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Reinforcement learning (RL) has witnessed significant strides in integrating Transformer architectures, which are known for their proficiency in handling long-term dependencies in data. This advancement is crucial in RL, where algorithms learn to make sequential decisions, often in complex and dynamic environments. The fundamental challenge in RL is twofold: understanding and utilizing past observations (memory)…

In the News The power shift inside OpenAI OpenAI’s new CEO of Applications frees up Sam Altman to focus on GPUs, brain-computer interfaces, and consumer hardware. theverge.com In The News Is Google’s Reveal of Gemini’s Impact Progress or Greenwashing? Google has released a technical paper detailing the energy, water and carbon footprint their Gemini models….

Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Google’s Nobel prize winners stir debate over AI research Google has been at the forefront of AI research, but has been forced on the defensive as it tackles competitive pressure from Microsoft-backed (MSFT.O),…

With new releases and introductions in the field of Artificial Intelligence (AI), Large Language Models (LLMs) are advancing significantly. They are showcasing their incredible capability of generating and comprehending natural language. However, there are certain difficulties experienced by LLMs with an emphasis on English when managing non-English languages, especially those with constrained resources. Although the…

A team of researchers from the University of Washington has collaborated to address the challenges in the protein sequence design method by using a deep learning-based protein sequence design method, LigandMPNN. The model targets enzymes and small molecule binder and sensor designs. Existing physically based approaches like Rosetta and deep learning-based models like ProteinMPNN are…

3D-aware Generative Adversarial Networks (GANs) have made remarkable advancements in generating multi-view-consistent images and 3D geometries from collections of 2D images through neural volume rendering. However, despite these advancements, a significant challenge has emerged due to the substantial memory and computational costs associated with dense sampling in volume rendering. This limitation has compelled 3D GANs…