探索開源人工智慧的商業策略

本報告調查了開源 AI 的商業策略，並總結了開源 AI 收入預測、開源策略案例研究、開源 AI 策略領導者和建議。

實際好處：

• 確定並制定開源人工智慧的新商業策略
• 從開源人工智慧商業化案例研究中學習最佳實踐
• 制定長期的內部、社區、貢獻和商業化策略

重要問題的答案：

• 誰是商業上最先進的開源人工智慧工程師？
• 供應商如何最大化其開源投資的價值？
• 對於市場、產品和公司發展而言，最有效的長期開源策略是什麼？
• 供應商該如何開始支援開源人工智慧開發？

研究亮點：

• 開源人工智慧策略評估
• 企業開源人工智慧軟體支出：傳統人工智慧與生成人工智慧
• 開源人工智慧策略案例研究

目錄

重要要點

開放人工智慧收入預測：2023-2030

供應商如何制定開源策略

可以透過開源實現的策略

策略個案研究

開源人工智慧策略的領導者

供應商如何利用開源人工智慧脫穎而出

開源人工智慧策略：建議

Actionable Benefits:

• Identify and develop new commercial strategies for open-source Artificial Intelligence (AI) contributions.
• Explore and learn from best practice open-source AI commercial case studies.
• Develop long-tern internal, community, contribution, and commercialization strategies.

Critical Questions Answered:

• Who are the most commercially advanced open-source AI contributors?
• How can vendors maximize the value of open-source investment?
• What will be the most effective long-term open-source strategies for market, product, and company development?
• How should vendors start supporting open-source AI development?

Research Highlights:

• Open-source AI strategy evaluation.
• Enterprise open-source AI software spend: traditional versus Generative Artificial Intelligence (Gen AI).
• Open-source AI strategy case studies.

Who Should Read This?

• AI executives looking to engage with the open-source ecosystem.
• Software strategists looking to translate contributions into monetization.

TABLE OF CONTENTS

Key Takeaways

Open AI Revenue Forecasts 2023 to 2030

How Can Vendors Develop an Open-Source Strategy

What Strategies Can Open Source Enable

Strategy Case Studies

Leading Open-Source AI Strategies

How Can Vendors Build Differentiation in Open-Source AI

Open-Source AI Strategic Recommendations