Search AI Products and News

The Silicon Base Flow platform has launched the open-source MoE model Kimi K2 developed by Moonshot AI. The model has a total of 1T parameters and 32B activated parameters, supports a context length of 128K, and performs excellently in coding and agent tasks. The pricing is 4 yuan per million tokens for input and 16 yuan per million tokens for output. New users can get 14 yuan in trial credit upon registration. The model has three technical advantages: 15.5T tokens of large-scale training, MuonClip optimizer for stable expansion, and design optimized for agent tasks. Tests show that it excels in coding

Recently, AI Infrastructure company SiliconBase Flow officially announced a strategic cooperation with Alibaba Cloud. SiliconBase Flow has joined the "Alibaba Cloud Flower Program" and entered the Alibaba Cloud Marketplace. This collaboration marks the beginning of deep cooperation in the AI field, working together to promote the development of large model services. According to the cooperation content, the core API services of SiliconBase Flow's large model inference platform, SiliconCloud, will fully integrate into Alibaba Cloud Bailian Platform, supported by Alibaba Cloud Lingjun Intelligent Computing Clusters, providing convenient and efficient large model services for cloud customers.

A comprehensive analysis of the features, user experience, and actual effects of the RepediaAI AI job platform, including services like smart job matching, interview practice, and resume optimization, to help you determine if this AI job assistant is worth using.

WeChat has recently fully launched the 'Q&A Host' function, opening a new door for creators to communicate. Previously, users could only ask questions through the 'Post' option in Q&A, with an invisible poster identity, limiting the interaction热度. With the release of the new function, creators can use the 'Initiate Discussion' option to showcase their official accounts or video accounts and obtain prominent host identifiers, enhancing their presence on the platform. The core of the 'Q&A Host' function lies in not only making the questioner's identity clearer but also...

In recent years, the field of artificial intelligence has undergone tremendous changes, especially with large language models (LLMs) making remarkable progress in multi-modal tasks. These models have demonstrated strong potential in their ability to understand and generate language, but most current multi-modal models still adopt auto-regressive (AR) architectures, which limit inference processes to be rather monotonous and lacking flexibility. To address this limitation, a research team from The University of Hong Kong and Huawei Noah's Ark Lab has proposed a brand new model – FUDOKI, aiming to break these constraints. The core innovation of FUDOKI is

The rapid development of drone technology is changing our way of life, and research on controlling drones with voice commands is undoubtedly a pioneer in this field. A project named UAV-Flow is emerging with an innovative approach. By utilizing natural language processing technology, users can precisely control drones with only voice instructions. This technological breakthrough is expected to significantly reduce the threshold for drone operation and promote its widespread use in consumer, industrial, and rescue scenarios. Here is AIbase's in-depth analysis of the project. UAV-Flow Project: Control with Language

Family members, today I must tell you about a super cool new achievement in the academic world - Flow-GRPO! This thing is something special; it's like injecting a super evolution agent into image generation models, directly elevating them from 'Bronze' to 'King'. Do you want to know how it does that? Quickly grab your stools and listen carefully! The Growing Pains of Image Generation Models: Nowadays, image generation models, such as those based on flow matching, have a solid theoretical foundation and generate high-quality results.

BD (Becton, Dickinson and Company), a leading global medical technology company, recently launched the revolutionary HemoSphere Alta™ hemodynamic monitoring platform. Equipped with AI predictive algorithms, it provides early warnings of potentially fatal blood pressure fluctuations during surgery, offering clinicians critical decision support. Image Note: Image generated by AI, image licensing provided by Midjourney. Technological Breakthrough: Cerebral Blood Flow Autoregulation Index. This platform introduces the groundbreaking Cerebral Blood Flow Autoregulation Index (C...

According to LatePost, ByteDance recently made significant adjustments to its AI product department, Flow. The social companionship AI product, Cat Box, has a new leader. The previous head, Liang Chenqi, has left the company, and has been replaced by Xi Yuan (codename), the former head of Xinghui. Meanwhile, the Xinghui team, which develops AI camera and image generation applications, is slated to merge into the Doubao App, under the unified management of Doubao App's head, Lu You (codename). The Flow department is headed by Zhu Jun and includes Doubao, Cat Box, Xinghui, Doubao Aixue, and G.

Following its $32.1 million Series B funding round in October, data governance platform provider Relyance AI has launched its new Data Journeys platform. Designed to address key challenges enterprises face when adopting AI, the platform provides precise visibility into how data flows through complex systems. It tracks how and why data is used across applications, cloud services, and third-party systems, filling gaps left by traditional data lineage methods. Relyance AI CEO and co-founder A...

Imagine you've painstakingly trained a brilliant AI large model capable of handling complex tasks. However, if the pipeline to this intelligent brain—the Model Context Protocol (MCP)—is insecure, you've left an opening for hackers. Don't worry! Created by blockchain security experts SlowMist, the MCP Security Checklist acts as a professional AI 'shield' providing enhanced security for MCP-based AI tools.

AI startup Luma recently announced on X that it has open-sourced a new image model pretraining technique called Inductive Moment Matching (IMM). This breakthrough technology has garnered significant attention for its efficiency and stability, considered a major advancement in the generative AI field. According to X user linqi_zhou, IMM is a novel generative paradigm capable of stable training from scratch with a single model and single objective, surpassing existing methods in both sampling efficiency and sample quality.