Real-world data is often costly, messy, and limited by privacy rules. Synthetic data offers a solution—and it’s already widely used: LLMs train on AI-generated text Fraud systems simulate edge cases ...

NVIDIA has released Llama Nemotron Nano 4B, an open-source reasoning model designed to deliver strong performance and efficiency across scientific tasks, programming, symbolic math, function calling, ...

Many websites lack accessible and cost-effective ways to integrate natural language interfaces, making it difficult for users to interact with site content through conversational AI. Existing ...

Language models (LMs) have great capabilities as in-context learners when pretrained on vast internet text corpora, allowing them to generalize effectively from just a few task examples. However, fine ...

Large Reasoning Models (LRMs) like OpenAI’s o1 and o3, DeepSeek-R1, Grok 3.5, and Gemini 2.5 Pro have shown strong capabilities in long CoT reasoning, ...

Meta has introduced KernelLLM, an 8-billion-parameter language model fine-tuned from Llama 3.1 Instruct, aimed at automating the translation of PyTorch modules into efficient Triton GPU kernels. This ...

Data Scarcity in Generative Modeling Generative models traditionally rely on large, high-quality datasets to produce samples that replicate the underlying data distribution. However, in fields like ...

The Model Context Protocol (MCP) represents a powerful paradigm shift in how large language models interact with tools, services, and external data sources. Designed to enable dynamic tool invocation, ...

Recent advancements in LM agents have shown promising potential for automating intricate real-world tasks. These agents typically operate by proposing and executing actions through... Amazon Web ...

VLMs have become central to building general-purpose AI systems capable of understanding and interacting in digital and real-world settings. By integrating visual and textual data, VLMs have driven ...

Recent progress in LLMs has shown their potential in performing complex reasoning tasks and effectively using external tools like search engines. Despite this, teaching models to make smart decisions ...

This hands-on tutorial will walk you through the entire process of working with CSV/Excel files and conducting exploratory data analysis (EDA) in Python. We’ll use a realistic e-commerce sales dataset ...