以下为为您找到的关于大模型的相关 PPT 资料：
OpenAI 科学家最新讲座(完整版)：2023 年的大模型核心观点：模型足够大，某些能力才会显现，GPT-4 即将超越拐点并在其能力上实现显著跳跃。GPT-3 和 GPT-4 之间的能力存在显著差距，尝试弥合与当前模型的差距可能无效。需要改变观念，不断更新甚至摒弃过去基于某些理念建立的认知。 [大语言模型介绍] Pathways Language Model(PaLM):Scaling to 540 Billion Parameters for Breakthrough Performance: https://ai.googleblog.com/2022/04/pathways-language-model-palm-scaling-to.html PaLM API & MakerSuite:an approachable way to start prototyping and building generative AI applications: https://developers.googleblog.com/2023/03/announcing-palm-api-and-makersuite.html The Power of Scale for Parameter-Efficient Prompt Tuning: https://proceedings.neurips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64a-Paper.pdf Google Research,2022 & beyond:Language models: https://ai.googleblog.com/2023/01/google-research-2022-beyond-language.html#Langu ageModels Accelerating text generation with Confident Adaptive Language Modeling(CALM): https://ai.googleblog.com/2022/12/accelerating-text-generation-with.html Solving a machine-learning mystery: https://news.mit.edu/2023/large-language-models-in-context-learning-0207 Here are the assembled readings on generative AI: Ask a Techspert:What is generative AI? https://blog.google/inside-google/googlers/ask-a-techspert/what-is-generative-ai/ Build new generative AI powered search & conversational experiences with Gen App Builder: https://cloud.google.com/blog/products/ai-machine-learning/create-generative-apps-in-minutes-with-gen-app-builder What is generative AI? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-generative-ai [周鸿祎免费课 AI 系列第二讲-企业如何拥抱 AI] THINK DIFFERENT——大模型发展并非只有一条路，除了越做越大，还能越做越专。企业大模型要走“越来越专”的路。实践证明，百亿参数的场景大模型训得好，专业能力可以超越 GPT4 。