HuggingFace researchers have developed a new tool called Quanto to streamline the deployment of deep learning models on devices with limited resources, such as mobile phones and embedded systems. The tool addresses the challenge of optimizing these models by reducing their computational and memory footprints. It achieves this by using low-precision data types, such as…
The capabilities of computer vision studies have been vastly expanded due to deep features, which can unlock image semantics and facilitate diverse tasks, even using minimal data. Techniques to extract features from a range of data types – for example, images, text, and audio – have been developed and underpin a number of applications in…
Large language models like GPT-4, while powerful, often struggle with basic visual perception tasks such as counting objects in an image. This can be due to the way these models process high-resolution images. Current AI systems can mainly perceive images at a fixed low resolution, leading to distortion, blurriness, and loss of detail when the…
Research in materials science is increasingly focusing on the rapid discovery and characterization of materials with specific attributes. A key aspect of this research is the comprehension of crystal structures, which are naturally complex due to their periodic and infinite nature. This complexity presents significant challenges when attempting to model and predict material properties, difficulties…
The production of realistic human facial images has been a long-standing challenge for researchers in machine learning and computer vision. Earlier techniques like Eigenfaces utilised Principal Component Analysis (PCA) to learn statistical priors from data, yet they notably struggled to capture the complexities of real-world factors such as lighting, viewpoints, and expressions beyond frontal poses.…
In the world of machine learning, large language models (LLMs) are a significant area of study. Recently, model merging or the combination of multiple LLMs into a single framework has fascinated the researcher's community because it doesn't require any additional training. This reduces the cost of creating new models considerably, sparking an interest in model…
iRobot co-founder and MIT Professor Emeritus, Rodney Brooks, warned about overestimating the capabilities of generative AI during a keynote speech at the "Generative AI: Shaping the Future” symposium. This marked the start of MIT’s Generative AI Week, which aimed to examine the potential of AI tools like OpenAI’s ChatGPT and Google’s Bard.
Generative AI refers to…
Companies like FedEx utilize intricate software to efficiently deliver holiday parcels, but these complex processes can often take hours or even days to complete. The software, known as a mixed-integer linear programming (MILP) solver, is often halted partway through by firms, accepting the best solution that can be gleaned in a particular timeframe, even if…
In an attempt to assure the "safe, secure, and trustworthy" integration of Artificial Intelligence (AI) systems, the United Nations (UN) General Assembly has adopted a new resolution, with the backing of over 120 member states. The resolution, an informal agreement drafted by the United States, emphasizes the potential of AI to expedite progress toward the…
Emad Mostaque, founder and CEO of Stability AI, has announced his resignation from both his executive role and the company board. Stability AI is recognized for its image generation tool named Stable Diffusion, which previously led to various copyright infringement lawsuits and claims of enabling the creation of illicit images.
In the interim, the COO and…
Researchers and developers often need to execute large language models (LLMs), such as Generative Pre-trained Transformers (GPT), with efficiency and speed. The choice of hardware greatly influences performance during these processing tasks, with the two main contenders being Central Processing Units (CPUs) and Graphics Processing Units (GPUs).
CPUs are standard in virtually all computing devices and…