machine learning
 |
The AI Testing Singularity Machine learning is rapidly growing more powerful, already sometimes imitating the actions and judgments of humans better than humans. In the near future, even before machines are conscious, they will be able to mimic human software testers. What will be the impact of AI on testing? Jason Arbon has a bunch of ideas. |
|
 |
Saving Birdsong: Using Machine Learning to Monitor Kiwi Birds and Possums In an attempt to turn birdsong and predator monitoring into data that can help improve pest trapping ability, the Cacophony Project is an open-source conservation project employing technologies such as embedded systems, web applications, backend services, and machine learning pipelines. |
|
 |
What’s Our Job When the Machines Do Testing? It’s a safe bet that testing jobs won't be taken over by machines anytime soon. However, those of us in the test industry would be wise to heed cross-industry applications of analytics and machine learning and begin staking out the proper role of the machine in our testing domain. What could AI mean for testing? |
|
 |
Keeping Your Software Testing Abilities Relevant Today, Tomorrow, and Beyond Development and product teams have embraced agile and DevOps. What can testers do to keep up with their development peers? Here are some ideas about what testers can learn, what skills we can add, and what processes we can start doing in order to continue delivering quality today, tomorrow, and further into the future. |
|
 |
IBM’s Watson Will Help You File Your Taxes at H&R Block Customers at H&R Block will be able to get tax advice from IBM’s famous supercomputer, Watson. Watson has been fed all 74,000 pages of the US tax code and will use its natural language processing to interact with clients in order to answer questions, uncover deductions and credits, and help calculate refunds. |
