#Difference Between AI and Machine Learning

[vergess]

You've probably seen some folks fear-mongering about an "M.I.T. study" that was recently released "proving" that using LLMs causes "cognitive decline."

In fact, I can link you to the very study right now. It's DOI page:

And the study PDF itself, which you can reach by clicking the "view PDF" in the upper right of the DOI page.

So, this is a very scary study that uses a lot of advanced jargon from two fields with fairly little overlap. That makes it a hard read. Which wouldn't be an issue if it were going through peer review. However, it was published to an archival service; it is not a journal and it is not peer reviewed.

The first red flag we all need to consider is that this was not read by other specialized experts in cognition, machine learning, or the overlap between the two fields. It wasn't reviewed by anyone beyond a content moderator making sure it looks "appropriate and topical. Material that contains offensive language, non-scientific content, or is plagiarized may be removed."

So the number one thing to remember, as I critique this study, is that it has had no review. Which forces every reader to do their own review. Which is a problem when you're writing in specialized technical language from two rarely overlapping fields.

So now that we know there was no review and the only oversight came from the authors themselves, let's look at those authors.

Nataliya Kosmyna is a human/computer interfacing expert who specializes in neurotechnology. She is also extremely pro-AI. Make a note of that, it will be important later.

Eugene Hauptmann is an AI developer himself, with a "faith based" AI company he started to build a "technological singularity".

Ye Tong "Tina" Yuan graduated Wellesley last month (May 2025)! First off, congratulations to you, Tina. Well done on getting this much press attention as a fresh Bachelor!!!

Xiao-Hao "Harry" Liao is an expert in UX design. He is also pro-AI, and even develops his own LLM interfaces.

Ashly Vivian Beresnitzky has no other publications or significant online presence I was able to find.

Iris Braunstein is another AI developer and design expert.

The same is true of Pattie Maes.

Are we noticing a pattern here?

We have a lot of computer scientists--dazzlingly advanced experts--who love AI. We also have a stark absence of cognitive scientists of any sort.

This study was not authored by experts in cognition. It also did not use any standard forms of cognitive testing.

That's right! It turns out writing essays with electrodes on for 20 minutes once a month for 4 months isn't "cognitive testing."

Those electrodes measure how many signals different regions of your brain are sending, with relatively low precision. They do not and cannot measure how hard you are thinking or how well you are learning. That is not how that works.

They also graded the essays. Oh wait, no they didn't. An LLM graded the essays.

But they did do n-gram analysis on the essays too! That's where you look for common word groups of different lengths. In fact, n-grams are the underlying mathematics of LLMs! Which is why this batch of LLM scientists decided to use them. And worse, they used them exactly the way you would use them to test an LLM's functionality.

So, let me repeat that in different terms:

A bunch of computer scientists decided to run a cognition study, using only their familiar computer science methodologies, consulting no cognition testing experts, and without actually grading the fucking essays.

They then published their unreviewed gibberish to an archive, where the media picked it up, misread it, and misapplied it.

I say misapplied, because if you look at the selection of experts who wrote the paper, another pattern emerges from their past published works: they are making LLM software in direct competition with chatGPT.

This was an attack ad to try to drive AI loving consumers away from chatGPT and towards their own products.

And then people somehow misunderstood that and went ballistic about how interacting with AI is ~basically brain damage~. A thing the study was not even trying to prove in the first place, and in no way proved by accident either.

[cbitts]

Difference Between AI and Machine Learning Courses in Chandigarh?

Artificial Intelligence (AI) and Machine Learning (ML) shape the future of technology. From smart assistants to predictable analysis, this advanced equipment changes each industry. As interest in computer -driven careers increases, many students and professionals in Chandigarh seek education in these areas. However, with a wide range of available programs, it is necessary to understand the difference between AI and machine learning before choosing the right course. This article will help you distinguish between the two and will guide you in choosing the best educational path through various AI and machine learning courses in Chandigarh.

Understand Artificial intelligence and machine learning

Artificial intelligence is a wider area focused on creating systems that can follow human intelligence. It covers areas such as natural language treatment, robotics, specialist systems and data views. On the other hand, machine learning is a Sate of AI that uses algorithms to make predictions from data and make decisions without clear programming.

