CodeParrot AI, a startup offering AI-powered tools, aims to make the coding process more manageable for designers and developers. Its main function is to simplify the building of web parts by transforming Figma design into code components for React, Vue, and Angular. This streamlining tool automates the frontend work, ultimately making coding more efficient and…
Large language models (LLMs) like GPT-3 require substantial computational resources for their deployment, making it challenging to use them on resource-constrained devices. Strategies to boost the efficiency of LLMs like pruning, quantization, and attention optimization have been developed, but these can often lead to decreased accuracy or continue to rely heavily on energy-consuming multiplication operations.…
In today's digital era, the demand for ever-increasing computing power has been overwhelmingly huge, driven primarily by advancements in artificial intelligence. However, the constant innovation in computing technology is facing obstacles, primarily due to the limitations in the shrinking size of transistors used in chips. This imposes a strict limit on Moore's Law and Dennard's…
Generative AI is increasingly being utilized to generate synthetic data, enhancing organizations' abilities to deal with situations where actual data may be limited or sensitive. Over the past three years, DataCebo, an MIT spinoff initiative, has been offering a generative software system known as the Synthetic Data Vault (SDV) to enable organizations to create synthetic…
Large Language Models (LLMs) are complex artificial intelligence tools capable of amazing feats in natural language processing. However, these large models require extensive fine-tuning to adapt to specific tasks, a process that usually involves adjusting a considerable number of parameters and consequently consuming significant computational resources and memory. This means the fine-tuning of LLMs is…
Analogical reasoning, which enables understanding relationships between objects, is key to abstract thinking in humans. However, machine learning models often struggle with this task, requiring assistance to draw abstract rules from limited data. A process known as the relational bottleneck has been adopted to help rectify this issue, using attention mechanisms to detect correlations between…
The field of document understanding, which involves transforming documents into meaningful information, has gained significance with the advent of large language models and increasing use of document images across industries. The primary challenge for researchers in this field, however, is the effective extraction of information from documents that contain a mix of text and visual…