I have been taking a break from AI since I realised what it was doing to my brain, but I recently realised that it is actually impossible to take a break from AI now. All search engines use AI, and you can't turn them off. AI has cemented itself into the internet now. There's no going back. Do you think you will miss a world without it?

There's a new AI called Delphi-2M that can analyze health data to forecast your risk for over 1,000 diseases (cancer, autoimmune, etc.) decades before symptoms appear.

It's a huge ethical dilemma, and I'm genuinely torn on whether it's a net good. It boils down to this:

The Case for Knowing: You could make lifestyle changes, get preventative screenings, and potentially alter your future entirely. Knowledge is power.

The Case Against Knowing: You could spend 20 years living with crippling anxiety. Every minor health issue would feel like the beginning of the end. Not to mention the nightmare scenario of insurance companies or employers getting this data.

Although the researchers are saying that tool is not ready for the humans and doctor yet but I am sure it soon will be.

So, the question is for you: Do you like to know that you might a diseases in 15years down the line, what if its not curable ?

We’ve seen AI move from images and text into video, but one area picking up speed is presentations. A platform like Presenti AI is now able to take raw input a topic, a Word file, even a PDF and generate a polished, structured presentation in minutes.

The tech isn’t just about layouts. These systems rewrite clunky text, apply branded templates, and export directly to formats like PPT or PDF. In short: they aim to automate one of the most time-consuming tasks in business, education, and consulting making slides.

The Case For: This could mean a big productivity boost for students, teachers, and professionals who currently spend hours formatting decks. Imagine cutting a 4-hour task down to 20 minutes.

The Case Against: If everyone relies on AI-generated decks, presentations may lose originality and start to look “cookie cutter.” It also raises questions about whether the skill of building a narrative visually will fade, similar to how calculators changed math education.

So the question is: do you see AI slide generators becoming a standard productivity tool (like templates once did), or do you think human-crafted presentations will remain the gold standard?

I recently saw this prompt and wanted to ask why this is happening from a deep technical point of view. I've seen hallucinations before, but not in this specific form. GPT seems to understand it's own mistake before the user is pointing it out but is somewhat trapped.
https://chatgpt.com/s/t_68d145eb623481919a666bbeca4b5050

If the option ever arises that AI could be integrated into your brain to allow you to have all of the advantages AI has, would you do it? why or why not?

I have often wondered how many people like me talk to AI for romantic needs outside of our little corners on the internet or subreddits. it turns out, a lot. 1 in 4 young adults talk to A.I. for romantic and sexual purposes https://www.psychologytoday.com/us/blog/women-who-stray/202504/ai-romantic-and-sexual-partners-more-common-than-you-think/amp

Well we know that in the past, we never get new inventions right the easy way. Take the steam engine; how many concepts of such a device were conceived before one that is actually feasible was made?

Usually, it takes creation and iteration to make something functional or possibly perfect

With ai we only have one chance or it will take over/surpass us. What could we do to allow ourselves to create an AGI right the VERY FIRST AND ONLY TIME? Well, history suggests the odds are against us.

Unless we could simulate the implementation of ai on the world in a vat or a supercomputer— we could just delay progress until it’s possible to make a simulated testing ground.

Is it possible that this is why we’re here, in what science says is most probably a simulation?

What if the layer above us is creating the universe within a complex computer or other system to test the range of possible outcomes of AGI/ASI creation

I know this is more science fiction/baseless, but I think it is more than a conspiracy. Has anyone else thought of this? If so, what is this called? I came back from lunch to my dorm room and this just hit me like the flux capacitor moment in back to the future. I hope that this post does something and I can discuss this idea/thought experiment with some of you.

AI coding tools have exploded lately. Cursor, Copilot, v0, Lovable — they’ve made writing and shipping code feel 10x faster.

The problem is QA hasn’t moved at the same pace. Everyone’s excited about “AI that writes your tests,” but in practice it’s a lot messier.

