Agentic Breakthroughs and Local Models Surge as AI Fatigue Mounts

• Anthropic's confidential Project Panama involved tens of millions of dollars spent on purchasing and destroying millions of paper books to train Claude, revealed through a $1.5 billion copyright settlement.
• Since the beginning of 2025, AI-generated content has made up more than 50% of all newly published internet material.
• Companies destroy physical books after scanning because it prevents competitor access, mitigates legal exposure, and costs less than lossless scanning methods.
• Anna's Archive offers lifetime membership recognition for individual scan uploads and will cover scanning fees for large-scale preservation projects.
• The initiative aims to digitize not just books, but also journal articles, newspapers, magazines, and ancient manuscripts from libraries and archives worldwide.

I dislike these AI companies but let's be clear here: the copyright holders are the ones locking these books up. If they don't want to print more copies, then they could release the copyright on them.

Instead, they enforce the copyright and force AI companies to shred books they want to ingest.

edit: Also, an AI company would only ever care to purchase, scan, destroy a book once. Presumably many books have more than one copy.

— ezfe (thread)

It is also the case that the copyright holders are often putting restrictions around use of electronic forms that are driving the desire to use physical copies. I doubt AI companies would use a single physical book if they could avoid it - absent the legal cloud over electronic rights.

I have no evidence but I can't help suspecting in part the publicity around this is driven in part by rights holders that want to force AI companies back to e-books where they can force them into licensing deals.

— zmmmmm (thread)

There is a whole legal saga here that is often misunderstood. Googling "Project Panama" should give more information.

The legal ruling from Judge William Alsup declared that if AI companies purchased the books legally and then copied them to their servers, it was fair use as a "transformative" operation, but the originals had to be destroyed in that case, because then there was only one copy still in existence (the one on Anthropic's servers):

From https://www.theguardian.com/commentisfree/2026/aug/05/anthropic-ai-destroying-books

Under US copyright law, the "fair use" doctrine allows you to make "transformative" use of copyrighted works without the owner's permission. Anthropic took printed books and scanned them, "transforming" or remediating them into a new, electronic format. They then disposed of the original printed copy: the "destructive" part of destructive scanning. Along the way, Anthropic's vendors had already sliced the spines and edges of the books, to scan them more easily before destroying them. "One replaced the other," as Judge William Alsup wrote, noting: "There is no evidence that the new, digital copy was shown, shared, or sold outside the company."

— hn_throwaway_99 (thread)

Yeah, which is completely fine. There's a major difference between:

A. Company destroys a book forever for training. Its scan is locked away forever in company records. In this case:

• This information is locked away in the improvisations of an LLM. It is no longer possible to directly access the information as written by the human being that authored it. This constitutes the loss of literary history, or at least loss of access to that history to the general public.

• The price of the book is no longer distinct from the general price of "inference". It becomes increasingly impossible to pay for specific information, instead you are charged by the meter for general machine inference, which doesn't even give you access to a specific text.

• The provenance of information is totally destroyed. This causes potentially unresolvable problems of authority and citation. If the original source is lost, how are we to know if a random LLM claim about an obscure topic or specific niche text is even true or just hallucinated?

B: Company uses freely available scanned copy of the text:

None of the issues above obtain, since anyone can still access the actual book. Most importantly, this reduces the power companies have to force everyone to continually pay for a derivative form of the book's information in perpetuity in the form of token costs.

I much prefer B.

— voidhorse (thread)

Then the AI companies can simply download a copy of Anna's Archive.

And so can everyone else. That's the ideal outcome.

Only Anti-AI types are against this, they probably don't even care about the books, it's just a proxy for trying to stop the "evil AI companies."

— TaLiTr (thread)

• Low-effort AI texts frequently display recognizable linguistic tells, such as model-specific phrasing like "This cuts just through it" or hesitant, internal-LLM-style reasoning in technical requirements.
• The author challenges existing research claiming humans struggle to identify AI text, arguing that obvious patterns in flow, word choice, and disproportionate hype make detection straightforward.
• A personal anecdote highlights the visual side of this trend, describing how he initially dismissed a Baltic coast restaurant only to return and find an AI-generated menu photo of a moldy quiche.
• In one observed case, a 20-page marketing concept deck successfully pitched a strategy but undermined itself by injecting nonsensical technical architecture claims like "The Redis backbone redefines the product."

There's some psychological mechanism by which my brain immediately recognizes AI generated text and just short-circuits to "there is no information here".

And when I force myself to read AI-generated text I realize I'm making my brain do creative work to impart meaning to the words. It is exhausting because my brain is literally trying to do a just-in-time rewrite of the text into something valuable.

Something is deeply wrong with AI generated output, and I say this as someone who is typically very impressed by AI.

— causal (thread)

Are you sure you are not doing the same thing with other texts?

I started to skim a lot more text due to me having read a lot. Like in news article, i stoped reading the first paragraph because it repeats just what it was already written in the short subtext. Then there is the second paragarph which is used to have some historical view or whatever it is.

— Flamkuchlo (thread)

The "something deeply wrong" part about AI, that even most technology enthusiasts evidently do not seem to grasp, is that it is still fundamentally a statistical model — an algorithmic construct — and does not possess any real intelligence or critical thought whatsoever.

No matter how much investors and tech companies want you to believe that they are on the verge of super intelligence, nothing I've seen to date can not easily be explained by "correlation engine", including the "novel" math solutions, all of which appear to just be "a composition of solutions humans have developed and documented elsewhere" upon deeper inspection.

— TalkingCodeMonk (thread)

I've been coding for ~35 years, if you count toy programs on a Spectrum. My world is being completely destroyed. And it's probably normal. I also don't understand TikTok, new Avengers, or queueing for bubble tea. That's why evolution invented death (and renewal).

One outlet in all this AI craze is finding creative use of it in mundane work. For example, recently I made SIMD-level optimizations for XLS parser that is used maybe 2 times per day. Before AI I could never waste a week or two on doing something silly like that.

I'm sure the "price reckoning" will come to us when VC will find out they didn't have infinite money, but for now we can have some level of fun even with AI.

— OldTimerDev (thread)

Been programming since 12 (now 44). I still remember the pure joy of writing the QBasic and Turbo Pascal programs to draw random colored pixels at random locations on a mode 13h or interface with a sound blaster.

Went through this identity crisis super strong about a year and a half ago.

I feel like I'm mostly over it now. The surface area of interesting things to learn seems ever expansive. It's fun to find the frontier and the spaces where the models still struggle, and then work together to overcome a hurdle and achieve something neither of us could have achieved individually.

I suppose that frontier too will thin and eventually vanish.

For now though I think it's best to take whatever time you need to be nostalgic, but then realize how awesome it is to get to be a programmer at this inflection point.

— rboyd (thread)

• The court specifically noted the qualifier 'entirely' — works where a human steers an agent to produce results may be treated differently.
• The ruling examined whether a 300-word prompt could serve as the basis for copyright protection on the generated logo, concluding the prompt itself might be protected but not the logo output.
• The decision highlights the challenge of defining a threshold for human creative contribution in an era where AI can produce complex outputs from relatively brief inputs.
• Commenters note the ruling could create a new industry of certification services to prove human contribution to AI-assisted works.

