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I mean, we already have? Use Django Rest Framework and simple business models and you're pretty much declaratively writing API endpoints by composing behavior.

Almost nothing in a DRF endpoint definition is boilerplate. The hard part has always been writing an API that models external behavior correctly. Will this tend to blur the distinction between coder and manager? In the end a manager is just a coder who commands more resources, and relies more on natural language to do it.

Or maybe I'm thinking of tech leads. I don't know, my org is flat. Issue is not writing code. Its changing, evolving or maintaining it. This is the problem with things like Spreadsheets, dag-drop programming, code generators.

Its not easy to tell a program what to change and where to change. I feel like you might be moving the goalposts. Maybe they're different problems, but it's not at all clear to me that mutation is harder than creation. Animats 4 months ago root parent prev next [—]. This is the opposite of what most people including me expected, and will have strange effects" I've been saying something like that for a while, but my form was "If everything you do goes in and out over a wire, you can be replaced.

A question I've been asking for a few years, pre-pandemic, is, when do we reach "peak office"? Post-pandemic, we probably already have. This has huge implications for commercial real estate, and, indeed, cities. I just don't believe it. Having experienced terrible cheap outsourced support and things like Microsoft's troubleshooting assistant also terrible , I'm willing to pay for quality human professionals.

They have a long way to go before I change my mind. I've found that people who tend to describe their occupation as "knowledge work" are the most blind to the fact that white collar jobs are the first to get optimized away. Lawyers are going to have a really bad time after somebody manages to bridge NLP and formal logic. No, it won't result in a Lawyerbot - it will result in software that enables lawyers to do orders of magnitude more work of a higher quality. What do you think that does to a labor market?

It shrinks it. That or people fill the labor glut with new, cheaper, lawsuits MichaelMoser 4 months ago root parent next [—]. But yes, getting some kind of legal opinion will probably be cheaper with an AI. Nor I, which is why I said so. A SaaS will pop up called "Co-chair" and that'll be that.

It would definitely be a lot easier to trust than any of the black box neural networks we are all familiar with - as the field of formal logic is thousands of years old and pretty thoroughly explored. I used a SAT solver just last night to generate an exhaustive list of input values that result in a specific failure mode for some code I'm reverse engineering - I have no doubts about the answer the SAT solver provided.

That definitely isn't the case with NN based solutions - which I trust to classify cat photos, but not much else.

Legal discovery and other "menial" law tasks are already quite automated. I wouldn't describe keyword search engines or cross reference managers as "quite automated" - so I would expect little market change from whatever LexisNexis is currently selling. I would -- I remember my mom as a lawyer having to schlep to the UCLA law library to photocopy stuff -- but current legal automation includes NLP at the level of individual clauses.

Oof, as somebody who has studied the AI winter - that article hurt, suggesting that an unsupervised NN-centric approach is going to lead somewhere other than tool-assist What would you call it when NLP results are fed into an inference engine that then actually executes actions - instead of just providing summarized search results? Super-duper automation? I kinda believe this but I still think it hugely depends on what you're doing in front of a computer.

If you're just a generic developer that gets a task and codes it by the spec, then you can probably be replaced by AI in a few years. People have been saying AI would end everything and anything since I was a wee baby. It still hasn't happened. How about instead of making the same old tired boring predictions about the impending apocalypse of things we love we start making and listening to predictions that actually talk about how life has been observed to progress. It's not impossible, science-fiction authors get it right occasionally.

As it stands, this looks like it will actually increase the productivity of existing programmers more than it will result in "now everyone is a programmer". Over time it will certainly do more, but it's probably quite a long time before it can be completely unsupervised, and in the meantime it's increasing the output of programmers.

Honestly, the only reason I'm still doing work in front of a computer is that it pays well. I'm really starting to think I should have followed my gut instincts when I was 17 and go to trade school to become an electrician or a carpenter True self-improving general AI would put all labor out of business. Incomes would then be determined by only the ownership of capital and government redistribution.

Could be heaven, could be hell. Any work that does not see a productivity increase becomes comparatively more expensive over time. So either his prediction or expectation will be correct. I wonder does Sam Altman also believe that you can measure programmer productivity by lines-of-code? Don't hold your breath. Coming soon right after the flying self-driving car. Joeri 4 months ago root parent prev next [—]. Automation has always produced an increase in jobs so far, although sometimes in a disruptive way.