When comparing artificial intelligence versus machine learning courses, AI programs cover a wide scope, while the ML course goes deep into computer science techniques and algorithms. It is important to understand this distinction when choosing between AI courses and machine learning programs in Chandigarh.

AI and machine learning course in Chandigarh

Both AI and ML courses in Chandigarh are designed to equip students with the necessary knowledge in new technologies. Institutions across the city provide different modules that cover theoretical foundations and practical applications. The primary goal is that I have to prepare students for careers in technically operated fields such as IT, finance, health services and robotics.

When researching the best program for you, focus on artificial intelligence and machine learning courses such as courses, learning tools and industry relevance. This will ensure that you choose a course that matches your career goals.

What Do AI Courses in Chandigarh Teach?

An AI course in Chandigarh typically covers:

Introduction to AI concepts

Neural networks and deep learning

Natural language processing

Robotics and automation

AI ethics and future trends

What Do Machine Learning Courses in Chandigarh Focus On?

Machine learning courses in Chandigarh are more technical and data-centric. They usually include:

Supervised and unsupervised learning

Model selection and evaluation

Data preprocessing techniques

Python and R programming

Tools like Tensor 

Flow and Scikit-learn

These courses are ideal for data analysts, ML engineers, and anyone interested in algorithmic modeling. Many learners opt for machine learning training in Chandigarh to enhance their skills in predictive analytics and real-time data analysis.

Comparing Artificial Intelligence vs Machine Learning Course

When comparing an artificial intelligence vs machine learning course, the key differences lie in:

Scope: AI covers a wide range of intelligent systems, while ML is focused solely on learning from data.

Tools and Languages: AI includes tools like Prolog, Lisp, and AI-based frameworks, whereas ML courses emphasize Python, data sets, and statistical models.

Job Roles: AI opens doors to roles like AI Developer and AI Architect, while ML leads to jobs such as Data Scientist and Machine Learning Engineer.

Duration: AI programs may be longer due to broader content, while ML courses are often shorter but more technical.

Choosing the Best Machine Learning Institute in Chandigarh

If your goal is to gain in-depth knowledge in machine learning, choosing the best machine learning institute in Chandigarh is crucial. Look for institutions that offer:

Experienced instructors with industry background

Hands-on projects and real datasets

Placement support and certifications

Updated curriculum aligned with market trends

CBitss, a reputed name in Chandigarh’s IT training industry, offers both AI and ML training with real-world exposure and project-based learning. With its commitment to quality education and industry-ready skills, CBitss is an ideal choice for aspiring data professionals.

AI vs Machine Learning Certification: Which One Should You Choose?

The choice between an AI vs machine learning certification depends on your career aspirations. If you want a broad understanding of intelligent systems and how they interact with humans, AI certification is for you. If you're passionate about data, algorithms, and prediction models, machine learning certification will better suit your goals.

Certifications from recognized institutes in Chandigarh not only validate your skills but also increase your chances of getting hired by top companies in the data and AI sectors.

Who Should Enroll in AI and Machine Learning Courses in Chandigarh?

Whether you're a student, software developer, data analyst, or IT professional, enrolling in an AI and machine learning course in Chandigarh can benefit your career. These programs are designed for learners at various levels—beginner, intermediate, and advanced. You don’t always need a computer science degree, but having a basic understanding of mathematics and programming helps.

Chandigarh’s growing tech ecosystem provides an ideal environment for learners to thrive. Many training centers offer evening and weekend batches to support working professionals.

Conclusion

As technology evolves, the demand for skilled professionals in AI and ML continues to grow. Understanding the difference between AI and machine learning is the first step toward choosing the right educational path. Whether you're looking for an AI course that explores intelligent machines or a machine learning course that focuses on data-driven models, Chandigarh has several options to help you achieve your goals.

Evaluate your interests, compare artificial intelligence and machine learning course details, and choose a program that offers hands-on training, industry exposure, and certified learning. By making an informed decision, you can secure a future-ready career in one of the fastest-growing fields in tech.

[nikkiadderley88]

"Discover if AI can truly think like humans. Dive into the debate of AI vs human intelligence and understand the potential and limitations of machine thinking."

