AI in the Enterprise Lessons from seven frontier companiesContents A new way to work 3 Executive summary 5 Seven lessons for enterprise AI adoption Start with evals 6 Embed AI into your products models 13 Get AI in the hands of experts 16 Unblock your developers 18 Set bold automation goals 21 Conclusion 22 More resources 24 2 AI in the EnterpriseA new way 
 to work As an AI research and do their best work with sophisticated, complex, interconnected workflows and systems. We’re seeing AI deliver significant, measurable improvements on three fronts: 01 Workforce performance Helping people

cooperatively fetch dependent data out_channel WwWly, pm Bly zx) https://docstvm ai/ PVR TOPI Alibaba ALLabs 阿里巴巴人工智能实验室 Blocking Splits the workload into thread blocks (work

2025!3" Manus AI!Agent"#$ChatGPT%& #$% SAC NO. S0570519080006 | SFC NO. BQZ938 &'( SAC NO. S05701220801381 !"#$%&'() !"#$ • !"#$%&'()*AI+!"#$,-./012334%&'(56789:;<=>?@A BC%&'() • DEFGHI)*DEFGJKH abcde&fghi=>.gjklmno5pqLr?E=PstOuv5w%xyabz {|L}=>~}m•O2€.jk• • ‚ƒc„…†Agent…‡ˆAGIO‰Š‹Œ•1 Manus AI!"#$%&'Agent3 Manus AI%&'() • Manus !"#$%&'()*+,-./012345-6708,9):;<=>Manus ?@A+'BCDEFGHIJK,LMN OPQMR<"S>TUVWXY3 "#$%Bloomberg*&'()4 Manus AI%*+,- !"#$%Bloomberg*&'()5 Manus AI%./01 • GAIA !"#%‡•ž$% AI Ÿ G¡¢ž£,¤¥-UL6¦§¨©ª«Level 1cLevel 2cLevel 3¬G-•>Manus AI L®‰¯# §¨©ª°±²³{´µG SOTA œ=> • Manus AI ¶·fgG$%JKA+)€,¸¹!Lº»JK«Level

Layers: A New Era for Scalable Analytics, Search, and AI v 1.1Table of Contents Introduction 1. The Interconnection of Analytics, Search, and AI 2. What is a Real-Time Unified Data Layer? 3. Why Do experiences and ensure performance. 32. The Interconnection of Analytics, Search, and AI Analytics, search, and AI are deeply interconnected in how they process, interpret, and extract value from data information, enhancing discoverability, accelerating decision-making, and improving operational efficiency. AI acts as the intelligence layer, optimizing both search and analytics by making them faster, smarter

IntelligenceTrends – Artificial Intelligence (AI) May 30, 2025 Mary Meeker / Jay Simons / Daegwon Chae / Alexander Krey2 Context We set out to compile foundational trends related to AI. A starting collection of several ’ At the time, the pace of change catalyzed by the internet was unprecedented. Consider now that AI user and usage trending is ramping materially faster…and the machines can outpace us. The pace and OpenAI’s ChatGPT with its extremely easy-to-use / speedy user interface. In addition, relatively new AI company founders have been especially aggressive about innovation / product releases / investments

政企、创业者必读政企、创业者必读 一张图读懂一堂DeepSeek课政企、创业者必读 AI给了一个比互联网更大的机会  互联网是连接平台，人工智能是生产力  互联网是赋能性技术，生产力属性较弱  人工智能既能单兵作战，也能外部赋能 互联网创造了能写140个字的推特和分享照片的Instagram AI能帮助人解决登陆火星、能源自由的问题 5政企、创业者必读 大模型是真智能，是人工智能的重大拐点。你相不相信？ 大模型是真智能，是人工智能的重大拐点。你相不相信？ 大模型是一场工业革命，将重塑所有产品和业务。你相不相信？ 不拥抱AI的组织和个人，会被拥抱AI的组织和个人淘汰。你相不相信？ 建立AI信仰 6政企、创业者必读 大模型不是泡沫，而是新一轮工业革命的驱动引擎 蒸汽革命 电气革命 信息革命 以大模型为代表的 人工智能革命 人工智能是新质生产力的关键支撑技术，人工智能+百业千行将带动新一轮工业革命，为高质量发展注入强大动能 7政企、创业者必读 8 AI不仅是技术革新，更是思维方式和社会结构的变革 国家 产业 个人 企业政企、创业者必读 人工智能发展历程（一）  从早期基于规则的专家系统，走向基于学习训练的感知型AI  从基于小参数模型的感知型AI，走向基于大参数模型的认知型AI  从擅长理解的认知型AI，发展到擅长文字生成的生成式AI  从语言生成式AI，发展到可理解和生成声音、图片、视频的多模态AI  从生成式AI，发展到推理型AI

TVM Meetup - Linaro Jammy Zhou November 16th, 2019Bringing together the Arm ecosystemLinaro AI Initiative Provide the best-in-class Deep Learning performance by leveraging Neural Network acceleration and SoCs from the Arm ecosystem, through collaborative seamless integration with the ecosystem of AI/ML software frameworks and librariesArm NN open source project ● Linaro-hosted https://www.mlplatform or WIP: Hexagon DSP (via llvm), Ascend NPU, and more Green: Linaro 96BoardsLinaro for TVM ● Linaro AI/ML group can be a good fit for TVM collaborations on Arm based platforms to support more devices with

project. A goal is to nurture the TVM community and contribute new infrastructure and features. octom|.ai @octoml Q octoML Founding Team - The Octonauts - 四人全外日 Luis Ceze Jason Knight Seattle WA Register Todayl! QQ octoML tvmconf.org 15 Q OctoML Questions? We are hiring see octoml.ai for more detailsl

Presenter: Zhi Chen, Cody Yu Amazon SageMaker Neo, Deep Engine Science Bring Your Own Codegen to TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Considering You... Design Q&A System Prototyping https://github.com/apache/incubator-tvm/pull/4258 RFC https://discuss.tvm.ai/t/bring-your-own-codegen-to-tvm/4501© 2019, Amazon Web Services, Inc. or its Affiliates. All rights

All rights reserved. Animesh Jain Amazon SageMaker Neo Compilation of Quantized Models in TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Quantization Overview • reserved. QNN Conv2D Operator • Calculations are different from FP32 Conv2D https://discuss.tvm.ai/t/tf-lite-quantized-conv2d-operator-conversion/2651/8 𝑟𝑒𝑎𝑙_𝑣𝑎𝑙𝑢𝑒 = 𝒔𝒄𝒂𝒍𝒆 ∗ (𝑞𝑢𝑎