Large Language Model-ChatGpt
What is High Modernism?
Why is high modernism a problem when designing AI?
Can diversity help?
- Currently, significant attention is being given to Chat-GPT and other similar “giant artificial intelligences’ ‘ (gAI)such as Bard, Chinchilla, PaLM, and LaMDA.
- Chat-GPT is an example of a large language model (LLM) which is a type of (transformer-based) neural network that is great at predicting the next word in a sequence of words.
- Ensuring safe data- OpenAI has taken measures to ensure that the data used for training is safe and suitable for training purposes.
- Trillion Parameters- OpenAI takes advantage of GPT-4’s large size and trillion parameters to help them reach their goal of making “artificial general intelligence that benefits all of humanity,”
- Multiple use-There are many use-cases intended for these systems, including legal services, teaching students, generating policy suggestions and even providing scientific insights.
- Novel Thoughts-The objective behind gAIs is to automate knowledge work, a realm that was traditionally considered beyond the scope of automation.
|Understanding The Term
Large language model:
- The current driving philosophy of states is high modernism, a faith in order and measurable progress. It has following features:
- Top-Down Approach: gAIs leave no room for democratic input since they are designed in a top-down manner with the premise that the model will acquire the smaller details on its own.
- Disregarding complex human behaviour: States seek to improve the lives of their citizens, but when they design policies from the top-down, they often reduce the richness and complexity of human experience to that which is quantifiable.
- Neglect of local knowledge: This ideology often ignores local knowledge and lived experience, leading to disastrous consequences.
|How top down planning may lead to negative impacts?
- Standardisation over sustainability: Such a business model tends to prioritize standardization over sustainability or craftsmanship, resulting in a homogenized market where everyone has access to cheap, mass-produced products.
- Destruction of local shops: This often leads to the gradual demise of local small-town shops, as they struggle to compete against the convenience and widespread availability offered by online platforms.
- Threat to language diversity: The risk of such language loss is due to the bias induced by models trained only on the languages that already populate the Internet, with English being predominant (~60%).
- Inherent Biases of gAI: There are other ways in which a model is likely to be biased, including on religion sex and race.
- Unreasonable Intelligent response: LLMs are unreasonably effective at providing intelligible responses. Presenting Myopic view lacking multi-dimensionality. For Example, An atlas is a great way of seeing the whole world in snapshots. However, an atlas lacks multi-dimensionality required to capture intricate details. This knowledge is abstracted away by gAIs in favour of the atlas view of all that is present on the internet.
|Case Study implying lack of multi-dimensionality in gAI
- A part of the failure to capture the territory is demonstrated in gAIs’ lack of understanding.
- If one is cautious in their inquiries, these systems can generate remarkable responses.
- However, posing the same question with slight variations can result in illogical answers
- This pattern has led computer scientists to refer to these systems as “stochastic parrots,” implying that they can imitate language but exhibit random behavior.
- Promoting democratic inputs: Artificially slowing down the rate of progress in AI commercialisation to allow time for democratic inputs.
- Development of diverse models: Ensure there are diverse models being developed. Diversity’ here implies multiple solutions to the same question, like independent cartographers preparing different atlases with different incentives: some will focus on the flora while others on the fauna.
- Adequate time frame before final outcome: Research on diversity suggests that the more time passes before reaching a common solution, the better the outcome. A better outcome is critical when dealing with the stakes involved in artificial general intelligence – an area of study in which a third of researchers believe it can lead to a nuclear-level catastrophe.
- BLOOM, an open-source language model (LLM), has been developed by scientists using public funding and has undergone thorough filtering of the training data.
- This model is also capable of handling multiple languages, including 10 Indian languages, and is supported by an active ethics team that regularly updates the license for its use.
- Consideration of ethical implications: While ChatGPT-4 offers tremendous potential, it is essential to consider the ethical implications and challenges associated with its deployment.
- Ensuring transparency and accountability: As an AI language model, it reflects the biases and limitations in the data it was trained on. It is crucial to mitigate any biases and ensure transparency and accountability in its usage.
- Responsible use: Striking a balance between innovation and responsible deployment is paramount to maximize the benefits while minimizing potential risks.
- Human-centric approach: While ChatGPT-4 can simulate human-like interactions, it is essential to recognize its limitations and ensure that human oversight and judgement are integrated into its applications
- OpenAI has taken steps toward addressing these concerns by emphasizing AI’s safety, robustness, and responsible use.
- Ongoing research and collaboration with experts in various fields are essential in refining and improving models like ChatGPT-4, making them more aligned with human values and societal needs.