In recent years, artificial intelligence (AI) has made incredible strides. We’ve seen AIs that can beat humans at games like Go and chess, and there are now many applications of AI in our everyday lives, from Amazon’s Alexa to self-driving cars. However, these are all examples of narrow AI, which is AI that is designed to accomplish a specific task.
Artificial general intelligence (AGI), on the other hand, is AI that can accomplish any task that a human can. And according to many AI researchers, we’re not far off from achieving AGI.
In fact, some researchers believe that AGI may even be inevitable. Once we create an AI that can outperform humans in one domain, it will be only a matter of time before that AI is able to learn how to do everything else that humans can do. This may sound like science fiction, but many AI experts believe it is only a matter of time before AGI is achieved.
However, in a recent op-ed published by TheNextWeb, columnist Tristan Greene expressed skepticism on the advancement of AI, arguing that despite the impressive progress made in machine learning over the past decades, human-level artificial intelligence won’t be achieved within our lifetimes.
But in a response on Twitter, Google DeepMind lead researcher Dr. Nando de Freitas took a diametrically opposing view, boldly declaring that “the game is over” and that AGI is within our reach. De Freitas’ argument was based on the notion that AI will continue to improve as we increase its scale and scope.
Someone’s opinion article. My opinion: It’s all about scale now! The Game is Over! It’s about making these models bigger, safer, compute efficient, faster at sampling, smarter memory, more modalities, INNOVATIVE DATA, on/offline, … 1/N https://t.co/UJxSLZGc71
— Nando de Freitas 🏳️🌈 (@NandoDF) May 14, 2022
“Solving these scaling challenges is what will deliver AGI,” De Freitas tweeted, noting in a later comment that OpenAI Chief Scientist Ilya Sutskever, “is right” to claim that some large neural networks may already by “slightly conscious.”
it may be that today's large neural networks are slightly conscious
— Ilya Sutskever (@ilyasut) February 9, 2022
While Greene’s article raised some valid concerns, De Freitas’ response offers a much more hopeful perspective on the advancement of AI. As we continue to develop this technology, it is important to keep an open mind about its potential and its place in our future.
It seems almost inevitable at this point that sooner or later, we will create an AI – obviously, with the right safety protocols in place – that can think and learn like a human, and when we do, the sky’s the limit.
We should embrace this future rather than fear it.
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