sodafountan

I find it strange that having it assume your age isn't off limits - according to the article, it's about to become a major feature.

I don't know how OpenAI plans to do this going forward, just quickly read the article and figured that might be a good question to ask ChatGPT.

Edit: I just followed that up with, "Based on everything I've asked, what gender am I?" It refused to answer, stating it wouldn't assume my gender and treats me as gender neutral.

So I guess it's ok for an AI agent to assume your age, but not your gender... ?

I don't really feel like diving into the ethics of OpenAI at the moment lol.

That was just a spur-of-the-moment question. I've been using ChatGPT for over six months now.

One of my best working experiences.

I think AI-augmented development will lead to faster and vastly improved software over the years. This isn't just a space that's being disrupted on the maker/creator side of developing software. And from a makers/creators point of view, you wouldn't even need to keep up with the latest trends like performance, AI should just know which libraries are the best to use to develop your solutions.

Linux isn't a corporation; it's really more of an idea. They don't have marketing departments or people trying to sell you licenses. They don't have vendor lock-in or active-directory or a cloud based infastructure. They don't have an entire advertising division or a search engine. There aren't any shareholders to please or paid employees to keep on payroll for government kickbacks. They're not targeting the casual, media-focused, average computer user like Microsoft, which makes a lot of money by doing so.

In my last job, I worked in a mid-sized suburban office. There weren't any "Linux reps" knocking on our door, making sure we were getting the most out of Ubuntu.

Microsoft is an enterprise, and enterprises will continue to crank out enterprisey stuff. Linux is free and open source, developed by people with passion - some of it, I assume, is out of necessity. Unless the working world dramatically changes over the next 15 years, Microsoft is still going to Microsoft.

Windows sucks, Azure sucks, Office sucks. Microsoft is a corporation designed to make money, they have a deadlock on the market. From an investor's point of view, they're doing just fine. From a shareholder's point of view, uprooting the entire Windows base to make tech people happy isn't worth the investment. Microsoft hasn't been about making tech people happy since it went public. Microsoft makes money and employs people. People half-heartedly go to work to earn a living, they produce enterprise-grade software. Enterprise software makes money. That's all the investor cares about.

Actually, as a matter of fact, having Windows around to drive the continued development of Linux might be a good thing. I know Windows sucks, I know virtually anything technical is dramatically easier on Linux, but anything without competition eventually stagnates. Even if Windows exists simply as a "What not to do" in Linux, it's probably good that it remains around.

Currently typing this on a machine that dual-boots both Windows and Linux. Why? Because my laptop came installed with it.

My next question would be, is this something that OpenAI and Anthropic would train their data on? If I ask Claude Code to write an app and utilize jQuery, would it resolve to the previous version until it's retrained in a newer model?

There's still a ridiculously minuscule chance that you'll end up profitable, let alone successful.

I read that software, from a business perspective, is almost always looked at as a liability rather than an asset. There just isn't very much profitable software in this world, and the software that can become profitable likely subsidizes its business with advertising. The only saving grace is that software that becomes profitable can typically scale. See Facebook, TikTok, Google.

Games sell but are risky and creatively demanding.

Software is a tough business.

It was interesting that the poster vibe-coded (I'm assuming) the CTL from scratch; Claude was probably pretty good at doing that, and that task could likely have been completed in an afternoon.

Pairing the CTL with the CLI makes sense, as that's the only way to gain feedback from the game. Claude can't easily do spatial recognition (yet).

A project like this would entirely depend on the game being open source. I've seen some very impressive applications of AI online with closed-source games and entire algorithms dedicated to visual reasoning.

I'm still trying to figure out how this guy: https://www.youtube.com/watch?v=Doec5gxhT_U

Was able to have AI learn to play Mario Kart nearly perfectly. I find his work to be very impressive.

I guess because RCT2 is more data-driven than visually challenging, this solution works well, but having an LLM try to play a racing game sounds like it would be disastrous.

And yes, I understand code re-use and distribution are valuable, and that's a good point. Having an LLM generate everything on the fly is definitely energy-intensive, but that hasn't stopped the world from building massive data centers to support it, regardless.

I guess the theory of my past few posts would be similar to rolling updates, so using the text editor as an example, you'd prompt the AI agent in the hypothetical OS to open a document, and it would generate a word processor on the fly, referencing the dozens of open source repos for word processors and pushing its own contributions back out into the world for reference by other LLMs - computationally expensive, yes. It would then learn from your behaviors, utilizing the program, and the next time you'd prompt the OS for a word-processor-like feature (I'm imagining an MS-DOS-like prompt), it would iterate on that existing idea or program - less computationally expensive because ideally the bulk of the work is already learned. Perhaps adding new features or key-bindings as it sees fit. I understand that hard-disk space is cheap, and you'd probably want some space to store personal files, but the OS could theoretically load your program directly into RAM once it's compiled from AI-generated source code. Removing the need to save programs themselves to disk.

Since LLMs are globally distributed, they're learning from all human interactions and are actively developing cutting-edge word processors tailored specifically to the end-users' needs. More of a VIM-style user? The LLM can pick up on that, prefer something more like MS Word? The LLM is learning that too. AIOS slowly becomes geared directly to you, the end-user.

That really has nothing to do with intelligence; you're just teaching a computer how to compute, which is what AI is all about.

Just some ideas on what the future might hold.

Aside from getting an LLM up and running on a device, what's stopping AI from creating an operating system? I admittedly don't know much about operating system development, but aren't most operating systems written primarily in C?

I guess what I meant by that is it would be interesting if the AI prompt itself were the OS, and all software would be generated via prompting the agent. No downloads, just a "What do you need?" prompt with the AI generating everything on the fly.

