The local Austin machine learning community will be busy this week.Read more
Data Day Texas, now in its 9th year, is an Austin tradition for data geeks in the area. While the conference has always focused on data generally, the organizers found that AI has grown so much in popularity that it justified turning the one-day event into a two-day event, with the first day dedicated to AI. And that’s why we’ll be at Texas AI Summit.Read more
Artificial Intelligence continues to be one of the hottest and most controversial topics covered by technology analysts and researchers in 2018. By the end of the year, most of us use some form of AI in our individual lives everyday. Everytime we ask Alexa how many tablespoons are in a cup or follow a recommendation made by Netflix or Amazon, we are interacting with and using AI. in fact, everytime you follow a recommendation you are training that AI, ensuring it makes better and better recommendations for you over time.Read more
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
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
Machine learning (ML) enables computers to “discover patterns and relationships in data instead of being manually programmed.” This science to date is already impacting the way we live, “driving everything from Netflix recommendations to autonomous cars.” However, the more experiences that are built with ML, the more obvious it becomes that UXers are still in a learning phase when it comes to controlling the technology.Read more