Beijing, China – April 15, 2025– In a strategic move that underscores its technological prowess and global ambitions, potentially paving the way for a future IPO, Chinese AI company Zhipu.AI has announced the comprehensive open-sourcing of its next-generation General Language Models (GLM). This release includes the advanced GLM-4 series and the groundbreaking GLM-Z1 inference models, […]
Beijing, China – April 15, 2025– In a strategic move that underscores its technological prowess and global ambitions, potentially paving the way for a future IPO, Chinese AI company Zhipu.AI has announced the comprehensive open-sourcing of its next-generation General Language Models (GLM). This release includes the advanced GLM-4 series and the groundbreaking GLM-Z1 inference models,
Beijing, China – April 15, 2025– In a strategic move that underscores its technological prowess and global ambitions, potentially paving the way for a future IPO, Chinese AI company Zhipu.AI has announced the comprehensive open-sourcing of its next-generation General Language Models (GLM). This release includes the advanced GLM-4 series and the groundbreaking GLM-Z1 inference models,
DeepSeek AI, a prominent player in the large language model arena, has recently published a research paper detailing a new technique aimed at enhancing the scalability of general reward models (GRMs) during the inference phase. Simultaneously, the company has hinted at the imminent arrival of its next-generation model, R2, building anticipation within the AI community.
DeepSeek AI, a prominent player in the large language model arena, has recently published a research paper detailing a new technique aimed at enhancing the scalability of general reward models (GRMs) during the inference phase. Simultaneously, the company has hinted at the imminent arrival of its next-generation model, R2, building anticipation within the AI community.
DeepSeek AI, a prominent player in the large language model arena, has recently published a research paper detailing a new technique aimed at enhancing the scalability of general reward models (GRMs) during the inference phase. Simultaneously, the company has hinted at the imminent arrival of its next-generation model, R2, building anticipation within the AI community.
Just a year after the initial explosion of interest in AI video generation, the competitive landscape is reportedly undergoing a significant transformation. The focus is shifting from simply achieving video generation capabilities to the critical challenge of demonstrating profitability. This evolution appears to be eroding the once seemingly unassailable dominant status of OpenAI’s Sora, as
By John P. Desmond, AI Trends Editor The AI stack defined by Carnegie Mellon University is fundamental to the approach being taken by the US Army for its AI development platform efforts, according to Isaac Faber, Chief Data Scientist at the US Army AI Integration Center, speaking at the AI World Government event held in-person and virtually
Best Practices for Building the AI Development Platform in Government Read More »
By John P. Desmond, AI Trends Editor Advancing trustworthy AI and machine learning to mitigate agency risk is a priority for the US Department of Energy (DOE), and identifying best practices for implementing AI at scale is a priority for the US General Services Administration (GSA). That’s what attendees learned in two sessions at the AI
Advance Trustworthy AI and ML, and Identify Best Practices for Scaling AI Read More »
By AI Trends Staff While AI in hiring is now widely used for writing job descriptions, screening candidates, and automating interviews, it poses a risk of wide discrimination if not implemented carefully. That was the message from Keith Sonderling, Commissioner with the US Equal Opportunity Commision, speaking at the AI World Government event held live and virtually in
Promise and Perils of Using AI for Hiring: Guard Against Data Bias Read More »
