Social Media Companies Remind Us It Is Still Hard To Replace Humans With AI

  • 📰 Forbes
  • ⏱ Reading Time:
  • 62 sec. here
  • 3 min. at publisher
  • 📊 Quality Score:
  • News: 28%
  • Publisher: 53%

Italia Notizia Notizia

Italia Ultime Notizie,Italia Notizie

As Silicon Valley rushes us forward towards our AI future, even it is hiring armies of humans to work alongside those algorithms. Our automated future will look a lot less like robots replacing humans and a lot more like symbiotic workforces blending the best of both our worlds.

Companies have rushed to embrace deep learning’s potential in their efforts to automate their enterprises, often with an eye towards replacing as much of their human workforce as possible or to scale their operations without expanding their hiring. An endless stream of success stories tout AI’s success in replacing an ever-growing array of traditionally automation-resistant jobs, while developers are hard at work finding ways to replace the rest of them.

Facebook represents this contradiction. While publicly touting the company’s AI-driven future and investing heavily in building a world-class AI research staff, the company is also rapidly hiring human content moderators. Even as the company increasingly deploys AI algorithms to moderate speech on its platform, it has more than 15,000 community operations staff and growing.

Much like an infant’s simplest movements spark wonderment in new parents, so too do the most basic of AI accomplishments give rise to an image of intelligent machines just around the corner. The simple fact is that while impressive compared to past algorithmic approaches, today’s most advanced AI systems remain primitive compared to even the youngest human child.

Content understanding showcases both deep learning’s greatest strengths and its greatest weaknesses. Today’s algorithms are light years ahead of where they were just a decade ago, yet at the same time, they struggle immensely to cope with the complexities of human discourse. Machines still see imagery largely through the lens of metadata subject tags applied through classifiers, while textual posts are understood through similar classification or simple embeddings.

Abbiamo riassunto questa notizia in modo che tu possa leggerla velocemente. Se sei interessato alla notizia puoi leggere il testo completo qui. Leggi di più:

 /  🏆 394. in İT
 

Grazie per il tuo commento. Il tuo commento verrà pubblicato dopo essere stato esaminato.

Italia Ultime Notizie, Italia Notizie

Similar News:Puoi anche leggere notizie simili a questa che abbiamo raccolto da altre fonti di notizie.

Can Social Media Companies Detect Future Mass Shooters?Trump has called for such initiatives, though he didn't specify what they would be.
Fonte: papermagazine - 🏆 409. / 53 Leggi di più »