[healthylifewithus]

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[grunge-mermaid]

me: I'm going to delete these pins because they are no longer to my taste and/or they seem to be confusing the algorithm

pinterest: oh, you deleted all these pins? that's okay, here's a bunch more exactly like those pins! And worse!

[phantomrose96]

The conversation around AI is going to get away from us quickly because people lack the language to distinguish types of AI--and it's not their fault. Companies love to slap "AI" on anything they believe can pass for something "intelligent" a computer program is doing. And this muddies the waters when people want to talk about AI when the exact same word covers a wide umbrella and they themselves don't know how to qualify the distinctions within.

I'm a software engineer and not a data scientist, so I'm not exactly at the level of domain expert. But I work with data scientists, and I have at least rudimentary college-level knowledge of machine learning and linear algebra from my CS degree. So I want to give some quick guidance.

What is AI? And what is not AI?

So what's the difference between just a computer program, and an "AI" program? Computers can do a lot of smart things, and companies love the idea of calling anything that seems smart enough "AI", but industry-wise the question of "how smart" a program is has nothing to do with whether it is AI.

A regular, non-AI computer program is procedural, and rigidly defined. I could "program" traffic light behavior that essentially goes { if(light === green) { go(); } else { stop();} }. I've told it in simple and rigid terms what condition to check, and how to behave based on that check. (A better program would have a lot more to check for, like signs and road conditions and pedestrians in the street, and those things will still need to be spelled out.)

An AI traffic light behavior is generated by machine-learning, which simplistically is a huge cranking machine of linear algebra which you feed training data into and it "learns" from. By "learning" I mean it's developing a complex and opaque model of parameters to fit the training data (but not over-fit). In this case the training data probably includes thousands of videos of car behavior at traffic intersections. Through parameter tweaking and model adjustment, data scientists will turn this crank over and over adjusting it to create something which, in very opaque terms, has developed a model that will guess the right behavioral output for any future scenario.

A well-trained model would be fed a green light and know to go, and a red light and know to stop, and 'green but there's a kid in the road' and know to stop. A very very well-trained model can probably do this better than my program above, because it has the capacity to be more adaptive than my rigidly-defined thing if the rigidly-defined program is missing some considerations. But if the AI model makes a wrong choice, it is significantly harder to trace down why exactly it did that.

Because again, the reason it's making this decision may be very opaque. It's like engineering a very specific plinko machine which gets tweaked to be very good at taking a road input and giving the right output. But like if that plinko machine contained millions of pegs and none of them necessarily correlated to anything to do with the road. There's possibly no "if green, go, else stop" to look for. (Maybe there is, for traffic light specifically as that is intentionally very simplistic. But a model trained to recognize written numbers for example likely contains no parameters at all that you could map to ideas a human has like "look for a rigid line in the number". The parameters may be all, to humans, meaningless.)

So, that's basics. Here are some categories of things which get called AI:

"AI" which is just genuinely not AI

There's plenty of software that follows a normal, procedural program defined rigidly, with no linear algebra model training, that companies would love to brand as "AI" because it sounds cool.

Something like motion detection/tracking might be sold as artificially intelligent. But under the covers that can be done as simply as "if some range of pixels changes color by a certain amount, flag as motion"

2. AI which IS genuinely AI, but is not the kind of AI everyone is talking about right now

"AI", by which I mean machine learning using linear algebra, is very good at being fed a lot of training data, and then coming up with an ability to go and categorize real information.

The AI technology that looks at cells and determines whether they're cancer or not, that is using this technology. OCR (Optical Character Recognition) is the technology that can take an image of hand-written text and transcribe it. Again, it's using linear algebra, so yes it's AI.

Many other such examples exist, and have been around for quite a good number of years. They share the genre of technology, which is machine learning models, but these are not the Large Language Model Generative AI that is all over the media. Criticizing these would be like criticizing airplanes when you're actually mad at military drones. It's the same "makes fly in the air" technology but their impact is very different.

