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As a technical founder of a tech startup, I often interact in sales conversations with other CTOs or tech leads. Don’t take the title literally — these tips may also be of interest to tech leads, VPE or other leadership roles at any tech startups.

This articles aims to simply share what I’ve personally learned. I’d like to start by pointing out that I’m touching 2.5 years into this role and still learning. I’m a first time CTO, and we’re a seed-stage startup with about 20 people.

Our aim at Aflorithmic is to:

“Create the authoritative infrastructure for the next…


Our mission is to create frictionless audio experiences through coding. Video is a very important part — since video is often connected to audio.

Video creation itself is already widely accessible: There are stock videos you can use to create your content and there are audio libraries with royalty-free music, many of them free. You can even use text-to-speech voice-overs if you don’t want to narrate the content yourself.

Now, with api.audio, you can do all of that programmatically through our api. …


Before we start I just wanted to give full disclosure that I’m a Co-Founder of Aflorithmic, so expect some bias towards what we’re building. Not only is it my job, audio tech is my passion.

Aflorithmic makes scalable audio, something that has never been possible before, due to the fact that voice content has to be recorded. Our main product api.audio provides the infrastructure to do that. You can use Text to speech for creating voice content, add a sound design, master the track and do all of that automatically for thousands of versions. Job done? Well, there’s more. …


The screenshot above is specifically about Luxembourg, however I think this will be of interest to other ‘startup hubs’ and policy folks, entrepreneurs and those who are interested in the question of how to foster an innovative ecosystem.

I’m an Irish entrepreneur — with a company that has offices in London and Barcelona, I did my masters in Luxembourg, and spent a few years working in its ‘tech sector’. I strongly felt the tech sector was nascent about 5 years ago, and while I regularly visit it and talk to people in its ecosystem, I haven’t seen ‘growth’ or success…


One of the apps built with our App creation technology— Nutridi

by Peadar Coyle and Salih Kasım Benli

We used Expo managed flow for a year. Here are some things we’ve learned over the past 18 months with a small developer team.

Aflorithmic Labs (www.aflorithmic.ai) is a deep-tech focused startup that’s building a platform for brands to create personalized audio experiences. Our clients and users often look for apps as a delivery mechanism so we’ve built some tooling to make it easy to create apps, connecting to our APIs in the backend.

When we were starting our journey about 18 months ago, our founder Peadar evaluated React-Native, native code, and flutter.


(Disclaimer: Working on something exciting and new in the audio/voice space, but we’re still in stealth mode — you can DM me on the internets to find out more)

I was recently listening to the podcast mentioned here this is where Marc Andressen the legendary investor and thinker about technology said:

Audio is going to be titanically important — Marc Andressen

Now it’s worth digging deep into why that’s the case. Here are 5 reasons I’m excited about audio/voice tech. And why I think we’ve only scratched the surface of what can be built in that space.

  1. Airpods

This chart from Nick Pappageorge shows one estimate from Loup ventures, although other estimates are lower. However, anecdotally I counted my overground carriage into work last week and I saw about…


You have a problem that you think might need some Bayesian modelling

A common question I’m asked is how do you start?

In this tutorial I take you from a fresh data set, the data set is an educational dataset. I don’t know anything about the data, and I have no specific domain knowledge. I adapt the model from the PyMC3 documentation.

I then evaluate the model using tools such as Arviz, to explain and evaluate your modelling decisions. I use this to inform a better model and we see from our evaluation of the model that the second model is much better. …


Probabilistic Programming versus Machine Learning

In the past ten years, we’ve seen an explosion in Machine Learning applications, these applications have been particularly successful in search, e-commerce, advertising, social media and other verticals. These applications have been particularly focused on predictive accuracy and often involve large amounts of data — sometimes in the region of terabytes — in fact this drove a lot of innovation at the Tech giants such as Netflix, Amazon, Facebook and Google.

Fundamentally though these models often are ‘black boxes’ and are not easily understood by observers, in applications such as churn modelling or building targeted advertising models it doesn’t matter…


Probabilistic Programming versus Machine Learning

In the past ten years, we’ve seen an explosion in Machine Learning applications, these applications have been particularly successful in search, e-commerce, advertising, social media and other verticals. These applications have been particularly focused on predictive accuracy and often involve large amounts of data — sometimes in the region of terabytes — in fact this drove a lot of innovation at the Tech giants such as Netflix, Amazon, Facebook and Google.

Fundamentally though these models — often are ‘black boxes’ and are not easily understood by observers, in applications such as churn modelling or building targeted advertising models — it…


I’m going to write a bit about expectations management in Data Science projects. Now this is something that the academic side of my personality finds a bit ‘business-speak’. However it matters in commercial environments (and probably in non-commercial environments like not-for-profits too).

It’s worth sharing a Dilbert comic. Just because it’s always relevant when discussing ‘business-speak’.

Copyright: Scott Adams and Dilbert

So the following are some tips I’ve learned. The reason I share these is that managing expectations is a difficult part of the Data Science process. Research and Development type work and even software work are hard, they’re hard…

Peadar Coyle

Cofounder of www.Aflorithmic.ai building www.api.audio a simple developer tools for adding audio to your applications

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