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Gabriela Sá Pessoa is a journalist passionate about the intersection of human rights and climate change. She came to MIT from The Washington Post, where she worked from her home country of Brazil as a news researcher reporting on the Amazon, human rights violations, and environmental crimes. Before that, she held roles at two of…
Large Language Models have shown immense growth and advancements in recent times. The field of Artificial Intelligence is booming with every new release of these models. From education and finance to healthcare and media, LLMs are contributing to almost every domain. Famous LLMs like GPT, BERT, PaLM, and LLaMa are revolutionizing the AI industry by…
Socrates once said: “It is not the size of a thing, but the quality that truly matters. For it is in the nature of substance, not its volume, that true value is found.” Does size always matter for large language models (LLMs)? In a technological landscape bedazzled by LLMs taking center stage, a team of…
Despite only seeing the world in two dimensions, humans are adept at navigating, thinking, and interacting with their three-dimensional environment. This suggests a profoundly ingrained cognitive awareness of the traits and actions of the 3D environment, which is a great aspect of human nature. Artists who can create detailed 3D reproductions from a single photograph…
ChatGPT has been the talk of the town since the day it has released. Over a million users are already using the revolutionary chatbot for interaction. For the unaware, ChatGPT is a large language model (LLM) trained by OpenAI to respond to different questions and generate information on an extensive range of topics. It can…
The 3D computer vision domain was flooded with NeRFs in recent years. They emerged as a groundbreaking technique and enabled the reconstruction and synthesis of novel views of a scene. NeRFs capture and model the underlying geometry and appearance information from a collection of multi-view images. By leveraging neural networks, NeRFs offer a data-driven approach…
Large language models, such as PaLM, Chinchilla, and ChatGPT, have opened up new possibilities in performing natural language processing (NLP) tasks from reading instructive cues. The prior art has demonstrated that instruction tuning, which involves finetuning language models on various NLP tasks organized with instructions, further improves language models’ capacity to carry out an unknown…
The remarkable results achieved by transformer-based models like GPT-2 and GPT-3 gravitated the research community toward exploring large language models (LLMs). Additionally, ChatGPT’s recent success and popularity have only served to increase people’s interest in LLMs. In-context learning and chain-of-thought prompting are two other major discoveries that have significantly improved the accuracy of the models….
In-context learning is a recent paradigm where a large language model (LLM) observes a test instance and a few training examples as its input and directly decodes the output without any update to its parameters. This implicit training contrasts with the usual training where the weights are changed based on the examples. Here comes the…
Though recent advances have been made in large language model (LLM) reasoning, LLMs still have a hard time with hierarchical multi-step reasoning tasks like developing sophisticated programs. Human programmers, in contrast to other token generators, have (usually) learned to break down difficult tasks into manageable components that work alone (modular) and work together (compositional). As…
