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Hackernoon logoFabio Manganiello on Home-Made Computer Vision, IoT, Automation, AI by@noonies

Fabio Manganiello on Home-Made Computer Vision, IoT, Automation, AI

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@nooniesNoonies

The Tech Industry's Greenest Awards. Public Nominations Are Open. Voting Starts Aug 13.

Fabio Manganiello writes about solutions he's discovered while building a platform, library of plugins and an API to connect/manage any device and service through any backend, allowing users to easily set up any kind of automation. Fabio is based in Amsterdam, the Netherlands, and has been nominated for a 2020 #Noonie for exceptional contributions to the IoT tag category on Hacker Noon.

🚀 This Year's Noonies were made possible by: Sustany Capital.TECH DomainsGrant for the WebSkillsoftFlipside CryptoUdacity, and BeyondskillsVOTE until 12 Oct 2020 at NOONIES.TECH! 🚀

The Noonies are Hacker Noon’s way of getting to know — from a community perspective —  what matters in tech today. So, we asked our Noonie Nominees to tell us. Here’s what Fabio had to share.

1. Which 2020 Noonie have you been nominated for?

Hacker Noon Contributor of the Year - IoT

2. Tell us a bit about yourself.

I'm a software engineer who likes to build and automate things.

3. Tell us about the things you make / write / manage / build.

Platypush, a versatile platform, library of plugins and API that aims to connect and manage any device and service through any backend, and allow users to easily set up any kind of automation.

Most of my articles describe solutions based on this project, from home-made computer vision, to automating the delivery of RSS feeds, building custom voice assistants, creating a custom media center or robots etc.

4. What are you most excited about right now?

The increasing power and affordability of SoC systems is making it increasingly feasible to run machine learning models even on a recent RaspberryPi.

More and more open source projects now come with a Tensorflow model that can easily run on a $50 machine, and that's a great step forward in democratizing AI.

5. What are you worried about right now?

Society is becoming increasingly polarized because of the information bubbles created by social media.

I'm not sure that all the problems can be fixed, but surely the lack of accountability so far demanded by some social platforms and the toxic feedback loops caused by an engagement-and-ads-driven business model won't help.

6. How has the pandemic changed your life and/or career?

I have been lucky enough to be able to work from home without any major disruptions to my daily job. The pandemic has also been an occasion to try and help the research with my skills and learn something new on the way. I have worked in the initial phases of the pandemic on an ML model for detecting similarities and mutations among the genome samples publicly available and predict the mutation rate for a certain area.

Unfortunately, it proved to be a much bigger challenge than expected given the small size of the team I tried to put together, but I have been positively impressed by the engagement of the people I've reached out for help - within a couple of days I had been given access to large swaths of GPU power to run the computationally intensive algorithms for genetic alignment.

And on the way I learned lots of new things about bioinformatics that I hope I could reuse in the near future.

7. If we gave you $10 million to invest in one thing right now, where would you put it?

Building an MVP for an affordable, modular and 100% open source laptop/tablet aimed to make STEM education more accessible to everyone.

8. What's an opinion you have that most people don't agree with?

That it's time to have a honest discussion with all the involved parties (media and news companies, social networks and other IT giants) to think of a business model alternative both to the ads and the lock-in subscription.

They have created way too many side effects down the way.

9. Which apps can't you live without?

Feedly - with a list of RSS feeds I started curating since the early days of Google Reader

10. What are you currently learning?

Generative adversarial neural networks.

I have experience with ML models to predict or recognize something, but GANNs offer creative ways to use ML to actively generate content instead of passively recognizing it.

VOTE for Fabio Manganiello as Hacker Noon Contributor of the Year - IoT before voting closes on 12 October, 2020! 🚀

With gratitude to Hacker Noon's 2020 Noonies Partners: Sustany Capital.TECH DomainsGrant for the WebSkillsoftFlipside CryptoUdacity, and Beyondskills!

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