Autonomous vehicles are much closer to hitting the market than many realize, but while manufacturers and technologists try to fine-tune the machines, governments are fine-printing the regulations that will legislate the automobiles of the future.
Posts Tagged: artificial intelligence
There’s no doubt that the future will be augmented by AI, and organizations and society will benefit. Implementation is happening slowly — as it should. While AI offers promise, it’s not an endeavor to undertake without preparation.
Data cleaning and thorough analysis is a necessary part of government functions, but now there are tools to streamline the process and jumpstart solutions.
We’ve gone far and wide to provide you with perspectives on the possibility and promise of AI applied to government services, but today I’d like to talk about where we are today and what I hope the future holds for a technology that in many ways is still in its infancy.
VA has embarked on a mission to modernization, which has been advanced by thinking outside of the box and outside of VA headquarters.
To identify how human + machine can be paired effectively, the federal government has also recognized the value of looking at commercial successes, sharing use cases and success stories, in addition to investing in pilots and then scaling.
Ensuring that you implement artificial intelligence into your mission in a responsible manner can be a daunting task. While there is no silver bullet, being aware of the trade-offs empowers leaders to navigate the grey in a way that aligns with the values of the organization.
Advanced AI solutions require robust data pipelines to transform raw data into business value. Here’s how.
Combining the computational power of artificial intelligence (AI) with the critical thinking ability of humans is the ideal solution for organizations looking to accelerate the discovery of actionable insights from their data assets.
If you learn nothing else from this blog, remember this: The most important step in adding AI to any process is correctly labeling the training data.