CIO
NOVEMBER 16, 2023
A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. Vector databases and RAG For most companies looking to customize their LLMs, retrieval augmented generation (RAG) is the way to go.
TechCrunch
NOVEMBER 5, 2023
Kai-Fu Lee, the computer scientist known in the West for his bestseller AI Superpowers and in China for his bets on artificial intelligence unicorns, has a new venture — and a great ambition. AI with the vision to develop a homegrown large language model for the Chinese market. […] © 2023 TechCrunch.
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CIO
MARCH 5, 2024
India’s Ministry of Electronics and Information Technology (MeitY) has caused consternation with its stern reminder to makers and users of large language models (LLMs) of their obligations under the country’s IT Act, after Google’s Gemini model was prompted to make derogatory remarks about Indian Prime Minister Narendra Modi.
Hacker Earth Developers Blog
JANUARY 31, 2020
Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% billion by the end of 2025. Alex Champandard.
Hacker Earth Developers Blog
JANUARY 31, 2020
Machine Learning (ML) is emerging as one of the hottest fields today. The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% The Machine Learning market is ever-growing, predicted to scale up at a CAGR of 43.8% billion by the end of 2025. Alex Champandard.
TechCrunch
FEBRUARY 13, 2023
Writer is such a one, and it just announced a new trio of large language models to power its enterprise copy assistant. The company lets customers fine-tune these models on their own content and style guides, from which point forward the AI can write, help write or edit copy so that it meets internal standards.
CIO
APRIL 12, 2023
Data is a key component when it comes to making accurate and timely recommendations and decisions in real time, particularly when organizations try to implement real-time artificial intelligence. The underpinning architecture needs to include event-streaming technology, high-performing databases, and machine learning feature stores.
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