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Iranian Hackers Tried to Give Hacked Trump Campaign Emails to Dems
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.
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California Can Slake the Thirst of Its Farms by Storing Water Underground
A new study finds that the state should replenish groundwater aquifers to sustain agriculture.
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The 44 Best Movies on Netflix Right Now (September 2024)
Wicked Little Letters, Rebel Ridge, and The Platform are just a few of the movies you should watch on Netflix this month.
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The 44 Best Shows on Netflix Right Now (September 2024)
Terminator Zero, The Perfect Couple, and Sweet Home are just a few of the shows you need to watch on Netflix this month.
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LASR: A Novel Machine Learning Approach to Symbolic Regression Using Large Language Models
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…
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Contextual Retrieval: An Advanced AI Technique that Reduces Incorrect Chunk Retrieval Rates by up to 67%
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…
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Sketch: An Innovative AI Toolkit Designed to Streamline LLM Operations Across Diverse Fields
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…
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ZML: A High-Performance AI Inference Stack that can Parallelize and Run Deep Learning Systems on Various Hardware
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…
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Comprehensive Evaluation of Quantized Instruction-Tuned LLMs: Exploring Quantization Methods for Models Ranging from 7B to 405B Parameters
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…
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MMSearch Engine: AI Search with Advanced Multimodal Capabilities to Accurately Process and Integrate Text and Visual Queries for Enhanced Search Results
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…