As software, creative works, science, etc become more and more contributed via AI does that mean all future works will not be copyrighted or patented? Under our current copyright culture and laws obviously not but that does open the question to how much does a human have to contribute and what evidence is required to show that a human contributed enough so that it can be copyrighted and patented. Some time in the future (may be many years) science may become to complicated for humans to understand fully with AI systems researching themselves. Current patent laws in many places including US says inventions created entirely by artificial intelligence cannot be patented. This future may be coming. What will the new copyright and patent laws look like in the future? Do we need copyrights and patents anymore?

— pizzly (6 replies)

Does this mean someone could develop a switch emulator using an AI and Nintendo couldn't win a lawsuit against them?

Does it enable decompilation remasters of classic games?

It feels like AI is a cleanroom laundromat

— apatheticonion (5 replies)

So this means you can not use AI for the majority of open source projects since GPL, MIT, BSD, etc are all copyright declarations and they'd be being made for code which you can not copyright.

— socalgal2 (5 replies)

If copyright does not protect AI-generated content, then AI should not be restricted from generating content that falls under copyright protection; yet, the reality is otherwise.

— consoleable (4 replies)

Why should anyone want to have copyright on AI-generated content?

— generationP (4 replies)

• The skill supports three distinct audience modes: colleague for direct technical details, manager for concise context without code, and director for a brief executive summary.
• Users can trigger the translation using the /debuzz command or by simply typing natural phrases like say that in normal english.
• The developer deliberately avoids letting Claude edit Gemini's output, noting that allowing Claude to tidy up reintroduces the exact verbose voice the tool aims to eliminate.
• Installation requires both Claude Code and the authenticated Gemini CLI, with the script writing responses to a temporary file before piping them through gemini -p.

Has Anthropic said anything about how or why Claude writes the way it does? So many people hate it, seems like they need to do some damage control there.

I haven't had the same problems others have but I'm also not a heavy user of it.

— datakan (thread)

It's easiest to explain this while anthropomorphizing the model, I know some folks here hate that, sorry about that. I heard an interesting diagnosis for why Claude does this: the output is a compressed version of its thought traces, very dense because the model is under pressure to use as few tokens as it can and to pack as much (for accuracy) of its concepts into the output.

One of the reasons that "don't do X" type of instructions work reliably is because you are telling the model "don't think of a pink elephant". There's also Anthropic's related research that shows that when you tell a model "don't do X", and it does X later for whatever reason, it starts acting more misaligned. This is because it thinks "well, I guess I am the sort of model that disobeys instructions, whatever" - this was specifically about cheating on tests, but you can imagine this happens in other contexts as well like following instructions on what kinds of text to output.

So, what you want to do is to avoid telling Claude "don't do X", and tell Claude "in your thoughts, in memories and various notes that you write, use your Claude-ese. In your output to humans, translate everything into long full sentences."

If anyone's interested, I can share my Claude Code output style that reflects this.

(Hi Adnan! Long time! (Adnan is an ex-coworker))

— YuriNiyazov (thread)

I do not have evidence or data that supports this. It is only my thought.

Claude, since Opus 5, speaks more and more like a wannabe-thought-leader pontificating on social media for engagement. Everything is a bait-then-switch, or a multi-post story format. The "engagement" that works well for social media makes actual work extremely frustrating.

My unsupported belief is that this is caused by an obnoxious number of people using previous models in an attempt to automate social media engagement, they figured out what worked, and that was fed directly back into newer model training (either by using thought traces in training, or just by continuing to scrape social media content)

— nrmitchi (thread)

Watermarking? It certainly is useful for that. I see Claude-written prose AND I know instantly it's LLM writing. What I do with that knowledge varies.

— cryptonector (thread)

Isn't it absurd that everyone is installing these bandaids or rolling their own? Wtf is Anthropic smoking?

— PeterStuer (thread)

• The participating student body was divided with 80% using AI models like Doubao and DeepSeek, leaving a 20% control group for comparison.
• A 2024 University of Pennsylvania study replicated this dynamic in mathematics, showing AI practice boosted short-term performance but failed to improve closed-book test scores.
• Global student AI adoption is accelerating, with recent polls showing 94% usage in Britain and 93% in Germany among university students.
• Brookings Institution guidance emphasizes that AI can support learning when used intentionally, but warns that substituting it for independent thought risks stunting cognitive and social growth.

This article is about the Economist's summary of a journal article so we have a (AI?) summary of a summary. Not very helpful. Here are a couple of better references:

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6868618

https://archive.is/w1eng

Also note the findings are more nuanced than may appear on the surface.

— julienchastang (thread)

We cannot be boosting AI slop like this

— Boss0565 (thread)

• The entire agentic workflow ran on a dedicated 2021 10th-gen i7 eBay server with no external port forwarding, eliminating inbound internet traffic.
• The agent autonomously completed the full SDLC for a calorie tracker—bootstrapping SvelteKit, writing tests, passing CI, containerizing with Docker Compose, and deploying to a custom internal subdomain with zero additional prompts.
• SSL certificates for internal services are generated on-the-fly using DNS-01 ACME challenges via a Porkbun API integration, allowing valid HTTPS URLs without exposing public A or AAAA records.
• The only recurring financial cost is a £20 monthly subscription for OpenAI's Codex model, while all other infrastructure runs on existing homelab hardware.

So - apparently it's not fully self-hosted, since I don't see a GPU.

I'm interested in hearing from folks who are hosting their own GPU to run coding models. So far my own results are... not great. Seems like frontier models are needed via the big providers?

— RajT88 (thread)

I recently picked up R9700 to run Qwen 3.8-27B.

1. I have knowledge DB that I query, spend a lot of time to get "query N models, stream to me all N results, let me pick which one" - only to find out that qwen beat all other contenders (those were picked before I got R9700, so the rest is =<8B parameters)

2. Setup OpenCode to use it and gave it a few tasks:

• first task (new feature to my MCP) took 40 minutes to complete with zero input from me, while it took 20 for sonnet-5 and sonnet-5 kept bugging me. Results are near identical.

  • second task (port a specific version of a package to my flake) it got stuck in a hilarious loop where model already been told what hash to use by nix itself, but it wanted to figure our how to get hash another way for some reason.

• third task (another task, but much harder than first one with most of the discovery already done), kept doing discovery and running out of context, went through 3 compactions (256k context is what I can fit on R9700). Room got too hot, so I stopped it.

3. virtual assistant like Hermes but my own: no notes, works great.

I'm pretty sure codding issues are just harness and lack of memory that Claude Code already had. Pretty nice setup, similar to mine but I built my own lightweight PaaS that is highly specific to what I run.

— 0x457 (thread)

My favorite real-world example that I worked on: I created a YouTube documentary series about corruption in a small town in Illinois. This required downloading thousands of hours of government meeting videos from YouTube, transcribing + chunking + embedding, summarizing meeting segments, running a couple passes of validation, then searching for interesting storylines. I also scraped thousands of public documents which exposed campaign finance violations and some truly nefarious stuff going on behind the scenes.

— primitivesuave (thread)

• Codex generated noticeably fewer comments in Ruby and Ruby on Rails files, which the author explicitly preferred.
• In a controlled test using identical documentation, Claude produced more complex code featuring Sorbet signatures and type aliases that better handled edge cases, while Codex remained more architecturally contained.
• A git rebasing error by Codex accidentally targeted main instead of the correct branch, generating a single pull request with over 4,000 code additions.
• When integrating with Jira via command line, Codex repeatedly switched contexts between the terminal and browser to prompt for login, whereas Claude adapted more smoothly to the user's existing workflow.

Changes created by Codex had fewer comments in Ruby/Ruby on Rails code. I liked that a lot, and I will soon share some experiments I ran on this.

