rights reserved. 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 models© 2019, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Support dynamic model in TVM ● Support Any-dim in typing ● Use shape function to compute the type at runtime ● Virtual input_name = "data" input_shape = [tvm.relay.Any(), 3, 224, 224] dtype = "float32" block = get_model('resnet50_v1', pretrained=True) mod, params = relay.frontend.from_mxnet(block, shape={input_name:

Model and Operate Datacenter by Kubernetes at eBay 辛肖刚, Cloud Engineering Manager, ebay 梅岑恺, Senior Operation Manager, ebay Agenda About ebay Our fleet Kubernetes makes magic at ebay Model + Controller Controller How we model our datacenter Operation in large scale Q&A About ebay 177M Active buyers worldwide $22.7B Amount of eBay Inc. GMV $2.6B Reported revenue 62% International revenue 1.1B b e Converge & Reconcile WIRI: What it really is Kubernetes Core concept of Kubernetes - Declarative magic What is an application looks like? Replica Config LoadBalancer Rolling Update Quota

The Future of Cloud Native Applications with Open Application Model (OAM) and Dapr @markrussinovich Application models Describes the topology of your application and its components The way developers services and data stores Programming models Distributed Application Runtime (Dapr) Open Application Model (OAM) https://oam.dev State of Cloud Native Application Platforms Kubernetes for applications of concerns Application focused Application focused Container infrastructure Open Application Model Service Job Namespace Secret Volume Endpoint ConfigMap VolumeAttach CronJob Deployment

Memory Model C++11 – C++23About Me: alex.dathskovsky@speedata.io www.linkedin.com/in/alexdathskovsky https://www.cppnext.comAlex Dathskovsky | alex.dathskovsky@speedata.io | www.linkedin.com/in/a

Efficient Mixture-of-Experts Language Model DeepSeek-AI research@deepseek.com Abstract We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model characterized by economical training and DeepSeek-V2 and its chat versions still achieve top-tier performance among open-source models. The model checkpoints are available at h t t p s : / / g i t h u b . c o m / d e e p s e e k - a i / D e e p Work 21 A Contributions and Acknowledgments 27 B DeepSeek-V2-Lite: A 16B Model Equipped with MLA and DeepSeekMoE 29 2 B.1 Model Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

.. 79 7.4. Declarative transaction management ...................................................................................... 80 7.4.1. BeanNameAutoProxyCreator, another declarative approach .. ................................................... 82 7.5. Choosing between programmatic and declarative transaction management ....................................................................... ................................................................................... 88 8.4.2. Declarative transaction management .......................................................................

.. 74 7.4. Declarative transaction management ...................................................................................... 75 7.4.1. BeanNameAutoProxyCreator, another declarative approach .. ................................................... 77 7.5. Choosing between programmatic and declarative transaction management ....................................................................... ................................................................................... 83 8.4.2. Declarative transaction management .......................................................................

.. 78 7.4. Declarative transaction management ...................................................................................... 79 7.4.1. BeanNameAutoProxyCreator, another declarative approach .. ................................................... 81 7.5. Choosing between programmatic and declarative transaction management ....................................................................... ................................................................................... 87 8.4.2. Declarative transaction management .......................................................................

.. 82 7.4. Declarative transaction management ...................................................................................... 83 7.4.1. BeanNameAutoProxyCreator, another declarative approach .. ................................................... 85 7.5. Choosing between programmatic and declarative transaction management ....................................................................... ................................................................................... 91 8.4.2. Declarative transaction management .......................................................................