Large language models (LLMs) are increasingly in use, which is leading to new cybersecurity risks. The risks stem from their main characteristics: enhanced capability for code creation, deployment for real-time code generation, automated execution within code interpreters, and integration into applications handling unprotected data. It brings about the need for a strong approach to cybersecurity…
The development and progress in the field of artificial intelligence (AI) are unending, with the recent emergence of the AI model, "gpt2-chatbot", generating significant interest within AI circles on Twitter. This model, known as a large language model (LLM), has incited considerable exploration and curiosity amongst AI developers and enthusiasts, who are constantly searching to…
French researchers have developed the first publicly available benchmark tool, 'DrBenchmark', to evaluate and standardize evaluation protocols for pre-trained masked language models (PLMs) in French, particularly in the biomedical field. Existing models lacked standardized protocols and comprehensive datasets, leading to inconsistent results and stalling progress in natural language processing (NLP) research.
The advent and advancement…
In the field of computational linguistics, large amounts of text data present a considerable challenge for language models, especially when specific details within large datasets need to be identified. Several models, like LLaMA, Yi, QWen, and Mistral, use advanced attention mechanisms to deal with long-context information. Techniques such as continuous pretraining and sparse upcycling help…
Emerging research from the New York University's Center for Data Science asserts that language models based on transformers play a key role in driving AI forward. Traditionally, these models have been used to interpret and generate human-like sequences of tokens, a fundamental mechanism used in their operational framework. Given their wide range of applications, from…
A recent Gartner poll highlighted that while 55% of organizations experiment with generative AI, only 10% have implemented it in production. The main barrier in transitioning to production is the erroneous outputs or 'hallucinations' produced by large language models (LLMs). These inaccuracies can create significant issues, particularly in applications that need accurate results, such as…
Text-to-image (T2I) models, which transform written descriptions into visual images, are pushing boundaries in the field of computer vision. The principal challenge lies in the model's capability to accurately represent the fine-detail specified in the corresponding text, and despite generally high visual quality, there often exists a significant disparity between the intended description and the…
Cohere AI, a leading enterprise AI platform, recently announced the release of the Cohere Toolkit intended to spur the development of AI applications. The toolkit integrates with a variety of platforms including AWS, Azure, and Cohere's own network and allows developers to utilize Cohere’s models, Command, Embed, and Rerank.
The Cohere Toolkit comprises of production-ready applications…
Large Language Models (LLMs) are a critical component of several computational platforms, driving technological innovation across a wide range of applications. While they are key for processing and analyzing a vast amount of data, they often face challenges related to high operational costs and inefficiencies in system tool usage.
Traditionally, LLMs operate under systems that activate…
Large Language Models (LLMs) are integral to the development of chatbots, which are becoming increasingly essential in sectors such as customer service, healthcare, and entertainment. However, evaluating and measuring the performance of different LLMs can be challenging. Developers and researchers often struggle to compare capabilities and outcomes accurately, with traditional benchmarks often falling short. These…