當醫院為疾病纏身的你安排好了一檔重要的手術，這時你聽說你的主刀醫生其實是一個機器人，這時你會怎麼想？
雖然機器智慧在醫療中的應用還遠沒有達到這個階段，但我們確實在一步一步得創造更加智慧的機器以儘可能的使之與人類智慧相配。今年六月六日至七日，機器智慧峰會及機器智慧醫療峰會將會在中國香港展開，眾多人工智慧與機器智慧領域的專家學者將會出席，並與我們一同探討醫學影像、醫療診斷技術的轉變，以及機器智慧的崛起在解釋資料和醫療應用變革中的作用。
At some point in our lives, the majority of people will need to use a healthcare service whether this is for a scan, an operation or medication. Previously, diagnosing and treating diseases has been a lengthy process, but as AI is advancing so rapidly in the space, healthcare professionals are able to treat, diagnose and even predict disease more efficiently, and with decreased error.
Joining us in Hong Kong, Ankur Purwar, Principal Scientist at Procter & Gamble will discuss diagnostics and personalisation in skin care via AI. It’s not uncommon to be uncomfortable with your skin pigmentation, texture, or scarring and the mass beauty aisle is often crowded and confusing and experiences with beauty counselors in specialty department stores can be overwhelming. Ankur will share how he is working towards personalised skin care with the newly developed Olay Skin Advisor, a web-based skin analyst and advisor tool that uses AI to address this problem.
Continuing the discussion on personalised medicine, Artur Kadurin, Chief AI Officer at Insilico Medicine will talk about using AI-driven blockchain solutions to return the control over personal and medical data back to the individual. The platform Insilico Medicine are using, Longenesis, facilitates human data transactions between Contributors (the general public) and Customers (Drug development/Pharmaceutical companies). Artur explained how leveraging machine learning to generate meaningful leads in illnesses such as cancer and age related diseases is ‘humanity's most pressing cause and everyone in machine learning and data science should be contributing.’
Presenting at the Machine Intelligence Summit, Danfeng Li, Director at Alibaba will explain how user behaviour data is a goldmine, and will explain how they ‘dig it’. When businesses have behaviour data on their customers that’s directly related to their business it’s easy to read, but Danfeng will demonstrate how seemingly non-related behavior can also be very useful through ML and data mining. The examples Danfeng will use will be in internet finance risk control, and online advertising to show how sophisticated models can find the underlying correlation between business goals and online behavior.
Every industry touched by AI is being transformed, and NASA Ames Research are using machine learning for space projects. Last year in Boston we heard from Sangram Ganguly from NASA Earth Exchange Platform who explained that their vision is ‘to provide science as a service to the Earth science community addressing global environmental challenge’ and to ‘improve efficiency and expand the scope of NASA earth science tech, research and application programs’. This year Hamed Valizadegan, Senior ML Scientist will explain how the success of the space projects depends much on our ability to understand and analyze their collected science and engineering data. In the science domain, the amount of collected data is so very large that requires building automatic tools to make sense of them. In this domain, often the data is not annotated well and/or there is not enough representative features for effective model construction.
This is RE•WORK’s first summit in Hong Kong, following an increasing demand for Summits to be hosted in Asia after a the hugely successful Deep Learning Summit in Singapore last year. This event will sell out, so register now to guarantee your place. Super Early Bird tickets are on sale and you can save nearly HK$4000 when you register before February 16.
Additional confirmed speakers include
Michal Szczecinski, Head of Analytics and Data Science, GoGoVan
Johnson Poh, Head of Data Science at DBS Bank
Pallab Maji, Senior Research Engineer at Mercedes-Benz R&D India
Lawrence Wee, Chief Data Scientist at Allianz Asia-Pacific
... and many more.