Trends Artificial Intelligence
AI Will Likely Do in Ten Years, per ChatGPT Source: ChatGPT (5/15/25) AI = Circa 2035?36 AI Development Trending = Unprecedented37 Machine-Learning Model* Trending = In 2015... Industry Surpassed Academia Models by Sector – 2003-2024, per Stanford HAI Annual New Notable Machine-Learning Models AI Development Trending = Unprecedented38 AI Developer Growth (NVIDIA Ecosystem as Proxy) = +6x to 6MM Developers to reach 2 million.’ Source: NVIDIA blog posts, press releases, & company overviews +6x AI Development Trending = Unprecedented Global Developers in NVIDIA Ecosystem (MM) – 2005-2025, Per NVIDIA390 码力 | 340 页 | 12.14 MB | 5 月前3
DeepSeek-V2: A Strong, Economical, and Efficient
Mixture-of-Experts Language ModelLanguage Models (LLMs) (Anthropic, 2023; Google, 2023; OpenAI, 2022, 2023) have undergone rapid development, offering a glimpse into the dawn of Artificial General Intelligence (AGI). In general, the intelligence models, and even beats most of closed-source models. In order to facilitate further research and development on MLA and DeepSeekMoE, we also release DeepSeek-V2-Lite, a smaller model equipped with MLA and minimizing the need for human supervision. By prioritizing ethical considerations and responsible development, we are dedicated to creating a positive and beneficial impact on society. • Currently, DeepSeek-V20 码力 | 52 页 | 1.23 MB | 1 年前3
Google 《Prompt Engineering v7》More on this table format, the importance of tracking prompt engineering work, and the prompt development process is in the Best Practices section later in this chapter (“Document the various prompt problem, try chain of thought. Please refer to the notebook10 hosted in the GoogleCloudPlatform Github repository which will go into further detail on CoT prompting: Prompt Engineering February 2025 appropriate examples/instructions. Please refer to the notebook14 hosted in the GoogleCloudPlatform Github repository, which goes into a bit more detail showing the actual LLM inputs and outputs with a more0 码力 | 68 页 | 6.50 MB | 6 月前3
Gluon DeploymentAll rights reserved. Amazon Trademark Like GluonCV? Go build! https://gluon-cv.mxnet.io https://github.com/dmlc/gluon-cv© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Scientist and SDE positions 2. Internship for students interested in ML system. 3. Research & Development 3. Please contact Yida (wangyida [AT] amazon [DOT] com) if interested. We are hiring! 1 20 码力 | 8 页 | 16.18 MB | 5 月前3
OpenAI - AI in the Enterprisevalue faster and with greater buy-in from users and stakeholders. Our approach: iterative development OpenAI is organized around three teams. Our Research Team advances the foundations of AI, developing are best-placed to improve it with AI. 06 Unblock your developers Automating the software development lifecycle can multiply AI dividends. 07 Set bold automation goals Most processes involve Libre, Latin America’s largest ecommerce and fintech company, partnered with OpenAI to build a development platform layer to solve that. It’s called Verdi, and it’s powered by GPT-4o and GPT-4o mini.0 码力 | 25 页 | 9.48 MB | 5 月前3
TVM: Where Are We GoingApache TVM recently. Independent governance, allowing competitors to collaborate. Open Code Open Development Open GovernanceAcknowledgement Apache (incubating) TVM community Our awesome community members0 码力 | 31 页 | 22.64 MB | 5 月前3
DeepSeek从入门到精通(20250204)需要考虑的因素 任务目标、目标受众、文章类型、字数要求、特殊要求 在分析阶段,首先明确 任务目标和关键问题 通过四个关键步骤:分析(Analysis)、构思(Ideation)、发展(Development) 和评估(Assessment),为提示语链的设计提供系统化的指导。 构思阶段注重创新性思 维,探索多种解决方案 在发展阶段,逐步深化 构思并形成具体的内容 方案 最后的评估阶段用于反0 码力 | 104 页 | 5.37 MB | 8 月前3
清华大学 DeepSeek 从入门到精通需要考虑的因素 任务目标、目标受众、文章类型、字数要求、特殊要求 在分析阶段,首先明确 任务目标和关键问题 通过四个关键步骤:分析(Analysis)、构思(Ideation)、发展(Development) 和评估(Assessment),为提示语链的设计提供系统化的指导。 构思阶段注重创新性思 维,探索多种解决方案 在发展阶段,逐步深化 构思并形成具体的内容 方案 最后的评估阶段用于反0 码力 | 103 页 | 5.40 MB | 8 月前3
XDNN TVM - Nov 2019Optimization Framework Tensor Graph to Xilinx Tensor Graph Frontend Deep Learning Frameworks https://github.com/xilinx© Copyright 2018 Xilinx TVM as Unified ML Front End >> 6 Relay (and NNVM) Graph Parser Performance Pipelines ˃ References to our latest results: https://github.com/Xilinx/AI-Model-Zoo (embedded i.e. ZC104/Ultra96) https://github.com/Xilinx/ml-suite/blob/master/examples/caffe/Benchmark_README by slowest one ˃ Performance results based on Xilinx own runtime pipeline available in github (https://github.com/Xilinx/ml-suite/blob/master/examples/deployment_modes/mp_classify.py) Streamlined multi-process0 码力 | 16 页 | 3.35 MB | 5 月前3
开源中国 2023 大模型(LLM)技术报告围内对于大模型技术及其应用的关注和热情。2023 年, 国内外各大厂商均投身于大模型的浪潮当中,涌现了诸多 知名的大模型及应用,它们结合了文本、图片、视频、音 频多种介质,在文本生成、图片生成、AI 编程等方向均 有出色的表现。 GitHub Copilot 16 / 32 大模型应用现状:知名大模型 在全球范围内,已经发布了多款知名大模型,这些大模 型在各个领域都取得了突破性的进展。 处理文本数据的 GPT-4,能同时处理和理解多种类型数 的形式出现,它们大多交互直观且使用门槛低,大大 提高了 AI 编程工具的使用率。 GitHub Copilot 和 Codeium 是比较常见的 AI 编程 插件,而 Cursor 和 Warp 分别是具有 AI 编程能力 的 IDE 和终端工具。 除了海外产品,国内如姜子牙、CodeFuse、 CodeGeeX、百度 Comate 等都是十分优秀的 AI 编 程工具。 GitHub Copilot Codeium Warp 进行交互。 LangChain 于 2022 年 10 月作为开源项目推出,并于 2023 年 4 月注册成立公司,累计获得超过 3000 万美元的 投资,估值达到了 2 亿美元。 在 GitHub 上,LangChain 已经获得了超过 7 万个 Star 和 超过 2000 名贡献者。 27 / 32 LLM 的工具和平台:MaaS 平台 Gitee AI 是开源中国旗下的 MaaS0 码力 | 32 页 | 13.09 MB | 1 年前3
共 16 条
- 1
- 2













