OuteAI has released two new models of its Lite series, namely Lite-Oute-1-300M and Lite-Oute-1-65M, which are designed to maintain optimum efficiency and performance, making them suitable for deployment across various devices. The Lite-Oute-1-300M model is based on the Mistral architecture and features 300 million parameters, while the Lite-Oute-1-65M, based on the LLaMA architecture, hosts around…
Neural Magic, an AI solutions provider, has recently announced a breakthrough in AI model compression with the introduction of a fully quantized FP8 version of Meta's Llama 3.1 405B model. This achievement is significant in the field of AI as it allows this massive model to fit on any 8xH100 or 8xA100 system without the…
Artificial Intelligence (AI) and Machine Learning (ML) technologies have shown significant advancements, particularly via their application in various industries. Autonomous agents, a unique subset of AI, have the capacity to function independently, make decisions, and adapt to changing circumstances. These agents are vital for jobs requiring long-term planning and interaction with complex, unpredictable environments. A…
The recent release of scores by the LMSys Chatbot Arena has ignited discussions among AI researchers. According to the results, GPT-4o Mini outstrips Claude 3.5 Sonnet, frequently hailed as the smartest Large Language Model (LLM) currently available.
To understand the exceptional performance of GPT-4o Mini, a random selection of one thousand real user prompts were evaluated.…
In the field of natural language processing (NLP), integrating external knowledge bases through Retrieval-Augmented Generation (RAG) systems is a vital development. These systems use dense retrievers for pulling relevant information, utilized by large language models (LLMs) to generate responses. Despite their improvements across numerous tasks, there are limitations to RAG systems, such as struggling to…
Large Language Models (LLMs), which focus on understanding and generating human language, are a subset of artificial intelligence. However, their use of the Transformer architecture to process long texts introduces a significant challenge due to its quadratic time complexity. This complexity is a barrier to efficient performance with extended text inputs.
To deal with this issue,…
Competition is vital in shaping all aspects of human society, including economics, social structures, and technology. Traditionally, studying competition has been reliant on empirical research, which is limited due to issues with data accessibility and a lack of micro-level insights. An alternative approach, agent-based modeling (ABM), advanced from rule-based to machine learning-based agents to overcome…
Recent advancements in large language models (LLMs) have expanded their utility by enabling them to complete a broader range of tasks. However, challenges such as the complexity and non-deterministic nature of these models, coupled with their propensity to waste computational resources due to redundant calculations, limit their effectiveness.
In an attempt to tackle these issues, researchers…
Large language models (LLMs), used in applications such as machine translation, content creation, and summarization, present significant challenges due to their tendency to generate hallucinations - plausible sounding but factually inaccurate statements. This major issue affects the reliability of AI-produced copy, particularly in high-accuracy-required domains like medical and legal texts. Thus, reducing hallucinations in LLMs…
A team of researchers from Meta FAIR have been studying Large Language Models (LLMs) and found that these can produce more nuanced responses by distilling System 2 reasoning methods into System 1 responses. While System 1 operates quickly and directly, generating responses without intermediate steps, System 2 uses intermediate strategies, such as token generation and…