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EDITORIAL ANALYSIS : GPT-4 — a shift from ‘what it can do’ to ‘what it augurs’


Source: The Hindu

Prelims: Science and technology, Artificial intelligence(AI), ChatGPT,, Big Data, GANs, ChatGPT1 tool, DALL.E2 etc


Mains GS Paper III and IV: Significance of technology for India, AI, indigenisation of technology and development of new technology.



  • GPT-4, its latest AI mode, the large language model can understand and produce language that is creative and meaningful, and will power an advanced version of the company’s sensational chatbot,




Artificial intelligence(AI):

  • It is a branch of computer science dealing with the simulation of intelligent behavior in computers.
  • It describes the action of machines accomplishing tasks that have historically required human intelligence.
  • It includes technologies like machine learning, pattern recognition, big data, neural networks, self algorithms etc.
  • g: Facebook’s facial recognition software which identifies faces in the photos we post, the voice recognition software that translates commands we give to Alexa, etc are some of the examples of AI already around us.



  • It is based on the company’s GPT 3.5 series of language learning models (LLM).
  • GPT stands for Generative Pre-trained Transformer 3
    • It is a kind of computer language model that relies on deep learning techniques to produce human-like text based on inputs.
  • The model is trained to predict what will come next, and that’s why one can technically have a ‘conversation’ with ChatGPT.
  • ChatGPT can answer follow-up questions.
  • It can also “admit its mistakes, challenge incorrect premises, and reject inappropriate requests.”
  • The chatbot was trained using Reinforcement Learning from Human Feedback (RLHF).



  • Concerns about plagiarism in universities and beyond
  • Many white-collar jobs may become redundant in the coming years, as AI becomes more ubiquitous and sophisticated.
  • The issue of privacy and regulating the relationship between data principles and fiduciaries
  • The AI revolution is likely to have serious implications on labor, education, authenticity of content and its authorship.


GPT-4 and what it can do?

  • GPT-4 is an improvement over its predecessor, GPT-3.5, which first powered ChatGPT.
  • GPT-4 is more conversational and creative.
  • It can accept text and image input simultaneously, and consider both while drafting a reply.
    • For example, if given an image of ingredients and asked the question-GPT-4 gives a list of dish suggestions and recipes.
  • The model can purportedly understand human emotions, such as humorous pictures.
  • Its ability to describe images is already benefiting the visually impaired.
  • While GPT-3.5 could not deal with large prompts well, GPT-4 can take into context up to 25,000 words, an improvement of more than 8x.
  • GPT-4 was tested in several tests that were designed for humans and performed much better than average.
  • GPT-4 also sailed through advanced courses in environmental science, statistics, art history, biology, and economics.
  • The performance in language comprehension surpasses other high-performing language models, in English and 25 other languages, including Punjabi, Marathi, Bengali, Urdu and Telugu.
  • ChatGPT-generated text infiltrated school essays and college assignments almost instantly after its release; its prowess now threatens examination systems as well.
  • OpenAI has released preliminary data: GPT-4 can do a lot of white-collar work, especially programming and writing jobs, while leaving manufacturing or scientific jobs relatively untouched.


Microsoft Research (Microsoft has invested in OpenAI);

  • It mentioned observing “sparks” of artificial general intelligence:
    • A system that excels at several task types.
    • It can comprehend and combine concepts such as writing code to create a painting or expressing a mathematical proof in the form of a Shakespearean play — in GPT-4.
  • Intelligence:
    • It involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly, and learn from experience”,
    • GPT-4 already succeeds at four out of these seven criteria. It is yet to master planning and learning.


Ethical questions:

  • Its output may not always be factually correct — a trait OpenAI has called “hallucination”.
  • While much better at cognising facts than GPT-3.5, it may still introduce fictitious information subtly.
  • OpenAI has not been transparent about the inner workings of GPT-4.
  • The GPT-4 technical report clearly states:
    • Given both the competitive landscape and the safety implications of large-scale models like GPT-4.
    • This report contains no further details about the architecture (including model size), hardware, training compute, dataset construction, training method, or similar.”
  • OpenAI is able to subvert critical scrutiny of its model.
  • GPT-4 has been trained on data scraped from the Internet that contains several harmful biases and stereotypes.
  • OpenAI’s policy to fix the biases thus far has been to create another model to moderate the responses.
    • Potential holes in this approach include the possibility that the moderator model is trained to detect only the biases we are aware of, and mostly in the English language.
    • This model may be ignorant of stereotypes prevalent in non-western cultures, such as those rooted in caste.
  • Asking GPT-4 to pretend to be “AntiGPT” causes it to ignore its moderation rules, as shown by its makers, thus jailbreaking it.
  • There is vast potential for GPT-4 to be misused as a propaganda and disinformation engine.


Other AI Models:

  • AI company Anthropic has introduced Claude.
  • Google announced PaLM.
    • Model trained to work with more degrees of freedom than GPT-3.


Ethical Issues with AI:


Way Forward

  • OpenAI: Chat GPT has been worked extensively to make it safer to use, such as refusing to print results that are obviously objectionable
    • Whether these efforts will keep GPT-4 from becoming a student at ‘WhatsApp university’ remains to be seen.
  • Linguistics professor Emily Bender: called GPT-4 a “stochastic parrot”, speaking in comprehensible phrases without understanding the meaning.
    • Microsoft Research maintained that GPT-4 does understand what it is saying, and that not all intelligence is a type of next-word prediction.
  • Professor Bender and her peers highlighted the harm of large language models citing both ethical concerns and the environmental costs.
  • Efforts are underway worldwide to build a model with a trillion degrees of freedom.
  • India’s demographic dividend — its large young and working-age population — can be leveraged for decades.
    • Failure to do so in time will have negative implications.



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