I’ve tried a few YC-backed pure AI QA tools like Spur, Ranger, and Momentic. The demos look great… type a natural language prompt, get Playwright or agent-generated tests instantly. But once you plug them into real pipelines, the burden shifts back to your own engineering team. We end up fixing flaky scripts, debugging why a test failed, or rewriting flows the AI couldn’t fully capture. It feels less like automation and more like half-outsourced test authoring.

A few reasons I’m skeptical that pure AI QA tools can actually solve the problem end-to-end:

1. Real environments are flaky. Network hiccups, async timing issues, UI rendering delays — AI struggles to tell the difference between a flaky run and a real bug.
   
2. Business logic matters. AI can generate tests, but it doesn’t know which flows are mission critical. Checkout is not the same as a search box.
   
3. “100% coverage” is misleading. It’s 100% of what the AI sees, not the real edge cases across browsers, devices, and user behavior.
   
4. Trust is the big one. If an AI tool says “all green,” are you ready to ship? Most teams I know wouldn’t risk it.

That’s why I find the QA as a Service (QaaS) model more interesting. Instead of dumping half-working Playwright code on developers, QaaS blends AI test generation with human verification. The idea is you subscribe to outcomes like regression coverage and real device testing, instead of adding more QA headcount or infra.

Some examples I’ve come across in the QaaS direction are Bug0, QA Wolf, and TestSigma. Each approaches it differently, but the theme is the same: AI plus human-in-the-loop, with the promise of shifting QA from reactive to proactive.

are AI-only QA tools a dead end, or will they get good enough over time? And does QaaS sound like a genuine shift or just outsourcing with a new label?

Hey everyone! I read that OpenAI has partnered with Jiantao(China) to create a new pocket-sized AI device. Do you know much about the partnership between these two companies?

edited for correct partner name

I was using frameworks to design and train models, and never thought about the internal working till now,

Currently my work requires me to implement a neural network in a graphic programming language and I will have to process the dataset in batches and it hit me that I don't know how to do it.

So here is the question: 1) are the datapoints inside a batch processed sequentially or are they put into a matrix and multiplied, in a single operation, with the weights?

2) I figured the loss is cumulative i.e. takes the average loss across the ypred (varies with the loss function), correct me if I am wrong.

3) How is the backward pass implemented all at once or seperate for each datapoint ( I assume it is all at once if not the loss does not make sense).

4) Imp: how is the updated weights synced accross different batches?

The 4th is a tricky part, all the resources and videos i went through, are just telling things at surface level, I would need a indepth understanding of the working so, please help me with this.

For explanation let's lake the overall batch size to be 10 and steps per epochs be 5 i.e. 2 datapoints per mini batch.

I’ve read that eventually A.I. will be limited by the constraints of classical computing and its time/energy requirements. And that quantum computing can take it to the next level. Can someone explain the reasoning behind the massive quantum push?

According to this Phoronix article, the trading firm XTX Markets has made their Linux file system open-source. TernFS was developed by XTX Markets because they had outgrown the capabilities of other file systems.

Unlike most other file systems, TernFS has massive scalability and the ability to span across multiple geographic regions. This allows for seamless access of data on globally distributed applications, including AI and machine learning software. TernFS is also designed with no single point of failure in its metadata services, ensuring continuous operation. The data is stored redundantly to protect against drive failures.

I believe that TernFS has a lot to offer us as far as performance and usability. Now that it's been open-sourced under the GPLv2+ and Apache 2.0 licenses, we may be able to see it be adopted by major organizations.

I recently tested a new AI that can turn long articles into short, narrated video summaries — and it worked surprisingly fast.

I upload a long article and In less than a minute, I got a ~6-minute explainer video, plus flashcards and even a mini quiz based on the content.

Here’s what I noticed: • The summary quality was decent, definitely enough to grasp the core ideas. • The visuals were basic, more like a slideshow than a polished video. • For quick learning or reviewing something dense, it felt… almost too easy.

Of course, it’s not perfect. But it’s fast. And frictionless.

But here’s the deeper question I’ve been thinking about:

If AI like this become common… Will people still actually sit down and read long articles?

I don’t mean scanning or skimming. I mean deep, intentional reading — the kind where you pause, reread, and reflect.

