Welcome to On Tech: AI. It’s a pop-up newsletter that tells you about artificial intelligence, especially new breeds of chatbots like his ChatGPT, in just five days.
We will tackle some big themes and questions about AI. By the end of the week, you’ll know enough to command the room at her dinner party or impress your co-workers.
There will be quizzes and homework every day. (Pro Tip: Ask the chatbot itself questions about how it works or about concepts you don’t understand. Answering such questions is one of the chatbot’s most useful skills. But remember they sometimes do the wrong thing.)
What is artificial intelligence?
Let’s start from the beginning.
The term “artificial intelligence” is often used to describe things that seem vaguely futuristic, such as robots, self-driving cars, and facial recognition technology.
The term was coined in the late 1950s by a group of scholars who set out to build machines that could do anything the human brain could do. Skills like reasoning, problem solving, learning new tasks, and communicating using natural language.
Progress was relatively slow until around 2012 when one idea changed the entire field.
was called neural networkIt may sound like a computerized brain, but it’s actually a mathematical system that learns skills by finding statistical patterns in vast amounts of data. For example, it can learn to recognize cats by analyzing thousands of cat photos. Neural networks enable Siri and Alexa to understand your words, identify people and objects in Google Photos, and instantly translate dozens of languages.
The following major changes: large scale language model. Around 2018, companies such as Google, Microsoft, and OpenAI began building neural networks trained on vast amounts of text from the Internet, including Wikipedia articles, e-books, and academic papers.
Somewhat to the surprise of experts, these systems have learned to write their own prose, computer code, and have sophisticated conversations.this is sometimes called Generative AI (More on this later this week.)
As a result, ChatGPT and other chatbots are about to dramatically change our daily lives. Over the next four days, we’ll discuss the technology behind these bots, help you understand their capabilities and limitations, and where they’re headed in the future.
1 week schedule
Tuesday: How do chatbots work?
Wednesday: What’s Wrong?
Thursday: How can I use them now?
Friday: Where Are They Going?
first challenge
I have homework. One of the best ways to understand AI is to use it yourself.
The first step is to sign up for these chatbots. Bing and Bard chatbots are rolling out slowly and you may need to be on a waitlist to access them. ChatGPT currently has no waitlist, but you need to set up a free account .
When you’re ready, just type a word (called a prompt) into the text box and the chatbot will reply. Try different prompts and see if you get different responses.
Challenge of the Day: Have ChatGPT or one of its competitors write you a cover letter for your dream job, such as being an astronaut for NASA.
I want to see the results! Share as a comment and see what others have submitted.
Let’s talk about chatbots
We have been covering the development of artificial intelligence for a long time and have written a recent book on the subject. But this moment feels distinctly different. Recently on Slack, the editor spoke with Adam Pasick about how we’re approaching this unique point.
Cade: The technology driving the new wave of chatbots has been percolating for years. But the release of ChatGPT really opened people’s eyes. It has sparked a new arms race across Silicon Valley. Tech giants such as Google and Meta have been reluctant to release this technology, but are now racing to compete with OpenAI.
Kevin: Yeah, that’s crazy — I feel dizzy. It’s easy to be skeptical of technology trends. Aren’t cryptocurrencies supposed to change everything? Aren’t we talking about the Metaverse? it’s different. We interviewed teachers, filmmakers, and engineers who use tools like ChatGPT every day. And it was released just four months ago.
Adam: How do you balance the excitement there while being careful about where this could go?
Cade: AI is not as powerful as it seems. If we take a step back, we find that these systems cannot perfectly reproduce our common sense and reasoning. Remember the hype about self-driving cars? Were those cars impressive? Yes, very much. Were they ready to replace human drivers? Not by a long shot.
Kevin: Tools like ChatGPT are actually more More powerful than they think. We haven’t discovered all they can do yet. And at the risk of being too existential, I’m not sure if these models work that differently from our brains. Aren’t we just predicting what will happen in
Cade: These systems mimic humans in some ways, but not in others. They demonstrate what can be called intelligence. But as the CEO of OpenAI told me, this is “alien intelligence.” Yes, they will surprise us. But they can also trick us into thinking they look more like us than they really do.
Kevin: You look like someone I know!
quiz
Question 1/3
What do we know about artificial intelligence?
Choose an answer and start the quiz.
Glossary
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neural network: A mathematical system modeled after the human brain that learns skills by finding statistical patterns in data. It consists of layers of artificial neurons. The first layer receives input data and the last layer outputs results. Even experts in creating neural networks don’t always understand what happens in between.
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Large language model: A type of neural network that learns skills such as generating prose, conducting dialogue, and writing computer code by analyzing vast amounts of text on the Internet. While their basic function is to predict the next word in a sequence, these models have learned new abilities that have surprised experts.
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Generative AI: Techniques for creating content such as text, images, videos, and computer code by identifying patterns from large amounts of training data and creating new, original material with similar properties. Examples are ChatGPT for text and DALL-E and Midjourney for images.
Click here for glossary terms.
