Our AI writing assistant, WriteUp, can assist you in easily writing any text. Click here to experience its capabilities.

Early days of AI (and AI Hype Cycle)

View Original View Raw

Summary

This article is about the early days of AI and the AI Hype Cycle, discussing the difference between the CNN/RNN/GAN world and the new era of AI, which is marked by transformer-based and diffusion-model based approaches. It also talks about the 4 Waves of AI Adoption, which include the GenAI native companies, the early startup adopters and fast mid-market incumbents, the next wave of startups, and the first big enterprise adopters. The article ends by noting the potential of this new wave of tech to impact humanity and the fact that we are still in the very earliest days of AI.

Q&As

What is the difference between the prior ML wave and the current AI wave?
The prior ML wave was largely focused on CNN/RNN/GAN models, while the current AI wave is focused on transformer-based and diffusion-model based approaches.

What launched in June 2020 that was a major step forward for AI?
GPT-3 launched in June 2020.

How long does it usually take for enterprises to embrace new technology?
It usually takes 3-6 months for enterprises to plan and then another year to prototype and build.

What are the four waves of AI adoption?
The four waves of AI adoption are: GenAI native companies, early startup adopters and fast mid-market incumbents, the next wave of startups currently being founded, and the first big enterprise adopters.

What potential do new AI technologies have to improve humanity?
New AI technologies have the potential to improve humanity by providing better medical care, improving education, and creating new enterprise and consumer software.

AI Comments

👍 This article is very informative and gives great insight into the early days of AI and AI hype cycle. Elad Gil provides a comprehensive overview of the four waves of AI adoption and the potential of this new wave of technology to revolutionize many aspects of life.

👎 This article is overly technical and may be difficult to understand for those who are not well-versed in the AI industry. Elad Gil also makes many assumptions such as the peak of AI hype and AI usage being far away, which may not be true.

AI Discussion

Me: It's about the early days of AI and how it's different from past "AI" and how it's a new era of technology. It goes on to talk about the different waves of AI adoption that we should expect in the coming years.

Friend: Oh wow, that's really interesting. It sounds like AI is really going to revolutionize the way we do things. What do you think the implications of this are?

Me: Well, I think the implications of this are huge. AI is already having a big impact in many industries, but it is likely to become even more prominent in the coming years. It could change the way we do business, communicate, and interact with the world. It could also have a huge impact on the way we do things like healthcare, education, and transportation. It could even lead to the development of entirely new industries and products.

Action items

Research the current AI wave and the companies that are leading the charge.
Analyze the potential impact of AI on different industries and sectors.
Develop a plan to incorporate AI into your business or organization.

Technical terms

LLMs: Long-Short Term Memory, a type of artificial neural network used in deep learning.
Transformers: A type of artificial neural network used in natural language processing.
Diffusion Models: A type of artificial neural network used in machine learning.
CNN/RNN/GAN: Convolutional Neural Network, Recurrent Neural Network, and Generative Adversarial Network, all types of artificial neural networks used in deep learning.
RLHF: Reinforcement Learning with Human Feedback, a type of machine learning algorithm.
GPT-3: Generative Pre-trained Transformer 3, a type of artificial neural network used in natural language processing.
GPT-4: Generative Pre-trained Transformer 4, a type of artificial neural network used in natural language processing.
MedPaLM2: Medical Patient Language Model 2, a type of artificial neural network used in natural language processing.