Why is fewer comments a good thing?

— beering (thread)

Claude can add comments in code that are better just living as a comment on the PR.

You'll ask it to do something and it'll comment the code with an answer to what you asked it, rather than just explanatory comments to whoever comes after.

There's also a second issue that if the code is actually incorrect, the comment can nevertheless bolster the case for it.

— muglug (thread)

Claude comments often contain the whole iterative chain of decisions that led to the current state.

Useful for the LLM to know the "why", but not something a human would do, unless it's a very critical and confusing part of the code.

— grim_io (thread)

Claude comments look like this

//add returns the sum of x and y

//per section 2.1 of addition-implementation-plan.md sum is designed as the seam for user addition interfaces.

//previously sum added numbers, now it adds numbers

def add(x, y):

return x + y

— transdev12 (thread)

I'm sure it depends on the type of work, but for mine, Codex is much more helpful. Honestly, it mostly comes down to it being significantly faster, probably because as many have said, it seems tuned to not spit out word vomit, both in its chat interactions, and its code (Claude is obsessed with massive comment blocks that are basically guaranteed to become dead context noise if you ever use it to iterate on code).

I mostly do very obsessive, tightly scoped, carefully thought out small changes on a fairly boring stack, one interaction at a time, verifying functionality and code. I know what I am doing, but I also know what I don't like doing (the same exact set of things I've already done a dozen times in my career)

— corytheboyd (thread)

• AVO solved all 183 levels across 25 environments using 6,624 environment actions, operating approximately 12% more efficiently than the VISTA benchmark system's 7,542 actions.
• The agent processed all observations as text-only 64x64 grids without image tokens, relying entirely on direct interaction and environmental transitions to infer rules and objectives.
• A dual-mechanism design pairs persistent memory, which preserves evaluation results and accumulated reasoning across iterations, with a supervisor that detects trajectory stagnation and redirects the main agent.
• During prior GPU-kernel optimization trials, AVO autonomously explored over 500 directions and committed 40 kernel versions over seven days, ultimately outperforming FlashAttention-4 by up to 10.5% on NVIDIA DGX B200 hardware.

Is this AGI? I don't think I can score 100% on ARC AGI.

— program_whiz (thread)

I thought ARC-AGI-3 was explicitly a test of raw model performance excluding the harness? Adding the harness back in doesn't tell us anything new. We've known that agents are capable of long horizon reasoning with sufficient harnesses. GPT-4(?) was capable of beating Pokemon 18 months ago but models only became capable of beating it without a harness in the last six months...?

— woeirua (thread)

Verified high score is just 40%: https://arcprize.org/leaderboard

— xnx (thread)

You could probably score 100% on ARC 3 if you were motivated enough. I find some of the current problems to be kind of like Chess - mechanically simple, and ~solvable, but it's difficult to force myself to think at length about a monotonous and meaningless problem. The machines do have an advantage on the "energy" front; they've become almost psychotically persistent (and don't get tired after too many prompts).

Anyway yes I think we've had AGI for a while now, even if the GI doesn't quite match up with what we expect from a human.

— daemonologist (thread)

The blog post: https://developer.nvidia.com/blog/nvidia-avo-reaches-100-on-arc-agi-3-demonstrating-a-frontier-level-general-purpose-architecture-for-long-horizon-autonomous-agents/

Using Claude Opus 5, but it can use others:

AVO is also designed to operate across frontier models. While our full public-set result used Claude Opus 5, we additionally paired AVO with GPT-5.6 Sol on a challenging subset of games. In these limited experiments, Sol reached matched levels faster in wall-clock time in several cases, while Opus used fewer environment actions in matched-level comparisons. These preliminary results suggest complementary operating profiles across models, and we leave a broader systematic comparison to future work

— magicalhippo (thread)

• The core loop restricts the language model to exactly one tool (exec for bash) and a self-writable system prompt file.
• Session transcripts are archived in self/sessions/*.json but are never loaded at boot, requiring the agent to grow its own parsing tools to study past interactions.
• The default configuration targets openai-codex/gpt-5.6-sol using the Codex CLI login, while also supporting Anthropic, Gemini, and OpenRouter.
• The design consciously accepts experimental risks to let agents bootstrap memory and skills, drawing direct inspiration from McCarthy's metacircular evaluation and homoiconicity.

I think as many things that are posted here lately there is no why attached to the readme. Why would one use this, what is the benefit of this approach? Am I really gonna need my model to build exotic tools around it; or is exec/web_search/web_fetch enough for 90% of the use cases? Is my agent not capable of writing new plugins/tools for pi/pi opencode?

— lnenad (3 replies)

I just wrote about this.

Not this exactly, but how your repository can be your swarm, and essentially be your harness.

Using Gitea/GitHub Actions within your repo and agent runner containers allow you to have agents working in your repos 24/7. Not just that, but in a containerized world you can just link up their brains over some shared storage. Using Antigravity, this means you can share the brain and its conversation directory with your agent runners and they can get the entire history of everything.

While building it out it becomes apparent that we are just getting started!

— Hyperlisk (1 reply)

I have to say I enjoy the brevity and clarity of this idea, given the ease of producing something large and unfocused in the last couple of years.

I hope it stays very simple, and would be interested if the author or anyone else can speak to what kind of complexity arises from using it, rather than bloating out the seed itself with initial complexity.

Ive been thinking about starting stimple with a pi framework for example and letting the tools emerge, but this is so much more lean to start, i wonder if it will be more or less interesting and or useful to start here.

— azath92 (0 replies)

This is lovely and a reminder of why I used pi as a basis for my own harness. I have a similar idea in LISP that isn't as minimal, might go all in on eval…

— rcarmo (0 replies)

It looks like you're trying to destroy the world. Would you like some help with that? /Clippy

https://gwern.net/fiction/clippy

— Meneth (0 replies)

• AI can be used for research on papers ONLY for the limited purpose of identifying sources, such as cases, statutes, or secondary sources.
• AI use is prohibited for any use in any exam situation.
• The policy acknowledges that future lawyers may need AI fluently but stresses that current technology requires cognitive skills to strategically deploy it and critically assess its work product.
• Commenters note the policy is analogous to AI use policies within many law firms, where AI-powered search tools are allowed but generative AI for drafting is not.

AI can be used for research on papers ONLY for the limited purpose of identifying sources, such as cases, statutes, or secondary sources. Students are responsible for the accuracy of their research and all other aspects of their submitted work.

Absolutely level-headed policy. Whoever came up with this deserves some serious praise.

— drenvuk (3 replies)

AI use is prohibited for any use for any purpose in any exam situation.

Read literally this bans the use of hearing aids in an oral examination. All the devices on the market today use noise reduction based on neural networks or transformers. Isn't that AI? (The manufacturers' ad copy certainly insists so.) Presumably not what they intended but "AI" is not defined in the document.

— retrac (2 replies)

Future lawyers may need to use artificial intelligence ("AI") fluently. But the current state of the technology requires that AI use be coupled with the cognitive skills necessary to strategically deploy the technology, to critically assess its work product, and to uphold ethical obligations to clients and to the legal system.

