“The 'Open' in OpenAI is supposed to mean 'open source'. And it was created as a nonprofit open source. And now it is a closed-source for maximum profit, which I think is not good karma.”Elon Muskhttps://t.co/Dn9eo3HFPx ...

Core Insights - EPAM Systems, Inc. has launched DIAL 3.0, an open-source GenAI platform aimed at facilitating enterprise AI adoption through a modular and open-source approach [1][3] - DIAL 3.0 is designed to help clients accelerate value delivery while avoiding vendor lock-in, bridging commercial models with open innovation [3][4] - The platform has evolved from an internal tool to a comprehensive framework utilized by global clients across various industries, including financial services, healthcare, and retail [4][5] Company Strategy - EPAM emphasizes a hybrid strategy that combines structured platform thinking with the flexibility of open source, allowing organizations to move faster in AI deployment [4] - The platform supports agentic workflows and data-native reasoning, addressing structural challenges of deploying AI at scale across business functions [4] - DIAL 3.0 introduces new methodologies for working with both structured and unstructured data, promoting collaboration across enterprises [4][5] Client Engagement - Altera Digital Health, an early adopter of DIAL, highlights the platform's ability to improve operational efficiency and the importance of EPAM's commitment to open-source innovation [5][6] - The continued evolution of DIAL has fostered trust among clients as they scale their AI solutions [6] Industry Position - EPAM Systems has established itself as a leading global provider of digital engineering and AI-enabled transformation services, addressing clients' transformation challenges through integrated strategy and technology consulting [10] - The company is recognized for its significant impact in the industry, being included in the S&P 500 and Forbes Global 2000, and is noted for its leadership in various IT service categories [10]

Core Insights - Huawei announced the launch of HarmonyOS 6 at the HDC2025, marking a significant advancement in its operating system and AI capabilities, with a developer public beta now available [1] - The new HarmonyOS 6 features a fully self-developed architecture, achieving a 30% improvement in system smoothness, a reduction of 1.5GB in running memory, and an increase in battery life by nearly 1 hour [1] - The introduction of the HarmonyOS Intelligent Agent framework aims to enhance human-machine interaction and collaboration, with over 50 intelligent agents set to launch across various applications [1] Group 1 - HarmonyOS 6 has been developed just 8 months after the public beta of HarmonyOS 5, showcasing Huawei's rapid innovation cycle [1] - The system supports efficient multi-device collaboration, enabling interactions between smartphones, vehicles, and robots [1] - The new Pangu Model 5.5 has been released, with upgrades in natural language processing and multimodal capabilities [1] Group 2 - Over 40 Huawei terminal products are currently running HarmonyOS 5, with more than 260 new features added [2] - The introduction of a new "full-scene interconnection architecture" in HarmonyOS 6 is expected to drive innovation in intelligent applications [2] - The ecosystem is expanding as more developers and enterprises join, enhancing the collaborative technology community [2] Group 3 - More than 30,000 applications and meta-services are in accelerated development, covering nearly 20 industries including government, healthcare, and manufacturing [3] - The number of HarmonyOS developers has surpassed 8 million, making it the fastest-growing open-source operating system with over 130 million lines of code [3] - Approximately 120 listed companies are involved in the HarmonyOS ecosystem, with significant participation from companies like Softcom and Tuowei [3] Group 4 - The continuous iteration of HarmonyOS is expected to lead industry development, accelerate ecosystem prosperity, and enhance global competitiveness [4]

“The 'Open' in OpenAI is supposed to mean 'open source'. And it was created as a nonprofit open source. And now it is a closed-source for maximum profit, which I think is not good karma.”Elon Musk https://t.co/0qae6EIYs0 ...

[Music] right. Hello everyone. Who's excited to chat about MCP today.Okay, we can we can work on that. We can get it a little bit better by the end of this talk. Uh but I'm Theo.I am a product manager at Anthropic work on MCP. Uh prior to this was also a startup founder uh working in the AI space. Um couple fun facts about me because everyone says make yourself a little bit more personable.Uh is that I like playing poker mostly losing money at poker, not uh making money at poker. Uh and I also really like c ...

Core Viewpoint - The article highlights the significant advancements of the open-source AI model DeepSeek-R1 (0528), which has demonstrated competitive performance against leading proprietary models like Claude Opus 4 and GPT-4.1 in various benchmarks, marking a notable milestone in the open-source AI landscape [1][14]. Performance in Benchmarks - DeepSeek-R1 (0528) achieved a score of 1408.84 in the WebDev Arena, surpassing Claude Opus 4's score of 1405.51, and tying with Gemini-2.5-Pro-Preview-06-05 for the top position [4][5]. - In the LMArena public benchmark tests, R1 (0528) outperformed several top closed models, showcasing its coding capabilities [3][4]. - The model ranks sixth in the Text Arena, indicating strong performance in language understanding and reasoning tasks [6]. Technical Specifications - DeepSeek-R1 (0528) utilizes a mixture of experts (MoE) architecture with a total parameter count of 685 billion, activating approximately 37 billion parameters during inference for efficient computation [9]. - It supports a long context window of 128K tokens, enhancing its performance in long text understanding and complex logical reasoning tasks [9]. Community Reactions - The release of DeepSeek-R1 (0528) has sparked discussions in developer communities, with some users expressing skepticism about its performance compared to proprietary models [10][11][16]. - Users have noted the impressive coding capabilities of R1, suggesting that developers using this model could outperform those using closed models [16]. Competitive Landscape - The article mentions the recent release of Kimi-Dev-72B, another open-source model that has achieved high scores in programming benchmarks, indicating a competitive environment in the open-source AI space [22][23]. - Kimi-Dev-72B scored 60.4% in the SWE-bench Verified programming benchmark, surpassing DeepSeek-R1 (0528) in specific coding tasks [23]. Conclusion - The advancements of DeepSeek-R1 (0528) signify a critical moment for open-source AI, demonstrating that open models can compete with proprietary systems in terms of performance and capabilities [14].

