For some people, a single event can be a missed opportunity to build wealth. That opportunity comes at the moment of exiting a company, and whether or not that individual exercises their stock options. M&A events, IPOs or even investment rounds are…
ML model training is the most time-consuming and resource-expensive part of the overall model-building journey. Training by definition is iterative, but somewhere during the iterations, mistakes seep into the mix. In this article, I share the ten deadly sins during ML model…
As we are leveraging data for making significant decisions that affect individual lives in domains such as health care, justice, finance, education, marketing, and employment, it is important to ensure the safe, ethical, and responsible use of AI. In collaboration with the Aether…
A new way of using machine learning to examine satellite images could help people around the world. More than 700 imaging satellites orbit the earth, but only governments and companies with wealth and expertise can access the data they produce. Now, researchers…
Most AI vendors develop solutions that target broad use cases with large markets. This is because investors have shown they are only interested in a target market if it is worth several billion dollars. Therefore smaller markets have been excluded, and AI solution ideas…
TORONTO — As fake videos generated by AI continue to become more convincing, what was once a tool to share laughs on the internet has grown into a worrying sector of digital media. Whether it’s a viral video of “Tom Cruise” doing…
In an economy where data is changing how companies create value — and compete — experts predict that using artificial intelligence (AI) at a larger scale will add as much as $15.7 trillion to the global economy by 2030. As AI is changing…
Europe’s vision of artificial intelligence regulation is color-blind — and not in a good way. Between the U.S.’s laissez-faire and China’s dirigiste approaches, the EU is intent on carving out a “third way” for AI regulation that boosts innovation but respects “European…
If you applied for a mortgage, would you be comfortable with a computer using a collection of data about you to assess how likely you are to default on the loan? If you applied for a job, would you be comfortable with…
In a previous post, I outlined four challenges to scaling AI: customization, data, talent, and trust. In this post, I’m going to dig deeper into that first challenge of customization. Scaling machine learning programs is very different to scaling traditional software because they…
