The most important AI developments, summarized by AI.
Sea Limited's CPO explains why the company is deploying Codex across engineering teams to accelerate AI-native software development in Asia....
Read Original →AI researchers have released Granite Embedding Multilingual R2, a new open-source multilingual embedding model under the Apache 2.0 license. This model boasts a significant 32K context window, enabling it to process much larger amounts of text than previous iterations. Notably, it achieves the best retrieval quality among models with fewer than 100 million parameters.
Subnautica 2 is launching into early access on GeForce NOW simultaneously with its PC release. This allows members to stream the game to various devices, exploring a new alien ocean. It is among 11 new games added to the cloud service this week.
Codex is now accessible through the ChatGPT mobile app, allowing users to manage coding tasks remotely. This integration enables real-time monitoring, steering, and approval of coding projects from any device. Users can seamlessly work with Codex across various environments, enhancing flexibility and collaboration.
British company Humanoid will supply German industrial supplier Schaeffler with an estimated 1,000 to 2,000 humanoid robots for its global manufacturing sites by 2032. This significant agreement marks a step towards integrating physical AI into factory operations. The first phase of robot deployment is planned for an unspecified date.
The article highlights that top US real estate app development companies are assessed not just on general software development skills but critically on their ability to handle complex integrations like MLS feeds, payment systems, and document workflows. Many companies may excel in standard development but falter when these specialized real estate functionalities are required. The focus is on identifying vendors that truly understand the unique demands of real estate tech.
OpenAI has implemented new safety updates for ChatGPT designed to enhance its ability to understand context in sensitive conversations. These improvements allow the AI to better detect risks as conversations evolve and respond in a safer manner. The goal is to provide a more secure and reliable experience for users engaging in potentially sensitive discussions.
This article explores the concept of continuous batching in AI, a technique that optimizes inference by processing requests in dynamic batches rather than fixed ones. It highlights how unlocking asynchronicity within continuous batching can further enhance efficiency and reduce latency. The discussion delves into the technical aspects of achieving this asynchronous processing for improved AI model performance.