Remove AI Development Remove Inference Engine Remove Large Language Models
article thumbnail

Baichuan-Omni: An Open-Source 7B Multimodal Large Language Model for Image, Video, Audio, and Text Processing

Marktechpost

Recent advancements in Large Language Models (LLMs) have reshaped the Artificial intelligence (AI)landscape, paving the way for the creation of Multimodal Large Language Models (MLLMs). Don’t Forget to join our 50k+ ML SubReddit.

article thumbnail

Agent-as-a-Judge: An Advanced AI Framework for Scalable and Accurate Evaluation of AI Systems Through Continuous Feedback and Human-level Judgments

Marktechpost

As a result, the potential for real-time optimization of agentic systems could be improved, slowing their progress in real-world applications like code generation and software development. The lack of effective evaluation methods poses a serious problem for AI research and development.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Differentiable Adaptive Merging (DAM): A Novel AI Approach to Model Integration

Marktechpost

Model merging, particularly within the realm of large language models (LLMs), presents an intriguing challenge that addresses the growing demand for versatile AI systems. DAM proves that focusing on efficiency and scalability without sacrificing performance can provide a significant advantage in AI development.

article thumbnail

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.

article thumbnail

Start Up Your Engines: NVIDIA and Google Cloud Collaborate to Accelerate AI Development

NVIDIA

Teams from the companies worked closely together to accelerate the performance of Gemma — built from the same research and technology used to create Google DeepMind’s most capable model yet, Gemini — with NVIDIA TensorRT-LLM , an open-source library for optimizing large language model inference, when running on NVIDIA GPUs.

article thumbnail

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. For instance, while the latest NVIDIA driver (545.xx) xx) supports CUDA 12.3,

article thumbnail

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.