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AI/ML/DL [clear filter]
Tuesday, October 27

17:15 GMT

Prometheus Enabled AI Deep Observability Based on eBPF - Ivy He, Huawei Technologies Co, LTD
AI training process is complex and invisible, when running the task, there are some monitoring blind spots by using the traditional tracing tools, which brings many difficulties to the developers to debug and tuning. For this reason, we choose eBPF to analyze the changes what we want to know in the real-time, such as: to understand whether a specific kernel function is called, short-lifetime processes, etc. With the data collected dynamically by eBPF, we choose the Prometheus to monitor and show them to the developers. In this topic, I will share the practice of eBPF in the observability of AI kernel. While running the AI training and reasoning tasks, we can dynamically inject the eBPF code into the kernel function to collect data, and report the data to the Prometheus in a unified format for visual management. The practice of the observability is currently in the experimental stage.

avatar for Luwei He

Luwei He

I am Ivy He, an open source engineer from Huawei. I was involved in open source work related to high-performance storage and edge computing. Contributed in SPDK, Kubernetes, Akraino and other open source communities. Currently I am mainly engaged in open source practice in AI obs... Read More →

Tuesday October 27, 2020 17:15 - 18:05 GMT
AI/ML/DL Theater
  AI/ML/DL, AI Observability

18:30 GMT

Using Volcano and Kubernetes for Cutting-Edge AI Deployment - Yedong Liu & William Wang, Huawei
Over the past few year, cloud native software brought many benefits to industry for deployment, management etc. MindSpore, a new open source deep learning framework, is also one of them. As it suggests, MindSpore is working on collaboration with CNCF projects such as Kubernetes and Volcano to allow deploying MindSpore job on container environment. This session will show the technical details as well as the examples on how a MindSpore training job runs in the container env and distributed GPU demo with Volcano. Together with long term goals of MindSpore & other cloud native projects are also included in this session.


Yedong Liu

Open source engineer, Huawei
Yedong Liu is an Open Source Engineer from Huawei, he participated in Open Source communities including ONNX, Volcano etc. He is now a member of the MindSpore community which is a newly open sourced deep learning framework. Yedong is working on bringing more convenience to the developers... Read More →

William Wang

Architect, Huawei
Volcano member, software developer, currently working on Volcano Job scheduling across multiple cluster development. Experienced in batch system and Bigdata, AI worklaod performance acceleration. Spearker in ArchiSumit sharing spark on kubernetes best practice.

Tuesday October 27, 2020 18:30 - 19:20 GMT
AI/ML/DL Theater
  AI/ML/DL, Machine and Deep Learning
  • Skill Level Any
  • Technical Talk No

19:30 GMT

Building Trustworthy AI: Lessons from Open Source - Abigail Cabunoc Mayes, Mozilla
Algorithms influence our lives: they decide what videos we watch next, and whether someone is eligible for parole. Yet every day, we hear new stories on how AI discriminates and amplifies bias. How can we build AI that is worthy of our trust? The free software movement was founded on principles protecting user rights (to use, modify, and distribute software). Through mechanisms like open source licenses, transparency, and collaboration, open source thrived and transformed our digital world. AI is at a similar crossroad – staged to change the digital landscape, but limited by questions of ethics and user rights. We have an opportunity to take lessons from open source to protect our rights while innovating towards an AI revolution. --- This session has not been presented before, however I will be presenting a version at COSCUP 2020 (Taiwan, Aug 2020). If selected, I hope to adapt this for a European audience and build on what was presented on COSCUP based on feedback and new work.

avatar for Abigail Cabunoc Mayes

Abigail Cabunoc Mayes

Program Manager, Mozilla
Abigail Cabunoc Mayes (@abbycabs) leads Mozilla’s developer-focused trustworthy AI strategy around MozFest and open source. Previously, Abby founded and led Mozilla Open Leaders, a program that has worked with over 600 open projects globally. With a background in open source and... Read More →

Tuesday October 27, 2020 19:30 - 20:20 GMT
AI/ML/DL Theater
  AI/ML/DL, Trusted and Responsible AI
  • Skill Level Any
  • Technical Talk No
Wednesday, October 28

12:00 GMT

Productionizing ML with ML Ops and Cloud AI - Kaz Sato, Google
The hardest part of ML adoption in enterprises is Productinization. As we see in recent discussions around ML Ops, there is a big gap between Data Scientists' PoC code and production ML development and operation with Ops team. Such as, preparing manageable ML dev environment, building a scalable ML serving infrastructure, setting up a ML pipeline for continuous training, and automated validation of data and model. In this session, we will learn how to leverage various Google's ML/AI offerings such as TensorFlow Extension (TFX), TensorFlow Enterprise, Cloud AI Platform Notebooks, Training, Prediction, and Pipelines for productionizing your ML service with the ML Ops best practices.

avatar for Kaz Sato

Kaz Sato

Developer Advocate, Google
Kaz Sato is Staff Developer Advocate at Google Cloud for machine learning and AI products, such as TensorFlow, Cloud AI and BigQuery. Kaz has been invited as a speaker at major events including Google Cloud Next, Google I/O, NVIDIA GTC and etc. Also, authoring many GCP blog posts... Read More →

Wednesday October 28, 2020 12:00 - 12:50 GMT
AI/ML/DL Theater

13:00 GMT

Hands-On Real Time Stream Processing for Machine Learning - Alejandro Saucedo, The Institute for Ethical AI & Machine Learning
This talk will provide a practical insight on how to build scalable data streaming machine learning pipelines to process large datasets in real time using Python Asyncio, Kafka, Faust, SpaCy and Seldon. We will be covering a case study performing automated content moderation on Reddit comments in real time. Our dataset will consist of 200k reddit comments from /r/science, 50,000 of which have been removed by moderators. We will be handling the stream data in a Kafka cluster, and the stream processing will be handled using the stream processing library Faust. We will be running the end-to-end pipeline in Kubernetes with various components legeraging SKLearn, SpaCy and Seldon. We will then dive into fundamental concepts on stream processing such as windows, watermarking and checkponting, and we will show how to use each of these frameworks to build complex data streaming pipelines that can perform real time processing at scale. Finally we will show best practices when using these frameworks, as well as a high level overview of tools that can be used for monitoring, including Grafana and Kafka Manager.

