Groq Launches Large Model Inference Chip, Exceeding GPU Speeds at 500 Tokens Per Second

Aethir Launches AI Unbundled Alliance to Accelerate Web3 AI Innovation

Aethir, a decentralized GPU cloud computing provider, today announced the launch of an industry alliance called "AI Unbundled" to advance the Web3 artificial intelligence ecosystem. This initiative brings together leading organizations including 0G Labs, Biconomy, Polyhedra, Oasis Protocol Foundation, ChainGPT, IoTeX, iExec, Geodnet, Flock.io, and Alpha Ne.

Intel Open-Sources AI Playground: Arc GPU-Powered Local AI Model Execution

Intel recently announced the open-sourcing of its AI Playground software, designed for local generative AI. AI Playground provides a powerful platform for running AI models on Intel Arc GPUs. It supports various image and video generation models, as well as Large Language Models (LLMs), significantly lowering the hardware barrier for AI applications by optimizing local computing resources. The project is available on GitHub and has attracted developers and AI enthusiasts worldwide.

Intel Open Sources AI Playground for Intel Arc GPUs and Various AI Models

Intel has announced the open-sourcing of its generative AI software, AI Playground, generating significant interest within the AI community. Optimized for Intel Arc GPUs and integrated graphics, AI Playground is described as an 'AI hub' that supports local running of chat-based Large Language Models (LLMs), as well as image and video generation capabilities. This open-sourcing signifies Intel's commitment to advancing the accessibility of generative AI technology.

AMD GPU Performance Leap! Significant Stable Diffusion Model Optimization

AMD's advancements in AI are noteworthy, particularly its latest optimizations for the Stable Diffusion model. Recently, Stability AI released an ONNX-optimized version of Stable Diffusion, resulting in significantly improved performance for AMD Radeon GPUs and Ryzen integrated graphics in AI tasks, with speed increases up to 3.8 times faster. This progress narrows the gap with NVIDIA's ecosystem...

Former Intel CEO Criticizes Nvidia's AI Chip Pricing, Sees Inference as Future Opportunity

Former Intel CEO Pat Gelsinger recently criticized Nvidia's pricing strategy for its AI GPUs on the Acquired podcast during Nvidia's 2025 GPU Technology Conference, arguing that the high cost makes them unsuitable for large-scale AI inference tasks. Gelsinger highlighted that inference is crucial for deploying AI models and that the industry should focus more on inference, a domain where Nvidia's technology falls short in terms of cost-effectiveness. Image source omitted.

Wang Xing: Meituan's Developed Internal Large Language Model LongCat, Investing Billions in GPU Resources

Meituan CEO Wang Xing detailed the company's strategic plan for artificial intelligence (AI). Wang revealed that over the past year, Meituan prioritized securing GPU resources, investing heavily in AI infrastructure. He further stated that Meituan plans to further increase investment in key AI infrastructure in 2025 to strengthen its position in this field.

Open-Sora 2.0: Commercial-Grade Video AI at a Tenth the Cost!

HPC-AI Tech recently announced Open-Sora 2.0, a groundbreaking video AI system achieving commercial-grade quality at approximately one-tenth the typical training cost. This represents a potential paradigm shift in the resource-intensive field of video AI, mirroring efficiency gains seen in language models. While existing high-quality video generation systems like Movie Gen and Step-Video-T2V can cost millions of dollars to train, Open-Sora 2.0 offers a significantly more affordable alternative.

Nvidia Showcases Next-Generation AI Chips, Focusing on Blackwell Series GPUs

Suzhou Issues Measures to Accelerate the Development of AI Chip Industry

Moore Threads Open-Sources Two Major AI Frameworks, Achieving Over 90% Training Efficiency on Domestic GPUs