Harshit Kumar

How do you compare and benchmark Frontier AI models?

Model Context Protocol (MCP) is an open-source protocol that standardizes how AI models (LLMs) connect to external tools, data sources, and services.

Language models (LM) can be evaluated in two broad ways: Intrinsic evaluation Measures the language model on its training objective e.g. next-word prediction.

A prompt is the input you give to LLM or AI agent like ChatGPT or Claude.

Training large language models requires large amounts of GPU memory, far beyond what a single GPU can provide.

The multimodal models that can learn from both image and text are called Vision Language Models (VLM).

Matrix multiplication is at the heart of deep learning.

While Large Language Models (LLMs) are revolutionary, they sometimes get it wrong like citing varying figures for something as critical as Tesla’s total assets on a given date.

In modern deep learning, getting models to train faster and run efficiently in production is a constant challenge.

PyTorch libraries torchvision: for computer vision torchtext: for NLP torchaudio: for speech PyTorch API (Python, C++, and CUDA) torch: core library torch.nn: for neural networks torch.nn.functional: defines functions torch.optim: for optimizers such as S…