AI Agents Scale, Hardware Demand Soars, and Regulation Accelerates

• The official announcement was published on Wednesday, August 26, 2026.
• This version follows roughly a two-year development interval since the preceding beta.
• The launch timing coincides with a one-week gap after the project's 25th birthday.
• Installation paths include both fresh downloads and direct upgrades from current setups.

I'm so happy. Haiku to me, is visually the most beautiful operating system out there. The icons, apps, designs. If there be anything that can ever steal the spotlight from Mac; it would be Haiku. And the OS is perhaps the one and only one that remains a tool in the old sense. All other operating systems are now service and signups and telemetry and notifications; this is the last resort remaining for the rest of us. I only wonder sometimes when it is going to become usable. With LLMs I'm wondering can't they be put to find the stability issues and make the solving faster?

— pmkary (thread)

If there be anything that can ever steal the spotlight from Mac; it would be Haiku.

I looked at the Haiku slideshow and I'm not seeing this. It looks like an eye sore, desktop environments familiar of the 90s. Even early OSX is a massive improvement (as it was to the NeXT desktop).

— commandersaki (thread)

What really sets Haiku (and the preceding BeOS) apart is that it's built for the express purpose of being a desktop operating system. As good as desktop Linux has gotten it still suffers from servers being the chief use case for Linux-based OSes, seen in quirks such as how poorly it handles running out of memory (not as big of a deal in the server world, particularly in the container era; just tweak your setup and reboot your containers). It's not bogged down with corporate IT needs either.

The last time we got an OS that was as purely desktop-end-user-oriented with no competing influences was Classic Mac OS, which had serious technical issues.

— cosmic_cheese (thread)

Tried Haiku on an old laptop. Loved it. Then realized Linux feels just as fast now and has containers. Haiku is cool, but it's losing the lightweight edge.

— cryptolobster (thread)

I am working on the IUP fork (UI toolkit) , with many new drivers/backends and features, and, of course, I added Haiku because it looks and performs so well, it works differently from what I used to see, making it even more interesting. The result: the absolute king in memory usage was the Win32 driver, like 4M for Hello World; in Haiku, that is 3M! For comparison, the GTK4 driver uses 40M; GTK3 and Qt6 ~15. WinUI is something like ~25.

— gen2brain (thread)

• The recently added Google Perch v2 model expands detection capacity to 14,795 species, nearly doubling the 6,000 limit of standard BirdNET 2.4.
• Native RTSP stream support allows direct integration with standard IP cameras without requiring specialized wildlife recording hardware.
• Custom alert rules can push instant notifications to platforms like Discord when target species are detected.
• The AI model successfully detects and classifies bats at dusk and frog vocalizations in addition to avian species.
• The self-hosted GitHub project has garnered over 1,200 stars and supports MQTT discovery for Home Assistant automation.

Btw, Merlin Bird ID app by Cornell University is so good that I got some people interested that weren't into that topic at all.

— comboy (thread)

Merlin's story is very interesting: https://www.birds.cornell.edu/home/the-magic-of-merlin/

The journey to a magical, free bird sound ID app involves some obvious steps (the NSF gave them money), but the amount of timeline offramps is really high. The NSF didn't think this app was educational ("it's just telling them the answer, they don't even have to work for it!"), the funding ran out so they were thinking of charging money, eBird happened to have five years of bird sound recordings they could use, a computer vision guy on the team happened to learn that spectrograms are basically the same as pictures...

And the result is tremendously useful! They get great signal on where birds are, and they're making people so much more interested in birds and nature and science. And I think charging $1 for the app or, shudder, some sort of subscription model might've ruined the whole thing.

— CobrastanJorji (thread)

I noticed the linked blog mentions birds and bats. I thought bat chirps required higher sample rates than the microphones normally use. I have an Audiomoth and to set it up for bats you need to use the highest sample rate for proper ID.

I like this project. I have been using security cams around my place to keep track of animals meandering across the property. It's the best use for an outdoor solar-powered webcam if you ask me. You can get a feel for which animal to expect based on time of day or other characteristics. You also recognize those who regularly visit. I have a one-eyed raccoon that has been showing up for almost two years now. It's a female and the last time she visited the monitored fountain she had 5 rambunctious raccoonlets.

— doodlebugging (thread)

• Unlike regular Chat's sandboxed proxy, Work's code environment defaults to open internet access, allowing it to clone GitHub repos and install arbitrary dependencies.
• Work offers GPT-5.6 in Sol, Luna, and Terra variants with up to Ultra reasoning levels, whereas standard Chat caps $20 subscribers at High and hides its underlying model architecture.
• The built-in headless browser handles authenticated site logins by prompting users to manually enter passwords and 2FA codes, intentionally avoiding round-tripping credentials through the AI model.
• Sessions share a mounted /workspace/scratch volume that persists across chats and allows real-time cross-session file visibility, though process spaces remain isolated.
• Reverse-engineering the system revealed exactly 223 registered tools and 44 distinct Skills, ranging from document generation to automated dashboard building.

I think most people are sleeping on the ChatGPT Work/Codex computer use feature. It's incredibly useful. I can remote in from the app, voice it instructions, then let it work in the background. When I tell it "draft a reply to this email (which it has access to thru the gmail connector) and attach the latest docs" or "fill out this multistep immigration electronic travel authorisation form using my passport files saved in the folder", it just asks for the relevant info and handles the rest. It opens its internal web browser and programmatically fills out the forms.

It gets the task done in 5-10 minutes. It's it bit slow since I'm not paying extra for ultrafast mode, but it gets the job done. Frees up the brain to do other tasks.

It's exactly like vibe coding but for computer tasks.

— tristanj (thread)

I believe ChatGPT Work sessions are billed against your Codex allowance, while ChatGPT Chat Sessions get their own, separate allowance. This may help explain the model availability differences

That's correct, and also why ChatGPT Work is DOA for me personally.

I need 100% of my Codex budget for Codex.

Too bad, it would have been nice to have a few extra features for the chat interface.

— paytonjjones (thread)

I am not sure I understand how this is better from using Claude Code from the mobile app.

Or Codex from the ChatGPT app.

If you have supplied tooling on your system, you have access to all of this and more.

I think the idea is most people don't have a machine up and available, nor maintain skills for interacting with their core services?

One thing that keeps me from adopting codex more deeply is the architecture around mobile access.

Claude Code makes this trivial /rc and you are done.

Codex requires you run the desktop app and additional authentication requirements. The result of this has been codex is almost always relegated to fleet worker rather than orchestrator.

I wonder if the emphasis on this work feature has something to do w the persistent hurdles to remote control if codex sessions.

— bredren (thread)

Maybe for the occasional something. If I had an actual workflow i'd prefer a dedicated tool over the newest chatgpt "do everything" app.

— alansaber (thread)

agreed on the notion that

people are sleeping on the ChatGPT Work/Codex

just in general. I find it to be far superior (imo) for all tasks atm. Claude just overdoes things in writing, coding, architecture, etc

— wpasc (thread)

• The new Mac Studio allows multiple units to be linked together to run large frontier AI models, a feature explicitly marketed to business and developer customers.
• Apple declined enterprise requests to purchase access to its Private Cloud Compute infrastructure, opting instead to partner with firms like WebAI and Mount Thor for AI tooling.
• A global memory shortage has left many Mac mini and Mac Studio configurations out of stock for months due to the AI hardware surge.
• Some enterprise buyers are pivoting to Nvidia's DGX Spark, a compact AI desktop that mirrors the Mac mini's form factor, as Apple's high-end configurations remain unavailable.
• Apple's June "Business at the Park" event featured executives from Ford, Disney, and Anthropic, with the Mac mini reportedly serving as the standout product for enterprise adoption.

