Make Your Own ChatGPT

👉AI was crap. What changed? [Altucher Confidential] August 16, 2023 [WEBSITE]( | [UNSUBSCRIBE]( AI was crap for a long time. Everyone realized it was just statistics. Here’s what changed. [Hero_Image] Make Your Own ChatGPT New Biden Bucks Follow-Up Available Now Hey, it’s Jim Rickards. Since posting my original Biden Bucks presentation online, millions of people have viewed it. Snopes and the Associated Press have even attempted to “fact check” me and claim my warnings are false: [Click here to learn more]( Point being, my message has raised a storm and caused a lot of controversy. But in the time between my message and now, a lot of new developments have come to light. That’s why I’ve just released an update to my original prediction… one which will likely be even more controversial. [>> Click here now to access my new 2023 Biden Bucks follow-up](. [James Altucher] JAMES ALTUCHER Dear Reader, Hey. James here. The wave of innovation surrounding AI has only just begun and I want you to be fully prepared when the wave finally hits the shore. The launch of ChatGPT at the end of last year opened the eyes of the media masses. Now a good number of the headlines revolve around AI-generated music, writing, videos, ads, software… the list goes on and on. There’s also a lot of talk about biases and regulation, and how this ground-breaking technology will affect the entire world as we know it. But to understand, let’s go back to the beginning so that we can fully understand what AI is and what it is actually capable of. Whether you’re trying to learn how to use AI or you just want a basic understanding of what the heck everyone is talking about, you need to know the basics. So let’s dive in… AI 101 Here’s how AI works in a nutshell… - Give the computer a large amount of data and label the data. - Example: here are 10,000 X-Rays of a lung. 5000 of the X-Rays are labeled “Cancer” and 5,000 are labeled “Healthy”. - Give the computer a new X-Ray and ask it: does this X-Ray show cancer or not? - The computer runs its AI software on it. It determines, given the 10,000 labeled examples, if the new X-Ray is a closer match to the 5,000 labeled “Cancer” or a closer match to the 5,000 X-rays labeled “Healthy”. - How does it do this? - It can use statistics. - It can use neural networks. The method doesn’t matter so much in basic AI. More advanced AI uses neural networks to learn and categorize patterns. The important thing is: AI does pattern recognition. It asks the question, “What does this look like that I have seen before?” And then it asks, “And given that I have seen this before, what should I then tell the user?” Computers are much better than humans at detecting cancer in an X-Ray. They are so much better, that a law was passed that says, “Human doctors are required to tell the answer to a patient.” Or else there would be no need for radiologists. [pub] Except for computer vision. Using the early techniques of speech recognition, computer vision became a big deal. One time, early on, I applied for a job at MIT Lincoln Laboratories. The task: use early computer vision techniques to determine which objects in space were junk abandoned by rockets and which objects might be guided missiles heading for the US. Later, the same technology would be used by cars doing automated driving to “see” if something was a stop sign or a little baby crawling in the street. Here’s an interesting thing: [James Altucher] You know when you log into a website and it says, “Prove you are not a bot? Click on the images that have bicycles in them?” And then eight images show up and you have to click the five that have bicycles. Guess what, the computer already knows you are a human. “Bots” have a tendency to click the exact center of an image so as soon as you click, the system knows you are imperfect enough to be a human. But when you click the five out of eight (or three out of eight or two out of eight or whatever) images that contain bicycles, your response and those images are fed into a MASSIVE database of images with the label “bicycle” or “no bicycle”. The real purpose of Captcha is not to determine if you are human or not but to label billions of images with data that are used by computer vision systems. Gotcha! Computer vision systems use neural networks. The brain works like this: You have 100 billion neurons, give or take. When you see an image, a bunch of neurons fire up. Some of those neurons are related to color (the red neurons might fire up if you see a stop sign and the blue neurons fire up if you see the sky). Some of those neurons are related to edges. When you look at the sky, the edge neurons fire up when you focus on the edge that separates the top of the trees from the beginning of the sky. They then send electrical signals to other neurons. “I just saw red! I just saw an edge!” Those neurons signal other neurons and so on. There is constant electricity going on in your brain. Eventually, enough neurons are triggered that they reach out to neurons that store all of your memories. A memory neuron might light up and say, “That looks like me! I’m a stop sign.” Neural networks work the exact same way. When a neural network is trained with labeled data (like the Captcha examples) it creates weights that link neurons together. The more data it is fed per category (a category like “red” or “bicycle”) the stronger the weights get for future inputs in that category. So it knows which neurons to signal for which patterns. This is not that important. Just think of it as advanced statistics. Now we get to ChatGPT… GOOGLE SEARCH QUERIES When you type the letter “t” into the Google search box, what comes up? If it’s the first time you are using Google, the word “the” might pop up in a menu even if you just typed in “t”. That’s because “the” is the most popular word in the English language and, of course, the most likely word you intend to type into Google once you type the letter “t”. Google then “learns” what you usually search for, what members of your house usually search for, what people in your city usually search for, etc. and they build a better AI model of how to fill out the rest of your search query. This is what comes up for me when I type in “t” right now on Google. [pub] This is basic AI using basic statistics. Crypto Bombshell