In the rapidly expanding world of generative artificial intelligence (AI), the importance of independent evaluation and 'red teaming' is crucial in order to reveal potential risks and ensure that these AI systems align with public safety and ethical standards. However, stringent terms of service and enforcement practices set by leading AI organisations disrupt this critical…
Artificial Intelligence (AI) is at the forefront of innovation in the fast-changing field of healthcare. Among the most advanced AI initiatives is ChatGPT, an AI developed by OpenAI, known for its deep learning capabilities. This application is transforming healthcare practices by making them more accessible, efficient, and personalized. This article lists ten pivotal applications of…
In the ever-evolving digital landscape, 3D content creation is a constantly changing frontier. This area is crucial for various industries like gaming, film production, and virtual reality. The innovation of automatic 3D generation technologies is triggering a shift on how we conceive and interact with digital environments. These technologies are making 3D content creation democratic…
Researchers at MIT, Harvard, and the National Institutes of Health have utilized a new search algorithm to identify 188 different types of rare CRISPR systems in bacterial genomes. This data holds potential to advance genome-editing technology, enabling more precise treatments and diagnostics.
The algorithm, developed in the lab of prominent CRISPR researcher, Professor Feng Zhang uses…
Visual Language Models (VLMs) have proven instrumental in tasks such as image captioning and visual question answering. However, the efficiency of these models is often hampered by challenges such as data scarcity, high curation costs, lack of diversity, and noisy internet-sourced data. To combat these setbacks, researchers from Google DeepMind have introduced Synth2, a method…
Machine learning (ML) workflows have become increasingly complex and extensive, prompting a need for innovative optimization approaches. These workflows, vital for many organizations, require vast resources and time, driving up operational costs as they adjust to various data infrastructures. Handling these workflows involved dealing with a multitude of different workflow engines, each with their own…
In the realm of artificial intelligence, notable advancements are being made in the development of language agents capable of understanding and navigating human social dynamics. These sophisticated agents are being designed to comprehend and react to cultural nuances, emotional expressions, and unspoken social norms. The ultimate objective is to establish interactive AI entities that are…
Google Research has recently launched FAX, a high-tech software library, in an effort to improve federated learning computations. The software, built on JavaScript, has been designed with multiple functionalities. These include large-scale, distributed federated calculations along with diverse applications including data center and cross-device provisions. Thanks to the JAX sharding feature, FAX facilitates smooth integration…
Scientists from the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information at the National Institutes of Health have developed a new algorithm that can sift through massive amounts of genomic data to identify unique CRISPR systems. Known as Fast Locality-Sensitive Hashing-based clustering…
In the field of digital replication of human motion, researchers have long faced two main challenges: the computational complexities of these models, and capturing the intricate, fluid nature of human movement. Utilising state space models, particularly the Mamba variant, has yielded promising advancements in handling long sequences more effectively while reducing computational demands. However, these…
The Retrieval Augmented Generation (RAG) approach is a sophisticated technique employed within language models that enhances the model's comprehension by retrieving pertinent data from external sources. This method presents a distinct challenge when evaluating its overall performance, creating the need for a systematic way to gauge the effectiveness of applying external data in these models.
Several…
Large language models (LLMs), exemplified by dense transformer models like GPT-2 and PaLM, have revolutionized natural language processing thanks to their vast number of parameters, leading to record levels of accuracy and essential roles in data management tasks. However, these models are incredibly large and power-intensive, overwhelming the capabilities of even the strongest Graphic Processing…