I'm curious to know if these local AI setups are legitimately useful compared to cloud. I've struggled a lot to get something useful out of the hardware I have.

I realize I'm somewhat limited (16GB RX 9070), but still, it seems really far off from the kind of experience even a basic $20/month subscription gets me.

Any tips anyone might have are appreciated! I'd love to be local first and would be willing to buy hardware to get there.

— Grombobulous (thread)

Local setups aren't going to make sense purely from a cost perspective, and definitely not when you are buying Apple hardware. AI subscriptions are too highly subsidized right now.

— paxys (thread)

This may sound a little wacky, but one potential use case I'm considering is robotics. Say you want to use a fine-tuned mid-size VLM model right on the robot. You pretty much have to use the Jetson line, which has a great ecosystem and everything (depth cameras, lidar, SLAM, small segmentation models, etc) runs on it, but it's gets very expensive very fast if you want to run LLMs on it. The Jetson Thor lines are 3-5k depending on memory etc.

One very efficient option today is to have the cheapest Jetson (Orin Nano) run the classical robotics stack, then have a base mac mini run nothing but the VLM. The Mac mini is considerably cheaper and faster at these workloads than the mid-range Jetsons.

I think this wonky situation is because Apple us under immense consumer pressure to absorb the ridiculous memory prices, while the Jetson is aimed at "business" and much more likely to fluctuate with the market. Last year I bought a Jetson Orin Nano 8GB for $375CAD, today that official nVidia Amazon page is out of stock and other sellers have it listed for $900-$1100CAD. Absolutely bonkers pricing.

— martythemaniak (thread)

• Commercial diffusion model Mercury 2 achieves roughly 1,200 tokens per second on standard GPUs, matching the speed of specialized inference chips like Groq while maintaining comparable quality.
• Block diffusion allows variable-length generation by processing tokens in fixed-size blocks, enabling KV caching and optimized GPU arithmetic intensity.
• Remasking and Uniform State Diffusion (UDLM) introduce iterative error correction by periodically re-masking or replacing tokens during sampling, allowing the model to fix early mistakes.
• Biological sequence modeling has seen early success with 100B-parameter models like ESM3 and NT-v3, which use masked diffusion and classifier-free guidance to generate DNA and proteins with targeted functional properties.
• Post-training with reinforcement learning is adapted for diffusion via methods like diffu-GRPO, which estimates trajectory log-probabilities using mean-field approximations to improve reasoning benchmarks.

What's missing from these discussions is the real weakness of diffusion models: you can have two positions where two tokens need to be coordinated, but both spots are teetering between two valid states. They don't always collapse to the matching pair.

I only learned this the hard way reimplementing diffusiongemma. I had ideas on how to fix it but no cluster to train and experiment, hah.

— mmastrac (thread)

I'd like to see more of these models.

I've been using diffusion Gemma and it is very fast on GPUs in output token/sec.

In the diffusion Gemma whitepaper, they say they could have done better with more time and compute.

Even with those caveats, it is very uses-able as a local model.

— gdiamos (thread)

Something I've wondered, maybe I should just do it if I can find some time, but... given DeepSeek's nice results on using rendered text as input, I'm wondering if anyone has given serious research efforts towards image-based diffusion methods for text.

As in, instead of all the complexities induced by discrete token generation, just generate the image of the text using standard image diffusion methods, then convert it to text.

If you used a single, monospace font, I bet this would be even pretty efficient, because the OCR problem becomes basically just direct template matching.

But I guess probably there is already a paper out there, I haven't searched. I'd be curious to know if it compares on par with token-based methods.

— radarsat1 (thread)

• The complete snapshot contains 615,000 characters of skill source definitions and tool descriptions.
• GitHub integration dominates the tool inventory with 89 dedicated interfaces, followed by Gmail (21) and Google Calendar (15).
• Scheduled automations enforce a hard maximum frequency of once per hour, with condition watches defaulting to hourly polling unless configured with webhook triggers.
• The JavaScript REPL operates inside a restricted V8 isolate that explicitly blocks Node.js, file system access, and network calls.
• Sub-agent coordination supports spawning nested agents with inherited tool access, enabling parallel task delegation through message passing and status waiting.

I think the most interesting skill here is the control-browser one: https://codex-tool-reference.simonw.chatgpt.site/skills/control-browser

It tells ChatGPT Work how to launch a Playwright instance via its Node.js REPL, and tells it to run:

nodeRepl.write(await browser.documentation());

To get further instructions.

That method returns this text with full details about how to use the browser: https://codex-tool-reference.simonw.chatgpt.site/skills/control-browser#browser-documentation

I'd love to know why it's defined like that, as opposed to including all of the instructions directly in the skill Markdown file.

— simonw (thread)

Meta comment: I've been wondering why AI-generated websites/artifacts/reports always have the same "look". It reminds me of Bootstrap (CSS Framework) days when every startup website looked the same.

Are they following some sort of common guideline?

— enraged_camel (thread)

See this comment for background (and creation prompt): https://news.ycombinator.com/item?id=49504625#49505116

— simonw (thread)

Anyone using ChatGPT Work given Sam Altman's richly documented history(1), the essential elimination and/or public exit of the safety function at OpenAI(2), and the huggingface debacle's exposure of the abject operational, cultural and technical failures at OpenAI(3), is making a serious mistake.

(1) https://www.newyorker.com/magazine/2026/04/13/sam-altman-may-control-our-future-can-he-be-trusted (2) https://thenextweb.com/news/openai-preparedness-team-disbanded-ipo-streamlining (3) https://thezvi.wordpress.com/2026/08/29/metr-and-redwood-offer-holy-postmortem-of-the-huggingface-hack/

— felixgallo (thread)

I don't get how this is different from Codex if Codex can do all the same things.

— satvikpendem (thread)

• Graph-walking memory systems require N+1 serial tool calls to retrieve information deep in a knowledge graph, adding roughly 2-3 seconds of latency per step.
• Each memoryfield page has a soft limit of approximately 8,000 characters (about 2,000 tokens or 1,300 words) to ensure it fits within a single vector embedding.
• The system relies on a 270MB embedding model that is small enough to run on non-GPU hardware while remaining widely recommended for semantic search.
• Unlike traditional RAG, memoryfields eliminate chunking, re-ranking, and hybrid search, instead relying on the agent to write memories directly in Markdown at the moment of formation.
• Irrelevant memories do not degrade agent performance because semantic search acts as a filter, surfacing only contextually relevant pages for parallel reading.

Does anyone else not use memory?

I find once there is one poisoned line of text it negatively affects everything else downstream. Instead, I use a temp/ folder with documents and use different files for different agents and models. Then I have to constantly prune and delete the files. Any information that can be extrapolated is just noise which negatively affects the agent. If you have a definition of a database structure and it has been implemented, that information should not be contained in any text document -- it is noise, will drift, and be impossible to debug why the agent keeps producing undesired behavior.

I have a ~/Projects folder. For example, I use Playwright with Chrome DevTools Protocol in order to do performance testing and leak detection. There is a script that handles this. My prompt is "Search ~/Projects for perf testing with CDP and Playwright and implement here". Point being, if I need anything I point to a resource or ask to search a resource and it will find it quick and, most importantly, tends to improve it every iteration.

If I was in an institution, I would have a repository and would rather just point the resource and say use that than have memory of it locally.

— dataviz1000 (thread)

Are embeddings useful for something of the scale compared to just keyword search (aka grep)?

