired on My Path to Becoming a Data Scientist

Data science has emerged as one of the most sought-after fields in recent years, and my journey into this exciting discipline has been nothing short of transformative. As someone with a deep curiosity for extracting insights from data, I was naturally drawn to the world of data science. In this blog post, I will share the skills I acquired on my path to becoming a data scientist, highlighting the importance of a diverse skill set in this field.

The Foundation — Mathematics and Statistics

At the core of data science lies a strong foundation in mathematics and statistics. Concepts such as probability, linear algebra, and statistical inference form the building blocks of data analysis and modeling. Understanding these principles is crucial for making informed decisions and drawing meaningful conclusions from data. Throughout my learning journey, I immersed myself in these mathematical concepts, applying them to real-world problems and honing my analytical skills.

Programming Proficiency

Proficiency in programming languages like Python or R is indispensable for a data scientist. These languages provide the tools and frameworks necessary for data manipulation, analysis, and modeling. I embarked on a journey to learn these languages, starting with the basics and gradually advancing to more complex concepts. Writing efficient and elegant code became second nature to me, enabling me to tackle large datasets and build sophisticated models.

Data Handling and Preprocessing

Working with real-world data is often messy and requires careful handling and preprocessing. This involves techniques such as data cleaning, transformation, and feature engineering. I gained valuable experience in navigating the intricacies of data preprocessing, learning how to deal with missing values, outliers, and inconsistent data formats. These skills allowed me to extract valuable insights from raw data and lay the groundwork for subsequent analysis.

Data Visualization and Communication

Data visualization plays a pivotal role in conveying insights to stakeholders and decision-makers. I realized the power of effective visualizations in telling compelling stories and making complex information accessible. I explored various tools and libraries, such as Matplotlib and Tableau, to create visually appealing and informative visualizations. Sharing these visualizations with others enhanced my ability to communicate data-driven insights effectively.

Machine Learning and Predictive Modeling

Machine learning is a cornerstone of data science, enabling us to build predictive models and make data-driven predictions. I delved into the realm of supervised and unsupervised learning, exploring algorithms such as linear regression, decision trees, and clustering techniques. Through hands-on projects, I gained practical experience in building models, fine-tuning their parameters, and evaluating their performance.

Database Management and SQL

Data science often involves working with large datasets stored in databases. Understanding database management and SQL (Structured Query Language) is essential for extracting valuable information from these repositories. I embarked on a journey to learn SQL, mastering the art of querying databases, joining tables, and aggregating data. These skills allowed me to harness the power of databases and efficiently retrieve the data required for analysis.

Domain Knowledge and Specialization

While technical skills are crucial, domain knowledge adds a unique dimension to data science projects. By specializing in specific industries or domains, data scientists can better understand the context and nuances of the problems they are solving. I explored various domains and acquired specialized knowledge, whether it be healthcare, finance, or marketing. This expertise complemented my technical skills, enabling me to provide insights that were not only data-driven but also tailored to the specific industry.

Soft Skills — Communication and Problem-Solving

In addition to technical skills, soft skills play a vital role in the success of a data scientist. Effective communication allows us to articulate complex ideas and findings to non-technical stakeholders, bridging the gap between data science and business. Problem-solving skills help us navigate challenges and find innovative solutions in a rapidly evolving field. Throughout my journey, I honed these skills, collaborating with teams, presenting findings, and adapting my approach to different audiences.

Continuous Learning and Adaptation

Data science is a field that is constantly evolving, with new tools, technologies, and trends emerging regularly. To stay at the forefront of this ever-changing landscape, continuous learning is essential. I dedicated myself to staying updated by following industry blogs, attending conferences, and participating in courses. This commitment to lifelong learning allowed me to adapt to new challenges, acquire new skills, and remain competitive in the field.

In conclusion, the journey to becoming a data scientist is an exciting and dynamic one, requiring a diverse set of skills. From mathematics and programming to data handling and communication, each skill plays a crucial role in unlocking the potential of data. Aspiring data scientists should embrace this multidimensional nature of the field and embark on their own learning journey. If you want to learn more about Data science, I highly recommend that you contact ACTE Technologies because they offer Data Science courses and job placement opportunities. Experienced teachers can help you learn better. You can find these services both online and offline. Take things step by step and consider enrolling in a course if you’re interested. By acquiring these skills and continuously adapting to new developments, they can make a meaningful impact in the world of data science.

[sensoryloss]

AI art is a good thing because it lowers the bar of entry for people that otherwise have no acquired artistic talent. the so-called “theft” used by algorithms is no different than the intrinsically adapted plagiarism that any artist would claim as inspiration, ie the idea already existed on some level in some way, you’re simply adding your spin to it.

above all else, the best argument for AI art is that it does indeed take the prospective hypothetical money out of the hands of self-proclaimed “artists” whose work is lackluster garbage that doesn’t actually add anything of value to artistry. these are the most vocal in opposition to AI, and by no surprise, the most desperate to try to make money off of their work, who think that they in particular are the ones being harmed by this technology when the reality is they’ve built their entire artistic “career” on the masochist notion that their drivel would ever be worth more than the experience of creation itself and fine-tuning their craft into something that is actually valuable on a marketable level.

artistic expression is important but to think that you deserve financial compensation for a non-interesting non-original non-idea is delusional at best and narcissistic at worse, and the two seem to operate simultaneously within a large number of these people. if you want to make money from your craft, you’re much better off getting really good at digging ditches, although you will have to use tools and advanced technology in order to complete the goal, so please don’t let that deter you from the true nature of what it means to be a ditch digger the same way you’ve contorted the idea of what it means to be an artist.

algorithmically generated words/images/music have more artistic value than anything these people could ever create by virtue of the narrative, emotion, and conversation evoked in seemingly every direction by merely existing, whereas your OC and fanfics do nothing but induce nausea in anyone with actual talent and further reinforces the idea that “my artistic voice matters” in the minds of people whose voices do not matter at all, artistic or otherwise.

as someone with talent, or at least some level of discipline and skill who has defined themselves as an artist the majority of my life, I’m happy AI is here, I’m happy you hate it, and I’m even happier that it’s ruining your dreams.

it’s time to wake up.