The
4th Chinese Congress on Artificial Intelligence (CCAI2018) which was led by
Chinese Association for Artificial Intelligence (CAAI), was held on July 28-29,
2018, in Shenzhen, China. As the largest official AI conference in China, CCAI
has been held annually to promote the advancement of artificial intelligence
globally. I attended the Congress and
summarized it for sharing AI trend to all quality professionals.
During
the congress, I met the Prof. Deyi Li (李德毅) (President of CAAI, Academician
of CAE) and took a photo for memory.
I
also met Prof. Qiang Yang (杨强) (Vice President of CAAI, AAAI/ACM/IEEE Fellow, President of IJCAI; Chair
Professor, Department Head of CSE, HKUST).
Day 1 (28 July 2018):
In
the beginning of the congress, Prof. Deyi Li (李德毅) (President of CAAI, Academician
of CAE) gave an opening speech and shared the AI Trend in China.
Mr. He
Haitao (贺海涛) (深圳市人大常委会党组成员、罗湖区委书记) gave guest speech and supported
AI industry in Shenzhen
Mr.
Wang Lixin (王立新) (广东省深圳市副市长) gave guest speech and he said his mind though Artificial Intelligence after
he was on board in Shenzhen.
Prof.
Tie-niu Tan (谭铁牛) (Vice President of CAAI; Academician of CAS) gave guest speech and he
said using four Chinese words for coming AI development that was “理性务实” (meaning Rational and Pragmatic).
Day 1 Congress reporting session named “The Future of AI is at Hand”, Prof. Chenqing Zone was session chair and introduced the first speaker.
The
first speaker was Mr. Harry Shum (沈向洋) (Executive Vice President of
Microsoft’s AI and Research group; ACM/IEEE Fellow) and his topic named “The
Future of AI is at Hand and Thinking about Xiaobing (小冰) product
implementation”. He said that AI developed very fast recently because of big computing, big data and
precise model.
Then
Mr. Harry Shum briefed Microsoft Research AI breakthroughs included 96% RESNET
vision test 152 layers in 2016, 5.1% Switchboard speech recognition test in
2017, 88.5% SQuAD reading comprehension test and 69.9% MT research system in
January and March 2018, respectively. And
then he briefed Microsoft Xiaobing (小冰) natures included dialogue platform, Bot Factory, EQ+IQ, AI
Creation and Business Opportunity.
Mr.
Harry Shum mentioned the Emotion Calculation Framework included human
perception, Dual AI and World context.
Microsoft
Xiaobing (小冰)
focused to break through the Emotion Calculation and established relationship
with users. It is one of largest user
based AI dialogue system in the world with 660M users (120M active users per
month). The evolution of line would be
from EQ+IQ to AI Creation. (From Retrieval Model → Generation Model → Empathy Model)
After
that Mr. Shum stated the Three Principles of AI Creation as follows:
i) Integrated EQ and IQ (Not only IQ);
ii) Product created by AI should have independent IP right;
iii) The process of AI Creation should correspond to human creativity, not
only simplify human labour work.
Mr.
Shum demonstrated AI sang a song.
At
the end, Mr. Harry Shum mentioned the concept “Intelligent Cloud” that means
calculation anywhere and Intelligent anywhere – The world is becoming a
computer. Lastly, he quoted Bill Gates
that “Most people overestimate what they can do in one year but underestimate
what they can do in ten years.”
The
second speaker was Prof. Qiang Yang (杨强) (Vice President of CAAI, AAAI/ACM/IEEE
Fellow, President of IJCAI; Chair Professor, Department Head of CSE, HKUST) and
his topic named “The Challenges that AI Faces and the Opportunities that
Transfer Learning Brings (Federal Transfer Learning)”. He discussed Big Data driven AI ideal and
fact, as well as, AI history in raising and fall.
Then
Prof. Yang told about data from different companies had different
characteristics that was difficult to communicate each other. AI’s Big Data had two difficulty situations
that they were privates (especially EU General Data Protection Regulation -
GDPR) and small data. He quoted Prof.
Pedro Domingos (29 Jan 2018) that Starting May 25, the European Union will
require algorithms to explain their output, making deep learning illegal!
And
then Prof. Yang introduced Federated Transfer Learning (FTL) (聯邦遷移學習) to establish machine learning
(ML) of enterprise ecosystem. It could
solve the data security problem through FTL framework.
“FLT
had Heterogeneous Transfer Learning to find latent representations and
Homomorphism-aware loss function via Polynomial Approximation, as well as, Privacy-Preserving
Entry-id Match.” Prof. Yang said.
Finally, he said establishment of security big data plus AI ecosystem
such as Financial Federated Learning Network that solved GDPR privacy
requirement.
The
third speaker was Mr Jason Dai (戴金权) (Senior Principal Engineer and CTO of Big
Data Technologies at Intel) and his topic named “An Introduction to Analytics
Zoo for Apache Spark and BigDL”.
He
would like to introduce the trends of AI as follows:
i)
Data Scale Driving Deep Learning Process
ii)
Hadoop Becoming the Center of Data Gravity
iii)
Real-World ML/DL Systems are Complex Big Data Analytics Pipelines
iv)
Unified Big Data Platform Driving Analytics & Data Science
Then
he introduced Unified Big Data Analytics Platform which consisted Apache Hadoop
and Spark Platform. Mr. Dai also mentioned challenges of productionizing
Large-Scale Deep Learning solutions as follows:
i)
Very complex and error-prone in managing large-scale distributed systems
ii)
Low end-to-end performance in GPU solutions
iii)
Very inefficient to develop the end-to-end processing pipeline
Lastly, he was talking about neural recommendation engine in China Life and summarized to make deep learning more accessible to big data and data science communities and using Analytics Zoo for end-to-end analytics plus AI platform for Apach Spark and BigDL.
