Some personal news: I went back to AI and Machine Learning

It was an opportunity too good to refuse, that’s what I said about two years ago, when I left AI for the crypto world and joined Civic Technologies to help build what now is a decentralized marketplace (identity.com) and the for-profit startup on top of it (civic.com), that eventually expanded from identity to identity and finch – decentralized finance / defi. It was a great journey, with an amazing team and I’m sure they will do well moving forward.

Now for the personal news. This October, I have joined the Figure Eight team, part of Appen, as the Director of Marketing Communications. The group is the biggest ML-assisted and crowd data labeling platform for machine learning. I can’t share too much about the journey ahead, but I can tell you big things will happen in this industry in the next 5-10 years. Machine learning is at a point where it has become productive in a few industries and more and more giants are now looking at their data sets, their processes and trying to figure out how to optimize and improve efficiency. 

Data is the new energy, and it’s likely we will see a similar revolution with ML departments as we have seen with the IT function. It (and IT, ha!) started out in the basement, with the servers, and evolved from a fringe function to the core of many of the most profitable businesses in the world. The best jobs out there rely on IT today and will do so in the future. I see the same future for machine learning, now elevated from curiosity/research only domain to part of the engineering team, where it plays various roles, from marginal to core business, depending on the company. Soon, with enough data and understanding of ML processes and principles, any enterprise will be able to scale faster and more effectively. 

You might wonder what data labeling has to do with all this.

“During the gold rush it’s a good time to be in the pick and shovel business,” Mark Twain reportedly said

Think of it like the gold rush, where people flock to gold bearing mountains to find the prize, gold. They need food, supplies, clothes, fuel, picks and shovels, mining gear and machines, cars and planes. It this case, the prize is profit, the gold rush is the digital age and data is the energy powering everything. The more energy you have and the more refined/adequate it is, the better your chances to find gold. Same goes for machine learning, the more high quality data you have, the less of it you need to train an efficient model, the less resources you spend on computing power. Also, data, unlike fuel, comes in all shapes and sizes, and there will always be more data to be labeled as it is being created. 

Long story short, I’m excited about the journey ahead and looking forward to sharing more stories along the way. 

Photo by David Edkins on Unsplash

And as always, opinions here are solely mine and don’t reflect the views of my employer

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