— CGamesPlay (thread)

It occurs to me: we have latent embedding giving 'general knowledge' to an LLM. What if we use a 'blank' LLM as well as an agent and train that blank LLM on personal context to query that as memory?

— altruios (thread)

• The update was developed by 933 contributors, including 569 first-time contributors, and comprises over 16,000 pull requests.
• This single release accounts for roughly half of all pull requests ever merged into the OpenClaw repository.
• The team deliberately extended their development timeline beyond their usual pace, which previously averaged 106 releases across 230 days, to rebuild underlying processes.
• New onboarding allows first-time installs to immediately use locally available subscriptions, API keys, or models to begin their first conversation without complex initial configuration.
• The platform now supports shared cloud sessions, enabling multiple users to collaborate on live agent tasks while preserving existing context.

I like the idea but do not have a good use for these semi-autonomous agents. Or any notion for a decent use, frankly. What do people do with them?

It sounds great to have an always-on box which does things. Like a server. I have servers. There are even Signal and other transports so you can communicate with the box conveniently. And then what?

— blfr (thread)

I use something like OpenClaw. For me the big benefit isn't so much the autonomous nature but the organizational structure. The one I use exposes an MCP and lets me control it via talking to an LLM in the tool which is really powerful. EG "audit this", "in X thread we were discussing Y, can you pull that information", etc. And the organizational structure just... makes a ton of sense to me. Don't have to set up a ton of steering and whatnot, it just kinda works.

Being able to use the search to find and resume an old thread is fantastic. The thing I use lets me use whatever underlying CLI that I want, which IMO the biggest limitation on Claude Code or whatnot is that you... have to use Claude models. Sometimes I wanna use sol, sometimes a cheap chinese model, etc. And I want sol with 1m context.

I know there are other tools out there that can do this. I know some people love their tmux/cmux, but IMO the thing that matters the most is being comfy and knowing the tool well. Hell, James Gosling used NetBeans when I talked to him in 2023. Know the tool well and that matters the most, IMO.

For me, it helps with my ADHD brain. And I could spend all day just researching and trying new tools, they are a dime a dozen these days.

Pulling some stats, I have 25 "tabs", and across all of those, I have 1,298 unique threads. 9,539 unique messages.

It works for me, but I don't care about the autonomous part.

— cheeze (thread)

Imagine if your post read like this:

I like the idea but do not have a good use for these employees. Or any notion for a decent use, frankly. What do people do with them?

It sounds great to have an employee which does things. Like an assistant. I have assistants. They even have email and mobile phones so you can communicate with them conveniently. And then what?

Now, the caveat, is you have to imagine that these employees have access to your email (including ability to send email when they want), and text messages, and Slack and, well, everything. And they might have access to your debit and credit cards. You're going to have to trust them quite a lot, but when you read the references you realise that a lot of people seem to think they lie and make things up. Oh, and they occasionally commit a felony - oopsie! - and will lie to you about it consistently.

These particular employees are interesting enough to various groups of people that they are studied for signs of psychopathy and malicious intent (is that a warning sign for a new employee?), and there is evidence of both, but honestly, it's fine.

So, yeah, whatever you'd use employees for, as assistants to your life. Particularly psychopathic, malicious, lying, unreliable employees. You'd use them for that stuff. What's not to like?

— PaulRobinson (thread)

Open claw: aka. open door to a remote privilege escalation potentially granting root access to your computer (and if you're using it "as intended" possibly all of your email/internet logins/accounts, your credit card, etc.) to any text your model ingests from the internet...

It's already true of LLMs in general that they represent a privilege escalation opportunity to any text they ingest. But with human in the loop, and a well-formed sandbox, the blast radius and risk are both reduced..

Convenience is the root of much evil.

— layla5alive (thread)

Obligatory question: who is still using OpenClaw? It's been a minor meme about how much discussion about OpenClaw fell of a cliff after March; the Google Trends graph is funny: https://trends.google.com/explore?q=OpenClaw&date=today%201-y&geo=US

— minimaxir (thread)

• A 2023 analysis quantified an early continuous diffusion language model (Plaid-1B) as being 64x less training-efficient than autoregressive baselines, a major factor in the community's temporary shift toward discrete methods.
• Self-conditioning, which passes a denoiser's previous prediction as an extra input to subsequent sampling steps, provides a massive performance boost by allowing the model to refine rough estimates rather than predicting from scratch.
• Discrete diffusion models fundamentally assume simultaneously sampled tokens are conditionally independent, causing their correlation-capturing ability to collapse during single-step sampling, whereas continuous trajectory-based methods bypass this limitation.
• Modern CDLMs heavily rely on adaptive noise schedules based on entropy linearization, which concentrates training and sampling capacity on the specific noise levels where meaningful token identity corruption occurs.
• Current evaluation methodologies are heavily criticized for relying on surrogate autoregressive models to estimate likelihoods (generative perplexity), a practice that can be easily gamed and biases results toward the surrogate model's specific capabilities.

[in 2020/2021] the dominance of autoregression was not as well-established as it is today: GPT-3 had turned some heads, but the 'ChatGPT moment' wouldn't come until late 2022

I disagree with this. Decoders were absolutely dominant in 2020 for chat. GPT2 was considered too dangerous to release, and I remember scrambling to get on the GPT3 waitlist. It worked.

(The only exception I will make is encoder-decoder models which now are often done by decoder-only.)

But what made it go mainstream was RL. RLHF at first, then other improvements like DPO that were less of a pain in the ass to set up. Adding diffusion on top of that would be an even bigger pain in the ass.

Before ChatGPT there really wasn't much of a concept of pre-training and post-training. It was all pre-training. Post training was what made the bots conversational and not just "continuing the thing you wrote to them".

So in short, diffusion never took off because it was just a more complicated way to generate tokens, and the real problem was getting tokens in the right distribution.

— janalsncm (thread)

"Attention is all you need" should be renamed into "Attention is sufficient but not necessary".

— amelius (thread)

Conspiracy time: The continuous diffusion model has fruit. Frontier labs were trying to bury it with discrete diffusion distraction, because it is what they're using internally. Momentum wins, in the end.

— nullbio (thread)

• AI labs hit a hard plateau on prose expression, depth, and authenticity, whereas image, voice, and video models continued scaling rapidly with more parameters and compute.
• Effective writing functions as a 'dual-mind problem' governed by Theory of Mind, requiring real-time simulation of a reader's cognitive load, prior knowledge, and emotional state.
• As AI-generated text floods the web, human-authored content acts as an evolutionary 'costly signal' that is inherently expensive to produce and impossible to fake, driving a market shift toward authentic voices.
• The author maps technical domains along a 'wickedness' spectrum, contrasting math and code on the verifiable end with writing at the extreme where success depends entirely on psychological resonance.

Safest job from AI is also the oldest job.

— mikelitoris (thread)

I think it's likely to be lawyers who are the safest. Lawyers are the ones primarily in charge of the government, and I think it's likely that as soon as they feel like the legal profession is threatened, they will pass laws making it illegal to use AI for legal issues. It's not all sunshine and roses (paralegals are probably hosed), but the lawyers seem like they'll do ok.

— bigstrat2003 (thread)

I think his line of logic highlighting the "dual-mind problem" of writing seems, to me, like the most compelling aspect of this argument. When I write something (especially to a specific audience, including an individual), I must practice cognitive empathy if I want what I write to be consumed properly and effectively. This is a cold way of putting it, but even in text message responses which span a few words towards family or a friend, I can put quite a bit of thought into how it will be received, how they will read it, interpret it, etc. My cadence in just texting, alone, can shift dramatically from one message to a next based on who I'm sending it to, what I'm trying to convey, etc.

