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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…
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ByteDance Introduced Hierarchical Large Language Model (HLLM) Architecture to Transform Sequential Recommendations, Overcoming Cold-Start Challenges, and Enhancing Scalability with State-of-the-Art Performance
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…
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CodeMaker AI Breakthrough in Software Development: Achieves 91% Accuracy in Recreating 90,000 Lines of Code, Setting a New Benchmark for AI-driven code Generation and Fine-Tuned Model
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…
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Adversarial attacks on AI models are rising: what should you do now?
With AI’s growing influence across industries, malicious attackers continue to sharpen their tradecraft to exploit ML models.Read More
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5 key takeaways from Dreamforce 2024
As Salesforce’s 2024 Dreamforce conference rolls up the carpet for another year, here’s a look at a few high points as Salesforce pitched a new era for its customers, centered around Agentforce, which brings agentic AI to enterprise sales and service operations. “We want to be the first to welcome you into the future,” said…