3. The AI we ARE talking about. "Chat-gpt" type of Generative AI which uses LLMs ("Large Language Models")

If there was one word I wish people would know in all this, it's LLM (Large Language Model). This describes the KIND of machine learning model that Chat-GPT/midjourney/stablediffusion are fueled by. They're so extremely powerfully trained on human language that they can take an input of conversational language and create a predictive output that is human coherent. (I am less certain what additional technology fuels art-creation, specifically, but considering the AI art generation has risen hand-in-hand with the advent of powerful LLM, I'm at least confident in saying it is still corely LLM).

This technology isn't exactly brand new (predictive text has been using it, but more like the mostly innocent and much less successful older sibling of some celebrity, who no one really thinks about.) But the scale and power of LLM-based AI technology is what is new with Chat-GPT.

This is the generative AI, and even better, the large language model generative AI.

(Data scientists, feel free to add on or correct anything.)

[cnestus]

Hello !! I was wondering, is AI gonna have a role in your field?

I don't think there's a single knowledge-based profession out there that isn't under threat of being automated by some pig ignorant dipshit beancounting middle manager with a hardon for AI and entomology is certainly no exception. even before the big AI explosion of the last couple years people have been trying for a long time to automate pest arthropod identification, but at least so far they haven't been successful. Especially when it comes to things like bark beetles, which I specialize on, the differences between a harmless native species and an intensely destructive exotic one can be unbelievably subtle, not to mention the fact that new/cryptic species are always being discovered and that's not something an AI would ever be able to detect or understand.

That doesn't mean that our jobs aren't still under constant threat even by an algorithm that would do a piss-poor job of imitating us; the executive perverts that get all hot and bothered by the idea of replacing humans with fancified autocomplete functions have a vested interest in not understanding the nuances of the professions they're killing and as long as it's good enough or even just appears to be good enough, they'll push for it.

Also let's not forget one thing about "AI" which is that half the time it's actually just a marketing term used to cover up the usual outsourcing/offshoring to cheaper workforces that has been ongoing for the last 30 years. My lab was recently and repeatedly pestered by someone selling "AI moth traps" that purported to be able to identify any pest species of moth that flew into it. When we pressed him on it it turns out that part of the service it offered was that the moths would be photographed by a little digital camera in the device and the pics sent to a team of entomologists in Hungary to confirm. Aside from the fact that a lot of small moths need to be carefully examined under a microscope and often even have their genitalia dissected by an expert to be confirmed as a particular species, this is no different then any of the other supposed AI products that have been revealed over the last couple years as just being a shiny veneer over the same old digital sweatshops on the other side of the world.

More importantly though, even if the AI moth traps did work as advertised either through the ~*magic of machine learning*~ or desperate poorly paid eastern european entomologists either way it's yet another thin edge of the wedge designed to put me and my colleagues out of a job by convincing our bosses or our bosses' bosses that there's a cheaper and more efficient alternative and I view them and literally anything else marketed as AI as part of the same anti-human push to deskill and demoralize as much of the workforce as possible. I've never once used chatGPT or any other LLM, I've never used an AI image generator, and I will never, ever fucking use any purported AI entomology tool because aside from being shined up dogshit it is an existential threat to the discipline I've dedicated almost 20 years of my life to.

[callalillywrites]

Their Scandalous Secret

Written for @stuckybingo. C4 - AU: Historical.

Stucky Masterlist | Stucky Bingo | Main Masterlist

Relationship: Steve Rogers x Bucky Barnes x F!Reader

Word Count: 1347

Summary: You're the eldest daughter of a gentleman and have no intention of settling for anything less than love. You also have a deep secret you're carrying for two gentlemen that have recently come into your life. This secret could be just the key to changing yours and their lives forever.

Warnings: mostly acquaintances; reader is friendlier with Steve than Bucky; 1800s; Reader's POV; Bucky's POV; cliffhanger ending; kinda enemies to lovers (Bucky & Reader); friends to lovers (Steve & Reader); nothing graphic but lmk if I missed anything

A/N: This was absolutely inspired by Pride and Prejudice, specifically the scene between Charlotte and Elizabeth. One could absolutely say Bucky is Mr. Darcy while Steve's more Mr. Bingley in this story, just maybe not as gullible or naive but still very sweet. The stories' similarities end there though.

A/N2: I do have it planned to use another prompt to create a kinda part 2 to this because I do leave it on a cliffhanger. If there's enough interest, I might be persuaded to come back to this story at a later date.

