Llama-3-Nephilim-v3-8B and llama-3-Nephilim-v3-8B-GGUF are two innovative models released on Hugging Face. Although these models were never explicitly trained for roleplay, they exhibit remarkable capability in this domain, highlighting the potential of “found art” approaches in AI development. The creation of these models involved merging several pre-trained language models using mergekit, a tool designed to combine…
In the rapidly developing field of Artificial Intelligence, it is more important than ever to convert unstructured data into organized, useful information efficiently. Recently, a team of researchers introduced the Neo4j LLM Knowledge Graph Builder, an AI tool that can easily address this issue. This potential application creates a text-to-graph experience by utilizing some great…
Large Language Models (LLMs) like GPT-3.5 and GPT-4 are advanced artificial intelligence systems capable of generating human-like text. These models are trained on vast amounts of data to perform various tasks, from answering questions to writing essays. The primary challenge in the field is ensuring that these models do not produce harmful or unethical content,…
Large language models (LLMs) have revolutionized the field of artificial intelligence, enabling the creation of language agents capable of autonomously solving complex tasks. However, the development of these agents faces significant challenges. The current approach involves manually decomposing tasks into LLM pipelines, with prompts and tools stacked together. This process is labor-intensive and engineering-centric, limiting…
Human reviewers or LLMs are often the only options for evaluating free-form material. However, their evaluation can be inaccurate and the process is time-consuming, costly, and arduous. The relief from this manual work comes with prompt engineering or the development of a unique optimization procedure, which is necessary for LLM evaluations to function as intended.…
Optimal transport is a mathematical discipline focused on determining the most efficient way to move mass between probability distributions. This field has wide-ranging applications in economics, where it is used to model resource allocation; in physics, to simulate particle dynamics; and in machine learning, where it aids in data alignment and analysis. By solving transportation…
Together AI has unveiled a groundbreaking advancement in AI inference with its new inference stack. This stack, which boasts a decoding throughput four times faster than the open-source vLLM, surpasses leading commercial solutions like Amazon Bedrock, Azure AI, Fireworks, and Octo AI by 1.3x to 2.5x. The Together Inference Engine, capable of processing over 400…
Conversational AI systems like ChatGPT have gained considerable attention among the various AI advancements. These systems utilize advanced machine learning algorithms and natural language processing to assist users in numerous tasks, such as drafting emails, conducting research, and providing detailed information. The proliferation of such AI tools significantly transforms how office tasks are executed, contributing…
Instruction-tuned LLMs can handle various tasks using natural language instructions, but their performance is sensitive to how instructions are phrased. This issue is critical in healthcare, where clinicians, who may need to be more skilled, prompt engineers, need reliable outputs. The robustness of LLMs to variations in clinical task instructions is thus questioned. Despite advancements…
Traditional methods, relying solely on formal proof data, overlook valuable informal reasoning processes crucial to human mathematicians. The absence of natural language thought processes in formal proofs creates a significant gap between human reasoning and machine-driven proofs. Existing language models specialized for generating tactics in formal mathematics often fail to leverage the benefits of thought…