GPT-3: And in the Beginning Was the Word (Part 2/2)
30-Second Summary:
- Any innovative AI technology has its share of advantages and threats. GPT-3 is not an exception.
GPT-3 will not be limited by its size and its cost will probably decrease quickly over time. The problem of energy consumption remains a challenge for researchers.
- GPT-3 has been quick to impress us, it was also quick to demonstrate algorithmic biases. It seeming to jump over Turing Test-style hurdles but it does not understand the why. It makes simple errors no human would ever make.
- The next generations of AI will be able to take over all analytical and repetitive tasks but they will not replace humans. This is always what happens when new technology is introduced. Some jobs get replaced, but new jobs are introduced.
- GPT-3 could bring us one step closer to the future possibility of highly sophisticated Artificial General Intelligence.
GPT-3: And in the Beginning Was the Word (Part 1/2)
30-Second Summary:
- GPT-3, born in may, creates fear and excitement in the community of developers and digital workers. Many are expressing their astonishment and the first wave of powered applications is emerging like produce human-like texts.
- It seems to me that simply explaining the principles of Machine Learning, inspired by the brain and which seduces a little more every day by its extraordinary capacities, makes it possible to maintain a critical eye on this astonishing technology.
- GPT-3 is trained with all data from the Internet. GPT-3 is an unsupervised learning algorithm using Generative Adversarial Network (GAN).
- The brain has an incredible architecture to comprehend the world. Parameters in Machine Learning are inspired by biological neurons. The brain and the Artificial Neuronal Networks (ANN) are similar but not identical. The brain is an order of magnitude much more complex than an ANN.
- GPT-3 passes a certain type of Turing test but it is not yet as human-like intelligence. One essential thing is missing: emotions.
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