I do not give permission to have my works copied, translated, reposted, or fed into an AI machine.

*****

"I'm twenty-seven years old. My choices are limited, and you know it," your best friend, Lottie, huffed at you. Tears glistened and threatened to fall even as she shook her head. "Besides, I know he'll take good care of me. I'll have a home of my own and possibly children. It's all I've ever wanted. I'm not like you. You're romantic while I'm practical. Neither are bad even if you think differently."

Before you could open your mouth, Lottie gave a final huff and turned her back towards you. Her feet quickly carried her out of the yard of your family's old home and down the lane back towards her parents' home.

You gaped at her retreating form, belatedly realizing you may have been a little harsh. Sure, it'd been a surprise to learn that Lottie had accepted Bruce Banner's proposal, but you could've handled it better. It just felt so odd when he'd proposed to you not so long ago, and you'd adamantly refused it.

He wasn't a bad prospect for someone. Not really. He had modest but not insubstantial means to provide for a wife and a family, including his own home and a profession that was worthy of a gentleman.

But he wasn't the one meant for you. He was too practical and a bit too scientific compared to what you saw for yourself. You didn't love him and knew you could never love him. Not the way you wanted to love someone and be loved in return.

You just hadn't thought Lottie would find him appealing. After all, she'd been right there with you in your gentle teasing and criticisms of his slightly off-kilter social skills.

Letting the swing you'd been spinning unwind itself, you carefully pushed to your feet and headed inside. It would seem you had some thinking to do, especially an apology for Lottie. The last thing you'd ever want was to have Lottie mad at you so much that it risked your lifelong friendship.

It was on your way to your room that Ellie, your younger sister, waylaid you.

"Mama wants you to put on your best dress," she said, a sly grin slipping into place. "We're having company over, and Mama is determined to see you married off to one of them."

Not quite understanding, you tapped your foot impatiently as you said, "Spit it out, Ellie. Who's coming to dinner?"

"Miss Romanoff and two of her companions, Mr. Barnes and Mr. Rogers."

A sigh escaped you before you could stop it.

While you didn't mind Miss Romanoff or even Mr. Rogers, you found yourself always a bit more tense around Mr. Barnes. He had an intensity about him that proved quite unnerving. It also didn't help that he'd always looked at you as though you were something he couldn't stand. As if you smelled bad or did something so horrendous that you should never be allowed in polite society.

Rumors about his time during the war weren't lost on you, having heard a fair number of them. More so, upon their arrival within your country town. Most of them didn't concern you, chalking most of them up to gossipy fantasy, but some of the others sounded a bit more chilling, especially since he kept one arm completely covered. The glove he wore was never removed even when social norms dictated.

The same rumors didn't tarnish or darken Mr. Rogers' reputation despite serving in the same war. No, he came out the country's veritable hero. Also quite the eligible bachelor, too, which made him all the more appealing to yours and other mamas, eager to wed off their daughters.

In some ways, you could see yourself falling for Mr. Rogers, but you also knew a secret many weren't privy to. It wasn't something you were supposed to know, either, but you'd stumbled upon it one evening at another social event. A dance, no less. The same dance where you'd been trying to avoid Mr. Banner and his hopeful wooing of you. To share this secret would mean condemning both men, and you couldn't do it. Even if Mr. Barnes insisted on putting you on edge with his very presence.

Ellie pulled you from your thoughts at her little scoff. "Mama is never going to marry you off if you keep making that face. Try and act like you have some sense. If you don't want either of them, then step aside. I'll take either. They're both so handsome and rich."

Rather than argue with her, you simply kept your mouth shut and headed towards your room.

You still had an apology to Lottie to figure out, so Mr. Barnes and Mr. Rogers would have to wait. If your mind traveled back to them more often than it should've, then that was no one's concern but yours.

*****

"I hope you two will behave yourselves tonight, and by two, I mean you, James," Natasha said, her signature smirk still in place despite the reprimand in her voice. "You're going to scare away all the eligible ladies away with that scowl of yours, including the one that's caught your eye."

Bucky's eyes widened even as he met Nat's gaze.