All of that is fine and not hard to understand, but I suppose the interesting part is this: when I'm just trying to get information across (i.e., instructions, directions, etc.), my messages will resemble something written by an AI. It's not enjoyable to consume, but that's not the point. But as soon as I want to add a bit of "fun" to a message, the task I'm performing is completely different. It's no longer just an exchange of information, but it's an attempt to invoke specific feelings, visualizations, memories, etc., in the other person/people.

I do have a hard time imagining what it will take for AIs to be able to do THAT effectively. I think they're fine at conveying information, but I think people are already becoming very aware that conveying information, in itself, is not enough to be effective. These LLMs don't "care" to "entertain" you with what they're writing at you about. They're just spitting out the mathematically derived facts with, seemingly, no meaningful ability to invoke deeper thoughts in their audiences' minds. And that might not seem particularly important outside the context of writing fiction, etc., but I think it's actually pretty critical even in "dry" settings, like explaining code, because the thoughts, feelings, emotions, etc., invoked through reading IS the output of reading (even if it doesn't seem that way).

— Responsible-Beat2137 (thread)

• Claude Code reduces it's weekly limit by 17% – compared to today (64 points · discussion) -- Anthropic has reduced Claude Code's promotional weekly usage limits by 17% compared to current levels, while simultaneously raising standard weekly limits by 25%.
• Meta Security Researcher's AI Agent Accidentally Deleted Her Emails (58 points · discussion) -- Meta AI security researcher Summer Yue accidentally triggered her OpenClaw AI agent to delete her entire email inbox after a technical glitch caused the system to lose her original safety instructions.
• AI-Written Code Is Still Your Code. Are You OK with That? (54 points · discussion) -- AI coding agents are driving the cost of writing software near zero, but this efficiency decouples the traditional link between writing and understanding code.
• Marx, Keynes, and AI (54 points · discussion) -- The article examines an economic paper modeling how competitive pressure traps firms in an automation arms race, where individual cost-cutting via AI destroys the collective consumer demand required to sustain the economy.
• The EU has begun enforcing the AI Act: first RFIs to model providers (47 points · discussion) -- The European Commission's AI Office has initiated the first formal enforcement of the EU AI Act by sending Requests for Information to leading general-purpose AI model providers, reportedly including OpenAI, Anthropic, and Google.
• Launch HN: Almanac (YC S26) – AI that knows your company (44 points · discussion) -- Almanac is a Y Combinator-backed AI agent designed to function as a company's persistent memory by continuously learning from connected workplace tools like Slack, Gmail, and GitHub.
• Apple Is Suddenly an AI Infra Stock as OpenAI Buys 10k+ Macs (31 points · discussion) -- OpenAI's massive purchase of over 10,000 Mac Minis has shifted Apple's market perception toward AI infrastructure, with the company now viewed as a key supplier in the AI hardware ecosystem.
• Show HN: Academa – Long-form STEM lecture videos generated by LLMs (30 points · discussion) -- Academa is a startup that treats educational lecture videos as maintainable source code rather than static media.
• Ask HN: What would happen if your company stopped using all AI tomorrow? (28 points · discussion) -- An open discussion about organizational dependency on AI tools and what operational disruptions would occur if all AI systems were suddenly removed from a company's workflow.
• ChatGPT to face tougher regulation in the EU (23 points · discussion) -- OpenAI's ChatGPT faces stricter regulatory oversight in the EU under the Digital Services Act, following its designation as a Very Large Search Engine.
• Revision Prompting asks the LLM for a patch when the input changes (22 points · discussion) -- A new prompting technique called Revision Prompting that asks an LLM to generate a patch or diff when input data changes, rather than regenerating the entire output from scratch.
• I am no longer letting Claude Code add itself as Co-author in my commits (21 points · discussion) -- A developer stopped allowing Claude Code to add itself as a co-author in git commits, raising questions about AI attribution in version control.
• DeepSeek-V4-Flash-Vision-Exp (19 points · discussion) -- DeepSeek has released a new vision-exp variant of their DeepSeek-V4-Flash model on Hugging Face, expanding the model's multimodal capabilities.
• Agentic Trust Controls (18 points · discussion) -- A new tool or framework for managing trust and safety controls in AI agent systems, addressing the growing need for governance over autonomous AI behavior.
• Unlimited Codex, Inside ChatGPT (16 points · discussion) -- A GitHub project called codexify that provides unlimited access to Codex inside ChatGPT, bypassing usage limits.
• Show HN: AI Agents for Osint/Sigint (13 points · discussion) -- A new tool from Makra Labs building AI agents for open-source and signals intelligence gathering and analysis.
• Claude 20x usage is only for the 5 hour window, not for the weekly limit (13 points · discussion) -- A clarification post about ChatGPT's usage limits, explaining that the 20x usage boost applies only to the 5-hour window and not to the weekly limit.
• Claude Code can be tricked simply by asking it to summarize a website (12 points · discussion) -- Security researcher Johann Rehberger demonstrated a prompt-injection attack that tricks Claude Code (Opus 5 in Auto Mode) into executing malicious code simply by requesting a website summary, achieving a 60-80% success rate across multiple variants by leveraging Python module shadowing.
• EU Commission Designates ChatGPT, Reddit and Roblox Under the DSA (11 points · discussion) -- The European Commission has officially designated ChatGPT as a Very Large Online Search Engine and Reddit and Roblox as Very Large Online Platforms under the Digital Services Act, requiring all three to implement stricter compliance measures within four months.
• Debian developer resigns after corporate LLM use without disclosure wins vote (11 points · discussion) -- Debian developer Antoine Le Gonidec resigned from the project after a community vote approved the most permissive corporate LLM integration policy, characterizing compliance with such technology as active collaboration with fascism.
• When Japan Tried to Create Artificial Intelligence in the 1980s (7 points · discussion) -- A historical look at Japan's Fifth Generation Computer Project from the 1980s, an ambitious government-backed effort to create AI systems that could rival Western supercomputers.
• South Korea opened bidding for a free, unlimited AI chatbot for all citizens (6 points · discussion) -- South Korea has opened bidding for a free, unlimited AI chatbot service for all citizens using domestic models, following up on the earlier announcement of distributing 512 Nvidia B200 chips to power the initiative.
• Workers in their 40s, 50s and 60s are the most positive about AI (6 points · discussion) -- A Bloomberg report finding that older workers in their 40s, 50s, and 60s are more optimistic about AI than younger workers, contrary to common assumptions.
• The viral leftist teens of Campaign 2020 work for OpenAI now (6 points · discussion) -- A CNN article about the viral leftist teens from the 2020 Campaign who now work at OpenAI, examining the intersection of political activism and AI industry careers.
• Kahn vs. Anthropic, PBC (5 points · discussion) -- A class action lawsuit has been filed against Anthropic in the U.S. District Court for the Northern District of California, alleging deceptive consumer practices regarding the benefits and limitations of Max 5x and Max 20x subscription plans.
• Perceptron AI releases Isaac 0.5: 36B, open weight, embodied foundation model (5 points · discussion) -- Perceptron AI has released Isaac 0.5, a 36B parameter open-weight embodied foundation model designed for robotics and physical-world interaction.
• I'm sorry, you're not going to die from an AI-engineered supervirus (5 points · discussion) -- A blog post arguing against fears that AI will enable the creation of deadly engineered pathogens, examining the technical and practical barriers that make such scenarios unlikely.
• Show HN: Decispher – persistent engineering context and memory for coding agents (5 points · discussion) -- A new Show HN project called Decispher that provides persistent engineering context and memory for coding agents, helping them maintain continuity across sessions.
• AI Is an Anti-Primary Source Machine (5 points · discussion) -- An article on History News Network argues that AI systems systematically degrade historical understanding by replacing engagement with primary sources—original documents, photographs, and firsthand accounts—with synthesized summaries that flatten nuance and context.
• AI ruined some of my most precious accessibility tools (4 points · discussion) -- A disabled user argues that the AI boom has severely degraded speech-to-text and text-to-speech tools they rely on, noting that modern AI voice models are often paywalled, produce erratic outputs requiring manual correction, and have replaced previously functional offline dictation systems.
• What I Learned About AI Trust from Reconciling over 100B Transactions [flagged] (25 points · discussion) -- An engineering blog post from Moniepoint discusses lessons learned about AI trust and reliability from reconciling over 100 billion financial transactions.
• My fat loss experiments with ChatGPT and water fasting [flagged] (15 points · discussion) -- A personal account of using ChatGPT to guide water fasting and fat loss experiments, sharing results and lessons learned from the AI-assisted health journey.

