Researchers from Sony AI and the King Abdullah University of Science and Technology (KAUST) have developed FedP3, a solution aimed at addressing the challenges of model heterogeneity in federated learning (FL). Model heterogeneity arises when devices used in FL have different capabilities and data distributions. FedP3, which stands for Federated Personalized and Privacy-friendly network Pruning,…
Training deep neural networks with hundreds of layers can be a painstaking process, often taking weeks due to the sequential nature of the backpropagation learning method. While this process works on a single computer unit, it is challenging to parallelize across multiple systems, leading to long waiting times.
This issue escalates further when dealing with enormous…
Hugging Face Researchers have unveiled Idefics2, an impressive 8-billion parameter vision-language model. It is designed to enhance the blending of text and image processing within a single framework. Unlike previous models which required the resizing of images to fixed dimensions, the Idefics2 model uses the Native Vision Transformers (NaViT) strategy to process images at their…
Artificial intelligence technology continues to evolve at a rapid pace, with innovative solutions bringing AI from prototype to production. Recognizing the challenges these transitions can present, TrueFoundry has introduced a novel open-source framework — Cognita — leveraging Retriever-Augmented Generation (RAG) technology to provide a more straightforward and scalable pathway to deploying AI applications.
Cognita is designed…
Social media giant, Meta, recently revealed its latest large language model, the Meta Llama 3. This model is not just an upgrade but is a significant breakthrough in the field of Artificial Intelligence (AI). The company has outdone itself by setting a new industry standard for open-source AI models.
The Meta Llama 3 is available in…
Large language models (LLMs) are used across different sectors such as technology, healthcare, finance, and education, and are instrumental in transforming stable workflows in these areas. An approach called Reinforcement Learning from Human Feedback (RLHF) is often applied to fine-tune these models. RLHF uses human feedback to tackle Reinforcement Learning (RL) issues such as simulated…
Google AI researchers have developed a new Transformer network dubbed TransformerFAM, aimed to enhance performance in handling extremely long context tasks. Despite Transformers proving revolutionary in the domain of deep learning, they have limitations due to their quadratic attention complexity— an aspect that curtails their ability to process infinitely long inputs. Existing Transformers often forget…
The increasing demand for AI-generated content following the development of innovative generative Artificial Intelligence models like ChatGPT, GEMINI, and BARD has amplified the need for high-quality text-to-audio, text-to-image, and text-to-video models. Recently, supervised fine-tuning-based direct preference optimisation (DPO) has become a prevalent alternative to traditional reinforcement learning methods in lining up Large Language Model (LLM)…
Tango 2: The Emerging Frontier in Text-to-Audio Synthesis and Its Outstanding Performance Indicators
As demand for AI-generated content continues to increase, particularly in the multimedia realm, the need for high-quality, quick production models for text-to-audio, text-to-image, and text-to-video conversions has never been greater. An emphasis is placed on enhancing the realistic nature of these models in regard to their input prompts.
A novel approach to adjust Large Language Model…
