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  • pdf文档 Facebook -- TVM AWS Meetup Talk

    0 码力 | 11 页 | 3.08 MB | 6 月前
    3
  • pdf文档 Trends Artificial Intelligence

    10/22 4/25 800MM Big Six* USA Technology Company CapEx *Apple, NVIDIA, Microsoft, Alphabet, Amazon (AWS only), & Meta Platforms Source: Capital IQ (3/25), Morgan Stanley 2014 2024 CapEx, $B +63% $212B estimates. Source: The Information, public estimates 2022 2024 Revenue (Blue) & Compute Expense (Red) +$3.7B -$5B Details on Page 173 2023 China Rest of World (excl. China & USA) USA 2014 20236 Admin Costs Margins Marketing Spend Effectivity ROIC Revenues Sales Productivity Customer Service Production / Output Revenue-Focused Cost-Focused ‘Traditional’ Enterprise AI Adoption = Rising
    0 码力 | 340 页 | 12.14 MB | 5 月前
    3
  • pdf文档 清华大学第二弹:DeepSeek赋能职场

    azure.com 671B(全量模型) 需注册微软账户并创建订阅,免费部署,支持参数调节。 亚马逊AWS https://aws.amazon.com/c n/blogs/aws/deepseek-r1- models-now-available-on- aws 671B(全量模型) 需注册AWS账户,填写付款方式,免费部署。 Cerebras https://cerebras.ai 70B
    0 码力 | 35 页 | 9.78 MB | 8 月前
    3
  • pdf文档 Gluon Deployment

    Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Overall Performance AWS DeepLens Acer aiSage NVIDIA Jetson Nano© 2019, Amazon Web Services, Inc. or its Affiliates. All Jetson Nano AWS DeepLens Acer aiSage NVIDIA Jetson Nano© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark Effects of Convolution operators using TVM AWS DeepLens com/dmlc/gluon-cv© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Trademark 1. AWS has most TVM contributors from industry. 2. We plan to build TVM team in China, based in Shanghai
    0 码力 | 8 页 | 16.18 MB | 6 月前
    3
  • pdf文档 OctoML OSS 2019 11 8

    to TVM o_uTVM: support for microcontrollers in TVM o_ Virtual Machine and dynamic NNs support (w/ AWS folks) o_ Improved NLP support, with focus on transformers QQ octoML Core Infrastructure Refactors currently implemented using copy, 10 Virtual Machine e Many improvements from contributors at UW, AWS, and OctoML. e Initial implementation is quickly moving towards production quality. o _VM compiler Apache(incubating) community members. e ASF Mentors and PMC members who make this awesome project Possiblel ee AWS for hosting the first Bay Area meetup QQ octoML 14 Annual TVM Conference 2019 Organized and participated
    0 码力 | 16 页 | 1.77 MB | 6 月前
    3
  • pdf文档 Bring Your Own Codegen to TVM

    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
    0 码力 | 19 页 | 504.69 KB | 6 月前
    3
  • pdf文档 TVM Meetup: Quantization

    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
    0 码力 | 19 页 | 489.50 KB | 6 月前
    3
  • pdf文档 Dynamic Model in TVM

    Presenter: Haichen Shen, Yao Wang Amazon SageMaker Neo, Deep Engine Science Dynamic Model in TVM AWS AI© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Models with dynamism
    0 码力 | 24 页 | 417.46 KB | 6 月前
    3
  • pdf文档 OpenAI 《A practical guide to building agents》

    sequence of steps that must be executed to meet the user’s goal, whether that's resolving a customer service issue, booking a restaurant reservation, committing a code change, 
 or generating a report. Applications judgment, exceptions, or 
 context-sensitive decisions, for example refund approval 
 in customer service workflows. 02 Difficult-to-maintain rules: Systems that have become unwieldy due to extensive and records, or sending messages. Send emails and texts, update a CRM record, hand-off a customer service ticket to a human. Orchestration Agents themselves can serve as tools for other agents—see the
    0 码力 | 34 页 | 7.00 MB | 6 月前
    3
  • pdf文档 OpenAI - AI in the Enterprise

    platform, introduced a new AI assistant to streamline customer service. Within a few months, the assistant was handling two-thirds of all service chats—doing the work of hundreds of agents and cutting average invested heavily in our API to make it easier to customize and fine-tune models—whether as a self-service approach or using our tools and support. We worked closely with Lowe’s, the Fortune 50 home improvement team Uses it to answer 40,000 questions a year on policies, compliance, and more. The Customer Service team Automates the sentiment analysis of NPS surveys. 16 AI in the EnterpriseAnd the wins continue
    0 码力 | 25 页 | 9.48 MB | 6 月前
    3
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