Multiple Ways to Give Feedback on CAP Documentation

Friday, Aug 29, 2025 10:26 am ET2min read

CAP documentation encourages collaboration through multiple feedback channels. Users can give quick feedback via the "Was This Page Helpful?" widget, participate in targeted surveys, report issues and request features on GitHub Issues, contribute directly by editing pages, nominate learning resources, and provide feedback on open-source components. These channels help identify areas for improvement and facilitate community engagement.

Microsoft has initiated public testing of its MAI-1-preview AI language model, signaling a significant shift in the company's AI strategy. This move underscores Microsoft's intention to reduce its reliance on OpenAI for powering AI features in products like Copilot. The model is currently accessible for evaluation on LMArena, a platform designed for benchmarking AI models [1].

Microsoft has indicated a phased rollout of MAI-1-preview for specific Copilot text functionalities in the coming weeks. This gradual implementation aims to gather user feedback and refine the model's performance. Developers interested in exploring MAI-1-preview can request early access through an online form provided by Microsoft. Initial assessments on LMArena positioned MAI-1-preview in 13th place for text-based tasks, behind models developed by OpenAI, Google, Anthropic, and xAI [1].

The development of MAI-1-preview involved substantial computational resources. Microsoft stated that the model was trained utilizing approximately 15,000 Nvidia H100 GPUs, alongside a cluster of Nvidia GB200 chips. These resources underscore the scale of investment and infrastructure required for training advanced AI models [1].

The evolution of strategic partnerships into competitive dynamics is evident through the changing relationship between Microsoft and OpenAI. In 2019, Microsoft made an initial investment of $1 billion in OpenAI, solidifying its position as OpenAI’s exclusive cloud provider via Azure. Over the subsequent five years, Microsoft’s total investment in OpenAI has exceeded $13 billion. Concurrently, Microsoft has been developing its own competing AI models, ultimately recognizing OpenAI as a competitor in its annual reports. This transition reflects OpenAI’s substantial growth, with a valuation now reaching $500 billion and ChatGPT boasting 700 million weekly users. This growth has transformed OpenAI from a collaborative research partner into a potential competitor to Microsoft’s AI ambitions [1].

Microsoft’s strategy for building MAI-1 underscores the importance of talent acquisition in swiftly developing AI capabilities. The company recruited Mustafa Suleyman from Inflection, an AI startup, along with several of his colleagues. Additionally, Microsoft added approximately two dozen researchers from Google’s DeepMind in recent months. Suleyman’s background includes co-founding DeepMind prior to its acquisition by Google in 2014 and later leading Inflection as a competitor to OpenAI [1].

This experience provides Microsoft with established AI leadership and industry connections. This "acqui-hiring" strategy allows Microsoft to accelerate AI model development by integrating established teams rather than organically developing expertise. Microsoft has stated that MAI-1-preview represents its "first foundation model trained end to end in house," suggesting that despite significant investment in OpenAI, the company recognized the need for independent AI capabilities [1].

References:
[1] https://dataconomy.com/2025/08/29/microsoft-trained-mai-1-on-15000-nvidia-h100-gpus/

Multiple Ways to Give Feedback on CAP Documentation

Comments



Add a public comment...
No comments

No comments yet