以下为为您找到的关于大模型的相关 PPT 资料:
核心观点:模型足够大,某些能力才会显现,GPT4 即将超越拐点并在其能力上实现显著跳跃。GPT3 和 GPT4 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。
Pathways Language Model:Scaling to 540 Billion Parameters for Breakthrough Performance: https://ai.googleblog.com/2022/04/pathwayslanguagemodelpalmscalingto.html
PaLM API & MakerSuite:an approachable way to start prototyping and building generative AI applications: https://developers.googleblog.com/2023/03/announcingpalmapiandmakersuite.html
The Power of Scale for ParameterEfficient Prompt Tuning: https://proceedings.neurips.cc/paper/2020/file/1457c0d6bfcb4967418bfb8ac142f64aPaper.pdf
Google Research,2022 & beyond:Language models: https://ai.googleblog.com/2023/01/googleresearch2022beyondlanguage.htmlLangu ageModels
Accelerating text generation with Confident Adaptive Language Modeling: https://ai.googleblog.com/2022/12/acceleratingtextgenerationwith.html
Solving a machinelearning mystery: https://news.mit.edu/2023/largelanguagemodelsincontextlearning0207
Here are the assembled readings on generative AI:
Ask a Techspert:What is generative AI? https://blog.google/insidegoogle/googlers/askatechspert/whatisgenerativeai/
Build new generative AI powered search & conversational experiences with Gen App Builder: https://cloud.google.com/blog/products/aimachinelearning/creategenerativeappsinminuteswithgenappbuilder
What is generative AI? https://www.mckinsey.com/featuredinsights/mckinseyexplainers/whatisgenerativeai
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 。
2024-08-26