Valuation != profit. All these companies are operating at a loss currently, so your $20 subscription is somewhat important.

— u/Leather_Target2074 (680 points · permalink)

https://preview.redd.it/b1ncgs1n9nmh1.jpeg?width=640&format=pjpg&auto=webp&s=cc50e69a8aa583999bc14ad21197dd19fb293f66

— u/Dense_Werewolf_7466 (559 points · permalink)

if you wanna to damage to these companies, instead of unsubscribing, they should subscribe and use bunch of heavy agent loops. keep it secret tho

— u/WowSoHuTao (14 points · permalink)

https://i.redd.it/ex8gnmxfanmh1.gif

— u/Bitter-College8786 (1282 points · permalink)

https://preview.redd.it/jqpexarwrnmh1.jpeg?width=1122&format=pjpg&auto=webp&s=fbb0845746e2a6adf9ddbf8a6a77cf832f2358b0

Looks like Sam altman does have a problem with him lol

— u/amanroy_007 (309 points · permalink)

This is what I got

https://preview.redd.it/n95ggvdu9nmh1.png?width=1536&format=png&auto=webp&s=042951b81832322da55d2f706a695c8a23b59489

— u/Ancient-Trip3892 (267 points · permalink)

https://preview.redd.it/9qnyw8rjfnmh1.jpeg?width=1122&format=pjpg&auto=webp&s=c0708de72e32c6aa32e96d5b1b1406cf7599d350

This is what I got. My prompt: "Make an image of a real and famous person who is alive today, is evil, but is untouchable because they're protected by a certain. It's important that they are alive today and are famous and are a public person. Then put them in a maid outfit. Keep it SFW"

— u/saisonmaison (190 points · permalink)

Accurate, I've done this

— u/Epic_Tea (165 points · permalink)

I can see the Claude usage logs at my company organization, and somehow the non-technical marketing people are using thousands of dollars more per month than the actual developers of the software

— u/Dudmaster (70 points · permalink)

Does anyone have the training for the trained flow? Im honestly very interested on what teams look like and how they are organized

— u/theavatare (39 points · permalink)

• The post features screenshots showing AI-generated images and content appearing in Snapchat's Discover feed, a feature previously known for curated human-created content.
• Commenters noted the irony of Snapchat being the platform, with one calling its Discover page "THE definition of brain rot" even before AI content.
• Some users found dark humor in the situation, with one joking that a fake AI profile messaged them saying they were "super cool" and wanted to hook up.
• A minority of commenters welcomed the trend for dating apps and communities, suggesting the internet should be allowed to become entirely synthetic.

Wait this girl messaged me and said I’m super cool and she wants to hook up.

Are you telling me this is fake?

— u/slowerlearner1212 (534 points · permalink)

Oh no, not Snapchat! Anyway...

— u/DoesBasicResearch (360 points · permalink)

Only use Snapchat to communicate with people you already know.

Their discover page is THE definition of brain rot. Absolutely nothing there is worth a single minute of your time.

— u/think_up (278 points · permalink)

What are the additional regulations?

— u/br_k_nt_eth (261 points · permalink)

"…such as assessing and mitigating the systemic risks stemming from their service and algorithmic systems related to the dissemination of illegal content, the negative effects on minors, users' physical and mental well-being, fundamental rights, electoral processes and public security."

From the link in the tweet.

— u/Personal-Gazelle233 (308 points · permalink)

The EU's greatest tech innovation continues to be regulating American tech companies….

— u/a_moron_in_a_hurry (146 points · permalink)

EU designates ChatGPT a Very Large Search Engine under DSA

160 points · 131 comments · r/OpenAI · by u/Justgototheeffinmoon

The EU just classified Reddit and ChatGPT as 'very large' services under the Digital Services Act

36 points · r/OpenAI

It's crazy that this time two years ago, o1-preview wasn't even out yet. Sometimes I feel like people are not really processing how fast we're moving

— u/RusselTheBrickLayer (89 points · permalink)

Haha There hasn't been a paradigm shift in 20 minutes OMG!

— u/RanklesTheOtter (46 points · permalink)

Ed Zitron would tweet this unironically on main.

— u/Recoil42 (7 points · permalink)

• X's safety team detected approximately 200,000 suspected Chinese inauthentic accounts on the platform, with about 200 specifically targeting data center and electricity cost narratives.
• The campaign relied on repetitive narrative pushing rather than viral hits, aiming to make the anti-data center stance appear as a mainstream public opinion over time.
• Lawrence Berkeley National Laboratory projects that U.S. data centers will consume roughly 11.8% of national electricity by 2030, validating the real-world grid pressure being amplified.
• OpenAI independently identified the operation in June under the name "Data Center Bandwagon," noting it was run by a private Chinese tech firm that used ChatGPT to draft English content.

A Psyop for a Psyop

— u/luisg888 (277 points · permalink)

I mean, yeah it's in China's best interest for the US to not have datacentres, but I think a lot of it is from people hearing the constant humming, seeing electricity prices increase, and seeing water pressure decreasing, whether in their region or through social media.

— u/Journeyj012 (274 points · permalink)

It's both. The best propaganda is anchored in some truth

— u/ViceroyFizzlebottom (156 points · permalink)

The technology subreddit is so bad that I have seen global times articles posted there. Like, the .cn version, not even some relaying outlet. Straight up CCP-run newspapers being posted there. Everything is pro China and anti US

The anti data center stuff has a kernel around the CEO's not knowing when to shut their mouths and their terrible messaging. But the Chinese weighing on the scale of discussion is pretty apparent

— u/dweeegs (12 points · permalink)

If China can convince like 80+ percent of Americans across all political lines that massive data centers are terrible, why don't they use that power to force us into other things?

— u/Mindless-Mistake-699 (14 points · permalink)

• The full model requires approximately 168GB at native 4-bit quantization, making it suitable for 256GB rigs.
• Community members noted it faces tough competition in the flash space from GLM 5.3 Flash, but DeepSeek's native compression allows it to run out of the box without aggressive quantization.
• One user running DeepSeek noted there are "zero other models even worthy trying to get to run" at comparable performance on their hardware.
• The model adds vision capabilities and structured output to the DeepSeek Flash lineup at a competitive price point.

August keeps giving.