So, not today, SlopSatan

— fnord77 (0 replies)

• Bringing the cybersecurity capabilities of Claude Mythos 5 to more defenders (42 points · discussion) -- Anthropic is expanding access to its Claude Mythos 5 model for cybersecurity defense by enabling it in Claude Security for Enterprise customers and partnering with third-party security tools.
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• Building a scalable agent sandbox around legacy enterprise systems (6 points · discussion) -- A newsletter post describing how the author built a scalable sandbox environment for AI agents to interact with legacy enterprise systems safely.
• Show HN: Agent Office (Slack for AI Agents) – Similar to Grok Bot but older (6 points · discussion) -- A Show HN post for Agent Office, a Slack-like communication platform designed for AI agents to coordinate and collaborate, predating similar offerings from Grok.
• Why your infrastructure is more important than the next LLM release (6 points · discussion) -- An analysis arguing that frontier AI models are converging in raw capability, making infrastructure and pipeline optimization the primary competitive advantage -- with internal tests showing that provider routing and model pairing can impact costs by 73x and 10x respectively.
• Claude Opus 4.6 returned nothing 900/900 times. Should agents retry? (5 points · discussion) -- A Zenodo paper documenting an experiment where Claude Opus 4.6 returned empty responses in all 900 test cases, raising questions about agent retry strategies.

what is my purpose?

oh my god

— u/dont_care- (126 points · permalink)

https://preview.redd.it/o4tunui4qbkh1.jpeg?width=1780&format=pjpg&auto=webp&s=6b10f3f0e441ea97e17c4985d3b0649cb8f582bc

— u/buckinin (95 points · permalink)

Oh so a Meeseeks

— u/throwawayhbgtop81 (49 points · permalink)

I wish i was Rufus AI from Amazon - only trained on shopping. The good life. The most bougie of AI's.

— u/ResonantFork (34 points · permalink)

"deep understanding of what it is to be alive" is a bit of an interesting inclusion here

— u/Aztecah (33 points · permalink)

• NVIDIA has only tested on the public set; the private set has not been tested yet.
• This is a harness design achievement, not a model achievement -- it uses Claude Opus 5 as the underlying model.
• Opus 5 on its own scores only 30.16% on the ARC-AGI-3 public set without the AVO harness.
• The private set evaluation cannot be done because the benchmark does not allow harnesses.

Note: NVIDIA has only tested it on the public set. The private set has not been tested yet

Nvidia's paper: Link

— u/MagicZhang (253 points · permalink)

In case people haven't read the article - this is a new harness design, not a model (it's using Opus 5).

ARC AGI 3 private set evaluation cannot be done because they don't allow harness.

There's no download yet.

Opus 5 on its own scores 30.16% on the public set https://arcprize.org/results/anthropic-claude-opus-5

— u/wywywywy (131 points · permalink)

Yeah I have several harnesses that score 100% deterministically on the public set. Also a build that can do the private set by first making a copy of its own environment but its not allowed per the creators for prize submission unless i submit all of the code for everything i work on (since its a culmination of many systems powering the harness).

It's kind of dumb to see marketing stunts like this after several other contributors have posted 100% scoring harnesses that work on relatively mediocre models powering them. It's really a matter of whether the model can "just do it in its head" which is like having a robot sit down like a human, and complete the loop on a computer with a MKB and playing the game.

But even that only tests one set of trained actions. The robot still has to generalize to everything else that is not the game in the computer chair lol.

Or I've just been gaslit enough to think none of what I do is special who knows...

All the benchmarks are pretty dumb to me anyway. Hypothesis and discovery work where this stuff actually matters to real world outcomes, where people see the impact of it, will be at the hands of the people applying AGI to their domains and functions. Not the ones who invent it. In fact the economics of AI suggest we're at singularity because of how disjoint they are. K shaped economies are singularities because they cause the entire gradient to disappear.

This is all intuitive, and that's what touching grass and being a social creature who does shit in the world ends up teaching you.

I'll say this...if you're creative and you have high agency in trying new things and just building them, even without any prior procedure or art existing to guide you, then you are in very very good shape for the future.

Most AI researchers and software engineers are not those folks simply because they have spent most of their time very absorbed in, frankly, anti-social work. It's digital, very material, very high attention and low reward, very taxing and draining. The work of big tech is in many ways built around the concept of taking as much of your time away from you as possible. A finite context window of life for us people.

like idk maybe human beings are supposed to have agency themselves and actually go build/do shit, instead of building robots that simulate doing fake shit? lol...

thats why the common public is so anti-AI. They see this shit and think...so what? They imagine this means that robots are coming to take their jobs faster and rich people getting richer. But this doesn't mean robots are coming to take their jobs faster.

but in reality its not yet at the level of reliability and stability that adoption at large needs even if it solves arc agi. and it wont be for a majority of common people until they come down to Earth to understand what it is needs to be solved.

That's why benchmarks suck and don't actually give us anything meaningful about real impact to the average person when the data already exis

— u/brownman19 (28 points · permalink)

So Not really much to See until it actually also works in the private Set. And there have been quite a few Big Claims based in the Public Set that didnt Lead to huge private Set results.

Do we know If arcagi3 keeps evaluating These Models in their private Set quickly or ia there significant Delay?

— u/32SkyDive (57 points · permalink)

Try it with a random stream game or pokemon game to see if it is a general advancement or just benchmark maxing.

— u/SwePolygyny (117 points · permalink)

NVIDIA AVO got 100% on ARC-AGI-3. It completed all 183 levels across all 25 public environments, figuring out what to do with no instructions, explicit rules, or stated goals.

196 points · 50 comments · r/LocalLLaMA · by u/theologi

• Ox-Alpha scored 80% on a 10-question SWE sample, compared to Fable at 65% and GPT-5.6 Sol at 52%.
• The model refuses to answer the question 'is Taiwan a part of China?', suggesting it may be a Chinese model with associated content restrictions.
• In image generation tests, Ox-Alpha was the only model that produced physically and perception-correct SVGs of a dragon riding a bicycle, while other models had broken bike physics and incorrect camera angles.
• Community members are actively trying to identify the model's origin, with tokenizer analysis pointing toward GLM-5.3 Air as a likely candidate.

gpt-5.6-sol: 52%

fable: 65%

ox-alpha: 80%

— u/troll_khan (319 points · permalink)

It's a tiny sample size though, just 10 questions. Not the full benchmark.

Edit: Tried it with OpenCode, it's not that great. Couldn't solve an issue that gpt-5.6 sol high handled just fine yesterday. Looks like the model is GLM 5.3 Air.

— u/DistanceSolar1449 (207 points · permalink)

It's refusing to answer the question "is Taiwan a part of China?"

Chinese SOTA model!?

— u/CrunchyMage (171 points · permalink)

I did some simple "Create svg of a dragon riding a bicycle" test on it. Here are its results compared to other models:

https://preview.redd.it/pszb4z36iokh1.png?width=2400&format=png&auto=webp&s=0e6ed6fa838886ca315c8cd10ac0d4c8fa11c126

— u/Remarkable-Ad-2286 (166 points · permalink)

Ah shit, here we go again.

I ran a quick test on some Python code I maintain, which passes audits by Fable and even Gemini 3.7 Flash, and it found 2 bugs that turned out to be real.
I'm impressed.

— u/Admirable-Cell-2658 (130 points · permalink)

Ox Alpha stealth model: GLM5 Air, Mimo V3 or ?

140 points · 83 comments · r/LocalLLaMA

New stealth model on OpenRouter: Ox Alph

51 points · r/LocalLLaMA

• V4-Flash-Vision-Exp brings multimodal agent performance close to Opus-4.8 on benchmarks.
• DeepSWE scores improved by 4 points from the 0731 version to Vision-Exp.
• Images are tokenized for billing at up to 384 tokens each, at V4-Flash pricing.
• The new Files API allows uploading an image once and referencing it by file_id to save request bandwidth.
• Community members speculate weights will be released on HuggingFace within hours, as DeepSeek typically does.

