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AI Decoded: Demystifying Large Language Models, the Brains Behind Chatbots

NVIDIA

Editor’s note: This post is part of our AI Decoded series , which aims to demystify AI by making the technology more accessible, while showcasing new hardware, software, tools and accelerations for RTX PC and workstation users. If AI is having its iPhone moment, then chatbots are one of its first popular apps.

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Meta AI Releases Code Llama: A State-of-the-Art Large Language Model for Coding

Marktechpost

In the ever-evolving landscape of software development, the need for efficient and productive coding tools has never been greater. Developers face the challenge of writing robust, well-documented code while navigating the complexities of debugging and code completion.

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Qdrant, an open source vector database startup, wants to help AI developers leverage unstructured data

Flipboard

But while there’s little question of a seismic sea change these past six months in terms of public awareness, the growing demand for AI could be outpacing the infrastructure required to power the myriad use cases that are emerging — and this is something that German startup Qdrant is looking to address.

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Chuck Ros, SoftServe: Delivering transformative AI solutions responsibly

AI News

.” Recognising the critical concern of ethical AI development, Ros stressed the significance of human oversight throughout the entire process. Softserve’s findings suggest that GenAI can accelerate programming productivity by as much as 40 percent.

Big Data 236
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Enterprises must shift their focus from models to data in AI development

Snorkel AI

In my capacity as a machine learning researcher, I’ve observed a profound paradigm shift in the field of AI development. We are transitioning from a focus on the models and algorithms that underpin AI to a greater emphasis on the data that powers these models.

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Enterprises must shift their focus from models to data in AI development

Snorkel AI

In my capacity as a machine learning researcher, I’ve observed a profound paradigm shift in the field of AI development. We are transitioning from a focus on the models and algorithms that underpin AI to a greater emphasis on the data that powers these models.

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Introducing Snorkel’s Foundation Model Data Platform

Snorkel AI

In 2007, Google researchers published a paper on a class of statistical language models they dubbed “large language models”, which they reported as achieving a new state of the art in performance. They used a very standard model and a decoding algorithm so simple they named it “Stupid Backoff” 1.