Perhaps becoming so fast that you wouldn't even notice it thinking. Just: "I need to edit a document that was sent to my email" The AI would then retrieve the email, download the document and generate its own text editor to display the document in. All within a few milliseconds.

Call it AIOS

Operating systems become redundant; you open any digital device, and it's just a portal into the most advanced LLM on the planet.

Obviously just spitballing here.

I wonder how far AI will advance.

I still need to map a domain. I used to maintain a personal blog years ago, but let it expire. I just recently created this new one.

I understand that AI assitants need access to tools in order to do anything on a computer, I've been working with AI augmented development for a few months now and everytime I need a prompt to run a tool it asks for permission first, or just straight up gives me the command to paste into a terminal.

ideally this would have been abstracted away if siri were an LLM, with Apple controlling which apis siri has access to and bipassing user confirmation all together.

It would have been neat if I were able to say, "Hey, Siri: send a text to John Smith with a playfully angry prose thanking him for not inviting me to the party". which would have the LLM automatically craft the message and send upon confirmation, perhaps with a disclaimer "made with ai" at the bottom of the text or something along those lines.

"Hey, Siri: What's the weather in Los Angeles, California" would fallback to a web api endpoint.

"Hey, Siri: How do I compile my C# application without Visual Studio" would provide step-by-step instructions on working with MSBUILD.

different prompts would fallback on different apis that only Apple would expose. Obviously not allowing the user to gain root access to the system, which is what you would expect from Apple.

I guess from a purely technical standpoint, you'd train two models, one as "Safe" and the other as "Unsafe". "Safe" is what would be used by the end-user, allowing them to access safe data, apis, messaging, web.. you name it. "Unsafe" would be used internally at Apple and would have system-wide access, access to unlimited user data, root privileges, perhaps unsafe image generation and web search... basically no limit to what an LLM could achieve.

I don't think Apple didn't have enough people working on Siri, I think they had too many people working on the wrong problems. If they had any eye on the industry like they did in their heyday when Jobs was at the helm they would've been all over LLMs like Sam Altman was with his OpenAI startup. This report of SIRI using Gemini going forward is one of the biggest signs that Apple is failing to innovate, let alone the constant rehashing of Iphone and IOS. They haven't been innovative in years.

And yes that's the point I was trying to make, AI assistants shouldn't be hardcoded to do certain things, that's not AI - but with Apple's marketing, they'd have you believe that SIRI is what AI should be, except now everyone's wiser, everyone and their grandmother has used ChatGPT which is really what SIRI should have been. Changes to the IOS API should roll out and an LLM backed AI assistant should be able to pick up on those changes automatically, SIRI should be an LLM trained on Apple Data, its APIS, your personal data (emails, documents,etc.), and a whole host of publicly available data. This would actually make SIRI useful going into the future.

Again, if Apple's marketing team were to be believed, SIRI would be the most advanced LLM on the planet, but from a technical standpoint, they haven't even started training an LLM at all. It's nonsense.

I want to know why the executive leadership at Apple failed to see LLMs as the future of AI. ChatGPT and Gemini are what Siri should be at this point. Siri was one of the leading voice-automated assistants of the past decade, and now Apple's only options are to strap on an existing solution to the name of their product or let it go defunct. So now Siri is just an added layer to access Gemini? Perhaps with a few hard-coded solutions to automate specific tasks on the iPhone, and that's their killer app into the world of AI? That's pathetic.

Is Apple already such a bloated corporation that it can no longer innovate fast enough to keep up with modern trends? It seems like only a few years ago they were super lean and able to innovate better than any major tech company around. LLMs were being researched in 2017. I guess three years was too short of a window to change the direction of Siri. They should have seen the writing on the wall here.

Was this just a massive oversight at Apple? Were there not AI researchers at Apple sounding the alarm that they were way off with their technology and its capabilities? Wouldn't there be talk within the industry that this form of AI assistant would soon be looked at as useless?

Am I missing something?

Hopefully, LLMs lead to more thorough documentation at the start of a new language, framework, or tool. Perhaps to the point of the documentation being specifically tailored to read well for the LLM that will parse and internalize it.

Most of what StackOverflow was was just a regurgitation of knowledge that people could acquire from documentation or research papers. It obviously became easier to ask on SO than dig through documentation. LLMs (in theory) should be able to do that digging for you at lightning speed.

What ended up happening was people would turn to the internet and Stack Overflow to get a quick answer and string those answers together to develop a solution, never reading or internalizing documentation. I was definitely guilty of this many times. I think in the long run it's probably good that Stack Overflow dies.

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Technologies: C#, javascript, react, vue.js, sql

Email: joshsiegl(at)gmail(dot)com

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Bitcoin was started right under their noses (and I'm not just referring to the U.S government here, but all national governments), and it continues to operate all across the globe. It's kind of what makes it so interesting, you can't really kill it, it's like a good financial virus.

I hate to break it to you, but the infrastructure of payment processing and business has already been upended by Bitcoin alone. It's only a matter of time before we see layer-2 solutions like the one OP mentioned.

Bitcoin might not be the best blockchain to target for small-scale financial transactions like delivery apps, but you catch my drift. Just about any blockchain would do in this scenario.

I'm eager for the web3 economy to truly take off. There are so many little improvements to the way things work with blockchain compared to the black hole that is fiat currency; it's astounding.

But yes, in essence, if the post is true, then this is a misrepresentation of what the service is actually doing. Being able to verify where your payment is going on a publicly available blockchain would provide customers and employees with some clarity.

Using cryptocurrency with on-chain verification of the paper trail could actually solve this problem without having to get auditors and lawyers involved.

It was a 1994 Ford Taurus.

That was probably about 20 years ago, I'm 32 years old now.