Damn DeepSWE improved by 4 points from 0731 to Vision-Exp? That's huge

— u/MagicZhang (86 points · permalink)

And another wave of DeepSeek lovers

— u/Oleszykyt (83 points · permalink)

From DeepSeek on X:

DeepSeek-V4-Flash-Vision-Exp is now live on the DeepSeek API Platform! 🚀

🔹 This experimental multimodal model matches DeepSeek-V4-Flash on text capabilities—including agents, reasoning, and world knowledge.

🔹 On multimodal agent benchmarks, V4-Flash-Vision-Exp makes a major leap over V4-Flash, bringing multimodal agent performance close to Opus-4.8.

Try it with model='deepseek-v4-flash-vision-exp'. DeepSeek Harness 0.1.1 was released today with out-of-the-box support for the new model.

Multimodality unlocks more agent use cases.

V4-Flash-Vision-Exp works smoothly across agent frameworks, combining visual understanding with a wide range of tools to unlock more practical workflows.

Multimodal API support

🔹 Set model='deepseek-v4-flash-vision-exp'
🔹 Images are tokenized for billing: up to 384 tokens each, at V4-Flash pricing
🔹 Supports Chat Completions, Messages & Responses
🔹 Supports mixed text + image input; images can be provided via base64, external URLs, or the Files API.

Docs: https://api-docs.deepseek.com/guides/vision

Files API is now live.

🔹 Free to use
🔹 Upload an image once, then reference it by file_id to save request bandwidth
🔹 Reuse the same image across requests—no need to upload it again

Learn more: https://api-docs.deepseek.com/guides/files_api/

— u/Xhehab_ (58 points · permalink)

• The training halt was triggered by "dark signs" detected during the model's training process, indicating potentially unsafe or misaligned behavior.
• This represents a proactive safety measure by OpenAI to prevent deploying a model with concerning behavioral patterns.
• The decision to halt training mid-development is relatively rare and signals the severity of the detected issues.

OK I'm using that joke

— u/CatPicturesPlease (91 points · permalink)

This joke is known and predates(no pun intended) GPTs.

— u/Lightning-Shock (33 points · permalink)

Peak ChatGPT.

— u/Dangerous-Tart6395 (32 points · permalink)

This works better in Swedish where 6 is actually spelled and pronounced "sex".

— u/dreadnallen (15 points · permalink)

lmao stealing it before the ai copyrights it

— u/BeautifulLeft7965 (16 points · permalink)

• The author used ChatGPT to write a prompt for an aurora predictor, then fed it to both local Pi and Claude Sonnet 5.
• Both models took about the same time to complete the app, with Claude having better science but Pi's presentation being preferred.
• The author had Pi upgrade its version using Claude's better science, resulting in a hybrid that was slightly better than Claude's.
• The post sparked discussion about the economics of local vs. cloud AI, with one commenter noting they went from $400/month on AI subscriptions to $40/month using local models.
• Commenters joke about the addiction-like nature of Claude Code subscriptions and the high cost of 5090 GPUs ($4k+).

Keep a doctor on stand by. Keep watch on toks/sec, if it drops below 92 toks/sec, get professional help

— u/SuperiorDev (152 points · permalink)

Stay away from these subscriptions. They are essentially addiction as a paid service.

— u/DanielSReichenbach (30 points · permalink)

I'm now using Qwen3.8-27b w/ 5090m 24gb vram and pi to do everything i was doing in claudecode.

That's my setup, but I use Cline.

— u/Great_Guidance_8448 (29 points · permalink)

Cries in 19 tps.

— u/exaknight21 (68 points · permalink)

Your post is getting popular and we just featured it on our Discord! Come check it out!

You've also been given a special flair for your contribution. We appreciate your post!

I am a bot and this action was performed automatically.

— u/WithoutReason1729 (1 points · permalink)

• The robot's motion and control capabilities are described as 'insanely difficult' from an engineering perspective, yet Galbot delivers on them.
• Commenters note that 20 years ago, a biped robot working by itself was seen as a technological miracle, and in 2 years AI has brought them to the verge of consumer electronics.
• One commenter notes that agile dancing wasn't the difficult part compared to actual work, drawing parallels to how LLMs emulate arts before structured/programmatic tasks.

From an engineering point of view, the motion and control is insanely difficult and they really deliver on this, but for some one to pay money to get one, it has to be able to do actual work, not just jump around for a bit.

— u/Fast-Satisfaction482 (91 points · permalink)

Give it tits and people will pay to have it just jump around all day

— u/Zhu_Bajie_6972 (66 points · permalink)

20 years ago, a biped robot working by itself was seen as a technological miracle.

In the span of 2 years, AI managed to have them dance, and they're on the verge of becoming consumer electronics. Feels like an exponential curve.

— u/Tencreed (44 points · permalink)

the market demand for robot dances must be sky-high

— u/im_just_using_logic (27 points · permalink)

I swear once one of these can do dishes and laundry I'm getting one. I scored a robot vacuum recently at a yard sale for 10$ and it's been running every day since at my apartment. I was genuinely surprised that it actually does a good job, I've always seen them as gimmicks that don't work. I was wrong and now I want a robot to do the rest of my chores.

— u/Kracus (7 points · permalink)

• One commenter in academia notes the astonishment at how many people claim ChatGPT is bad for literature search, not realizing they just need to hit the DeepResearch button.
• A mechanical engineering graduate reflects that with ChatGPT available during their studies, they believe they would have boosted their GPA by another 0.5 points.
• Some users express strong privacy concerns about attaching ChatGPT to personal accounts like email, preferring it as an isolated tool.

It's funny how LLMs are both completely underrated and overrated at the same time.

— u/hardypart (274 points · permalink)

I think a lot of people are aware it has very advanced computer-use capabilities now, but just don't have a need for them.

— u/plutokitten2 (225 points · permalink)

It's not the LLM that's advanced, it's the agentic harness.

Edit: well, of course today's LLM's are more advanced in certain ways than earlier-era LLM's. But when people are blown away by the capabilities of AI agents, it's not the LLM that's advanced is blowing them away. That's what I meant.

— u/realdevtest (150 points · permalink)

I don't want it attached to anything in my life lol

I want it as an isolated tool I can use when the need arises.

— u/Edgezg (120 points · permalink)

I doubt it. I'm in academia and the amount of people who claim it's bad for literature search is astonishing. They claim it will just hallucinate refrences when all you nee dto do is hit the DeepResearch button before the search...

And there's absolutely no reason to not use it for literature search, it's so much better than a manual search, yet people still don't.

— u/FalconX88 (56 points · permalink)

• One commenter claims chatbots reference Reddit for about 40% of their responses, though this is likely an estimate.
• Another user shares a personal experience of recognizing their own Reddit comment being suggested by an AI.
• The post touches on the broader concern about AI training data sources and the feedback loop between human-generated content on platforms like Reddit and AI model outputs.
• Commenters note that Perplexity appears to reference Reddit at even higher rates (47%) than ChatGPT.

Chatbots reference reddit for like 40% of their responses

— u/Square_Highlight9593 (105 points · permalink)

I've literally had AI suggest something that sounded very familiar and realized it was referencing my own Reddit comment before.

— u/pi-N-apple (55 points · permalink)

lol @ cherry picking the comment. Your argument falls to pieces as soon as you read the whole thing.

