The Mind’s Mirror Review Part Two: Fundamentals

Q: How long will it take to read this news story?

The story "The Mind’s Mirror Review Part Two: Fundamentals" has 1164 words across 50 sentences, which will take approximately 5 - 10 minutes for the average person to read.

Q: Which news outlet covered this story?

The story "The Mind’s Mirror Review Part Two: Fundamentals" was covered 18 hours ago by Forbes, a news publisher based in United States.

Q: How trustworthy is 'Forbes' news outlet?

Forbes is a fully independent (privately-owned) news outlet established in 1917 that covers mostly startups and technology news. The outlet is headquartered in United States and publishes an average of 52 news stories per day. It's most recent story was published 12 hours ago.

Q: What do people currently think of this news story?

The sentiment for this story is currently Negative, indicating that people regard this as "bad news".

Q: How do I report this news for inaccuracy?

You can report an inaccurate news publication to us via our contact page. Please also include the news #ID number and the URL to this story.<ul><li>News ID: #22998099</li><li>URL: https://beamstart.com/news/the-minds-mirror-review-part-17286562336878</li></ul>

Forbes Logo Forbes 18h ago

The Mind’s Mirror Review Part Two: Fundamentals - Forbes

Quick Summary:

In enterprise, it’s common to talk about these solutions as ‘decision support’ software.“The final judgment should fall to people, not algorithms,” she writes.

Finally, Rus ends with a case in healthcare that brings value.“This would not only demonstrate the effective practical application of AI, but reflect positively on everyone involved,” she writes, “from the manager or executive leaders who approve the project to the medical professionals who use the tool to improve patient care.

Mentioning the use of good old-fashioned AI or GOFAI, she covers many of the emerging classification tools and methods like reinforcement learning that drive ever more elegant machines – random forest algorithms, and decision trees, or Bayesian networks.