Category: Uncategorized

A new study finds that the state should replenish groundwater aquifers to sustain agriculture. Read more

Plus: The FBI dismantles the largest-ever China-backed botnet, the DOJ charges two men with a $243 million crypto theft, Apple’s MacOS Sequoia breaks cybersecurity tools, and more. Read more

Personalization is essential in many language tasks, as users with similar needs may prefer different outputs based on personal preferences. Traditional methods involve fine-tuning language models for each user, which is resource-intensive. A more practical approach uses retrieval-based systems to customize outputs by referencing a user’s previous texts. However, this method may fail to capture… Read more

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… Read more

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… Read more

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… Read more

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… Read more

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… Read more

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… Read more

With AI’s growing influence across industries, malicious attackers continue to sharpen their tradecraft to exploit ML models.Read More Read more