avatar for Alejandro Saucedo

Alejandro Saucedo

Chief Scientist, The Institute for Ethical AI & Machine Learning
Alejandro is the Chief Scientist at the Institute for Ethical AI & Machine Learning, where he leads the development of industry standards on machine learning bias, adversarial attacks and differential privacy. Alejandro is also the Director of Machine Learning Engineering at Seldon... Read More →

Wednesday October 28, 2020 13:00 - 13:50 GMT
AI/ML/DL Theater
  AI/ML/DL, Data Versioning

16:15 GMT

Milvus, How to Accelerate Approximate Nearest Neighbor Search (ANNS) for Large Scale Dataset - Jun Gu, Zilliz
Deep learning models has been proven to be an effective method to extract content from unstructured data like image, video, sound and text. When using pre-trained DL models in production, people will need to handle huge amount of feature vectors. Milvus is an open source vector similarity search engine, which could help users to perform efficient similarity search over billions of vectors. Jun has already introduced the big picture of Milvus project in previous OSS North America event. This time Jun will introduce the technology used in Milvus project, and how Milvus would accelerate ANNS for large scale dataset. Milvus is an incubation project in LF AI foundation.


Jun Gu

Technology evangelist, Zilliz
Jun Gu is the partner of Zilliz, performing the Senior Architect role. Before joined Zilliz, Jun received his under graduate degree of Computer Science from Peking University and worked as database technician for 14 years in companies like ICBC, IBM, Morgan Stanley and Huawei. Jun... Read More →

Wednesday October 28, 2020 16:15 - 17:05 GMT
AI/ML/DL Theater
  AI/ML/DL, Data Versioning

17:15 GMT

Become a Data Driven Organization through Unified Metadata Using ODPi Egeria - Mandy Chessell, IBM
Become a data-driven organization through exploration of the latest developments and trends in managing compliance, GDPR, data catalogs and governance. The ODPi Egeria project at the Linux Foundation will share how IBM, ING and others are collaborating to build an open ecosystem (interfaces, repositories, tools and experts to collaborate and exchange content) while adhering to governance guidelines and imperatives. Join this session to learn how an open metadata and governance and how you can benefit from it.

avatar for Mandy Chessell

Mandy Chessell

ODPi TSC Chairperson and ODPi Egeria project chairperson. IBM Distinguished Engineer, IBM
Mandy Chessell CBE FREng CEng FBCS is an IBM Distinguished Engineer, Master Inventor and Fellow of the Royal Academy of Engineering. Mandy is a trusted advisor to executives from large organisations, working with them to develop their strategy and architecture relating to the governance... Read More →

Wednesday October 28, 2020 17:15 - 18:05 GMT
AI/ML/DL Theater
  AI/ML/DL, Data Versioning

18:30 GMT

Inference on (the) KubeEdge - Adrian Gonzalez-Martin, Seldon
Machine learning models usually make predictions based on data coming from a wide range of IoT devices. If we think of images, audio recordings or brain waves we can see that they are all measured using hardware sensors. After being read, this data is usually sent to remote clusters where inference is performed. Wouldn’t it be great if we could expand these devices to also make predictions? Edge computing can help to address the privacy, latency and data ownership concerns by bringing this computation to the “edge”. In this talk we will discuss these concerns and we will introduce KubeEdge as a solution to treat our edge devices as Kubernetes nodes, which will enable us to use existing Kubernetes tools to deploy machine learning models and perform real-time inference.

avatar for Adrian Gonzalez-Martin

Adrian Gonzalez-Martin

Machine Learning Engineer, Seldon
Adrian is a Machine Learning Engineer at Seldon, where his focus is to extend Seldon’s open source and enterprise machine learning operations products to solve large scale problems at leading organisations in the Automotive, Pharmaceutical and Technology sectors. When he is not... Read More →

Wednesday October 28, 2020 18:30 - 19:20 GMT
AI/ML/DL Theater
  AI/ML/DL, AI on the Edge

19:30 GMT

How Jina Saves Your Time on Building Cloud-Native Neural Search Systems - Han Xiao, Jina AI
Today, with the ever more long documents and multimedia data, finding the right information is more important and challenging than ever. The rise of deep learning has ushered in a new era of "neural search". However, building a neural search system is non-trivial work for most of the engineers. The main challenges are: (1) long dev cycle due to the complex tech stack (2) poor scalability due to the glued-architecture (3) strong requirements on the domain knowledge to fine-tune the results. With Jina (https://github.com/jina-ai/jina), engineers can quickly build up a search engine powered by state-of-the-art AI in just minutes. In this talk, I will introduce the design philosophy and the key features of Jina; and showcase how Jina bootstraps a QA semantic search system and a short-video search system in just lines of code.


Han Xiao

CEO, Jina AI
Dr. Han Xiao is the Founder & CEO of Jina AI. Han has worked in AI OSS for quite some time. His Fashion-MNIST and bert-as-service were listed as the most popular AI open-source projects in 2017&18 world-widely. In 2018-2020, Han led a team on neural information retrieval at Tencent... Read More →

Wednesday October 28, 2020 19:30 - 20:20 GMT
AI/ML/DL Theater
  AI/ML/DL, Machine and Deep Learning

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