ThinkOnward's Geophysical Foundation Model is a pre-trained a Vision Transformer pre-trained on 450 synthetically generated Synthoseis 3D seismic volumes. We use a new elastic architecture and trace ...

TL;DR Key Takeaways : Liquid Foundation Models introduce a new generative AI architecture that diverges from traditional Transformers, aiming to reshape AI model design and functionality.

We introduce a novel polygonal training architecture for foundation model, designed to support large-scale training paradigms. Our approach incorporates critical factors such as model size, network ...

Liquid AI, a Massachusetts-based artificial intelligence (AI) startup, announced its first generative AI models not built on the existing transformer architecture. Dubbed Liquid Foundation Model (LFM) ...

MatterGen is a diffusion model, an AI architecture that has been used in image creation tools. Instead of generating pictures, MatterGen generates molecules for new materials. All the data that has ...

The DIFF Transformer significantly reduced hallucination rates compared to conventional models. In a detailed evaluation using question-answering datasets such as Qasper, HotpotQA, and 2WikiMultihopQA ...

K2 and JAIS: Advanced Foundation Models with Global Impact. ... The IFM's structure includes dedicated teams focused on model architecture, training methods, evaluation frameworks, ...

Accelerated delivery & Scalability: A single predictive foundation model will replace many individual models with a single architecture to deliver AI driven predictions faster and more efficiently.

Foundation models — neural networks trained on immense amounts of raw data — are ... GeForce RTX 50 Series GPUs, NVIDIA Blackwell architecture, GeForce GTX 580, Project R2X, NVIDIA ACE ...

Mixture of Experts (MoE) is an AI architecture which seeks to reduce the cost and improve the performance of AI models by sharing the internal processing workload across a number of smaller sub ...

Foundation models’ flexibility can help a business improve and streamline processes across teams without the cost and effort of developing an AI initiative from scratch.