The AI Edition [1]
Artificial Intelligence and Machine Learning present duelling opportunities and risks. Some minor and some existential. Few organisations and their leaders truly grasp this reality. We don't pretend to have all the answers in this latest edition of TQ, but we trust the content below gives you and your organisation a good start on your AI and ML journey.
FinTech and Artificial Intelligence: Fiction or Becoming Fact? [2]
Tech Research Asia dives into how artificial intelligence is driving a wave of FinTech developments in the ASEAN region. We offer examples of FinTech products and services already hitting the market that contain a significant AI component and outline what this means for organisational leaders.
Natural Language Processing and Generation Tools to Consider [3]
Creating conversational user interfaces and any output of AI or ML requires NLP and NLG tools. Today you have a choice of using open source libraries or a commercial service (via APIs). Read the List of NLP and NLG Tools Available [3] .
Chat Bot Services for Your New Customer Experience [4]
New interfaces and ways of engaging with our customers are quickly maturing and spreading. Chatbots aren’t new, but are part of this exciting new domain of the customer (and employee) experience. Read more here. [4]
Tech in Action [5]
Examples of Technology in Use
Expand your moat with machine learning: The Xero experience [6]
The Machines Talk: Kone's IoT and machine learning journey [7]
A conversation with the maker's of DRU [8]
One Japan, AI and the Millennial Generation [9]
Will chatbots replace your call centre or customer service agents? [10]
Leadership [11]
Leadership and strategy insights and advice for technology and business leaders.
How fast could you learn to use a swing? [12]
Artificial intelligence: the adventure has just begun [13]
The future of artificial intelligence: two experts disagree [14]
We don't want AI that can understand us – we'd only end up arguing [15]
Think [16]
Essays and opinion pieces designed to get your thinking more about innovation.
The People-Less Organisation [17]
How to make robots that we can trust [18]
Artificial intelligence researchers must learn ethics [19]
Humans in 2167: Internet implants and no sleep [20]
Natural language processing and affective computing [21]
Asimov’s Laws won’t stop robots harming humans so we’ve developed a better solution [22]
Reading Lists [23]
Essential resources to check out for your own strategy.">
Resources for Understanding AI and ML [24]
CxO Checklists [25]
In-depth strategy questions to ask of your own organisation.">