Caught LIVE On Camera Crypto millionaire James Altucher recently received this mysterious package in the mail: [Click here to learn more]( [Click Here to See James Open It LIVE On Camera]( Inside is a special device that EVERY crypto investor needs in their arsenal… One that’s delivered as much as $1,170 per month or more in passive crypto income. Today, you’ll discover what this piece of equipment is, and how YOU can get your hands on one. (Plus ANOTHER very special bonus opportunity!) [Click here to watch the video](. CHATGPT [pub] Chat GPT goes several steps further. First off, very important, ChatGPT doesn’t label data (in the beginning). It uses what is called “unsupervised learning”. Imagine if you feed a computer pictures of cats and pictures of dogs. You tell the computer there are two categories but nothing else. You don’t label the pictures. Unsupervised learning is when the AI system takes these pictures and uses neural networks to determine the “distance” between one input and another. Hmm, it might say, “This picture is very different from this other picture”. One was a photo of a cat and one was a photo of a dog. Gradually it realizes that the photos of cats belong in one category and the photos of dogs belong in another category. Later, if you say, “Show me other pictures like this one” and you put in a brand new photo of your German Shepherd, it will output other photos of dogs. If it has categorized further it might show you photos of large dogs or, even further, photos of German Shepherds. This is “unsupervised learning”. Where you feed in a large amount of data and it separates the data into clusters of similar data. NOW: MAKE YOUR OWN CHATGPT: - Feed in all the text ever written. All articles, books, Wikipedia pages, tweets, reddit posts, Facebook posts, etc. - Use unsupervised learning to categorize the text into millions of clusters. - Example: the following example text appears all over the Internet. It’s the beginning lyrics of a Bob Dylan song: Early one mornin' the sun was shinin' I was layin' in bed Wondrin' if she'd [changed]( at all If her hair was [still]( red This text might be in many categories in ChatGPT: “Bob Dylan”, “hair”, “poetry”, “rhyming”, “sentences about the color red”, etc. So now if someone says, “write a unique poem in the style of Nobel Prize winner Bob Dylan”, maybe the output might be: “I was layin’ in the sun And her red was hair And she changed into a bed”. Now Supervised learning might take place at this point. Someone would have to say, “This is not good output”. So ChatGPT tries again. “Her hair was shining And her hair was red I went off to do mining Where they found me dead.” And the person doing the supervised mining might say, “That’s better.” And so on. ChatGPT took all of the text ever written before 2021 (this is called an LLM - a large language model) and then fed it into neural networks to do unsupervised learning and develop millions and millions of clusters. This took 1.5 years. Then, when asked a query, it will try to create a sentence that overlaps all or most of the clusters of the query. In other words, it asks itself, “given the clusters I’ve seen, and given a sentence that matches all of these clusters, what is the most likely next sentence?” And despite the 1.5 years of unsupervised learning, it will still mess up the outputs. So 1000s of workers (mostly workers from Kenya getting paid $2 / hour) spent the next year doing supervised learning: labeling the outputs good or bad. [ALC] (Kenyan workers working on the supervised learning part of ChatGPT) So now ChatGPT then clusters the outputs so when it has to create new outputs it tries to figure out what are good outputs vs bad outputs. Doing this gives it knowledge of context, grammar, language structure, etc. This is how ChatGPT works. So now if I give it my biography and say, “Write my resume” it understands what are important parts of my biography in terms of resume writing, what a resume looks like, what the most successful resumes look like, and it is able to write my resume. If I say, “Write an eloquent post about me” it understands what words are considered eloquent vs not-eloquent and it knows my biography and is able to write about me in an eloquent way. And so on. ChatGPT is not conscious in any way at all. It is not sentient. It never will be. It takes a set of words, figures out all the contexts for that set of words, and determines the most likely response to that set of words, given all the contexts. That’s it. It knows nothing. It just figures out probabilities of what words appear next. Just like the Google Search Query system except a billion times more data and clusters. Investing in AI? That’s a tricky one. There’s a lot of hype. If you’ve considered getting into AI stocks yourself (or if you already own some), then I urge you to watch [my quick AI warning]( right away… [pub] I’ve been closely working on AI technology since 1988. And today, with AI growing in popularity among investors, I’m sounding the alarms… Because if you follow the crowd and buy the most popular AI stocks (such as NVIDIA), you might be leaving a lot of money on the table. [I’ve discovered a secret strategy to profit from the rise of AI that not 1 in 1,000,000 people are aware of.]( Like all things, it won’t last. So act quick! Best, [James Altucher] James Altucher For Altucher Confidential [( P.S. By the way, at a website I created, notepd.com, I fed in about 1000 of my articles and created an AI James. [pub] Warning: Will “Bidenflation” Destroy Your Retirement? [James Altucher]( If you’re like most Americans, you’ve worked hard for decades to build your financial legacy. And now, as a result of Biden’s disastrous money printing policies, that’s all at risk. According to one top retirement expert, “Bidenflation” threatens to destroy your retirement and make your hard-earned savings worthless. That’s why you must take action right away to protect yourself… [Click here now to get the simple, step-by-step actions to survive “Bidenflation.”]( [Paradigm]( ☰ ⊗ [ARCHIVE]( [ABOUT]( [Contact Us]( © 2023 Paradigm Press, LLC. 808 Saint Paul Street, Baltimore MD 21202. By submitting your email address, you consent to Paradigm Press, LLC. delivering daily email issues and advertisements. 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