The development of Artificial Intelligence (AI) models, especially in specialized contexts, depends on how well they can access and use prior information. For example, legal AI tools need to be well-versed in a broad range of previous cases, while customer care chatbots require specific information about the firms they serve. The Retrieval-Augmented Generation (RAG) methodology… →

Symbolic regression is an advanced computational method to find mathematical equations that best explain a dataset. Unlike traditional regression, which fits data to predefined models, symbolic regression searches for the underlying mathematical structures from scratch. This approach has gained prominence in scientific fields like physics, chemistry, and biology, where researchers aim to uncover fundamental laws… →

Inference is the process of applying a trained AI model to new data, which is a fundamental step in many AI applications. As AI applications grow in complexity and scale, traditional inference stacks struggle with high latency, inefficient resource utilization, and limited scalability across diverse hardware. The problem is especially pressing in real-time applications, such… →

Large language models (LLMs) have made significant leaps in natural language processing, demonstrating remarkable generalization capabilities across diverse tasks. However, due to inconsistent adherence to instructions, these models face a critical challenge in generating accurately formatted outputs, such as JSON. This limitation poses a significant hurdle for AI-driven applications requiring structured LLM outputs integrated into… →

Large Language Models (LLMs) have gained significant attention due to their impressive performance, with the release of Llama 3.1 in July 2024 being a notable example. However, deploying these models in resource-constrained environments poses significant challenges due to their huge parameter count. Low-bit quantization has emerged as a popular technique to compress LLMs, reducing memory… →

Traditional search engines have predominantly relied on text-based queries, limiting their ability to process and interpret the increasingly complex information found online today. Many modern websites feature both text and images. Yet, the ability of conventional search engines to handle these multimodal queries, those that require an understanding of both visual and textual content, remains… →

In an era of AI-transforming industries, CodeMaker AI has achieved a landmark breakthrough by autonomously recreating a 90,000-line software library with an astounding 91% similarity to the original codebase. This achievement marks a significant shift in how AI can be utilized in software development, demonstrating the potential to reduce manual coding efforts and accelerate development… →

Recommendation systems have become the foundation for personalized services across e-commerce, streaming, and social media platforms. These systems aim to predict user preferences by analyzing historical interactions, allowing platforms to suggest relevant items or content. The accuracy & effectiveness of these systems depends heavily on how well user and item characteristics are modeled. Over the… →