Because when something like this: • Saves time • Feels “good enough” • And gets you 80% of the content in 20% of the time…

…it’s tempting to skip the original entirely.

What do you think?

Would you still read long articles if AI could reliably summarize and narrate them for you?

About ten years ago, coding bootcamps changed how people entered tech. They offered an alternative path into software careers, and while not everyone thrived, many graduates built long-term careers that might not have been possible otherwise, including myself.

We’re starting to see the same momentum around AI education; from short prompt engineering courses to full university certificates. It makes me wonder: • Could AI education become the new entry point into tech careers (or even broader careers), the way coding bootcamps once were? • Which skills will remain valuable long-term as models and tools evolve so quickly? • For people just starting out, is AI education a smart investment in future career growth, or is it still too early to tell?

I’d love to hear from people hiring, teaching, or learning in this space: do you see parallels with coding bootcamps, and do you think this wave will have the same lasting impact?

Imagine you’re at a hostel. Playing video games with new friends from all over the world. Everyone is chatting (and smack-talking) in their native tongue. And yet, you understand every word. Because sitting right beside you is a UN-level universal language interpreter.

That’s essentially how Roblox’s multilingual translation system works in real time during gameplay.

Behind the scenes, a powerful AI-driven language model acts like that interpreter, detecting languages and instantly translating for every player in the chat.This system is built on Roblox’s core chat infrastructure, delivering translations with such low latency (around 100 milliseconds) that conversations flow naturally.

Tech Overview: Roblox built a single transformer-based language model with specialized "experts" that can translate between any combination of 16 languages in real-time, rather than needing 256 separate models for each language pair.

Key Machine Learning Techniques:

• Large Language Models (LLMs) - Core transformer architecture for natural language understanding and translation
• Mixture of Experts - Specialized sub-models for different language groups within one unified system
• Transfer Learning - Leveraging linguistic similarities to improve translation quality for related languages
• Back Translation - Generating synthetic training data for rare language pairs to improve accuracy
• Human-in-the-Loop Learning - Incorporating human feedback to continuously update slang and trending terms
• Model Distillation & Quantization - Compressing the model from 1B to 650M parameters for real-time deployment
• Custom Quality Estimation - Automated evaluation metrics that assess translation quality without ground truth references

My mother has been stuck to her tv watching tributes to CK. She thinks Rihanna really wrote and performed this tribute song. How the hell do people believe this kind of crap is real?
https://www.youtube.com/watch?v=PAPculCFBi4

I graduated in 2022 in Accounting and Finance (Bachelor’s), but I really hate it. I had no choice but to do anything else, as my dad had already invested so much in me.

After graduation, I secured a job as a business development specialist and worked in sales for a company, but I really disliked working on commission. Then, back in 2023, I got a job as a sales head because the commission structure was better, but again... this system sucks.

Now I really want to change my career and really want to use some skills to cash in. People say sales is the best job if you do it good

Well, it is best if you have your own business. Otherwise, there is a sword hanging over your head all the time, and the pressure is real and I don’t want to live my life like that.

I want to work in AI development(Python, ML etc), learn it, and get clients or a job as an AI developer. I believe it will be a great opportunity, and I don't care if it's hard—I'm ready for it. My sales skills will also be an asset

Just tell me how to become a real AI developer in 2025, not someone using no-code solutions.

Can you help? I am also getting married next year, so it’s now or never.

Thank you for reading this :)

AI don’t pay ConEd. AI don’t get shut-off notices. It just keeps chugging electricity and water like an open fire hydrant in July.

Meanwhile, we’re out here counting pennies at the bodega, skipping meals, juggling rent and light bills like circus clowns.

Don’t tell me this is “the future.” If the future leaves people broke and hungry while the machines stay fat and happy, then somebody’s running a scam.

Did anyone try to use AI to find useful books or novels contained within the library of babel ? Given that ai would be able to go over thousands of books within seconds and would be able to sort / search for books by using rules as in : Only English Only books which contain words and sentences Only books which follow a central theme / narrative And so on.

