Large Language Models (LLMs) are used in various applications, but high computational and memory demands lead to steep energy and financial costs when deployed to GPU servers. Research teams from FAIR, GenAI, and Reality Labs at Meta, the Universities of Toronto and Wisconsin-Madison, Carnegie Mellon University, and Dana-Farber Cancer Institute have been investigating the possibility…
Fine-tuning large language models (LLMs) is a crucial but often daunting task due to the resource and time-intensity of the operation. Existing tools may lack the functionality needed to handle these substantial tasks efficiently, particularly in relation to scalability and the ability to apply advanced optimization techniques across different hardware configurations.
In response, a new toolkit…
As parents, we try to select the perfect toys and learning tools by carefully matching child safety with enjoyment; in doing so, we often end up using search engines to find the right pick. However, search engines often provide non-specific results which aren't satisfactory.
Recognizing this, a team of researchers have devised an AI model named…
Advancements in large language models (LLMs) have greatly elevated natural language processing applications by delivering exceptional results in tasks like translation, question answering, and text summarization. However, LLMs grapple with a significant challenge, which is their slow inference speed that restricts their utility in real-time applications. This problem mainly arises due to memory bandwidth bottlenecks…
Researchers from MIT have been using a language processing AI to study what type of phrases trigger activity in the brain's language processing areas. They found that complex sentences requiring decoding or unfamiliar words triggered higher responses in these areas than simple or nonsensical sentences. The AI was trained on 1,000 sentences from diverse sources,…
As the AI technology landscape advances, free online platforms to test large language models (LLMs) are proliferating. These 'playgrounds' offer developers, researchers, and enthusiasts a valuable resource to experiment with various models without needing extensive setup or investment.
LLMs, the cornerstone of contemporary AI applications, can be complex and resource-intensive, making them often inaccessible for individual…
Scientists from MIT have used an artificial language network to investigate the types of sentences likely to stimulate the brain's primary language processing areas. The research shows that more complicated phrases, owing to their unconventional grammatical structures or unexpected meanings, generate stronger responses in these centres. However, direct and obvious sentences prompt barely any engagement,…
Researchers at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) presented three papers at the International Conference on Learning Representations, indicating breakthroughs in Large Language Models' (LLMs) abilities to form useful abstractions. The team used everyday words for context in code synthesis, AI planning, and robotic navigation and manipulation.
The three frameworks, LILO, Ada,…
In a captivating yet curious turn of events, an AI named "gpt2-chatbot" appeared and disappeared in a brief period on the LMSYS Chatbot Arena, a platform for comparing various AI chatbot models. Surpassing the capabilities of readily available models out there, gpt2-chatbot quickly became a topic of intrigue among AI enthusiasts. Amidst this mystery, it…
