Jiameng Gao: ‘Don’t Follow Advice: Including This’

Jiameng Gao: ‘Don’t Follow Advice: Including This’

An Interview with One of London’s Leading AI/ML Startup CTO’s. At its core, Machine Learning brings together the best bits of Data Science and Artificial Intelligence, landing firmly on the foundation of Statistics. At this core, the possibilities are endless in what you can find patterns in and whilst I find patterns in stock prices, Jiameng finds patterns in speech.

At its core, Machine Learning brings together the best bits of Data Science and Artificial Intelligence, landing firmly on the foundation of Statistics. At this core, the possibilities are endless in what you can find patterns in and whilst I find patterns in stock prices, Jiameng finds patterns in speech.

Jiameng Gao and I have been very good friends since we studied the same masters programme in Machine Learning at Cambridge University. Our lives have taken quite different routes since we graduated a few years ago in that as my career in Quant Finance developed, Jiameng was busy building his company Machine Learning based company, Papercup.

The following is an interview with a good friend who is currently in thick of it: funding rounds, 15+ staff, being in his 20’s and managing his business during a once-in-a-lifetime style pandemic.


What’s your name and where are you from?

Hey! I’m Jiameng Gao and I grew up in Beijing before moving to Brighton at the age of 10.

What’s your favourite colour, favourite food

Favourite colour — a good Blueish Azure, which is the colour of my pen ink at the moment.

Favourite food — nothing quite beats a good braised pork or braised beef short-ribs; thing is you have to commit and cook them for at least 3 hours.

Alright nice! Let’s jump straight into the deep end and talk your life experiences.

One of the hardest things is knowing when to settle on an idea and to dedicate the next 5–10 years of your life on it. What made you think “Yeah — this idea is awesome”

Admittedly, we’ve only been going for 3 years now, so perhaps the experience so far might not apply for a time scale that’s 5–10 years. And truth be told, it’s probably easier to say you’ll dedicate 5 years of your life to something than actually doing it.

Needless to say, doing a startup is a lot of work, and it’s often easier to focus on the negatives than the positives for your current situation, partially because you often have the clearest understanding of your own difficulties, and partially because negative experiences last in our heads much longer than positive ones.

startup business artificial-intelligence technology machine-learning

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