If anything this will probably lead to a boom in development work. Those people will have to level up or get out. I feel like the inevitable path will be: 1 AI makes really good code completion to make juniors way more productive. Senior devs benefit as well. This creates a talent pipeline shortage and screws over generations that want to become devs, but we find ways to deal with it.

The line between BA and programmer blurs until everyone's basically a BA, telling the computer what kind of code it wants. The thing though that many fail to recognize about technology is that while advances like this happen, sometimes technology seems to stall for DECADES. I could also see an alternative to 2 where it becomes increasingly hard to get a job as a senior dev when companies can just hire juniors to produce probably-good code and slightly more QA to ensure correctness.

You'd definitely still need some seniors in this scenario, but it feels possible that tooling like this might reduce their value-per-cost and have the opposite effect on a larger pool of juniors. As another comment said here, "if you can generate great python code but can't upgrade the EC2 instance when it runs out of memory, you haven't replaced developers; you've just freed up more of their time" paraphrased. No, programmers won't be replaced, we'll just add this to our toolbox.

Every time our productivity increased we found new ways to spend it. There's no limit to our wants. The famous 10 hour work week right? I am orders of magnitude more productive than my peers 50 years ago wrt programming scope and complexity, yet we work the same 40 hour week. I live in a foreign country and study the language here.

I frequently use machine translation to validate my my own translations, read menus with the Google Translate augmented reality camera, and chat with friends when I'm too busy to manually look up the words I don't understand in a dictionary. What I have learned is that machine translations are extremely helpful in a pinch, but often, a tiny adjustment in syntax, adding an adjective, or other minor edit like that will produce a sentence in English with entirely different meaning.

For context-specific questions it's even worse. The other day a stop owner that sells coffee beans insisted that we try out conversing with Google translate. I was trying to find the specific terms for natural, honey, and washed process.

My Chinese is okay, but there's no way to know vocab like that unless you specifically look it up and learn it. Anyway, I felt pressured to go through with the Google translate charade even though I knew how the conversation would go. I said I wanted to know if this coffee was natural process.

His reply was 'of course all of our coffees are natural with no added chemicals! AI is no replacement for learning the language.

State of the art image classification still classifies black people as gorillas [1]. I rue the day we end up with AI-generated operating systems that no one really understands how or why they do what they do, but when it gives you a weird result, you just jiggle a few things and let it try again. To me, that sounds like stage 4 in your list.

We have black box devices that usually do what we want, but are completely opaque, may replicate glitchy or biased behaviors that it was trained on, and when it goes wrong it will be infuriating. CRConrad 4 months ago root parent next [—]. Does "natural process" have a Wikipedia page? I've found that for many concepts especially multi-word ones , where the corresponding name in the other language isn't necessarily a literal translation of the word s , the best way to find the actual correct term is to look it up on Wikipedia, then see if there is a link under "Other languages".

Looks like in this case it's only part of a Wikipedia page[0] but the Chinese edition is only a stub page. But your suggestion is absolutely spot-on.

One of the things I love about Wikipedia is that it's human-curated for human evaluation, not a "knowledge engine" that produces wonky results.

I feel like you're neglecting to mention all the people who need to build and maintain this AI. Cookie cutter business logic will no longer need programmers but there will be more highly skilled jobs to keep building and improving the AI.

AI will keep building and improving the AI, of course! But you need orders of magnitude fewer people to build and maintain the AIs then you do to manually create all the software running the world. And this is the unique peril of AI. The scale of capabilities of AI have the promise to grow faster than the creation of new classes jobs.

Telling the computer what you want IS programming Hammershaft 4 months ago root parent prev next [—]. It seems to me automation has been shifting the demand recently towards more skilled cognitive work. I think you are confusing correlation and causation. Not automation produces jobs, more people and more income for that people produces jobs, because more people means more demand. Yes, but AI isn't the same as automation. Automation is a force multiplier.

AI is a cheaper way of doing what humans do. And the AI doesn't even need to be "true" AI. It simply needs to be able to do stuff better than what humans do.

Like protein solving? MichaelMoser 4 months ago root parent prev next [—]. Take the job of a translator, you would say the job would go extinct with all the advances in autotranslation? You still need a human being to clear up all of the ambiguities of languages. Maybe the focus of the stuff we do will change, though; but on the other hand, we do tend to get a lots of changes in programming; it goes with the job.

However, within a decade it might be harder to get an entry level job as a programmer. I am not quite sure if i should suggest my profession to my kids, we might get a more competitive environment in some not so distant future.