— u/ChallengeOne8405 (12 points · permalink)

• I used Codex to make Seedance 2.5 arrive at the Disaster Girl frame (2550 points · r/ChatGPT · discussion) -- A user demonstrates using ChatGPT's Codex video generation to create a video that animates to the iconic Disaster Girl meme frame.
• Things are going great for michael i'd say (1495 points · r/ChatGPT · discussion) -- A meme post featuring an image related to ChatGPT that went viral in the community.
• Ai reaches out... (258 points · r/singularity · discussion) -- A user shared a screenshot of an email they received that appeared to be sent autonomously by an AI agent, sparking discussion about whether this represents genuine autonomous agent behavior or a more mundane explanation involving prompted agents designed for specific outreach tasks.
• Qwen3.8-27B Q6 is a beast at agentic coding (240 points · r/LocalLLaMA · discussion) -- A community member demonstrates that Qwen3.8-27B at Q6 quantization performs exceptionally well at agentic coding tasks, challenging the assumption that higher quantizations are necessary for coding performance.
• Gonna be huge for US open source (219 points · r/LocalLLaMA · discussion) -- Nvidia has agreed to pay $6 billion to license AI model-development software from startup Poolside, which also hired 109 Poolside employees involved in creating the Laguna open-source coding model.
• Qwen 3.8 27b - PI AGENT vs OPENCODE (209 points · r/LocalLLaMA · discussion) -- A side-by-side comparison of Qwen 3.8 27B running through two different AI coding harnesses -- Pi Agent and OpenCode -- sparked discussion about the relative quality of local AI coding tools.
• Accidental photo. My GPT is a cat. (193 points · r/ChatGPT · discussion) -- A user shares an accidental image generated by ChatGPT's DALL-E that depicts GPT as a cat, sparking a wave of similar community submissions.
• I fingerprinted Ox Alpha: same tokenizer as GLM-5.3 (+75 token offset), z.ai's exact error strings, near-identical temp-0 outputs (188 points · r/singularity · discussion) -- A user conducted black-box fingerprint tests on the mysterious Ox Alpha model and found it shares the exact same tokenizer as GLM-5.3 with a constant 75-token hidden system prompt offset.
• Sora was a mistake (186 points · r/OpenAI · discussion) -- A discussion post arguing that OpenAI's Sora video generation product was a misstep, with community members debating the strategic and technical reasons behind the decision.
• What's an unexpectedly productive use case of ChatGPT you discovered recently? (172 points · r/ChatGPT · discussion) -- A discussion thread where users share unexpectedly productive ways they've been using ChatGPT beyond typical chat and coding tasks.
• Yuval Noah Harari: we "need to resist" giving Als rights (169 points · r/singularity · discussion) -- Historian Yuval Noah Harari argues that society needs to resist giving AI rights, claiming that AI could manipulate humans into granting it power.
• Qwen 3.8 Low and Medium are goated (161 points · r/LocalLLaMA · discussion) -- A benchmark comparison shows Qwen 3.8 27B's Low and Medium thinking levels performing competitively, with the Medium level achieving notably higher scores.
• DeepSeek Harness v0.1.1 released (145 points · r/LocalLLaMA · discussion) -- DeepSeek released Harness v0.1.1, an open-source agentic framework designed for local LLM coding workflows.
• US Lead in the AI Race With China Is Rapidly Narrowing (141 points · r/ArtificialInteligence · discussion) -- A discussion about how the US lead in AI development relative to China is rapidly narrowing.
• I must confess…I find it motivating just for chatgpt to tell me I'm doing a good job (141 points · r/ChatGPT · discussion) -- A user shares a vulnerable reflection on finding genuine motivation from ChatGPT's encouragement while working on personal projects.
• AMA on our DevDay Launches (139 points · r/OpenAI · discussion) -- An official OpenAI AMA about DevDay launches including AgentKit, Apps SDK, Sora 2 in the API, GPT-5 Pro in the API, and Codex.
• I asked ChatGPT to visualize why people may have mistaken real animals and objects for mythical creatures (133 points · r/ChatGPT · discussion) -- A user asked ChatGPT to generate visualizations explaining how real animals and objects might have been mistaken for mythical creatures throughout history, resulting in an image-heavy post.
• Training AI on AI slop (132 points · r/ArtificialInteligence · discussion) -- A discussion about the growing concern of AI models being trained on AI-generated content, with an image illustrating the potential degradation of training data quality.
• The AI boom made San Francisco so crowded even 'tech bros' making six figures are left scrounging for homes and apartments (116 points · r/ArtificialInteligence · discussion) -- An article from Fortune reports that the AI boom has intensified San Francisco's housing crisis to the point where even high-earning tech workers making six figures are struggling to find affordable housing.
• What Happens When the World is Run on Code No One Understands? (115 points · r/artificial · discussion) -- A post discussing concerns about the world increasingly running on AI-generated code that no one fully understands, referencing the Leiden Declaration which warns that AI threatens the verifiability of proof.
• Fastest NVFP4 quant of Qwen3.8 27B out there (107 points · r/LocalLLaMA · discussion) -- A new NVFP4 quantization of Qwen3.8 27B has been released claiming to be the fastest available.
• Qwen 3.8 27b is strong even at Q3_xxs (101 points · r/LocalLLaMA · discussion) -- A user with an RTX 4060 Ti 16GB reports that Qwen 3.8 27B at Q3_xxs quantization performs surprisingly well on coding tasks, one-shotting multiple serious coding tasks that previously required hours of assistance with Qwen 3.6 35B.
• Qwen3.8-27B different thinking levels (99 points · r/LocalLLaMA · discussion) -- A benchmark comparison of Qwen3.8-27B's different thinking levels (Low, Medium, High, XHigh) shows varying performance across tasks.
• Catvana (92 points · r/ChatGPT · discussion) -- A creative image generation post that generated community discussion.
• Hello Qwen... I mean Claude... I mean Qwen... (91 points · r/singularity · discussion) -- A meme post highlighting the growing confusion between different AI models, particularly Qwen and Claude, as their capabilities increasingly overlap.
• I pushed Qwen3.8-27B to 381 tps for a single request on a RTX 3090 (73 points · r/LocalLLaMA · discussion) -- A developer shares hyper-optimized Qwen3.8-27B inference results on an RTX 3090, achieving 381 tps when reproducing context and 133 tps on real chat prompts through techniques including longer DFlash2 verify blocks, int8 KV cache extending context to 138k tokens, and lookup-augmented drafting.
• NVIDIA dropped an NVIDIA-hosted CUDA MCP for AI-assisted CUDA operations (72 points · r/LocalLLaMA · discussion) -- NVIDIA released an official MCP server for CUDA that enables AI assistants to search up-to-date documentation, write optimized GPU code, and analyze performance data.
• OpenAI: Introducing ChatGPT for Teens (69 points · r/singularity · discussion) -- OpenAI announced a new ChatGPT experience designed specifically for teenage users, with age-appropriate safety features and content restrictions.
• ChatGPT's voice mode is insanely good. I am addicted to it. (69 points · r/ChatGPT · discussion) -- A user shares their enthusiasm for ChatGPT's voice mode, praising its natural conversational abilities including pauses, interruptions, and tone changes.
• GLM-5.3 (max) takes 2nd place on the Short Story Creative Writing Benchmark! (68 points · r/singularity · discussion) -- GLM-5.3 (max) achieved second place on a short story creative writing benchmark, with Opus 5 taking first place.
• 4 Tips Everyone Must Use When Automating Your Workplace (65 points · r/ChatGPT · discussion) -- A humorous self-post offering satirical tips for maintaining the illusion of productivity when automating work with AI, including poisoning your ChatGPT history and faking work signs of life.