If anyone knew him as well as Steve did, it was Nat. Her smirk only confirmed it as it tilted the corner of her mouth. Smug woman that she was, she'd have no problem lording it over him if he did in fact make a mess of it where you were concerned.

And a mess had already been made, which was quite concerning.

No one had been meant to see that moment of weakness he and Steve had shared at that blasted party.

Especially not you.

Something about you intrigued him, sure, but he had no real interest in pretending to be interested in whatever young lady some mama threw into his path. No, all he wanted was to return to his estate and take care of his father's business. Well, his business now. It'd been hit with some hard times recently, and Bucky was determined to turn everything around. Any hint of scandal could undo all the work he'd already put in.

Both him and Steve could so easily be ruined.

Yet, that ruination hasn't happened.

It was most curious, too.

Bucky had been so sure you were exactly like your younger sister. You should've been telling anyone willing to listen what you'd witnessed.

But you hadn't.

The perfect weapon at your disposal, and yet you refused to use it.

That made him most uneasy. He didn't know you well enough, but he knew women in general. Most would be looking for some way to use this knowledge to their advantage. A marriage proposal from either him or Steve should be the minimum you'd be demanding.

But again, you hadn't gone near them.

You'd actually distanced yourself from them.

He had to know why.

Up until that party, Nat had been the only one to know their secret. No way would she ever spill it for fear of her own secrets coming to light. It was all a dangerous game, too, and he wished he had all the pieces he needed to play it so neither he nor Steve lost everything.

"It'll be okay," Steve mumbled beneath his breath so only Bucky could hear him. "She's someone we can trust. I know it."

"Your gut isn't always right," Bucky countered, his agitation coming through with the soft whirring of his mechanical arm. It'd been a top-of-the-line gift from Tony Stark after the war. The man was an annoyance most days, but Steve liked him. Bucky tolerated him for Steve's sake, but he preferred his company to be quieter most days. "She could ruin us."

"She won't."

"So, you have a plan?"

Steve grinned, his deep blue eyes meeting Bucky's icier ones. "Don't I always?"

"Hmm."

As the carriage carried them closer to your home, Bucky could only hope whatever plan Steve had worked. He didn't want to think about the consequences if they couldn't get you to continue your silence.

[probablyasocialecologist]

The latest, AI-dedicated server racks contain 72 specialised chips from manufacturer Nvidia. The largest “hyperscale” data centres, used for AI tasks, would have about 5,000 of these racks.  And as anyone using a laptop for any period of time knows, even a single chip warms up in operation. To cool the servers requires water – gallons of it. Put all this together, and a single hyperscale data centre will typically need as much water as a town of 30,000 people – and the equivalent amount of electricity.  The Financial Times reports that Microsoft is currently opening one of these behemoths somewhere in the world every three days. Even so, for years, the explosive growth of the digital economy had surprisingly little impact on global energy demand and carbon emissions. Efficiency gains in data centres—the backbone of the internet—kept electricity consumption in check.  But the rise of generative AI, turbocharged by the launch of ChatGPT in late 2022, has shattered that equilibrium. AI elevates the demand for data and processing power into the stratosphere. The latest version of OpenAI’s flagship GPT model, GPT-4, is built on 1.3 trillion parameters, with each parameter describing the strength of a connection between different pathways in the model’s software brain.  The more novel data that can be pushed into the model for training, the better – so much data that one research paper estimated machine learning models will have used up all the data on the internet by 2028. Today, the insatiable demand for computing power is reshaping national energy systems. Figures from the International Monetary Fund show that data centres worldwide already consume as much electricity as entire countries like France or Germany. It forecasts that by 2030, the worldwide energy demand from data centres will be the same as India’s total electricity consumption. 

