Sam Altman returns as CEO, OpenAI has a new initial board

Powered by jotform.ai Welcome Interested in sponsorship opportunities? Join the AI conversation and transform your advertising strategy with AI weekly sponsorship aiweekly.co In the News Google DeepMind’s new AI models Google DeepMind is launching two new AI models designed to help robots “perform a wider range of real-world tasks than ever before.” The first, called…

Large language models (LLMs) have revolutionized various AI-infused applications, from chat models to autonomous driving. This evolution has spurred the need for systems that can efficiently deploy and serve these models, especially under the increasing demand for handling long-prompt workloads. The major hurdle in this domain has been balancing high throughput and low latency in…

Aging involves the gradual accumulation of damage and is an important risk factor for chronic diseases. Epigenetic mechanisms, particularly DNA methylation, play a role in aging, though the specific biological processes remain unclear. Epigenetic clocks accurately estimate biological age based on DNA methylation, but their underlying algorithms and key aging processes must be better understood….

Processing extensive sequences of linguistic data has been a significant hurdle, with traditional transformer models often buckling under the weight of computational and memory demands. This limitation is primarily due to the quadratic complexity of the attention mechanisms these models rely on, which scales poorly as sequence length increases. The introduction of State Space Models…

MLLMs, or multimodal large language models, have been advancing lately. By incorporating images into large language models (LLMs) and harnessing the capabilities of LLMs, MLLMs demonstrate exceptional skill in tasks including visual question answering, instruction following, and image understanding. Studies have seen a significant flaw in these models despite their improvements; they still have some…

Current multi-modal language models (LMs) face limitations in performing complex visual reasoning tasks. These tasks, such as compositional action recognition in videos, demand an intricate blend of low-level object motion and interaction analysis with high-level causal and compositional spatiotemporal reasoning. While these models excel in various areas, their effectiveness in tasks requiring detailed attention to…