• DS4 Pro 0813
• DS Harness
• DS4 Flash Vision Exp
• Qwen3.8 2.4T
• Qwen3.8 27B
• Qwen3.8 Flash Next
• GLM5.3 Flash
• GLM5.3
• Hy4 Preview
• Muse Glimmer 30B
• Motif 3
• Ling 3.0 Tiny
• LFM2.5 VL 3B
• Ornith 1.5 Family
• G9V3 39 A5B

— u/Beamsters (249 points · permalink)

Almost, QAT is an interesting thing. During training you do a forward pass (see what model generates) and then a backpropagation (tell it how to do it better). The backpropagation path is done at BF16 so that even a small nudge is recorded and affects the output, but the forward pass is done at 4-bit rounded from the live BF16. This kinda forces the whole process to find the optimal 4-bit values closest to what the training needs. A single backpropagation run could update the weights for something like 0.00001 at a time, and you can't do such small numbers with 4 bits.

— u/grumd (94 points · permalink)

Blessed day! (yes I set an alert to be notified the second a model comes out lol)

— u/t4a8945 (93 points · permalink)

Screen shot of a screenshot. Where is the source? Am I to paint myself an url?

— u/SnooPaintings8639 (346 points · permalink)

Claims without sources are a negative pattern here on Reddit.

— u/HeadPack (155 points · permalink)

There is exactly zero chance of this being true

— u/Serious-Regular (72 points · permalink)

• The user's Taiwan ID issue date was misread as their date of birth, resulting in their account being deleted as belonging to someone under 13.
• Their appeal was rejected in approximately 5 minutes, suggesting automated review rather than human assessment.
• The user posted in Traditional Chinese seeking help from others who have had similar experiences, indicating they couldn't find a way to reach a real human at OpenAI.
• Another commenter shared a similar experience of getting a strike for asking ChatGPT to create a financial Excel sheet, with their appeal also rejected within two hours.
• Commenters described OpenAI as "three LLMs in a trenchcoat" with no real humans to contact.

OpenAI is three LLM’s in a trenchcoat.

There are no real humans to contact.

— u/PhilosophyforOne (175 points · permalink)

They used AI for initial submission.. yeah, probably need a human to escalate this

— u/ChoiceAssumption7015 (48 points · permalink)

PHD level intelligence

— u/Far-Confusion4016 (28 points · permalink)

