Marktechpost

AUGUST 12, 2024

To address these challenges, existing methods, such as Retrieval-Augmented Generation (RAG) techniques, have enhanced the capabilities of large language models (LLMs) in processing and understanding financial text.

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NVIDIA

OCTOBER 15, 2024

Moving to accelerate enterprise AI innovation, NVIDIA founder and CEO Jensen Huang joined Lenovo CEO Yuanqing Yang on stage Tuesday during the keynote at Lenovo Tech World 2024. It enables organizations to create agentic AI and physical AI that transform data into actionable business outcomes more efficiently. “Our

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O'Reilly Media

NOVEMBER 19, 2024

One popular term encountered in generative AI practice is retrieval-augmented generation (RAG). Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. Do LLMs Really Adapt to Domains?

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ODSC - Open Data Science

MARCH 13, 2025

As AI continues to evolve, there is growing demand for lightweight large language models that balance efficiency and performance. Together in this blog, were going to explore what makes an LLM lightweight, the top models in 2025, and how to choose the right one for yourneeds.

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Marktechpost

FEBRUARY 28, 2025

Large Language Models (LLMs) rely on reinforcement learning techniques to enhance response generation capabilities. One critical aspect of their development is reward modeling, which helps in training models to align better with human expectations.

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Marktechpost

JUNE 29, 2024

Spatial decomposition can be applied in many scientific contexts where data samples are too large to fit on a single device. The evolution of AI for science includes the development of hybrid AI-simulation workflows, such as cognitive simulations (CogSim) and digital twins.

Neural Network 108

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ODSC - Open Data Science

APRIL 6, 2023

5 Practical Business Use Cases for Large Language Models LLMs are everywhere now. Let’s take a look at a few practical use cases for large language models and how they can shape your AI endeavors too. Check out some more highlights in the full schedule here!

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ODSC - Open Data Science

NOVEMBER 21, 2024

Understanding the Core Limitations of Large Language Models: Insights from Gary Marcus Gary Marcus, a leading voice and critic of AI, shared his thoughts in a recent podcast, where he explored LLMs’ limitations, the need for hybrid AI approaches, and more.

Data Science 40

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ODSC - Open Data Science

DECEMBER 2, 2024

In a recent episode of ODSC’s Ai X Podcast , which was recorded live during ODSC West 2024 , Gary Marcus, an influential AI researcher, shared a critical perspective on the limitations of large language models (LLMs), emphasizing the need for true reasoning capabilities in AI.

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