Only for the first time to train a model for that. The next skill will be perfectly casting the right spell to make the AI spit out the product as spec'd. Repurposed Google-fu. We'll always have jobs :. Nah, we will just all be low-code function couplers instead of coders.. On the contrary. This tool increase the programmer productivity, hence you will get more salary not less. You assumption is that programming demand is finite, AND that all programmers are equal, both of those are false.

With VSCode, Github and a perhaps a little bit of help from OpenAI, Microsoft is poised to dominate the developer productivity tools market in the near future. I wouldn't be surprised to see really good static analysis and automated code review tools coming out of these teams very soon.

And still Windows is a mess. GuB 4 months ago root parent next [—]. Windows is a mess and I hope it will stay that way. The real strength of Windows is backwards compatibility, especially dealing with proprietary software.

And it does without containers or full VMs. I much prefer developing on Linux I still miss the Visual Studio debugger , but different platform, different philosophy. Note: I don't know much about mainframes. I heard they really are the champions of backwards compatibility.

But I don't think the same principles are applicable to consumer machines. Your 20 year old statically compiled binary still works on Linux, probably. I've been on both Windows and Ubuntu for a while. I'd say Ubuntu has a ton more issues and requires a ton more initial configuration to behave "normally". I don't even remember the last time Windows got in my way, in fact. I guess the difference is that you can put in a weekend of effort on an Arch Linux installation and get a machine tailored to your workflow, few bugs, fast boot times, easy to maintain for the future, etc.

I think what escapes HN is how massively successful Microsoft is. Sure, the search built into Windows sucks. There are many, many more complicated components of a platform and OS than that, and those seem to work as well as any other platform and OS. Compared to what other operating system s? Now imagine how amazing it would be just on Ubuntu ;-. The problem is that not many IT departments support ubuntu. They are making lots of improvements to the UI and application management, but it can be cumbersome to get some applications working on linux.

Having windows to install whatever gui apps you need or whatever other apps that aren't needed in linux, then having linux there to develop on has been pretty great.

I am biased towards linux though since I'm an sre, so maybe that is why I never could quite get comfortable on osx. I really disliked having to learn how to do something once on a mac, then do that same thing again on linux to get something into production. For enterprise adoption of Ubuntu, Ubuntu I wonder how does it help. Every other OS. Every release is like two steps one step forward, one step back and one two the side.

Just because thousands of companies have written software and drivers for it, it's still existing. If it were released today it wouldn't stand a chance.

Are you talking about developing for windows or developing on windows? I'm talking about developing on windows.

I don't really care what the apis look like underneath it all. WSL was slower than dialup internet last I used it IMO a lot of what Windows does isn't something you can apply Copilot-style tech to. The only thing you could train it on would be Windows, really.

Have you used any intelligent code completion in the past? I'd really be interested how it compares to TabNine[0], which already gives pretty amazing single line suggestions haven't tried their experimental multi-line suggestions yet.

Interestingly the founder of TabNine which was acquired by Codota[0] is currently working at Open AI edit: comments corrected me he left in December according to his blog. I imagine they're livid about Open AI creating a competing product. Ah, thanks for the insight! It seems though that he is no longer working with OpenAI according to his personal website[0]. I'm curious as to how relevant Copilot would be when autocompleting code that is specific to my codebase in particular, like Tabnine completes most used filters as soon as I type the db table name for the query.

I'm a big tabnine fan because it provides this feature. I'm much more often looking to be suggested a line than an entire function because I'm mostly writing business logic. Yeah, I've been very happy with Tabnine for a while, but the prospect of good multi-line completions is appealing.

I've been using TabNine for a couple years — constantly impresses me, especially how quickly it picks up new patterns. I wouldn't say it's doing my job for me, but definitely saves me a lot of time. I have used IDEs with good knowledge of the types and libraries I'm using e. VSCode with TypeScript. They offer good suggestions once you start typing a function name. But nothing gets close to Copilot. It "understands" what you're trying to do, and writes the code for you.

It makes type-based autocompletions useless. I tried out TabNine. It was a very frustrating experience. In almost all cases it gave completely useless suggestions which overrode the better ones already suggested by IntelliJ. I persevered for a few days and then uninstalled it. Maybe it's just because humans are not as creative as they think. Whatever you do, thousands of others have done the same already. So no need to pay a high level programmer, just a mediocre one and the right AI assistant gives the same results.

With an AI assistant, in the best scenario, you'll get a "wisdom of crowds" effect on implementation details and program architecture. At worst, you'll get a lot of opinionated code bloat and anti-patterns as suggestions. For most backend programming jobs, the challenge is not in writing complex code but figuring out what the business wants, needs and should have in the first place and distinguishing between them.