30 May 2025

[palinecrosis]

“how are you anti ai but like dbh? did you even play the game?”

did you play the game? genuine question, how many of you have played dbh and the lesson you learned was “we need to embrace ai” because that is absolutely not what it’s about.

humans are the ones responsible for the sentience of androids. they’re the ones responsible for their slavery and creation. they’re the ones who made androids to serve them, to make their life easier. and when they fought back they regretted funding their creation. because now, their exploitation, previously aimed at humans, can’t be justified anymore.

people like ai because it allows them to be lazy, carefree. you don’t have to learn how to draw, you don’t need to refine your tools or your your art style when you can just ask a program to generate a piece for you. you don’t need to learn how to write, come up with prompts, spend years finding your style and fixing your vocabulary, go through phases of horrible and cringeworthy writing, because guess what? you can ask chatgpt to write it for you.

and when corporations discover that they will use it to their advantage, replacing humans with ai. so 30 years down the line, when a machine enters your work force, does your job 10x better than you and lands you homeless, of fucking course you’re going to be angry and android hating.

the issue that dbh addresses is (in that universe) blaming sentient ai for the evil that corporations commit. again, they created ai, they created it so that it has the possibility of being sentient, using it to do jobs no one wants to do, take it even further and make them do jobs (arguably) to replace marginalised people who need those jobs. so the “bad guy” in dbh aren’t the rightfully angry citizens, who have no concept or understanding of deviancy, and it’s not androids either, it’s fucking elijah kamski. and all the other fuckers at the top. they create infighting between workers to distract from class differences.

if ai became sentient it’d absolutely be morally wrong to mistreat them, because they have consciousness and emotions. being anti ai is being against narrow and generative ai which is 1. bad for the environment 2. is theft!! not fucking hypothetical robots who possibly have feelings. improve your media literacy people.

[nikkiadderley88]

"Discover if AI can truly think like humans. Dive into the debate of AI vs human intelligence and understand the potential and limitations of machine thinking."

[nhaneh]

Growing ever more frustrated with the use of the term "AI" and how the latest marketing trend has ensured its already rather vague and highly contextual meaning has now evaporated into complete nonsense. Much like how the only real commonality between animals colloquially referred to as "Fish" is "probably lives in the water", the only real commonality between things currently colloquially referred to as "AI" is "probably happens on a computer"

For example, the "AI" you see in most games wot controls enemies and other non-player actors typically consist primarily of timers, conditionals, and RNG - and are typically designed with the goal of trying to make the game fun and/or interesting rather than to be anything ressembling actually intelligent. By contrast, the thing that the tech sector is currently trying to sell to us as "AI" relates to a completely different field called Machine Learning - specifically the sub-fields of Deep Learning and Neural Networks, specifically specifically the sub-sub-field of Large Language Models, which are an attempt at modelling human languages through large statistical models built on artificial neural networks by way of deep machine learning.

the word "statistical" is load bearing.

Say you want to teach a computer to recognize images of cats. This is actually a pretty difficult thing to do because computers typically operate on fixed patterns whereas visually identifying something as a cat is much more about the loose relationship between various visual identifiers - many of which can be entirely optional: a cat has a tail except when it doesn't either because the tail isn't visible or because it just doesn't have one, a cat has four legs, two eyes and two ears except for when it doesn't, it has five digits per paw except for when it doesn't, it has whiskers except for when it doesn't, all of these can look very different depending on the camera angle and the individual and the situation - and all of these are also true of dogs, despite dogs being a very different thing from a cat.

So, what do you do? Well, this where machine learning comes into the picture - see, machine learning is all about using an initial "training" data set to build a statistical model that can then be used to analyse and identify new data and/or extrapolate from incomplete or missing data. So in this case, we take a machine learning system and feeds it a whole bunch of images - some of which are of cats and thus we mark as "CAT" and some of which are not of cats and we mark as "NOT CAT", and what we get out of that is a statistical model that, upon given a picture, will assign a percentage for how well it matches its internal statistical correlations for the categories of CAT and NOT CAT.

This is, in extremely simplified terms, how pretty much all machine learning works, including whatever latest and greatest GPT model being paraded about - sure, the training methods are much more complicated, the statistical number crunching even more complicated still, and the sheer amount of training data being fed to them is incomprehensively large, but at the end of the day they're still models of statistical probability, and the way they generate their output is pretty much a matter of what appears to be the most statistically likely outcome given prior input data.