The
forth speaker was Mr. Zhiqiang He (贺志强) (Senior Vice President of Lenovo Capital
and Incubator Group) and his presentation topic was “Multiple-speed Industry
Opportunities in Smart Internet Era”. He said Lenovo Investment aimed to
effective capital and entrepreneur’s power that included VC and Incubation.
He
then briefed the path from AI to Intelligent Internet including Internet +
boundary calculation + cloud + big data + AI that integrated into
industry. He also said high quality data
was the base of AI.
After
that Mr. He said core of AI was Data and Algorithm which immersed in cloud,
terminal and chip. He also said to seek
the investment opportunities on intelligent internet core technology as
following diagram.
At
the end, Mr. He said to plan for Great Bay Area and establishing Lenovo Open Platform
for value chain acceleration service.
In
afternoon session, Mr. Tong Zhang (张潼) (Director of Tencent AI Lab) was session
chair.
The
fifth speaker was Prof. Liwei Wang (王立威) (Professor of Peking University) and his
presentation topic entitled “Machine Learning and Artificial Intelligent”. He would discuss the core technology of
Machine Learning (ML) and supervised learning, as well as, trend of ML
development.
Firstly, Prof. Wang said ML is not a new things and he review some physics law such as Hooke's law and Kepler's laws which used for prediction. Therefore the core framework of ML is to collect data for learning model and then predict the new data.
Then
Prof. Wang stated the nature science used simple equation to describe the world
but ML designed complex model which learn from Big Data to solve complicated
problem. He also briefed the Supervised
Learning in which Generalization Capability (泛化能力) is the core concept. Their goal is to make generalization error as
small as possible.
After
that Prof. Wang briefed the history of ML from 1943 to 2006. Neural Networks is revitalized through Deep
Learning from 2006 to now, because of layer by layer training methodology,
hardware computing power increase significantly and big data. AI success implementation areas included
graphic, voice, translation and game.
However, AI only suitable implement in the close loop knowledge with
narrow scope.
Finally,
Prof. Wang discussed the trend of AI was not limited to solve narrow scope
problem. If no breakthrough of AI
development, we were not able to solve problem in open environment employing
common sense. Now, we needed to train up
industry habit for data collection and standardization especially in medical
health industry and financial industry.
Forum
II – Smart Chip: Industry Promotion and Innovation Development
Prof.
Yinhe Han (韩银和) (Professor of ICT, Chinese Academy of Sciences (CAS)) was session
chair and he firstly shared the topic Smart Chip that chip could provide special
intelligent capability focused on deep learning.
Prof.
Han mentioned the smart chip status from inference on device, on cloud and for
training. He also said CAS proposed “DianNao”
neural network processor unit in Feb 2014 and then their spin off company was
acquired by Xinlinx (FPGA factory) in Jul 2018.
The
first guest of forum was Prof. Yunji Chen (陈云霁) (Professor of ICT, CAS) and he
said that education was most important to promote smart chip. He explained Smart Computer that could provide
CPU and intelligent accelerator for developers’ programming.
And
then Prof. Chen introduced smart computer course and it aimed to achieve “Application
Drive and Full Stack Through (應用驅動、全棧貫通)”.
The
second guest was Dr. Yu Wang (汪玉) (Associate Professor of Tsinghua University; Cofounder of DeePhi) and
his sharing topic named “Neural Networks on Chip: From CMOS Accelerators to
In-Memory-Computing”. Firstly, he said AI
is a large area for business scope and introduced Software and Hardware
co-design which obtained the best performance.
After
that he mentioned Neural Network Accelerator Inference, Deep Learning Platform
to Vertical Markets and DeePhi Compression Tool, as well as DeePhi Reference
Algorithms.
Lastly he demonstrated their research and application. He also discussed the energy efficient should be considered for smart chip.
The
third guest was Dr. Jiaen Liang (Founder of Unisound) and he shared title was “Internet
of Things “Chip Era” – Open Source Solution from Module to Chip”. He introduced AIoT chip named UniOne. Their SoC included CPU (ARM), AI accelerator
(DeepNet) and Digital signal processor (DSP).
Then
he introduced their product named UniOne smart speaker and family solution.
The
fourth guest was Prof. Xin Li (李昕) (Professor of Duke University; IEEE Fellow) and his topic named “The missing
Components in AI Chips”. In the beginning,
he introduced AI supply chain.
Then
he mentioned 3 challenges we met below:
i)
Efficient Programming for Hardware Accelerators
ii)
Efficient Validation for Integrated Products
iii)
Efficient Adoption for Broader Applications (Business translators are
important!)
Finally,
he showed a 30-year R&D plan from 2020 to 2050.
The
fifth guest was Mr. Wenyuan Dai (戴文渊) (Founder of 4Paradigm, CEO) and he explained
the company name which was come from Project Jim Gray’s scientific development
from first paradigm to fourth paradigm which depended on data science.
He
said the integration of hardware and software from two stages. First stage is training
included tasks of graphic and decision; and the second stage is predication
included tasks of cloud and terminal. He
concluded that AI algorithm and application should be linked with server and
chip.
The
last guest was Mr. Zhiqiang He (贺志强) (Senior Vice President of Lenovo Capital
and Incubator Group) and he said Lenovo Capital invested in smart internet
since 2016.
At
the end of day 1 program, all guest took a group photo for memory.
Reference:
CCAI 2018 - http://ccai2018.caai.cn/englishPage.html
CAAI - http://www.caai.cn/
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