menu
techminis

A naukri.com initiative

google-web-stories
Home

>

Data Science News

>

Is It Too ...
source image

Analyticsindiamag

1d

read

309

img
dot

Image Credit: Analyticsindiamag

Is It Too Soon to Talk About AGI and Regulation?

  • AGI (artificial general intelligence) is a leap forward in mimicking the cognitive abilities of the human brain and bridging the gap between human and machine intelligence. However, the means to AGI and its regulation remain a topic of debate amongst experts.
  • Many AI systems have evolved from deep learning to LLMs (large language models), enabling accessible and democratic AI technology. However, the role of LLMs as a pathway to AGI has been a controversial topic.
  • AGI is designed to execute tasks autonomously, enabling systems to learn effectively and behave like humans. This evokes the question of singularity where machine intelligence can surpass human intelligence.
  • AGI's practical applications in healthcare offer unique solutions for disease management, but the development of AGI must go hand-in-hand with governance models to ensure ethical deployment and alignment with human values.
  • India as a hub of AI innovation needs to adopt a flexible regulatory framework that allows innovation to thrive while upholding foundational principles of human-centricity, accountability, and fairness.
  • Experts believe a proactive governance model, where startups and enterprises incorporate ethical practices by default, would be more effective in enabling innovation while ensuring compliance with ethical standards.
  • Regulators, innovators, and all stakeholders' collaboration is essential for establishing trust and preemptively addressing potential pitfalls, ensuring AGI serves humanity positively.
  • Time will tell if AGI is achievable, but current progress in the field proves that responsible AI deployment and regulation should be key objectives in creating a future where innovation and responsibility coexist.
  • Experts advise that everyone involved in regulating AI technology should deploy an ML model, sit with someone, or at least know how to deploy it.

Read Full Article

like

18 Likes

For uninterrupted reading, download the app