The Great Irony
2,078 karma · joined April 2, 2020
https://twitter.com/jeremybernier
Personal Site https://www.jbernier.com
Some personal projects:
• Open source offline-first Notion clone - https://mindgarden.app (work in progress)
• https://zsync.xyz, an attempt at a better Hacker News / Reddit
• https://nomadz.app, a crowdsourced site for useful places for nomads and remote workers, specifically work cafes.
Other social media:
https://www.youtube.com/c/JDiculous1 https://www.instagram.com/cityofjeremy
Posts here don't necessarily reflect my views as I may steelman an argument for the sake of greater understanding.
The Great Irony
Hard to take anything the author says seriously making nonsensical claims like this. The software engineering job market has been getting worse every year since 2022 by virtually every metric. This is especially true at the entry and mid level. For example, computer engineering and computer science majors now have the #2 and #4 highest unemployment rates amongst recent graduates [1]
Students are smart to be cautious about the future, and it's annoying that adults with no skin in the game so flippantly dismiss these concerns without any data to back it up.
[1] https://www.newyorkfed.org/research/college-labor-market?utm...
I do think it's a good experience to try either way since the challenges are so different from that of startups. These large multinationals look for different skills some of which you can't really develop at startups.
And the money doesn't hurt.
Behavioral interviews are actually my least favorite and I have no idea why I'm not passing them. Either my experience is not good enough, or I'm not presenting it well enough.
Anyways to anyone struggling out there - hang in there. Remember that all it takes is one offer to be employed.
Don't forget disability insurance, which is massively abused, functions like a UBI
I don't think most people are building landing pages anymore by handwriting code anymore. Same with blogs (eg. Wordpress). There are MVPs of successful businesses that've been built by Bubble.io. Internal dashboards and such can definitely be built without code such as via Retool or Looker or whatever.
WYSIWYG obviously makes sense for frontend, but less so for backend. For backend code I don't really see how some visual drag and drop editor could make for a better interface than code. And even if it could, the advantage of code is that it's fully customizable (whereas with a GUI you're limited by the GUI), and text itself as a medium is uniform and portable (eg. easy to copy and paste anywhere).
Not to say that we can't create better interfaces than text, but I do think some sort of augmentation on top of a code editor is probably a more realistic short-term evolution, similar to VSCode plugins.
Some suggestions though:
- Would be awesome to be able to open an existing animation (eg. like any of the ones showcased). It's a built overwhelming for a noobie opening up to a blank editor page.
- Could also consider putting a tutorial video
Anyways I'll have to play around with this.
For example I've noticed that a lot of the time when I ask ChatGPT a coding question it might get 90% of the answer. When I tell it what to fix and/or add, it usually gets the answer. I wonder if they're using these refined answers to fine-tune those original prompts.
I wonder how the LLM interacts with other software like the calculator or Python interpreter. It would be great if this were modular so that the LLM OS could be more like Unix than Windows which is what OpenAI seems to be trying to emulate.
Ultimately though it seems to me like AGI is fairly straightforward from here. Just train on more quality data - in particular enabling the machine to generate this training data, increase parameter size, and the LLM just gets better and better. Seems like we don't even need any new major breakthroughs to create something resembling AGI.
There are obviously legitimate risks to AI and safety is important, but this is the same for any new technology, and it's governments' responsibilities to ensure that people are safe. AI companies mindlessly slowing down and keeping their tech to themselves does no service to humanity, and if anything is a net-negative due to how tremendously useful this stuff is.
Education is analogous to AI because AI is an enormous education and productivity boost to humanity - sort of like everyone having a personal assistant, programmer, and tutor at their fingertips. This could be used for good and it could be used for bad, but the technology itself is neutral.
Again I want to emphasize that obviously there are downsides that could result from evil people using AI for bad purposes, but that does not justify slowing down AI progress - just like I don't see "people using information for bad purposes" as a legitimate reason for stifling advancement in education or something like Google search.
I have yet to see any convincing argument otherwise. Feel free to provide your counter-perspective.
This AI doomer stuff is such nonsense and I can't believe anybody takes it seriously. As if it's OpenAI's responsibility to save humanity from the pitfalls of AI.
Imagine if we decided to improve our education system and doomers were talking about "hitting the panic button" because students were getting too smart from all the quality education.
The management and bureaucracy depicted in the article sound like a corporate nightmare and unappealing place to work. I didn't know that Google had non-engineers running dev tool teams. Can this VP even reverse a linked list? /s
Seems like Google needs a change in leadership, starting with replacing CEO Sundar Pichar.
Shame because Google invented the transformer architecture that enabled the technology.
People here used to back up their bold claims with arguments.
Adam Grant - Hidden Potential
> We then used the location of the images as the output data and the screenshot of the webpage as the input data. And now we have exactly what we need — a source image and coordinates of where all the sub-images are to train this AI model."
I don't quite understand this part. How does this lead to a model that can generate code from a UI?