Основні поняття
Foundation models have revolutionized software development, leading to new challenges in developing trustworthy FMware. The approach to addressing these challenges requires innovation and collaboration.
Анотація
The development of FMware using foundation models presents unique challenges that impact productivity, risk, and compliance. From managing alignment data to ensuring regulatory compliance, addressing these issues is crucial for successful FMware development. Collaboration support and controllability are also key areas requiring attention to enhance the efficiency and effectiveness of FMware projects.
Статистика
The market size of FMware is estimated to grow at a compound annual growth rate (CAGR) of 35.9% from 2024 to 2030.
Microsoft reports that prompt engineering and testing for Copilot-like products are time-consuming and resource-constrained.
FMs exhibit limitations such as complex task limitations, hallucination limitations, and closed-loop limitations.
Cognitive architectures are emerging for different generations of software, including Promptware, Neuralware, Agentware, and Mindware.
Active learning methods demand significant manual input for constructing alignment data in FMware.
Tools like Snorkel AI use data programming to generate labels using expert knowledge for alignment data in FMware.
Цитати
"Developers constantly suffer from low productivity throughout the lifecycle when integrating FMs in software systems." - Microsoft
"Intrinsic limitations of FMs include complex task limitations, hallucination limitations, and closed-loop limitations." - Report findings
"Efforts towards ensuring regulatory compliance of FMware remain largely manual and process-heavy." - Compliance report