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Tencent officially launched and open-sourced a new member of the Hypermix large model family - the Hypermix-A13B model. The model adopts an expert mixture (MoE) architecture, with a total parameter scale of 80 billion and an activated parameter count of 13 billion. It maintains the performance of top-tier open-source models while significantly reducing inference latency and computational costs, providing a more cost-effective AI solution for individual developers and small and medium-sized enterprises.

MegaT AI Search has launched a brand new Ultra-fast model, marking a significant breakthrough in its artificial intelligence search technology. Through innovative technical means, the response speed of MegaT AI Search has reached an amazing 400 tokens/second, ensuring that most questions can be answered within 2 seconds. This advancement not only enhances user experience but also significantly improves information retrieval efficiency. The realization of the Ultra-fast model is thanks to the application of multiple advanced technologies. The MegaT AI team has optimized on GPUs using ker

Recently, MiTA AI Search officially launched the new ultra-fast model, bringing users a more efficient and accurate search experience. The MiTA AI Search team successfully achieved a maximum response speed of 400 tokens/second on a single H800 GPU through kernel fusion technology on GPUs and dynamic compilation optimization strategies on CPUs, with most responses provided within 2 seconds.

Recently, Mistral AI, headquartered in Paris, France, in partnership with All Hands AI, has launched an open-source AI model designed specifically for software development — Devstral. This model boasts up to 24 billion parameters and is currently in the "research preview" stage, released under the Apache2.0 open license, allowing developers and enterprises to use it freely in commercial applications. The release of Devstral marks a significant step forward for AI in the programming field.

American chipmaker Nvidia recently announced it would collaborate with Humain, an AI startup owned by the Saudi Arabian sovereign wealth fund, to provide 18,000 cutting-edge AI chips to Saudi Arabia. This announcement was made during the visit of a US delegation to Saudi Arabia, Qatar and the UAE, marking an important step for Saudi Arabia in artificial intelligence and cloud computing infrastructure. Nvidia founder Jensen Huang expressed this at the Saudi-US Investment Forum.

Shanghai is actively promoting innovation and upgrading within its automotive industry, focusing on the application of advanced technologies including high-performance computing chips and intelligent driving large models. This initiative aims to enhance the competitiveness and technological advancement of the city's automotive sector.

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 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 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'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...

Nvidia recently announced plans to establish over one million square feet of manufacturing space in Arizona and Texas for the production and testing of AI chips. This represents a significant move by Nvidia to bring some of its manufacturing back to the United States. Nvidia's Blackwell chip is already in production at TSMC's Arizona facility. Additionally, Nvidia is establishing "supercomputer" manufacturing plants in Texas, partnering with Foxconn in Houston and Wistron in Dallas. In Arizona, Nvidia is collaborating with Amkor and others.

nEye Systems Inc., a silicon photonics startup, announced today that it has closed a $58 million Series B funding round. The investment was led by CapitalG, the growth equity investment arm of Alphabet Inc., Google's parent company. Other participants include Microsoft's M12, Micron Ventures, Nvidia, and Socratic Partners. This brings nEye's total funding to over $72 million.

In a recent annual letter to shareholders, Amazon CEO Andy Jassy highlighted the company's significant investment in artificial intelligence (AI). He noted that while the development and deployment costs of AI remain high, future AI usage costs are expected to decrease significantly as technology advances. Image Note: Image generated by AI, image licensing provider Midjourney. Jassy revealed that Amazon plans to invest up to $100 billion in capital expenditures in 2025.

In today's rapidly expanding AI landscape, many businesses face high hardware costs, particularly the need for advanced computing chips. To address this challenge, Indian AI startup Ziroh Labs, in collaboration with researchers from top technical institutes in the country, has launched a novel, affordable system capable of running large AI models without relying on high-end computing chips from companies like Nvidia. This innovative system marks a significant step towards democratizing AI access by expanding device options.

Japan's state-backed Rapidus Corp. has begun adjusting its chipmaking equipment and is expected to start test production of advanced semiconductors by the end of this month. This is a crucial step for Rapidus as it pushes to enter the artificial intelligence (AI) components market. The two-year-old startup aims for mass production of 2nm semiconductors by 2027, aiming to rival Taiwan Semiconductor Manufacturing Company (TSMC), a leading semiconductor manufacturer. Image Caption: Image

Faster data transfer speeds are crucial for advancements in AI. Lightmatter, a Mountain View-based startup valued at $4.4 billion, has announced two new technologies to accelerate connections between AI chips. Having raised $850 million in venture capital, Lightmatter is part of the burgeoning silicon photonics trend in Silicon Valley. Their innovation lies in using optical fiber to transmit data via light signals instead of traditional electrical signals.