How we built an AI unicorn in 6 years

Today, Tractable is worth $1 billion. Our AI is used by millions of people across the world to recover faster from road accidents, and it also helps recycle as many cars as Tesla puts on the road.

And yet six years ago, Tractable was just me and Raz (Razvan Ranca, CTO), two college grads coding in a basement. Here’s how we did it, and what we learned along the way.

Build upon a fresh technological breakthrough

In 2013, I was fortunate to get into artificial intelligence (more specifically, deep learning) six months before it blew up internationally. It started when I took a course on Coursera called “Machine learning with neural networks” by Geoffrey Hinton. It was like being love struck. Back then, to me AI was science fiction, like “The Terminator.”

But an article in the tech press said the academic field was amid a resurgence. As a result of 100x larger training data sets and 100x higher compute power becoming available by reprogramming GPUs (graphics cards), a huge leap in predictive performance had been attained in image classification a year earlier. This meant computers were starting to be able to understand what’s in an image — like humans do.

The next step was getting this technology into the real world. While at university — Imperial College London — teaming up with much more skilled people, we built a plant recognition app with deep learning. We walked our professor through Hyde Park, watching him take photos of flowers with the app and laughing from joy as the AI recognized the right plant species. This had previously been impossible.

I started spending every spare moment on image classification with deep learning. Still, no one was talking about it in the news — even Imperial’s computer vision lab wasn’t yet on it! I felt like I was in on a revolutionary secret.

Source ; https://techcrunch.com/2021/07/20/how-we-built-an-ai-unicorn-in-6-years

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

Veille-cyber

Share
Published by
Veille-cyber

Recent Posts

Bots et IA biaisées : menaces pour la cybersécurité

Bots et IA biaisées : une menace silencieuse pour la cybersécurité des entreprises Introduction Les…

5 jours ago

Cloudflare en Panne

Cloudflare en Panne : Causes Officielles, Impacts et Risques pour les Entreprises  Le 5 décembre…

5 jours ago

Alerte sur le Malware Brickstorm : Une Menace pour les Infrastructures Critiques

Introduction La cybersécurité est aujourd’hui une priorité mondiale. Récemment, la CISA (Cybersecurity and Infrastructure Security…

5 jours ago

Cloud Computing : État de la menace et stratégies de protection

  La transformation numérique face aux nouvelles menaces Le cloud computing s’impose aujourd’hui comme un…

6 jours ago

Attaque DDoS record : Cloudflare face au botnet Aisuru – Une analyse de l’évolution des cybermenaces

Les attaques par déni de service distribué (DDoS) continuent d'évoluer en sophistication et en ampleur,…

6 jours ago

Poèmes Pirates : La Nouvelle Arme Contre Votre IA

Face à l'adoption croissante des technologies d'IA dans les PME, une nouvelle menace cybersécuritaire émerge…

6 jours ago

This website uses cookies.