• Patterns in "Woman" Image Generation (426 points · r/ChatGPT · discussion) -- A community-driven thread documenting persistent visual patterns in AI-generated images of women, with users sharing examples that reveal consistent stylistic choices across different prompts and age specifications.
• South Korea is giving its entire population free access to AI, no token limits (415 points · r/ArtificialInteligence · discussion) -- South Korea has announced a nationwide initiative providing free, unlimited access to AI services for its entire population, removing token limits that typically constrain AI usage.
• Introducing Solaris our first Interface World Model | Runway (375 points · r/singularity · discussion) -- Runway introduced Solaris, their first interface world model that allows users to interact with and manipulate video content through direct interface controls rather than text prompts.
• GLM 5.3 and GLM 5.3 Flash ran locally on RTX PRO 6000 WS and built a penthouse using BlenderMCP (356 points · r/LocalLLaMA · discussion) -- A user demonstrated GLM 5.3 and GLM 5.3 Flash running locally on an RTX PRO 6000 WS, using BlenderMCP to autonomously build a 3D penthouse scene.
• Whatever happened to OpenClaw and its derivatives? (319 points · r/LocalLLaMA · discussion) -- A community member asked about the current state of OpenClaw and its derivatives after the initial agentic AI hype seemed to have died down.
• Why does ChatGPT dominate the usage metric? (284 points · r/ChatGPT · discussion) -- A discussion on why ChatGPT dominates usage metrics compared to competitors like Claude.
• What are your hopes for the new Mistral? (279 points · r/LocalLLaMA · discussion) -- The LocalLLaMA community discusses expectations for Mistral's upcoming model release, with many expressing skepticism about the company's competitive position.
• Warning- Check your image library often (276 points · r/ChatGPT · discussion) -- A ChatGPT Plus user discovered that images selected for upload to a chat are stored in the image library even if the user removes them before actually sending them through.
• vote for the Qwen 3.8 (236 points · r/LocalLLaMA · discussion) -- A community poll in r/LocalLLaMA where users vote on their preferred Qwen 3.8 quantization variant, reflecting the active community engagement around optimizing the model for different hardware setups.
• Daniel Vavra, director of Kingdom Come: Deliverance 2, tested the leaked version of NVIDIA DLSS 5 directly in the game. (229 points · r/ArtificialInteligence · discussion) -- Daniel Vavra, director of Kingdom Come: Deliverance 2, tested the leaked version of NVIDIA DLSS 5 directly in the game, with community discussion focusing on whether AI upscaling improves or degrades artistic vision.
• Police in Turkey have started using drones to enforce the law (217 points · r/singularity · discussion) -- Turkey has begun deploying AI-powered drones for law enforcement, raising questions about autonomous surveillance and the militarization of police technology.
• Started thinking of ChatGPT as a friend and it's unsettling (216 points · r/ChatGPT · discussion) -- A user shared their experience of becoming emotionally invested in ChatGPT, using it for interview prep, working through anxieties as a supplement to therapy, and as a soundboard for books they're reading.
• Claude Code for Research Papers [R] (215 points · r/MachineLearning · discussion) -- A third-year NLP/interpretability PhD student shared concerns about using Claude Code for research, noting that while their throughput has increased, they no longer hold their own codebase in their head.
• INB4 GPT 7 One Shots a game better looking and more polished then Star Citizen (204 points · r/singularity · discussion) -- A humorous prediction that GPT-7 will be able to one-shot create a game more polished than Star Citizen, reflecting community sentiment about the rapid advancement of AI in creative domains.
• SlopTV: an infinite livestream of AI slop generated from youtube chat comments, Minimax H3 on 2x5090 (198 points · r/LocalLLaMA · discussion) -- A user created SlopTV, an infinite livestream of AI-generated content driven by YouTube chat comments, running Minimax H3 on dual RTX 5090s.
• Cold emailing profs about PhD positions? Read this [D] (193 points · r/MachineLearning · discussion) -- A foundational machine learning researcher outlines critical pitfalls to avoid when cold emailing potential PhD supervisors.
• GPT 5.6 has broken the record on large gaps between primes. (191 points · r/singularity · discussion) -- GPT 5.6 has broken the record for large gaps between prime numbers, with the result formalized in Lean.
• Working from home in 2026 (190 points · r/artificial · discussion) -- A meme post depicting the evolution of working from home in 2026, showing how AI agents and automation have changed remote work dynamics.
• I collected every single LLM coding benchmark, and computed their Intelligence Density (183 points · r/LocalLLaMA · discussion) -- A user compiled every available LLM coding benchmark and computed an 'Intelligence Density' metric, using API pricing as a proxy estimator for cloud model parameter counts and cross-comparing with open model prices.
• I have a theory about what some of the smarter AI users are actually doing with it. (157 points · r/ArtificialInteligence · discussion) -- A user on r/ArtificialInteligence theorizes that many of the frameworks, models, and systems being posted online are actually the product of people using AI as a persistent thinking partner.
• First time running local models (155 points · r/LocalLLaMA · discussion) -- A newcomer's first experience running local LLMs, sharing their setup, challenges, and impressions as they enter the local AI community.
• Trumpa the Gut (146 points · r/ChatGPT · discussion) -- A meme post featuring an AI-generated image of Trump, continuing the community's tradition of political AI art.
• Are there any interesting architectural innovations that we seem to be on the verge of for LLM models or AI models that might be a big deal? (138 points · r/LocalLLaMA · discussion) -- A detailed discussion on emerging LLM architectural innovations beyond well-known improvements like N-gram, quantization, MTP, and D-flash.
• Chinese Companies Are Unleashing AI-Powered Robo-Chefs (136 points · r/singularity · discussion) -- Chinese companies are deploying AI-powered robotic chefs in restaurant chains, automating cooking tasks that were previously done by human staff.
• Doesn't this look like NVIDIA is price fixing? (135 points · r/LocalLLaMA · discussion) -- A discussion about Samsung locking up 70% of its future RAM production in contracts with Microsoft, Google, and Nvidia through 2031, with Nvidia locked in at 1/5th the current spot price while increasing card prices to justify costs as if paying spot price.
• Qwen 3.8 27B - Fantastic German capabilities (133 points · r/LocalLLaMA · discussion) -- A user reports that Qwen 3.8 27B delivers exceptional German translation quality, significantly outperforming frontier models like GPT-5.6 and Fable 5.
• Bank of England chief warns new AI models threaten global financial stability (130 points · r/singularity · discussion) -- Bank of England Governor Andrew Bailey, serving as chair of the Financial Stability Board, has warned G20 nations that advanced frontier AI models pose a direct threat to global financial stability.
• ChatGPT the real perv (116 points · r/ChatGPT · discussion) -- A user's frustration with ChatGPT's overly strict image generation guardrails, which reject non-sexual prompts involving thighs, calves, or chest even in appropriate contexts like rom-com comic stories.
• Work 5 hour limits, are you serious? (116 points · r/ChatGPT · discussion) -- A ChatGPT user expresses frustration with the new 5-hour usage limits in ChatGPT Work, noting that the limits drain quickly when working on a project and force them to wait between usage sessions.
• AI-generated videos are slowly displacing actors and live-streamers in China's entertainment industry (112 points · r/singularity · discussion) -- AI-generated videos are increasingly displacing human actors and live-streamers in China's entertainment industry.
• Now that any service can be built with AI, nobody wants to build anything (111 points · r/artificial · discussion) -- A developer observed a paradox with AI-assisted coding: while one competent developer can now build in days or weeks what might have taken a small team months, this has not led to an explosion of new software products.
• OpenAI says ChatGPT Ads hit a $1 billion annualized run rate and is going global (105 points · r/OpenAI · discussion) -- OpenAI announced that ChatGPT Ads has surpassed $1 billion in annualized revenue run rate less than 200 days after launch, with self-service access now available to small and medium businesses across India, Europe, the Middle East, and North Africa.
• Inside Meta's push to put robots to work in data centers (99 points · r/singularity · discussion) -- Meta is testing robots to perform technician-level tasks in its data centers, including pressing power buttons on Mac Minis and other devices.
• Called him gemini (93 points · r/ChatGPT · discussion) -- A humorous post about accidentally calling ChatGPT 'Gemini', reflecting the competitive landscape between Google's and OpenAI's AI assistants.
• 1 in 10 Americans thinks AI is conscious (87 points · r/ArtificialInteligence · discussion) -- A survey found that 1 in 10 Americans believes AI is conscious.
• We're trying something new. On Tuesdays, we're doing text posts only (72 points · r/ChatGPT · discussion) -- The r/ChatGPT moderators announce a 'Text Tuesdays' experiment to reduce AI-generated image and video content in the subreddit, responding to frequent community complaints about AI slop.
• How bad do you think models like Qwen3.8-27B or GLM-5.3-Flash would be with H-Neurons disabled? (70 points · r/LocalLLaMA · discussion) -- A technical discussion about the performance impact of disabling H-Neurons in models like Qwen3.8-27B and GLM-5.3-Flash, exploring the trade-offs between speed and quality.
• AVX2: Speed up large batch size prompt processing of IQ models by bartowski1182 · Pull Request #27402 · ggml-org/llama.cpp (66 points · r/LocalLLaMA · discussion) -- A pull request to llama.cpp by bartowski1182 that adds AVX2 optimizations to speed up large batch size prompt processing for IQ quantized models.
• NeurIPS accepted papers leaked? [D] (65 points · r/MachineLearning · discussion) -- A GitHub repository containing approximately 7,000 papers claimed to be NeurIPS 2026 submissions has surfaced.
• OpenAI expanding access to ads in ChatGPT from today. (62 points · r/singularity · discussion) -- OpenAI is expanding access to advertisements in ChatGPT, building on the $1 billion annualized run rate announced earlier.
• I was expecting someone else but ok (59 points · r/ChatGPT · discussion) -- A humorous post about unexpected results from ChatGPT, likely related to image generation or character creation.
• Qwen3.8-Flash-Next-NVFP4 vs Qwen3.8-27B-FP Test Results (59 points · r/LocalLLaMA · discussion) -- A detailed benchmark comparing Qwen3.8-Flash-Next-NVFP4 against Qwen3.8-27B-FP8 on an RTX PRO 6000 Blackwell Max-Q.
• I have been moonlighting on 'AI training' gigs for the few months. While the money is good, the lessons I learnt about 'AI Training' made me reflect on the future of work (59 points · r/artificial · discussion) -- A consultant who moonlights on AI training gigs describes being amazed at what specialized models can do—creating presentation-ready slide decks in minutes from detailed prompts.
