The challenge lies in generating effective agentic workflows for Large Language Models (LLMs). Despite their remarkable capabilities across diverse tasks, creating workflows that combine multiple LLMs ...

In today’s fast-paced and interconnected world, mental health is more important than ever. The constant pressures of work, social media, and global events can take a toll on our emotional and ...

The challenge lies in generating effective agentic workflows for Large Language Models (LLMs). Despite their remarkable capabilities across diverse tasks, creating workflows that combine multiple LLMs ...

XAI, or Explainable AI, brings about a paradigm shift in neural networks that emphasizes the need to explain the decision-making processes of neural networks, which are well-known black boxes. In XAI, ...

Predibase announces the Predibase Inference Engine, their new infrastructure offering designed to be the best platform for serving fine-tuned small language models (SLMs). The Predibase Inference ...

A major challenge in the evaluation of vision-language models (VLMs) lies in understanding their diverse capabilities across a wide range of real-world tasks. Existing benchmarks often fall short, ...

Zyphra has officially released Zamba2-7B, a state-of-the-art small language model that promises unprecedented performance in the 7B parameter range. This model outperforms existing competitors,... In ...

Zyphra has officially released Zamba2-7B, a state-of-the-art small language model that promises unprecedented performance in the 7B parameter range. This model outperforms existing competitors,... In ...

Zyphra has officially released Zamba2-7B, a state-of-the-art small language model that promises unprecedented performance in the 7B parameter range. This model outperforms existing competitors, ...

Language models (LMs) are widely utilized across domains like mathematics, coding, and reasoning to handle complex tasks. These models rely on deep learning techniques to generate high-quality outputs ...

The problem with efficiently linearizing large language models (LLMs) is multifaceted. The quadratic attention mechanism in traditional Transformer-based LLMs, while powerful, is computationally ...

A Model Inversion (MI) attack is a type of privacy attack on machine learning and deep learning models, where an attacker tries to invert the model’s outputs to recreate privacy-sensitive training ...