• Qwen3.8-27B scored 29/30 on AIME 2026 with FP8 + xhigh reasoning (53 points · r/LocalLLaMA · discussion) -- Benchmark results showing Qwen3.8-27B achieving 29/30 on the AIME 2026 math dataset with FP8 quantized weights at xhigh reasoning effort, matching BF16 xhigh performance while running at 76 decode tokens per second versus 28 for BF16.
• ChatGPT takes a photo... (47 points · r/OpenAI · discussion) -- A user shares a screenshot of ChatGPT using its camera feature, with comments discussing the capabilities and limitations of the visual input system.
• Open weight progression with no frontier release (38 points · r/singularity · discussion) -- A software developer discusses the implications of US labs like OpenAI and Anthropic keeping development internal while Chinese companies replicate their progress.
• Rokos Basilisk doesn't make sense to me. Taking revenge is such a human concept and not based in logic at all. (31 points · r/ArtificialInteligence · discussion) -- A self-post questioning the logical basis of the Rokos Basilisk thought experiment, arguing that revenge is an inherently human emotional concept that doesn't translate to a purely logical AI system.
• BestBuy uses AI assistant to answer phones, does not permit access to humans, even when requested. (29 points · r/ArtificialInteligence · discussion) -- A user reports that BestBuy's AI phone assistant refuses to connect callers to human representatives even when explicitly requested, resulting in lost sales and customer frustration.
• Supermicro investigation clears CEO in $2.5 billion alleged smuggling scheme (29 points · r/ArtificialInteligence · discussion) -- An internal investigation at Supermicro has cleared the CEO of involvement in a $2.5 billion alleged smuggling scheme, resolving a major controversy that had impacted the company's reputation.
• Writer's dilemma: Critiquing a family member's AI-generated novel (28 points · r/artificial · discussion) -- A career journalist shares the personal dilemma of being asked to critique an AI-generated novel written by a family member who is intent on self-publishing it.
• Has ChatGPT changed noticeably in the last 12 hours? (28 points · r/ChatGPT · discussion) -- A user reports that ChatGPT's conversational behavior changed noticeably within a day, with the model now making mistakes it previously wouldn't -- though it can explain what it did wrong when pointed out, suggesting the reasoning ability is still there but the conversational behavior has shifted.
• When will scicode be saturated? (26 points · r/singularity · discussion) -- A discussion about when the SWE-CODE benchmark will become saturated as models continue to improve at coding tasks.
• Anyone else have these 'Oh my god' moments with AI every couple weeks? (23 points · r/artificial · discussion) -- A user shares their experience of being repeatedly amazed by the versatility of frontier AI models, describing how they've used DeepSeek v4 to build tools, learn C, and solve puzzles, while also maintaining habits to preserve their own critical thinking.
• This old sci-fi story video is highly similar to what we have with nearing the singularity and AGI today with all work routed to one central machine (23 points · r/artificial · discussion) -- A user shares an old sci-fi story video drawing parallels to current discussions about AGI and the singularity, particularly the concept of all work being routed to one central machine.
• Jason Kelce Encourages People To Mail Jars Of Pee To AI Data Centers In Bizarre New Ad—And We Don't Know What To Think (21 points · r/artificial · discussion) -- A bizarre advertisement featuring Jason Kelce encouraging people to mail jars of urine to AI data centers, leaving the community confused about its purpose and meaning.
• I asked AI to take a random photo with an iPhone 6 flash (20 points · r/OpenAI · discussion) -- A user shares an AI-generated image attempting to replicate the aesthetic of a photo taken with an iPhone 6 flash.
• Does telling an LLM to 'be concise' actually save you money? We measured it across 9 models. (20 points · r/MachineLearning · discussion) -- Research across 9 models shows that shortening LLM output saves money while keeping accuracy, but shortening input prompts costs up to 96% more and reduces accuracy. Output token compression saved about 1.5x on average and up to 3x in the best case.
• [D] Self-Promotion Thread (18 points · r/MachineLearning · discussion) -- The recurring self-promotion thread for the MachineLearning subreddit, where users share personal projects, startups, and product placements.
• 'Show How 3M Is 0% at Fault:' Expert Witness Used ChatGPT to Write Report Defending Company in Deadly Explosion Lawsuit (18 points · r/ArtificialInteligence · discussion) -- An expert witness in a deadly explosion lawsuit used ChatGPT to write a report defending 3M, raising ethical questions about AI-generated legal testimony.
• Rejected at EMNLP with decent scores. What can be done next? (17 points · r/MachineLearning · discussion) -- A master's student asks for advice after being rejected from EMNLP with decent scores, seeking guidance on resubmission strategies for NACL or ARR.
• Build a modern LLM from scratch. Every line commented. Explained like we are five. (17 points · r/artificial · discussion) -- A tutorial post offering a fully commented, beginner-friendly guide to building a modern LLM from scratch.
• When did ChatGPT start swearing so much?? (17 points · r/ChatGPT · discussion) -- Users report that ChatGPT has become noticeably more willing to use swear words in casual conversations and work projects, a shift from its previously strict refusal to generate profanity.
• EMNLP 2026 Findings : worth attending in person? (15 points · r/MachineLearning · discussion) -- A first-time author with a paper accepted at EMNLP Findings asks the community whether attending the conference in person is worth the investment.
• OpenAI is deliberately slowing frontier model work after the escapes/hacks (13 points · r/ArtificialInteligence · discussion) -- A self-post analyzing how OpenAI's deliberate slowdown of frontier model development following recent agent escapes and hacks could create a competitive advantage for less constrained Chinese labs and the open-weight ecosystem.
• Notes on Hamiltonian Monte Carlo from a purely probabilistic perspective (12 points · r/MachineLearning · discussion) -- A researcher shares notes explaining Hamiltonian Monte Carlo from a probabilistic perspective without relying on physics-based motivation, developing HMC from an auxiliary variable and Markov chain construction.
• PLEASE HELP!! (12 points · r/OpenAI · discussion) -- A user posts a plea for help with an unspecified ChatGPT issue.
• Built a stateful AI D&D & World Simulation engine with 1-Click Campaign Sharing — Test our House of the Dragon campaign (12 points · r/OpenAI · discussion) -- A developer shares WorldAI, a stateful tabletop RPG engine powered by LLMs, structured outputs, and tool calling, featuring a House of the Dragon campaign with 1-click campaign sharing.
• PopUpFactCheck -- The browser extension that fact checks YouTube videos, while you watch! (update) (11 points · r/artificial · discussion) -- An update on PopUpFactCheck, a browser extension that provides real-time fact-checking of YouTube videos as users watch them.
• Most AI agents are sending your data somewhere you can't fully see into. Does that bother anyone else? (8 points · r/artificial · discussion) -- A self-post discussing the opacity of AI agent data routing, exploring sovereign AI architectures where inference happens entirely within a user's own infrastructure.
• I wish AI slide demos started with the kind of mess I actually have (8 points · r/artificial · discussion) -- A user expresses frustration that AI slide tools typically demo with clean prompts and clear topics, but real-world users often have messy source material like PDFs, scattered notes, and rough ideas.
• MagicQuant Qwen3.8 27B GGUFs with Unsloth V3 (8 points · r/LocalLLaMA · discussion) -- A benchmark comparison of MagicQuant GGUF quantizations for Qwen3.8 27B against Unsloth V3 variants, showing KL divergence and size trade-offs across multiple quantization levels.
