This is the fourth in a series of posts about the effects of bias on ML algorithms. In the previous post we discussed what happens when you train an algorithm with data that isn’t representative of the universe the algorithm will operate in. This week’s focus in on the effects of human prejudice on machine learning.Read more
Spending on AI is exploding. IDC predicts today’s $12B/year investment will nearly quintuple over the next three years.Read more
This is the third in a series of posts on the types of bias that can affect AI systems. In the previous post we talked about bias in the algorithms themselves. With this post the series pivots to bias in the AI system’s training data.Read more
We’re doing a series of posts on the ways that bias can influence machine learning.Read more
Treat - The AI project mandated by the board just went into production without a hitch and is exceeding its forecasted bottom line impact. You’re a freaking superhero. Your CEO is on the cover of your industry’s biggest publication. You and your team have gotten bonuses and promotions. Sweet.Read more
We were excited to announce this morning that we've significantly enhanced the Alegion Training Data Platform. The new capabilities delivered with this release target the quality and efficiency requirements of large-scale machine learning initiatives.
You can read the press release below, and if you want to learn more about the Alegion Training Data Platform our website has a dedicated page here.
Alegion Announces Next-Generation Training Data Platform for Enterprise Artificial Intelligence (AI) InitiativesRead more
A recent article in The Register explored the increasing role of humans and how they come into play when training AI.Read more
The headline tells the story.
CIOs are increasingly recognizing the value of high-quality training data as they embrace their artificial intelligence initiatives, according to the industry experts at Gartner, Inc.Read more
To be successful with any AI project, one must take steps to fully comprehend “what deep learning is, how it works, and what its most effective applications are.” Ignoring these steps can only doom product development as well as introduce inefficiencies in team productivity.Read more