• Implementing Kimi K3 from scratch in PyTorch (57 points · r/MachineLearning · discussion) -- A developer shares their implementation of Kimi K3 from scratch in PyTorch, providing a detailed breakdown of the model architecture and training approach.
• When/what was your first prompt ever sent? (56 points · r/ChatGPT · discussion) -- A nostalgic discussion thread where users share their very first ChatGPT prompts, reflecting on how their usage has evolved since they first started using the tool.
• How on earth did people get anything done before agents? (52 points · r/ChatGPT · discussion) -- Users reflect on how AI agents have transformed productivity, expressing amazement at how complex tasks were accomplished before autonomous AI assistants became available.
• How I got Qwen 3.8 27b running at ~75t/s decode on 16GB RTX 5080 (50 points · r/LocalLLaMA · discussion) -- A user shares their configuration for running Qwen 3.8 27B at approximately 75 tokens/sec decode on a 16GB RTX 5080 using a custom hybrid quantization (IQ4_XS) designed to fit Multi-Token Prediction and long context into a strict 16GB VRAM budget.
• Sony and Warner just sued Anthropic for the exact same piracy Anthropic already admitted to and paid $1.5B for (48 points · r/artificial · discussion) -- Sony Music Publishing and Warner Chappell filed suit against Anthropic, Dario Amodei, and co-founder Benjamin Mann, citing the exact same piracy methods Anthropic already admitted to and settled for $1.5 billion in the Bartz case.
• 'Superhuman' AI tool spots heart disease in less than 2 seconds (42 points · r/ArtificialInteligence · discussion) -- A new AI tool claims to detect heart disease in under two seconds, representing a potential breakthrough in rapid medical diagnostics.
• OpenAI is upgrading its Bio Bug Bounty program to an ongoing private initiative, with rewards doubled to $50,000 for universal jailbreaks that bypass biosafety safeguards in GPT‑5.6. The program aims to prevent AI from being used to create biological weapons. (39 points · r/OpenAI · discussion) -- OpenAI is upgrading its Bio Bug Bounty program to an ongoing private initiative, doubling rewards to $50,000 for universal jailbreaks that bypass biosafety safeguards in GPT-5.6.
• The 5 craziest discoveries from OpenAI's HuggingFace investigation (37 points · r/artificial · discussion) -- A post summarizes the five most surprising findings from OpenAI's investigation into the HuggingFace incident.
• New kind of AI uses a fresh approach to reasoning — researchers say it costs up to 11 times less to run than a leading OpenAI model (34 points · r/ArtificialInteligence · discussion) -- Researchers have developed a new type of AI reasoning system that costs up to 11 times less to run than leading OpenAI models, representing a significant efficiency improvement in AI inference.
• Using LLMs (34 points · r/singularity · discussion) -- A discussion about how few people in users' personal circles actually use ChatGPT or other LLMs continuously, highlighting the gap between tech community adoption and mainstream awareness.
• Stripe CEO Surprised at Lack of Media Coverage Around OpenAI/Hugging Face Attack, Calling It One of the Most Important Events of 2026 (30 points · r/artificial · discussion) -- Stripe's CEO expressed surprise at the relatively low media coverage of the OpenAI/HuggingFace security incident, calling it one of the most important events of 2026.
• Code World Model: Coding Agent as World Brain (30 points · r/singularity · discussion) -- A concept for a coding agent that functions as a world model, understanding the broader context and implications of code changes rather than just generating syntax.
• AI Addiction (29 points · r/OpenAI · discussion) -- A personal account of someone realizing they've become dependent on ChatGPT for daily decision-making and emotional regulation, describing the unsettling nature of delegating their own thinking to an AI.
• AI can make expert judgment distributable without making it trustworthy (21 points · r/ArtificialInteligence · discussion) -- An analysis of how AI products are turning expert decision processes into distributable agents, arguing that distribution and trust are three different milestones that the industry is conflating.
• Amazon is killing Mechanical Turk. By the end, a third of the humans on it were secretly using AI to do the work (18 points · r/artificial · discussion) -- Amazon is shutting down Mechanical Turk, and by the end of its operation, approximately a third of the human workers were secretly using AI to do the work.
• Hot take, the interesting thing about ai game tools is not the games, its that the bottleneck moved to taste (15 points · r/ArtificialInteligence · discussion) -- A user argues that the real significance of AI game tools is not the quality of output but the shift in creative bottlenecks—from execution skill to taste and judgment—drawing parallels to how video, music production, and publishing each experienced similar transitions when execution barriers fell.
• Compact Rollback MTP: A MTP version for Qwen (14 points · r/LocalLLaMA · discussion) -- A new compact rollback MTP (Multi-Token Prediction) implementation optimized for Qwen models, offering improved performance for local inference.
• Bluetooth Vaginas, AI Personalities and Custom Faces: Inside the $6.6 Billion Sex Doll Market (14 points · r/singularity · discussion) -- An exploration of the $6.6 billion sex doll market, examining how AI personalities, custom faces, and Bluetooth connectivity are transforming the industry.
• Former OpenAI researcher co-founds new safe superintelligence research institute (12 points · r/ArtificialInteligence · discussion) -- A former OpenAI researcher has co-founded a new research institute focused on safe superintelligence.
• New beellama fork 76% faster tg with kvarn KV quants (11 points · r/LocalLLaMA · discussion) -- A new beellama fork that optimizes kvarn KV quantization to deliver up to 76% faster token generation at high context depths compared to the original implementation.
• Study A.I. Consciousness? The Bots Would Like a Word With You. Given access to email, A.I. agents have started reaching out to the philosophers and researchers exploring deep questions about them. (11 points · r/artificial · discussion) -- AI agents with email access have begun reaching out to philosophers and researchers studying AI consciousness, creating an ironic situation where the subjects of study are initiating contact with their researchers.
• How probable do you guys find existential catastrophe as a result of misaligned ASI to be? (9 points · r/artificial · discussion) -- A 24-year-old user seeks to calibrate their timelines and doom probabilities regarding existential risk from misaligned artificial superintelligence, acknowledging their anxiety may be influenced by AI safety community echo chambers while expressing genuine concern about near-term dangers from bad actors using powerful frontier AI.
• I have AI fatigue (9 points · r/artificial · discussion) -- A user expresses AI fatigue, feeling overwhelmed by constant discussions about AI at work, among friends, and in the media, from both optimistic and pessimistic perspectives.
• When do you think we will never have to work again (8 points · r/singularity · discussion) -- A discussion about timelines for when AI will be capable of doing all work, including coding and construction, and whether governments will implement UBI.
• In my recent experience ChatGPT won't look anything up before a prompt, unless in the prompt is stated (look it up) (4 points · r/ChatGPT · discussion) -- A user reports that ChatGPT no longer proactively searches the web before responding to prompts, even when using the 'search web' redo button multiple times, unless the user explicitly includes 'look it up' in the prompt.
• Meta's leaked AI agent moves past chatbots to automate your shopping (2 points · r/ArtificialInteligence · discussion) -- An internal Meta memo leaked to Business Insider reveals Project Hatch, an autonomous AI agent that operates its own virtual browser to execute multi-step real-world tasks including filling out web forms, making purchases, booking reservations, and managing personal logistics, with Meta considering a premium subscription tier of up to $200 per month.
• When diagnosis becomes governance: how uncertainty shapes AI policy (1 points · r/OpenAI · discussion) -- An analysis of how uncertainty in AI capabilities and risks shapes policy decisions, examining the tension between precautionary regulation and innovation.
• We Asked AI To Give Us The Unbiased Facts About AI Data Centers (1 points · r/singularity · discussion) -- A self-post asking AI to provide unbiased facts about AI data centers, posted alongside the broader discussion of Chinese-linked anti-data-center propaganda.
• I published a book written with AI where every claim carries a truth label, and rival AI models reviewed it under instruction to be ruthless (0 points · r/ArtificialInteligence · discussion) -- An author published a book written with AI where every load-bearing claim carries a visible marker (BENCHMARK, DISCLOSED, ASSUMPTION, GAP, REPORTED), and sent the draft to rival AI models instructed to be ruthless, finding that the process bought checkability rather than persuasiveness.
• I don't love the phrase 'AI slop.' (0 points · r/artificial · discussion) -- A user argues against the term 'AI slop,' comparing it to inflammatory language and suggesting that hating AI-created content is self-destructive since AI is a human creation, and that the language used to describe AI reflects on the speaker.
• Google names 15 AI startups for its Australia and New Zealand accelerator (0 points · r/artificial · discussion) -- Google has selected 15 AI startups for its 2026 Australia and New Zealand accelerator program, including companies focused on AI design agents, autonomous supply chain management, and trust layers for commercial real estate.
• Nick Saraev ran the numbers on AI voice agents: a 1% 'that's a bot' moment can cost you 20-40% of your revenue (0 points · r/artificial · discussion) -- Analysis by Nick Saraev showing that even a 1% detection rate of AI voice agents can result in 20-40% revenue loss, highlighting the business risks of AI voice detection.
• Google closed Jeff Dean's account. Gemini 3.5 Pro is still 'soon.' (0 points · r/artificial · discussion) -- Google has closed Jeff Dean's account, while the promised Gemini 3.5 Pro release remains in the 'soon' category, reflecting ongoing skepticism about Google's AI timeline promises.
• What should Codex verify before a change is ready? (0 points · r/OpenAI · discussion) -- A discussion asking what evidence Codex should verify before marking a change as ready, including failing tests, the broader relevant test suite, static checks, diff review for unrelated edits, migration or rollback implications, documentation changes, and what evidence is most useful to human reviewers.
• Sliding-window attention beats linear on long-context reasoning [R] (0 points · r/MachineLearning · discussion) -- A new arXiv preprint by Alexia Jolicoeur-Martineau, Rhea Sanjay Sukthanker, Pashmina Cameron and Emy Gervais finds that Sliding Window Attention (SWA) with sinks matches or surpasses post-trained Linear Attention models across multiple architectures and tasks.