AI公开课:19.05.22 Aya Soffer—IBM AI Tech VP《Advanced, scalable, and trusted AI 》课堂笔记以及个人感悟


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冥王星简单 2022-09-19 14:48:06 48956
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AI公开课:19.05.22 Aya Soffer—IBM AI Tech VP《Advanced, scalable, and trusted AI 》课堂笔记以及个人感悟

Introduction
        Aya Soffer is Director of Information Management for Analytics Research in IBM. In this role, Aya is driving the world-wide software research strategy in information management for analytics, ensuring IBM's position as a premier software research organization in this area and delivering Research technologies to IBM's software products and customers. In the Haifa Research Lab, Aya is the Department Group Manager of the Information and Interaction Technologies department that focuses on inventing and developing cutting edge technology that connects people and systems to information. Many of these innovations are already included in IBM product and services offerings. IBM’s product groups and customers to drive Research innovation in to the Market.

目录

The Session of Question and Answer

Live Pictures

The PPT of speaker 


The Session of Question and Answer

I am trying, please wait……

Professor LeiMing:from your own view,please talk about the development of NLP in the future
Aya Soffer VP:word embedding ,but deep learning is not enough.
Professor LeiMing:about the bert of google,so, computer power will be play an import part in the future? 
Aya Soffer VP:many many people ask, In fact ,it is diffficult,
Professor LeiMing:ok,let‘s, talk about computer vision,
Aya Soffer VP:it has many many application,CV is popular, Tuling test. simple case from AI,but we can do many amazing thing ,such as ALibaba. So,I think our work is just starting.
Professor LeiMing:AI, How far and How long. please talk about the difference of DL between the US and China. In China, we have a large number of users and a large number of data sets.
Aya Soffer VP:In fact,I don‘t know, may be 50years? haha. We have different cultures. 
Professor LeiMing:this question is from student. Talk about Alphazero
Aya Soffer VP:Alphazero,More data needs to be fed, and its performance will get better and better. It's amazing.
Professor LeiMing:another question, Lawyer's position will be defeated?  And the emotions of AI, How will it develop?
Aya Soffer VP:AI can provide better service for customers. The emotions of AI , some way to go.

Personal views:NLP will shine brilliantly in AI field.
Note: the text of the above dialogue is edited for the blogger to summarize. If slightly different from the original, please refer to the original recording. The time is pressing, if has the mistake, welcome the netizen comment to point out, the discussion.

Live Pictures

I am trying, please wait……

The PPT of speaker 

I am trying, please wait……

AI is … 
The deep learning revolution

  • Deep Neural Network
  • Large Data for Training
  • GPU Hardware Acceleration

The evolution of AI

  • Narrow AI
  • Broad AI
  • General AI
     

AI Agenda for the Enterprise

  • From narrow to broad AI
  • Operationalizing AI at scale

Who won? Two measures
Stance change

offline  Analysis  VS online Analysis

Calim Detection

Three major capabilities that power Project Debater

  • Data-driven speech writing and delivery
  • Listening comprehension
  • Modeling human dilemas

Potential Applications
 

Many industry problems require AI for vision and video
Challenge in video comprehension for the enterprise

Few-shorts and One-shot Learning

  • kids learn from a single example
  • Get machines to learn more like humans
     

Moments in Time Dataset
A large-scale dataset for recognizing and understanding action in videos
Activity Recognition

How can you put your AI models into production at scale?
Existing approaches leave two important questions unanswered

AI System:Automation tool(Power AI Inference Engine)for deep learning accelertor generation and optimization
AI AutoLearning-High Efficient AutoML

Trusting AI
Go beyond accuracy and performance metrics, to instrument AI models and systems with dimensions of trust, making
them fair, explainable, safe, accountable, and compliant with human norms and values.
What does it take to trust a decision made by a machine

AI Agenda for the Enterprise

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