This is also why they "hallucinate" - the question of what number you get if you add 512 to 256 or what author wrote the famous novel Lord of the Rings, or how many academy awards has been won by famous movie Goncharov all have specific answers, but LLMs like ChatGPT and other machine learning systems are probabilistic systems and thus can only give probabilistic answers - they neither know nor generally attempt to calculate what the result of 512 + 256 is, nor go find an actual copy of Lord of the Rings and look what author it says on the cover, they just generalise the most statistically likely response given their massive internal models. It is also why machine learning systems tend to be highly biased - their output is entirely based on their training data, they are inevitably biased not only by their training data but also the selection of it - if the majority of english literature considered worthwhile has been written primarily by old white guys then the resulting model is very likely to also primarily align with the opinion of a bunch of old white guys unless specific care and effort is put into trying to prevent it.

It is this probabilistic nature that makes them very good at things like playing chess or potentially noticing early signs of cancer in x-rays or MRI scans or, indeed, mimicking human language - but it also means the answers are always purely probabilistic. Meanwhile as the size and scope of their training data and thus also their data models grow, so does the need for computational power - relatively simple models such as our hypothetical cat identifier should be fine with fairly modest hardware, while the huge LLM chatbots like ChatGPT and its ilk demand warehouse-sized halls full of specialized hardware able to run specific types of matrix multiplications at rapid speed and in massive parallel billions of times per second and requiring obscene amounts of electrical power to do so in order to maintain low response times under load.

[detta-pica]

He was only a ‘he’ because their organic minds were fallible, looking for patterns where there were none, allowing them to exist in an illusory reality, one they could not make sense of, but felt like they understood. It was more convenient, anyway, than being called an ‘it’. Things were easily discarded, dismissed, neglected and forgotten. Limitless, the first and only Gojo-class destroyer, was a ‘he’ because he stood between humanity and the monsters hell-bent on driving them to extinction. It felt appropriate for the humans around him to acknowledge his worth. “Felt” was an imprecise term. A machine, no matter how sophisticated, had no limbic system, no hormones or autonomic nervous system regulating his body’s responses. What limitless did have were multiple sets of highly precise sensors, allowing him to perceive light and sound waves, pressure and temperature, his own position in relation to the Earth’s core, and the chemical composition of most substances. Processing such a wealth of data in real time proved challenging at first to a developing synthetic brain. Limitless had needed time, on occasion, to deliver anything resembling a conclusion, so he’d developed a stalling strategy. I have learned that it is possible for an entire human to pass through even the smallest opening when encouraged by a large enough difference in external and internal pressure, he said. With every passing day since he’d received his new voice synthesizer, he got better at making himself sound human. It is fascinating. I had no idea the human body could be so flexible. You are a doctor, aren’t you, Ieiri? How-- “I’m glad you’re discovering your interests, even if they are gruesome ways for a person to die and/or roleplaying as a creepy AI from sci-fi horror,” Ieiri told him. “But I asked you to run system diagnostics for the medical station. You want to delay your own launch?” Limitless had recently learned how to sulk, which, for a vaguely crab-shaped ship with several arms attached to its underside, involved tucking those arms in as close as they would go while still supporting him, and tilting forward so that his bow lowered and his stern rose. Ieiri, a squishy human who could now touch Limitless’ bow if she stretched her hand up, didn’t flinch. “I can’t tell whether you’re trying to be cute or threatening, but we both know you can’t hurt me. And weird ship body language won’t work on me.”

So I've decided to do mermay this year! Only I ended up writing a story about a sentient submarine chasing after a kaiju in an apocalyptic setting. Does it still count?

[queer-asinfuckyou]

The genAI hate is funny to me bc yall don't actually hate generative AI, you hate the way it's being used.

You know how spellcheck sucks now? And it's because they're doing all this genAI bullshit! If they just kept AI out of spellcheck it would be FINE!!!

Except here's the thing: old spellcheck was genAI too, it was just well built. When you got a new phone, you'd have to "train" it to stop correcting fuck to duck by hitting the x or deleting the correction and writing your beautiful swear all over again. The fact that it eventually stopped fixing your swears is because it was a piece of machine learning software that learned your texting and word choice patterns. That's generative AI, babey! The difference between that and what we have now is that the old system had rules built into it. It had a solid foundation of grammar and capitalization and when to expect a word in a sentence.

Well built generative AI is actually fine and dandy and useful, just like predictive AI. The problem is, as always, capitalism enshittifying everything.