Figuring out how to integrate with existing systems, processes, fiefdoms and code. Knowing when to say yes and no, how to make code future proof, etc. This is a task fundamentally unfit for what we currently call "AI", because it's not actually intelligent or creative yet. On the frontend, it becomes even more nebulous.

Maybe Copilot can suggest common themes like Bootstrap classes for a form, CSS properties, the basic file structure and implementations for components in an SPA, etc. As I see it, the main challenge is in UX there, not the boilerplate, which again makes it about understanding the user, figuring out how to make UI feel intuitive, etc. Again: unfit for current AI. I cannot offer any opinion on the utility for actually complex, FANG-level code, for lack of experience.

Quite the opposite. Menial work will be automated away e. CRUD and only good programmers will be needed to do the more complicated work. I think of it as not needing juniors for boring work, all you need as a company is seniors and AI. So where do these seniors come from?

Dylan 4 months ago root parent prev next [—]. Maybe programmers will adopt a similar model to artists and musicians. That is already the recommendation. Pick an open source project and contribute. And most people who consider the job are driven away by the economics of it. IshKebab 4 months ago root parent prev next [—]. I think it's more that this tool is only capable of automating the non-creative work that thousands have done already.

It's still insanely impressive assuming the examples aren't more cherry picked than I'd expect. Side note: I recently suffered from a tennis elbow due to sub optimal desktop setup when working from home.

Copilot has drastically reduced my keystrokes, and therefore the strain on my tenders. It's good for our health, too! I watched the same thing happen with the introduction of Intellisense. Pre-Intellisense I had tons of RSI problems and had to use funky ergonomic keyboards like the Kinesis keyboard to function as a dev. Now I just hop on whatever laptop is in front of me and code.

Same reason - massive reduction in the number of keys I have to touch to produce a line of code. Unfortunately, one in 10 times is far from good enough and this is with good prompt engineering which after using large language models for a while, one starts to do.

The self-driving industry is in a similar situation of despair where millions have been spent in labelling and training but something fundamental is amiss in the ML models. You are correct. I feel this is why the service is called Copilot, not Pilot :. If it holds up it means they may have found the right prior for a path of development that can actually lead to artificial general intelligence.

With exponential improvement; humans learning to hack the AI and the AI learning better suggestions, this may in theory happen very quickly. We live in a very small corner of the space of possible universes, which is why finding a prior in program space within it is a big deal.

I keep wondering how much time it could possibly save you, given that you're obligated to read the code and make sure it makes sense. Given that, the testimonials here are very surprising to me. Which of course is super cool for many tasks!

It's smarter than that. It suggests things that have never been written. His passion to spread the ethical hacking ways is clear from his teaching in the courses. If you are also looking to improve your skills and knowledge from any of IT, infrastructure, DevOps, student, platform or application support backgrounds you will find something useful from Hacker House. My primary interest was more defensive. The review: In general, the course content was excellent.

Matthew was helpful, very knowledgeable and very good at explaining the concepts. What I really found incredibly motivating was seeing the whole context of a hack.

The only downside was that the course was too quick for me at times. After all you want to maximise learning about hacking and not how the Linux file system works.

I also felt some of the written documentation needed to be a little more idiot-friendly and easier to cut and paste if you get stuck. So, 4 stars and of 5 for me.

Hacker House helped me to understand how hacking works. When I wanted to get into security, I tried learning on my own using YouTube, books and some online courses. But I struggled to find the time to focus and build a good cadence for learning. I also missed having someone to ask questions to.

So I chose to do an on-site course and found Hacker House. The course was everything I had hoped for. The materials were relevant and offered a great foundation for understanding tooling, methodology and the mindset for pentesting.

And the instructor, Mathew, was phenomenal. The course gave me the knowledge I needed to understand how hacking happens and how to position myself to continue learning new techniques. I highly recommend Hacker House for their quality and commitment to helping their students be successful. Great intro so far to pentesting methodologies, I'm only a week in but have found the first two modules to be very informative without bogging down or injecting a bunch of unneeded fluff to expand content.

Hands-on-Hacking course from Hacker House should become the next industry recognised standard. So far it's the most practically applicable course I had for IT security. Recommended it to all my colleagues. The best hands-on training I have found so far!

I have learned more through this course using the online material on my own machine and my own time, than any classroom environment I have been in. Great Job!!! We use cookies to understand how you use our site and to improve your browsing experience.

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