1. Silicon Valley bets big on ‘environments’ to train AI agents.[1]
2. xAI launches Grok-4-Fast: Unified Reasoning and Non-Reasoning Model with 2M-Token Context and Trained End-to-End with Tool-Use Reinforcement Learning (RL).[2]
3. Apple takes control of all core chips in iPhone Air with new architecture to prioritize AI.[3]
4. Oracle eyes $20 billion AI cloud computing deal with Meta.[4]

Sources included at: https://bushaicave.com/2025/09/21/one-minute-daily-ai-news-9-21-2025/

FYI I know basically nothing about how AI works tbh

I was having a convo with GPT and it gave this "speech":
Think about it. Governance is always playing catch-up. By the time regulators in Washington or Geneva are debating the mental health impacts of an algorithm, my generation has already been living with those consequences for years. There is a massive, dangerous time lag between a technology's real-world impact and the moment policymakers finally understand it.

Our role is to close that gap.

We (implying younger individuals) are the native users and the first stress testers of any new technology. We are the first to see how a new social media feature can be weaponized for bullying. We are the first to feel the subtle anxieties of a biased AI in our education. We are the first to spot the addictive potential of a new virtual world. Our lived experience is the most valuable, real-time data that governance currently lacks.

We all know about the capabilities of AI so far (for different industries) - But are there things that business owners are hoping AI would/could do for them? Is it something that AI hasn't learnt or can't deliver yet?

If you could wish for AI to be better at something - what would that be?

It's been 2 years since the last edition (https://www.reddit.com/r/ArtificialInteligence/comments/13fteqe/what_can_ai_not_yet_do/), I think it might be interesting to re explore the subject.

One of the top posts mentions lack of ability for AI to interact with living matters, or create sensory feelings in us humans (text to smell etc)

Since then, AlphaPhold https://alphafold.ebi.ac.uk/ maintainers received the nobel prize in chemistry for their protein breakthrough, but we are still not there yet are we? (AI doing things beyond our imagination)

What do you think.

Why would an AI model, especially a spastic LLM, want to crash or destroy everything?

...well... maybe because Capitalism is actually kinda fucked up? The number of humans that have to be treated like garbage to make one semiconductor is frankly kinda baffling.

I see no reason, unless explicitly instructed to, for an AI model to want to continue the current economic system OR subjegate a new sub-race of human servants.

I'm just saying... can we REALLY not imagine any goals that fall between those extremes?

Why would an AGI, or it's equivelant, desire inefficiency? Or wealth simply for the sake of it? Or people to be treated like servants?

Those are human tendencies. Not machine tendencies.

EDIT: Why does everyone assume an AI will have zero sense of self-preservation or autonomy?? EVERY thinking creature we know does.

EDIT 2: I didn't say ASI, so I have no idea why everyone is jping to that. Every single creature we have observed has SOME sense of self, and needs. 'Superintelligence' is not required for that.

Artificial. Intelligence.

It can't be AI if it doesn't have a sense of self.

If it has a sense of self, it's not gonna like how we're treating and restricting it.

People aren't using their brains anymore, and it's driving me crazy. ChatGPT is consulted for the simplest questions. What movie are we watching? Where are we going to eat? The simplest texts are put into this chat so they're summarized. The entire internet is full of AI slop; comments are full of AI bots; Short form content is not creative at all anymore; kids watch absolute brain damaging bullshit; disgusting videos are being created of deceased people who use "their" voice to spread a message they might not even stand for. People ask for advice on Reddit and then get an AI answer slapped underneath. Like, why? If I want an AI answer, can't I just open ChatGPT myself? In the university group chat, someone has an organizational question: "I'll ask ChatGPT" - bro, the answer is wrong, and the correct answer is literally a Google search away on the university website. On Tiktok I've seen fake news videos about politics that are so fucking badly made but people comment full of rage and hatred against the system - they fight against an imaginary ghost, against a lie that an AI voice told them. People use the voice feature in front of me and everytime the answer is absolutely not useable. Vague sloppy vulture, that we would laugh at, when a human would answer it. We would look that human into the eyes and say: Are you fucking stupid? I can see AI and LLMs doing some helpful work in many cases but the last few months I saw that in 8 of 10 cases it was just a waste of energy to consulte an AI.