We will be discussing deep learning techniques using neural networks to get a more accurate and precise understanding of the true impacts & applications of AI.
There is a lot of FOMO driving AI in every sector now, and a lot of hype surrounding AI. Many startups have rebranded themselves into one that is “AI-driven”, and Chinese and American investors are pouring in huge amounts of money into the space. On top of that, FANG and BAT are extremely avid in seeking acquisitions (e.g. DeepMind, DNNResearch), as well as going on technology demonstration sprees.
Most notably, we have:
1. Google’s AlphaGo beating Ke Jie (the world’s top Go player)
2. Baidu’s Xiaodu AI trumping humans in facial and voice recognition.
Everyone wants in on a piece of the action and a slice of the AI pie. The main challenge is to work out what is fluff and what is truly achievable with state-of-the-art techniques. Unfortunately, there are many extravagant headlines and articles mongering fear, uncertainty and doubt (“FUD”) – mostly over AI replacing jobs.
In this talk, the focus will be on discussing deep learning techniques using neural networks rather than AI in general or other machine learning techniques like SVM. This will lead us to a more accurate and precise understanding of the true impacts & applications of AI.
The speaker, Tomithy, will share on the following:
- What is AI & deep learning and how is it applied to different industries?
- What is all the hype of AI about and why is it important to get your hands dirty?
- How to get started with AI?
- Demo: simple AI learning how to play a game from scratch
This course will be taught in Python 3.0 + other high level AI programming framework. Attendees are expected to be able to program in Python and have a fair understanding of math and stats.
Tomithy plays the role of the seeker & investor with ST Telemedia, which invest across Telcos, Data Centres and growth stage tech companies in the Artificial Intelligence/Big data, Cybersecurity and Cloud technology space. He actively evaluates these companies in terms of their technology and business strategy to sieve out the golden snitch from the noise.
Tomithy is trained in computational biology and is self-taught for programming and artificial intelligence. He has a particular interest in applying evolutionary algorithm to neural networks, games playing AI and the stewardship and ethics of AI. Tomithy has more than 10 years of programming experience and has worked with various research groups including the Galaxy project, NUS-MBI, A*STAR (GIS, BII). He will share some key insights into AI and its application.