Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL). In a recent study, researchers at Google DeepMind and Stanford ...
AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...
The offline pipeline's primary objective is regression testing — identifying failures, drift, and latency before production. Deploying an enterprise LLM feature without a gating offline evaluation ...
Wonder what is really powering your ChatGPT or Gemini chatbots? This is everything you need to know about large language models. Lisa Lacy Former Lead AI Writer Lisa joined CNET after more than 20 ...
A new technical paper titled “Pushing the Envelope of LLM Inference on AI-PC and Intel GPUs” was published by researcher at Intel. “The advent of ultra-low-bit LLM models (1/1.58/2-bit), which match ...
Microsoft’s Semantic Kernel SDK makes it easier to manage complex prompts and get focused results from large language models like GPT. At first glance, building a large language model (LLM) like GPT-4 ...
In the world of artificial intelligence, the ability to build Large Language Model (LLM) and Retrieval Augmented Generation (RAG) pipelines using open-source models is a skill that is increasingly in ...
Small Language Models or SLMs are on their way toward being on your smartphones and other local devices, be aware of what's coming. In today’s column, I take a close look at the rising availability ...
AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...
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