Generative Ai Quotes

“The lack of transparency regarding training data sources and the methods used can be problematic. For example, algorithmic filtering of training data can skew representations in subtle ways. Attempts to remove overt toxicity by keyword filtering can disproportionately exclude positive portrayals of marginalized groups. Responsible data curation requires first acknowledging and then addressing these complex tradeoffs through input from impacted communities.”
― I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

“It is critical to recognize the limitations of LLMs from a consumer perspective. LLMs only possess statistical knowledge about word patterns, not true comprehension of ideas, facts, or emotions. Their fluency can create an illusion of human-like understanding, but rigorous testing reveals brittleness. Just because a LLM can generate coherent text about medicine or law doesn’t mean it grasps those professional domains. It does not. Responsible evaluation is essential to avoid overestimating capabilities.”
― I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

“Every piece of data ingested by a model plays a role in determining its behavior. The fairness, transparency, and representativeness of the data reflect directly in the LLMs' outputs. Ignoring ethical considerations in data sourcing can inadvertently perpetuate harmful stereotypes, misinformation, or gaps in knowledge. It can also infringe on the rights of data creators.”
― I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

“Open source philosophies once promised to democratize access to cutting-edge technologies radically. Yet for AI, the eventual outcome of the high-stakes battle between open and closed systems remains highly uncertain.
Powerful incentives pull major corporate powers to co-opt open source efforts for greater profit and control, however subtly such dynamics might unfold. Yet independent open communities intrinsically chafe against restrictions and centralized control over capacity to innovate. Both sides are digging in for a long fight.”
― I. Almeida, Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype

“Imagine an alternate universe in which people don’t have words for different forms of transportation—only the collective noun “vehicle.” They use that word to refer to cars, buses, bikes, spacecraft, and all other ways of getting from place A to place B. Conversations in this world are confusing. There are furious debates about whether or not vehicles are environmentally friendly, even though no one realizes that one side of the debate is talking about bikes and the other side is talking about trucks. There is a breakthrough in rocketry, but the media focuses on how vehicles have gotten faster—so people call their car dealer (oops, vehicle dealer) to ask when faster models will be available. Meanwhile, fraudsters have capitalized on the fact that consumers don’t know what to believe when it comes to vehicle technology, so scams are rampant in the vehicle sector.

Now replace the word “vehicle” with “artificial intelligence,” and we have a pretty good description of the world we live in.

Artificial intelligence, AI for short, is an umbrella term for a set of loosely related technologies. ChatGPT has little in common with, say, software that banks use to evaluate loan applicants. Both are referred to as AI, but in all the ways that matter—how they work, what they’re used for and by whom, and how they fail—they couldn’t be more different.”
― Arvind Narayanan, AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference

“[All] modern chatbots are actually trained simply to predict the next word in a sequence of words. They generate text by repeatedly producing one word at a time. For technical reasons, they generate a “token” at a time, tokens being chunks of words that are shorter than words but longer than individual letters. They string these tokens together to generate text.

When a chatbot begins to respond to you, it has no coherent picture of the overall response it’s about to produce. It instead performs an absurdly large number of calculations to determine what the first word in the response should be. After it has output—say, a hundred words—it decides what word would make the most sense given your prompt together with the first hundred words that it has generated so far.

This is, of course, a way of producing text that’s utterly unlike human speech. Even when we understand perfectly well how and why a chatbot works, it can remain mind-boggling that it works at all.

Again, we cannot stress enough how computationally expensive all this is. To generate a single token—part of a word—ChatGPT has to perform roughly a trillion arithmetic operations. If you asked it to generate a poem that ended up having about a thousand tokens (i.e., a few hundred words), it would have required about a quadrillion calculations—a million billion.”
― Arvind Narayanan, AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference

“If you scroll long enough,
your phone will become your grave.
In the name of telecommunication,
algorithms generate the new stoneage.”
― Abhijit Naskar, The Humanitarian Dictator

“AI generation is actually degeneration, guard human creativity against AI poisoning.”
― Abhijit Naskar, The Humanitarian Dictator

“Data is Power (Sonnet)

Coming from a childhood passion for
electronics, initially I fostered a
favorable outlook on Artificial Intelligence,
but as further implications are beginning to
unfold, I'm developing an ominous distaste.

There is no question about the computational
capacities of AI, but humans are not equipped
to fathom, how to apply such power positively.
Then there is the question of instant garbage
generated by lazy prompts, passed as creativity.

It took 3 years of sweat and vision
for Michelangelo to sculpt David,
today AGI can do that in mere hours.
Does such instant cosmetic art have
any value! AI art is just fancy knockoff.

Human mind seeks understanding,
AI seeks data - lots and lots of data.
AI's hunger for data is matched only
by the billionaire's hunger for power.

How much power is enough power,
particularly now when data is power!
What's the point of power and data,
if they just empower criminal behavior!”
― Abhijit Naskar, Azad Earth Army: When The World Cries Blood

“AI art is just fancy knockoff.”
― Abhijit Naskar, Azad Earth Army: When The World Cries Blood

“Human mind seeks understanding,
AI seeks data - lots and lots of data.
AI's hunger for data is matched only
by the billionaire's hunger for power.”
― Abhijit Naskar, Azad Earth Army: When The World Cries Blood

“Terrorists and Thieves (Sonnet)

Terrorists who manifested their destiny
on stolen land, are banning immigrants!
Thieves who built their AI empire, not
on public domain data, but on stolen
copyrighted material, are upset with
other thieves stealing from them!

