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Zhipu AI Releases GLM-4-Voice: A New Open-Source End-to-End Speech Large Language Model

Marktechpost

Zhipu AI recently released GLM-4-Voice, an open-source end-to-end speech large language model designed to address these limitations. It’s the latest addition to Zhipu’s extensive multi-modal large model family, which includes models capable of image understanding, video generation, and more.

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Katanemo Open Sources Arch-Function: A Set of Large Language Models (LLMs) Promising Ultra-Fast Speeds at Function-Calling Tasks for Agentic Workflows

Marktechpost

One of the biggest hurdles organizations face is implementing Large Language Models (LLMs) to handle intricate workflows effectively. Katanemo’s open sourcing of Arch-Function makes advanced AI tools accessible to a broader audience. Don’t Forget to join our 50k+ ML SubReddit.

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Deploying AI at Scale: How NVIDIA NIM and LangChain are Revolutionizing AI Integration and Performance

Unite.AI

NVIDIA Inference Microservices (NIM) and LangChain are two cutting-edge technologies that meet these needs, offering a comprehensive solution for deploying AI in real-world environments. Understanding NVIDIA NIM NVIDIA NIM, or NVIDIA Inference Microservices, is simplifying the process of deploying AI models.

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CMU Researchers Introduce ReLM: An AI System For Validating And Querying LLMs Using Standard Regular Expressions

Marktechpost

There are rising worries about the potential negative impacts of large language models (LLMs), such as data memorization, bias, and unsuitable language, despite LLMs’ widespread praise for their capacity to generate natural-sounding text.

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Overcoming Cross-Platform Deployment Hurdles in the Age of AI Processing Units

Unite.AI

Language Processing Units (LPUs): The Language Processing Unit (LPU) is a custom inference engine developed by Groq, specifically optimized for large language models (LLMs). LPUs use a single-core architecture to handle computationally intensive applications with a sequential component.

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Setting Up a Training, Fine-Tuning, and Inferencing of LLMs with NVIDIA GPUs and CUDA

Unite.AI

According to NVIDIA's benchmarks , TensorRT can provide up to 8x faster inference performance and 5x lower total cost of ownership compared to CPU-based inference for large language models like GPT-3. Accelerating LLM Training with GPUs and CUDA.

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Start Local, Go Global: India’s Startups Spur Growth and Innovation With NVIDIA Technology

NVIDIA

Conversational AI for Indian Railway Customers Bengaluru-based startup CoRover.ai already has over a billion users of its LLM-based conversational AI platform, which includes text, audio and video-based agents. NVIDIA AI technology enables us to deliver enterprise-grade virtual assistants that support 1.3