

Does a GPT future need software engineers?
Mar 21, 2023
01:39:18
GPT-4 Augments Software Engineering
- GPT-4 and chatbots like ChatGPT are transforming how software engineering is perceived and practiced.
- They serve as powerful tools augmenting productivity rather than replacing engineers.
Family Uses GPT Creatively
- Bryan Cantrill shared how his wife uses GPT to sift through complex SEC filings, saving time.
- His son found GPT useful for learning graphics code, showing diverse helpful applications.
GPT’s Confidence vs Accuracy Conflict
- GPT can confidently produce incorrect information, especially in niche domains.
- This 'hallucination' issue challenges its reliability in specialized software engineering tasks.
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Introduction
00:00 • 2min
The Future of Chat GPT
01:46 • 5min
The Dangers of Artificial Intelligence
06:45 • 3min
How Much Time Do You Spend Reading Code?
10:07 • 3min
The Importance of Machine Learning in the Workplace
13:06 • 3min
GPT-Based Code Review
16:05 • 2min
How to Write a Process Tree With Dtrace
18:20 • 3min
The Effects of Chatbots on Language Modeling
21:13 • 2min
The Weird Effectiveness of Big Language Models
22:55 • 2min
Entropic's Reverse Engineering of the Facebook Large Language Model
24:39 • 3min
The Future of Chat GPT
27:10 • 2min
The Unhinged Conversation With Bing
28:46 • 2min
The Skepticism of Evil Aji
30:58 • 3min
The Dystopian Future of Chatbots
33:43 • 2min
The Magic Rocks and the Future
35:16 • 4min
The Economic Implications of Studying Computer Science
38:52 • 4min
The Effect of Induced Demand on Programming
42:50 • 3min
How to Engage Yourself in Hacking News
46:06 • 2min
How to Avoid Dokameneurigic Engagement Loops
47:53 • 2min
How to Use Chat GPT to Improve Your Documentation
49:51 • 5min
The Weirdness Budget Detector
54:37 • 2min
The Importance of Ergonomics in Programming
57:07 • 5min
Code Review of a Draft PR
01:02:22 • 2min
The Limits of a Finite State Machine
01:04:46 • 6min
The Importance of Optimism
01:10:33 • 4min
The Fear of Open Source Software
01:14:39 • 2min
The Importance of Constraints in Software Development
01:16:47 • 5min
The Threat of Chat GPT
01:21:20 • 2min
How Chat GPT Will Change Your Relationship With Software
01:23:48 • 2min
How to Use Chat GPT to Solve Problems
01:25:52 • 5min
The Optimism of a Robot Lawyer
01:30:42 • 3min
The Future of AI and Machine Learning
01:33:22 • 6min
Bryan and Adam and the Oxide Friends take on GPT and its implications for software engineering. Many aspiring programmers are concerned that the future of the profession is in jeopardy. Spoiler: the Oxide Friends see a bright future for human/GPT collaboration in software engineering.
We've been hosting a live show weekly on Mondays at 5p for about an hour, and recording them all; here is the recording from March 20th, 2023.
In addition to Bryan Cantrill and Adam Leventhal, speakers on MM DD included Josh Clulow, Keith Adams, Ashley Williams, and others. (Did we miss your name and/or get it wrong? Drop a PR!)
Live chat from the show (lightly edited):
- ahl: John Carmack's tweet
- ahl: ...and the discussion
- Wizord: https://twitter.com/balajis/status/1636797265317867520 (the $1M bet on BTC, I take)
- dataphract: "prompt engineering" as in "social engineering" rather than "civil engineering"
- Grevian: I was surprised at how challenging getting good prompts could be, even if I wouldn't quite label it engineering
- TronDD: https://www.aiweirdness.com/search-or-fabrication/
- MattCampbell: I tested ChatGPT in an area where I have domain expertise, and it got it very wrong.
- TronDD: Also interesting https://www.youtube.com/watch?v=jPhJbKBuNnA
- Wizord: the question is, when will it be in competition with people?
- Wizord: copilot also can review code and find bugs if you ask it in a right way
- ag_dubs: i suspect that a new job will be building tools that help make training sets better and i strongly suspect that will be a programming job. ai will need tools and data and content and there's just a whole bunch of jobs to build tools for AI instead of people
- Wizord: re "reading manual and writing DTrace scripts" I think it's possible, if done with a large enough token window.
- Wizord: (there are already examples of GPT debugging code, although trivial ones)
- flaviusb: The chat here is really interesting to me, as it seems to miss the point of the thing. ChatGPT does not and can not ever 'actually work' - and whether it works is kind of irrelevant. Like, the Jaquard Looms and Numerical Control for machining did not 'work', but that didn't stop the roll out.
- Columbus: Maybe it has read the dtrace manual 😉
- JustinAzoff: I work with a "long tail" language, and chatgpt sure is good at generating code that LOOKS like it might work, but is usually completely wrong
- clairegiordano: Some definite fans of DTrace on this show
- ag_dubs: a thing i want to chat about is how GPT can affect the "pace" of software development
- sudomateo: I also think it's a lot less than 100% of engineers that engage in code review.
- Wizord: yes, I've had some good experience with using copilot for code review
- ag_dubs: chatgpt is good at things that are already established... its not good at new things, or things that were just published
- Wizord: very few people I know use it for the purpose of comments/docs. just pure codegen/boilerplayes
- chadbrewbaker: "How would you write a process tree with dtrace?" (ChatGPT4)
- TronDD: That's interesting as expensive, specialized code analysis tools have been varying level of terrible for a long time
- JustinAzoff: I did an experiment before where I asked it to write me some php to insert a record into a database. so of course it generated code with sql injection
- chiefnoah: It's ability seems to scale with how many times someone has done the exact thing you're trying to do before
- JustinAzoff: but then I asked if sql injection was bad, which it explained that it was. then I asked if the code it wrote me was vulnerable to sql injection. it then explained it was
- Columbus: It misses empirical verification; forming a hypothesis, testing it, and learning from the result. There have been some attempts to implement this by feeding back e.g. command output into the prompt
- JustinAzoff: so then the crazy part, I asked if sql injection was bad, why did it give me code that was vulnerable to sql injection. It the went on to say that the first thing it gave me was just for example purposes
- JustinAzoff: so no wonder people get into "prompt engineering" since it's clear that you need to do things like ask for code that does something, and is secure, high performance, does not have buffer overflows or sql injection vulns
- MattCampbell: In my test case ("Write a Win32 UI Automation provider in C++"), all it did was produce plausible-sounding crap
- ag_dubs: pattern matching over very very large data sets
- clairegiordano: Bryan just said this and I wanted to write it down, re GPT-3: "the degree that it changes its answers when you tell GPT-3 to think like someone else"
- JustinAzoff: or even just, "do that, but better"
- ag_dubs: i think a lot of the awe of gpt is recognizing how simple our own strategies are instead of how complex the AI's strategy is
- chadbrewbaker: "How would Bryan Cantrill re-write this script?" (ChatGPT4)
- antranigv: that's pretty hit on!
- chiefnoah: Yup. Most people are not doing things that haven't been done before. A significant portion of software is just building blocks of libraries
- Wizord: intelligence is compression, in some sense.
- dataphract: "critique the epoll API as though you are Bryan Cantrill"
- ag_dubs: a brain would be much stranger!!
- Wizord: the ability to reduce a large dataset to a coherent set of rules
- antranigv: "Explain the issues of epoll, write as if it's a Bryan ...