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Machine Heart
Machine Heart
Apr 24, 2026 · Artificial Intelligence

Cambricon Achieves Day‑0 Native Support for DeepSeek‑V4, Uniting Two Chinese AI Leaders

Cambricon leveraged its NeuWare stack and vLLM framework to deliver Day‑0 native support for DeepSeek‑V4‑flash (285 B) and DeepSeek‑V4‑pro (1.6 T), open‑sourcing the adaptation and showcasing rapid model migration alongside extreme performance optimizations across software and hardware layers.

AI inferenceCambriconDeepSeek-V4
0 likes · 5 min read
Cambricon Achieves Day‑0 Native Support for DeepSeek‑V4, Uniting Two Chinese AI Leaders
AntTech
AntTech
Jul 18, 2025 · Artificial Intelligence

Explore the 2025 CCF‑Ant Research Fund: 50 Cutting‑Edge Projects in AI, Security & Computing

The CCF‑Ant Research Fund 2025, now open for its first batch, invites global university and institute researchers to apply by August 25 2025 for up to 50 projects spanning data security, hardware‑software co‑design, supercomputing, and artificial intelligence, with detailed topics, eligibility rules, and submission channels provided.

High‑performance computingResearch Fundingdata security
0 likes · 11 min read
Explore the 2025 CCF‑Ant Research Fund: 50 Cutting‑Edge Projects in AI, Security & Computing
Kuaishou Tech
Kuaishou Tech
Nov 8, 2021 · Artificial Intelligence

FPGA-Based Real-Time Streaming ASR Acceleration for Kuaishou: A Case Study in Domain-Specific Hardware Optimization

This paper presents a full fixed-point FPGA-based hardware acceleration solution for TDNN+LSTM acoustic models in real-time streaming ASR, achieving 37.67% latency reduction and 7.5x concurrency improvement through software-hardware co-design and domain-specific optimization.

Domain-specific ArchitectureFPGA accelerationTDNN+LSTM
0 likes · 16 min read
FPGA-Based Real-Time Streaming ASR Acceleration for Kuaishou: A Case Study in Domain-Specific Hardware Optimization
Alibaba Cloud Developer
Alibaba Cloud Developer
May 21, 2019 · Artificial Intelligence

How Alibaba’s Offline AI Advances Model Compression and Edge Inference

Alibaba’s Machine Intelligence Lab shares two years of breakthroughs in offline AI, detailing low‑bit quantization, unified sparsity frameworks, hardware‑software co‑design, lightweight networks, and on‑device detection, alongside standardized training tools, multi‑platform inference engines, and productized edge solutions such as smart boxes and integrated cameras.

AIedge inferencehardware-software co-design
0 likes · 16 min read
How Alibaba’s Offline AI Advances Model Compression and Edge Inference