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Jiquan Ngiam
Building @ Lutra AI
Jiquan Ngiam is a highly accomplished professional with a strong background in computer science and artificial intelligence.
He holds a Doctor of Philosophy - PhD, Computer Science from Stanford University and a B.S., Computer Science from Carnegie Mellon University.
Ngiam has a diverse work history, having been the Co-Founder and CEO at Lutra AI, a Tinkerer at Self-employed, a Senior Staff Engineer at Google Brain, Employee #1 and Director of Engineering at Coursera, and a Software Engineering Intern at Google.
With his rich experience and expertise, Ngiam has made significant contributions in the tech industry, particularly in the fields of AI, engineering, and entrepreneurship.
Highlights
For gluing your martech stack together, there's on one end Zapier that is great for moving data one-way but isn't very powerful; and on the other end, more powerful tools like Make.com that are complex -- you'll need to understand data structures.
As the number of SaaS product we use grow, this problem only gets bigger. Do you have this challenge? We are building a AI-based solution that balances simplicity with power, would love to chat.
Nice article from https://lnkd.in/gdExAMhZ
Generative UX is the next frontier for AI applications.
Most AI applications are based in chat today -- while chat is flexible, it has many issues. Generative UX that creates custom experiences on the fly could solve a lot of these problems.
Two big issues we encountered was the (a) lack of affordance: it can be hard to understand what a chat-based system can and cannot do -- and in the case of AI, it's hard to "point and give feedback" to an AI system, (b) inefficiency: for frequent actions, being able to directly tap/click on a UI element is much simpler than asking chat to accomplish it; overtime, too much chat can lead to fatigue.
The idea of "prompt engineering" is a temporary stop-gap for dealing with these issues.
A lot of UX in today's business applications tend to be reflection of the underlying data representation, often resulting in endless menus and options.
But, what if the UX was instead on-the-fly tailored to the user's desired outcome? Can we automatically determine the appropriate controls to show, and also have affordances to let them dig deeper.
As we get into the world where each of us can build our own custom software, generative UX will be a big piece of the puzzle to figure out!
[1] https://lnkd.in/gQwvw5n2 [2] https://lnkd.in/g_Vb_Hve [3] https://lnkd.in/gmw_mCDk
