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Odaily News AMD, the semiconductor giant, announced the launch of its enterprise-grade AI programming platform, AMD Instinct Coder. The platform combines AMD chips, Supermicro servers, and Spectro Cloud software, aiming to help enterprises deploy AI coding assistants locally, reduce the cost of cloud-based AI models, and protect code and data security.AMD stated that Instinct Coder is an "out-of-the-box" end-to-end AI development platform, integrating AMD EPYC processors, AMD Instinct GPUs, Supermicro AI servers, Spectro Cloud PaletteAI Inference Launchpad software, and the AMD-optimized GLM-5.2 model. It can be used for software development scenarios such as code generation, application modernization, automated testing, and code review.AMD said that compared to relying on cutting-edge cloud-based AI models, Instinct Coder can help enterprises reduce total cost of ownership (TCO) by up to 70%, with the fastest payback period shortened to 6 months.AMD noted that more and more enterprises are looking to leverage AI to improve development efficiency, but face two major challenges: on one hand, the cost of invoking top-tier cloud models continues to rise; on the other hand, entrusting enterprise source code, intellectual property, and sensitive data to third-party services poses security and compliance risks.Through a local deployment model, Instinct Coder allows enterprises to maintain control over their data and code while providing more predictable infrastructure costs. The platform supports development tools such as Claude Code, OpenAI Codex, Visual Studio Code, and Cursor, with each node supporting up to 50 users (30 concurrent users).Additionally, the PaletteAI Inference Launchpad provided by Spectro Cloud enables AI workload management, model routing, request auditing, and cost monitoring, and supports invoking external models such as Anthropic, OpenAI, Google, or xAI when needed.AMD stated that Instinct Coder aims to help enterprises break free from the high costs of cloud-based AI services, accelerate AI-driven software development processes while ensuring data security and autonomous control.
"White-Haired Stock Guru" Serenity stated that while some observations in the UBS report hold anecdotal truth, the more noteworthy trend is the increasing number of Chinese-language reports regarding the distillation of Anthropic's models. Currently, many US startups and tech companies are opting to use cheaper Chinese models (such as DeepSeek) in their AI applications, as their unit task costs are significantly lower than those of inference models from Gemini, OpenAI, and Anthropic.Serenity believes this trend, driven by capitalism, creates a "typical paradox"—companies naturally gravitate towards lower-cost solutions, thereby eroding the leading advantage of US models. He proposes that the US needs to address this on two fronts:First, build stronger access control and authentication systems, such as "heavy KYC frontier models" for domestic US use and tiered access mechanisms for allies, to reduce the risk of model distillation and misuse. This could also be accompanied by introducing an identity verification system akin to "AI-grade banking authentication" (e.g., biometrics + short-lived permission tokens) to raise the barrier for model calls, and using regulatory measures to restrict account sharing and access resale.Second, enhance the cost efficiency of inference models, allowing them to comprehensively outperform competitors like DeepSeek in both price and performance.Serenity also noted that some high-end models are currently frequently targeted for "distillation exploitation." Ideally, access to models nearing the AGI level should involve increased friction costs. In summary, the core challenge for the US AI industry lies in achieving both "low-cost inference capabilities" and establishing model access security mechanisms comparable to those in the financial system.
sources say NVIDIA has begun pitching its first independent central processing unit (CPU) product, Vera, to Chinese clients. Designed specifically for Agentic AI systems, the chip has entered mass production, marking NVIDIA's attempt to further expand its presence in the Chinese market with a CPU offering.According to sources, some Chinese clients have already shown interest in Vera. One major Chinese cloud computing company plans to procure over 300 servers equipped with dual Vera CPUs for testing, and will decide whether to expand procurement after the tests are completed.Built on the Arm Holdings architecture, Vera is NVIDIA's first independent CPU product. NVIDIA has previously stated that Vera's performance in AI agent-related computing tasks is 1.8 times that of comparable competitor products, and expects the product to contribute approximately $20 billion in revenue by the end of this fiscal year (ending January next year).The report notes that as the AI industry's focus gradually shifts from model training to inference computing, CPUs and custom chips are gaining more attention. Vera also positions NVIDIA to directly compete with Intel and Advanced Micro Devices (AMD), which have long dominated the server CPU market.Sources indicate that due to strict U.S. export restrictions on high-end GPUs, CPUs face relatively smaller regulatory hurdles in the Chinese market compared to GPU products. Currently, some Chinese clients plan to first deploy Vera chips for testing in overseas data centers. Meanwhile, software ecosystem compatibility and existing domestic AI chip deployment frameworks may still impact the subsequent large-scale adoption of Vera. (Reuters)