“幻觉”影响“可靠性”！Salesforce高管称“对大模型的信任度已经下降”，已减少使用程度

Core Insights - Salesforce executives have acknowledged a decline in trust towards large models over the past year, leading to a strategic shift in their AI product Agentforce, which will now rely more on deterministic automation techniques rather than generative AI [1][2] Group 1: Strategy Shift - The adjustment aims to address technical failures such as "hallucinations" that large models experience when handling precise tasks, ensuring that critical business processes follow consistent steps [1] - Agentforce is now utilizing predefined instruction-based deterministic automation to eliminate the inherent randomness of large models [1] Group 2: Technical Reliability Challenges - Salesforce has encountered multiple technical challenges with large models, including the issue where models begin to omit instructions when given more than eight commands, which is problematic for tasks requiring precision [2] - The experience of Vivint, a home security company using Agentforce for customer support, highlights reliability issues, such as the failure to send satisfaction surveys despite clear instructions [2] Group 3: Addressing AI Drift - AI "drift" is another significant challenge, where AI agents lose focus on primary objectives when users ask unrelated questions [3] - To mitigate this, Salesforce has developed the Agentforce Script system, which identifies tasks that can be handled by non-large model agents to minimize unpredictability [3] Group 4: Operational Adjustments - Salesforce has also reduced its reliance on large models in its operations, despite previous statements about using OpenAI's models for customer service inquiries [4] - Recent responses from the company have shifted to providing links to blog articles instead of engaging in further inquiries, resembling traditional basic chatbot interactions [4] - The company has improved its topic structure and protective measures, leading to a projected 90% increase in resolved conversations by the end of the fiscal year [4] Group 5: Industry Trends - This trend reflects broader industry challenges, as evidenced by issues faced by other companies, such as a chatbot from Gap Inc. that provided inappropriate responses, highlighting the common problem of large models deviating from expected use [5]