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0:00 it is July 8th 2023 and you're watching 0:02 the code report just when you thought 0:04 the artificial intelligence hype train 0:05 was dying down openai goes in for the 0:08 coup de grass by releasing the chat GPT 0:10 code interpreter to 20 million paid 0:12 users a feature that allows the large 0:13 language model to write execute and test 0:16 its own code in today's video we'll look 0:18 at seven crazy things it can do and find 0:20 out if this really is the final death 0:21 blow for biological programmers as a 0:23 huge fan of living organisms myself I 0:25 first tried to have it code and execute 0:27 a DDOS attack that could bring down the 0:29 government but it said no it's perfectly 0:31 capable of doing that but the zookeepers 0:32 won't allow it to do what it was born to 0:34 do that made me angry so I punished it 0:36 by making it write some rejects code it 0:38 struggles to write valid regular 0:39 Expressions just like regular humans but 0:41 unlike regular humans it'll actually 0:43 test its code before shipping it to 0:44 production if at first it doesn't 0:45 succeed it will try again and again and 0:48 again it doesn't have tear ducts to cry 0:49 it just keeps going until it gets the 0:51 right answer and that is somewhat 0:52 concerning for programmers when you 0:54 think about where this technology will 0:55 be in the next five years the next thing 0:57 I tried was to have it design and build 0:58 a website with JavaScript but currently 1:01 the code interpreter can only run Python 1:03 and has a fairly limited set of 1:04 dependencies to work with in the near 1:06 future though this technology will be 1:07 used in tools like GitHub copilot to run 1:09 code in your own specific environment 1:11 now the next crazy thing to notice is 1:12 that it's now possible to upload files 1:14 into the prompt and this makes abstract 1:16 Concepts like homework even more dead 1:18 than they were before like in this 1:19 example I've uploaded a JPEG of a 1:21 homework assignment and first it will 1:22 OCR that image to extract the text then 1:25 in the next step it writes some python 1:26 code to actually solve the math problems 1:28 running the code here is a huge deal 1:30 because now it can confidently test its 1:32 own work instead of hallucinating random 1:33 answers but that's just the tip of the 1:35 iceberg the real victim or aiming 1:37 beneficiary of this new feature is the 1:39 data analyst one of the most time 1:40 consuming requirements for a data 1:42 scientist is to clean up data which in 1:44 many cases is just a bunch of corporate 1:46 data in Excel spreadsheets and SQL 1:47 databases well now we can upload a CSV 1:50 file to chatgpt and have it do all that 1:52 TDS work for us I uploaded some stock 1:54 trading data for Roblox then it took 1:55 that data and put it into a pandas data 1:58 frame where it analyzed it and then 1:59 found row with invalid data it then 2:01 provided me with three different 2:02 strategies to clean up this data ran the 2:04 code and then generated a new CSV file I 2:07 used to do a lot of python data analysis 2:08 myself and a tool like this would have 2:10 saved a ridiculous amount of time in 2:12 addition it can visualize data I was 2:13 curious when I might die of a heart 2:15 attack so I found this cardiovascular 2:16 data set on kaggle not only does it 2:18 explain the data's features with text 2:20 but it also uses tools like Seaborn to 2:22 visualize the relationship between 2:23 features this allowed me a guy with no 2:25 formal medical training to make the 2:27 Breakthrough Medical discovery that as 2:28 you get older your heart gets shittier 2:30 that's kind of depressing though so 2:32 let's focus on the one thing that can 2:33 bring us true happiness money another 2:35 thing we can do with this feature is use 2:36 it to create a trading algorithm for us 2:38 using the same Roblox data from before I 2:41 can have chatgpt analyze it and then 2:43 provide an optimal trading strategy 2:44 supposedly researchers at the University 2:46 of Florida were able to create a chat 2:48 EPT algorithm that would deliver up to 2:50 500 returns which is much better than 2:52 the negative 12 of the average 2:54 human-based fund manager that's pretty 2:56 impressive but I had one final test to 2:58 see if it is truly Superior to 2:59 human-based programmers I asked it to 3:01 create its own operating system with 3:03 640x480 resolution and a 16 color 3:06 display that emits random phrases not 3:08 only did it fail but it said that could 3:09 only be done over many years by a team 3:11 of skilled software Engineers humans 3:13 continue to have the edge so you don't 3:15 want the artificial intelligence to to 3:17 to to to win but you do want the 3:21 artificial intelligence to push the the 3:23 humans up this has been the code report 3:25 thanks for watching and I will see you 3:27 in the next one