large

In: Artificial Intelligence

Large language models (LLMs) can be used to perform natural language processing (NLP) tasks ranging from simple dialogues and information retrieval tasks, to more complex reasoning tasks such as summarization and decision-making. Prompt engineering and supervised fine-tuning, which use instructions and examples demonstrating the desired task, can make LLMs betterContinue Reading

In: Artificial Intelligence

DeepSeek-R1 is a large language model (LLM) developed by DeepSeek AI that uses reinforcement learning to enhance reasoning capabilities through a multi-stage training process from a DeepSeek-V3-Base foundation. A key distinguishing feature is its reinforcement learning step, which was used to refine the model’s responses beyond the standard pre-training andContinue Reading

In: Artificial Intelligence

This post is co-written with Marta Cavalleri and Giovanni Germani from Fastweb, and Claudia Sacco and Andrea Policarpi from BIP xTech. AI’s transformative impact extends throughout the modern business landscape, with telecommunications emerging as a key area of innovation. Fastweb, one of Italy’s leading telecommunications operators, recognized the immense potentialContinue Reading

In: Artificial Intelligence

In Part 1 of this series, we introduced Amazon SageMaker Fast Model Loader, a new capability in Amazon SageMaker that significantly reduces the time required to deploy and scale large language models (LLMs) for inference. We discussed how this innovation addresses one of the major bottlenecks in LLM deployment: the timeContinue Reading

In: Artificial Intelligence

The generative AI landscape has been rapidly evolving, with large language models (LLMs) at the forefront of this transformation. These models have grown exponentially in size and complexity, with some now containing hundreds of billions of parameters and requiring hundreds of gigabytes of memory. As LLMs continue to expand, AIContinue Reading

In: Artificial Intelligence

Large language models (LLMs) have witnessed an unprecedented surge in popularity, with customers increasingly using publicly available models such as Llama, Stable Diffusion, and Mistral. Across diverse industries—including healthcare, finance, and marketing—organizations are now engaged in pre-training and fine-tuning these increasingly larger LLMs, which often boast billions of parameters andContinue Reading

In: Artificial Intelligence

Hallucinations in large language models (LLMs) refer to the phenomenon where the LLM generates an output that is plausible but factually incorrect or made-up. This can occur when the model’s training data lacks the necessary information or when the model attempts to generate coherent responses by making logical inferences beyondContinue Reading