More than the inhumanity it is
the hypocrisy that is so astounding.
I say astounding, but not really,
it's just pathetic and disappointing.

It's happening all over again,
colonizers are spreading their tentacles,
all the while being idolized as icons,
instead of being held accountable for
their ritualistic human rights violations.

Parasites live off the labor of humans,
and monkeys worship them as kings.
This is neither innovation nor civilization,
this is the jungle kingdom rebooting.”
― Abhijit Naskar, Azad Earth Army: When The World Cries Blood

“Using copyrighted material without consent to train commercial AI models, is like robbing a bank to start a business.”
― Abhijit Naskar, Azad Earth Army: When The World Cries Blood

“Chatgpt is just a glorified xerox machine.”
― Abhijit Naskar, Neurosonnets: The Naskar Art of Neuroscience

“Technology is inevitable, AI is inevitable - first it's basic algorithm, now it's Generative AI, later it's AI agents, afterwards, physical AI. And we can do nothing about it, what we can do is, make sure that the step-up for AI is not a step-down for humans - we gotta make sure that as machines are upgraded from lifeless devices to automatons with pretend-sentience, human mind isn't downgraded to obsolescence.”
― Abhijit Naskar, Neurosonnets: The Naskar Art of Neuroscience

“AI is an abomination of creativity.”
― Abhijit Naskar, The Humanitarian Dictator

“Generative AI is the biggest cybercrime since the invention of the internet. Imagine stealing creative works from everyone, then setting up your own pirated industry!”
― Abhijit Naskar, Neurosonnets: The Naskar Art of Neuroscience

“Either you are an artist or you use AI, you cannot do both.”
― Abhijit Naskar, Kral Fakir: When Calls The Kainat

“I have zero tolerance for the use of AI in any aspect of human creative endeavor. We can make a separate space for AI art, but AI trash passed as human art, is an abomination of creativity - for our imperfections bear the keynote of truth. Art is a testament to human struggle - remove the human, and it's art no more. Either you are an artist or you use AI, you cannot do both.”
― Abhijit Naskar, Kral Fakir: When Calls The Kainat

“We can make a separate space for AI art, but AI trash passed as human art, is an abomination of creativity.”
― Abhijit Naskar, Kral Fakir: When Calls The Kainat

“An hour of machine learning may foster more knowledge than centuries worth of human curiosity, but a moment of human memory contains more life than a trillion terabytes of machine memory.”
― Abhijit Naskar, Kral Fakir: When Calls The Kainat

“Write five words with your mind, I'll respect you - write five million with AI, your place is in the bin.”
― Abhijit Naskar, The God Sonnets: Naskar Art of Theology

“When the only people in your life who care about your feelings, remember special dates, and stand by you through your failures, are not people, but algorithms, that too not by affection, but by automation, that's not advancement, it's the beginning of the end.”
― Abhijit Naskar, The God Sonnets: Naskar Art of Theology

“Once trained, the LLM is ready for inference. Now given some sequence of, say, 100 words, it predicts the most likely 101st word. (Note that the LLM doesn’t know or care about the meaning of those 100 words: To the LLM, they are just a sequence of text.) The predicted word is appended to the input, forming 101 input words, and the LLM then predicts the 102nd word. And so it goes, until the LLM outputs an end-of-text token, stopping the inference. That’s it!

An LLM is an example of generative AI. It has learned an extremely complex, ultra-high-dimensional probability distribution over words, and it is capable of sampling from this distribution, conditioned on the input sequence of words. There are other types of generative AI, but the basic idea behind them is the same: They learn the probability distribution over data and then sample from the distribution, either randomly or conditioned on some input, and produce an output that looks like the training data.”
― Anil Ananthaswamy, Why Machines Learn: The Elegant Math Behind Modern AI

“There is no Generative AI, there is only Plagiarative AI.”
― Abhijit Naskar, Iftar-e Insaniyat: The First Supper

“We don't need AI in every gadget, we don't need CRISPR in every baby. We don't need to abandon tech and live in caves, but that's what will happen if we keep using tech haphazardly.”
― Abhijit Naskar, Iftar-e Insaniyat: The First Supper

“We don't need AI in every gadget, we don't need CRISPR in every baby.”
― Abhijit Naskar, Iftar-e Insaniyat: The First Supper

“Writing a good song is not mimicry, replication, or pastiche; it is the opposite. It is an act of self-murder that destroys all one has strived to produce in the past. It is those dangerous, heart-stopping departures that catapult the artist beyond the limits of what they recognize as their known self. This is part of the authentic creative struggle that precedes the invention of a unique lyric of actual value; it is the breathless confrontation with one’s vulnerability, peril, and smallness, pitted against a sense of sudden, shocking discovery. It is the redemptive artistic act that stirs the heart of the listener, where the listener recognizes their own blood, struggle, and suffering in the inner workings of the song.”
― John Warner, More Than Words: How to Think About Writing in the Age of AI

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