Unite.AI

FEBRUARY 21, 2025

At the core of its performance are its advanced reasoning models, powered by cutting-edge deep learning techniques. This ability is supported by advanced technical components like inference engines and knowledge graphs, which enhance its reasoning skills.

AI Chatbots 179

AI Chatbots Chatbots AI AI 179

NVIDIA

APRIL 9, 2024

Qualified members of NVIDIA Inception, a global program supporting more than 18,000 startups, will have an accelerated path to using Google Cloud infrastructure with access to Google Cloud credits, offering up to $350,000 for those focused on AI.

AI Development 136

AI Development AI Developer Generative AI Inference Engine 136

Unite.AI

JUNE 21, 2024

The Rise of CUDA-Accelerated AI Frameworks GPU-accelerated deep learning has been fueled by the development of popular AI frameworks that leverage CUDA for efficient computation. Installation When setting AI development, using the latest drivers and libraries may not always be the best choice.

Deep Learning 130

Deep Learning Neural Network Convolutional Neural Networks Large Language Models 130

Unite.AI

AUGUST 12, 2024

1 With a successful Series Seed funding round of $31 million led by Andreessen Horowitz and support from notable angel investors, Black Forest Labs has positioned itself at the forefront of generative AI research. Black Forest Labs Open-Source FLUX.1 Introducing the Flux Model Family Black Forest Labs has introduced the FLUX.1

Natural Language Processing 246

Natural Language Processing Generative AI Inference Engine AI Tools 246

NVIDIA

OCTOBER 23, 2024

Fluid AI taps NVIDIA NIM microservices, the NVIDIA NeMo platform and the NVIDIA TensorRT inference engine to deliver a complete, scalable platform for developing custom generative AI for its customers. Karya also provides royalties to all contributors each time its datasets are sold to AI developers. “By

Conversational AI 96

Conversational AI Chatbots Generative AI Natural Language Processing 96

Marktechpost

OCTOBER 23, 2024

Differentiating human-authored content from AI-generated content, especially as AI becomes more natural, is a critical challenge that demands effective solutions to ensure transparency. Conclusion Google’s decision to open-source SynthID for AI text watermarking represents a significant step towards responsible AI development.

Large Language Models 107

Large Language Models Responsible AI Inference Engine Metadata 107