2. 部署快：训转推全流程自动化，让大模型部署像执行一行命令一般敏捷高效。 Figure 1 MindSpore生态快速迁移解决方案的技术架构 接下来，我们将揭开昇思 MindSpore的破局之道。 01 支持训练Day0迁移，构建跨框架的"无感智能翻译"能力 " 昇思MindSpore支持大模型训练Day0迁移、推理一键部署，携 手开发者共筑开源生态。 " 编辑丨 李希 大模型发展日新月异，新的大模型层出不穷，参数规模从十亿级跃升至万亿级，模型结构从稠密到稀疏， 应用范式走向多模态、 Agent… 如此多的模型和技术如何在昇腾上快速的使能和体验，是昇腾开发者的 核心诉求。昇思MindSpore "海纳百川"，全面融入主流生态，全面优化训练与推理全流程开发体验，让 开发者用极小成本完成SOTA大模型的迁移 ，昇思 Mind Spore 需攻克两大关键挑战： 1. 迁得快：让三方框架模型 "零成本"迁移，避免重复造轮子，同时模型精度完全对齐。 02 支持推理一键部署，分钟级拉起模型服务 在推理部署方面，借助 vLLM-MindSpore插件实现HuggingFace模型半小时部署上线。 面对千亿参数模 型，昇思 ...

鱼羊 发自 凹非寺 量子位 | 公众号 QbitAI DeepSeek终于还是在端午节前来炸场了： △ 图源：@flavioAd 也能做对难倒o3、Gemini 2.5 pro、Claude 4等一众顶流大模型的数字新难题" 9.9-9.11=？ "了。 R1更新新版本 DeepSeek-R1-0528 ，看名字你可能以为是个小版本更新，但实际上—— "在LiveCodeBench上几乎与OpenAI o3-high相当！" "讲真这其实就是R2吧。" 不怪网友们惊呼声一片，看第一波实测结果，就知道事情并不简单。 新版R1的小球弹跳实验，与旧版对比结果如下： 新模型已经在HuggingFace上释出，依然是MIT协议。 | 8 main v | DeepSeek-R1-0528 | | Q | | --- | --- | --- | --- | | | · 1 contributor | 9 History: 11 commits | | | | msr2000 Add files using upload-large-folder tool | 174da7f | | | | VERIFIED | | | ...

Core Insights - ByteDance's technology team has announced the open-source project DeerFlow, based on LangStack, officially available on ByteDance's GitHub organization [1] Group 1 - The new project DeerFlow is part of ByteDance's efforts to enhance its technological capabilities [1] - The open-sourcing of DeerFlow indicates ByteDance's commitment to fostering innovation and collaboration within the tech community [1]

Core Viewpoint - The establishment of the Modelers Community, led by China Telecom's Tianyi Cloud, aims to create an open platform for AI developers, providing resources such as models, data, and tools, while fostering collaboration across the entire AI industry chain [2][6][46] Group 1: Community Structure and Governance - The Modelers Community has officially formed a council responsible for managing and developing the community [3][6] - The council consists of representatives from various sectors of the AI industry, including chip companies, model and data enterprises, research institutions, and ecological organizations, totaling 14 members [7][9] - The governance structure includes committees focused on governance, construction, and operations, along with a secretariat for coordination [11][16] Group 2: Resources and Offerings - The community provides a wide range of resources, including various AI models, datasets, and tools optimized for different computing facilities [18][21] - Notable open-source models such as DeepSeek and Qwen have been included, with adaptations for domestic hardware [19][21] - The community also offers free domestic computing resources in collaboration with industry members [21] Group 3: Collaboration and Impact - The Modelers Community aims to bridge the gap between academia and industry, facilitating the practical application of academic research through demos and collaborative projects [24][28] - Small and medium enterprises benefit from the community by accessing open-source models that enhance their product offerings [26][28] - Future plans include partnerships with universities for joint talent development, expanding the community's reach [29] Group 4: Need for the Community - The Modelers Community addresses gaps in existing open-source platforms, particularly in the AI domain, by promoting collaboration and resource sharing among developers [30][42] - It aims to resolve issues related to data ownership and the challenges of integrating various AI tools and models [40][44] - The community's neutral and public-oriented approach distinguishes it from other platforms, making it a vital organizer for the AI industry [43][45]