The growth and development of Large Language Models (LLMs) in Artificial Intelligence and Data Science hinge significantly on the volume and accessibility of training data. However, with the constant acceleration of data usage and the requirements of next-generation LLMs, concerns are brewing about the possibility of depleting global textual data reserves necessary for training these…
Doctors are less accurate when diagnosing skin diseases in people with darker skin, according to a study by MIT researchers. The researchers found that dermatologists accurately characterized 38% of images of skin diseases, but only 34% of those images were of darker skin. The results were similar for general practitioners. The research team suggested that…
Researchers from MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) have designed a new type of game to enhance how artificial intelligence (AI) comprehends and produces text. This "consensus game" includes two parts of an AI system - the part that generates sentences and a part that evaluates those sentences. This model significantly improved the…
Amazon has launched Amazon Titan Text Premier, a new large language model (LLM) as part of its Titan Text models. The model is now available in Amazon Bedrock, a managed service that provides a selection of high-performing foundation models from leading AI companies. The new model is intended for large-scale enterprise-grade text generation applications.
Amazon…
OpenAI has announced its groundbreaking new artificial intelligence (AI) model - GPT-4o. Chief Technology Officer of OpenAI, Mira Murati unveiled the model at the company's live presentation. The term "o" in GPT-4o refers to "omni", reflecting its capability to proficiently interact using audio, images, and text in real time, closely emulating human cognition ability. Its…
The exploration of Artificial Intelligence has increasingly focused on simulating human-like interactions. The latest innovations aim to streamline the processing of text, audio, and visual data into one framework, addressing the limitations of earlier models that processed these inputs separately.
Traditional AI models often compartmentalized the processing of different data types, resulting in delayed responses and…
Large Language Models (LLMs) heavily rely on the process of tokenization – breaking down texts into manageable pieces or tokens – for their training and operations. However, LLMs often encounter a problem called 'glitch tokens'. These tokens exist in the model's vocabulary but are underrepresented or absent in the training datasets. Glitch tokens can destabilize…
Large Language Models (LLMs) such as GPT-4 and LLaMA2-70B enable various applications in natural language processing. However, their deployment is challenged by high costs and the need to fine-tune many system settings to achieve optimal performance. Deploying these models involves a complex selection process among various system configurations and traditionally requires expensive and time-consuming experimentation.…