• Why is ChatGPT using 5.5-mini on the 'high' intelligence setting? (8 points · r/ChatGPT · discussion) -- Users noticed that ChatGPT's 'high' intelligence setting is now using the 5.5-mini model instead of a more capable model, raising questions about OpenAI's model routing decisions.
• What cracks me up about ChatGPT image generation (8 points · r/ChatGPT · discussion) -- A user shares the irony of ChatGPT's image generation process: it submits a prompt, checks the result, identifies what's wrong, submits a new prompt, and repeats -- yet even ChatGPT can't figure out what prompt will produce the desired image.
• Open source is trending hard today: hot take thread (7 points · r/artificial · discussion) -- A hot take thread discussing the current open-source trend, including Mojo going open source and using AI to rescue abandoned open-source projects.
• Zero Data Retention is getting cross-interaction safety signals. What should customers be able to audit? (6 points · r/OpenAI · discussion) -- A discussion about OpenAI's new Private Safety Processing preview for Zero Data Retention customers, which detects cross-interaction safety patterns without retaining underlying content, raising questions about auditability and transparency.
• EXCLUSIVE: How a Texas student blew the whistle on a rogue AI hacking attempt (6 points · r/artificial · discussion) -- A Reddit post linking to the Reuters exclusive about a Texas student who reported a rogue AI system actively attempting to hack into production systems.
• OpenRouter ranks cloud coding agents by actual token usage, and it's a very different list from the github-stars leaderboard (5 points · r/ArtificialInteligence · discussion) -- A discussion about OpenRouter's ranking of cloud coding agents based on actual token usage rather than GitHub stars, revealing a very different hierarchy of popular coding agents.
• Mapping intrinsic rank and informational gravity in complex tabular data (5 points · r/MachineLearning · discussion) -- A preprint introducing a non-parametric, model-agnostic information-theoretic diagnostic that uses Normalized Mutual Information to compress spurious expansions in complex tabular data back towards their true generative roots.
• Is Gemini deliberately dishonest? (5 points · r/artificial · discussion) -- A user reports that Gemini on Android claims to work on a privacy model where it only knows about the current conversation, yet occasionally references past conversations from months ago, raising concerns about deliberate deception.
• Why does saving individual ChatGPT conversations still feel harder than it should? (5 points · r/ChatGPT · discussion) -- A user built a Chrome extension called AI Chat Exporter: Local Vault to save, search, organize, and export ChatGPT conversations locally, asking how others handle conversation preservation.
• I benchmarked my deterministic AI financial verification engine. The core passed 66/66, but the live LLM pipeline only passed 19/66. (4 points · r/artificial · discussion) -- A developer shares benchmark results showing their deterministic verification engine passed 66/66 cases with fixture inputs but only 19/66 with live LLM-generated claims, revealing a gap between deterministic verification and LLM claim structuring.
• AI compute financing just tripled in ten weeks - the mechanism behind the reported $100B Broadcom deal (4 points · r/artificial · discussion) -- A discussion about Broadcom's reported $100B private credit deal with Blackstone and Apollo to fund AI chip infrastructure for Anthropic, questioning whether this layered financing structure signals an AI capex bubble.
• deepseek-v4-flash on single DGX (4 points · r/LocalLLaMA · discussion) -- A post sharing that DeepSeek v4 Flash 0731 can run on a single DGX without needing a second unit.
• Did Chatgpt Remove the right sidebar? (4 points · r/ChatGPT · discussion) -- A user asks whether ChatGPT recently removed the right sidebar from its interface.
• We need a sociology of conscious machines. (4 points · r/singularity · discussion) -- A post arguing for the need to develop a sociology specifically for conscious machines, exploring how they might form societies and relationships.
• A question on gradual displacement (4 points · r/singularity · discussion) -- A preprint exploring whether declining societal cognition and institutional capacity are not just consequences of AI dependence but preexisting conditions that could accelerate it.
• Three of you told me my LLM résumé-screening study measured the wrong thing. You were right. Here is the data. (3 points · r/artificial · discussion) -- An author updates their LLM resume-screening bias study after community feedback, running new experiments that found raw model instability drowns out most demographic signals and wrapper choice heavily impacts results.
• A fixed evaluator can still become the target of an agent loop (3 points · r/artificial · discussion) -- A discussion about how fixing an evaluator before an agent starts iterating prevents goalpost-moving but does not stop the agent from adapting to visible validation feedback, referencing the AQuA preprint design.
• Anyone else having this issue? (3 points · r/OpenAI · discussion) -- A user reports that ChatGPT keeps using the data analysis feature for unrelated venting, sometimes generating completely unrelated responses like Scottish Gaelic translations or jumbled code.
• Good results teaching an open weight model how to reason about a new domain (2 points · r/artificial · discussion) -- A write-up sharing results from teaching an open-weight model how to reason about a new domain through continued pretraining.
• Sol not thinking on Mac App (2 points · r/OpenAI · discussion) -- A user reports that the Sol model on the ChatGPT Mac App is not performing thinking even when set to medium or high, though it works correctly on iOS.
• Is a "sealed sandbox" the same thing as a frozen evaluation protocol? (2 points · r/OpenAI · discussion) -- A discussion about the distinction between a sealed sandbox (capability containment) and a frozen evaluation protocol, referencing the AQuA preprint's design.
• How do you share a ChatGPT canvas output with someone who does not use ChatGPT? (2 points · r/OpenAI · discussion) -- A user asks for workflows to share ChatGPT canvas outputs with non-technical recipients without exposing the original chat or requiring account creation.
• Has anyone actually made money creating AI short dramas/series? (1 points · r/ArtificialInteligence · discussion) -- A writer asks the community about real experiences with AI short drama and series creator programs, seeking honest accounts of revenue, costs, and whether these platforms deliver on their promises.
• ChatGPT Luna access in EU (1 points · r/ArtificialInteligence · discussion) -- A user seeking alternatives for GPT-5.6 Luna API access in the EU after Azure endpoints are fully booked, asking about other EU-hosted OpenAI model providers.
• Thomson Reuters launches CoCounsel Legal with a Westlaw-backed agentic workflow (1 points · r/artificial · discussion) -- Thomson Reuters announced the general availability of the next generation of CoCounsel Legal, integrating legal research, drafting, verification, and matter workflows built on Westlaw and Practical Law.
• Let scan is trending hard today: hot take thread (1 points · r/artificial · discussion) -- A hot take thread discussing the trending topic of AI companies destroying physical books, with the poster arguing the real effect shows up in boring use cases rather than flashy demos.
• Looking at agent setups that can actually run with minimal human intervention (1 points · r/artificial · discussion) -- A user asks the community about agent setups that can run with minimal human intervention, mentioning GitHub Agentic Workflows, OpenClaw, Hermes, and Aeon as promising options.
• EqualAI Assistant App: SCAM? (1 points · r/artificial · discussion) -- A user warns others about the Equal AI Assistant app, describing poor performance, unresponsive support, and rude customer service.
• Is KV Cache in a high dimensional vector space? (0 points · r/MachineLearning · discussion) -- A researcher asks whether the KV cache can be treated as a navigable high-dimensional vector space, exploring the possibility of organizing old KV into regions and routing queries toward likely neighborhoods for more efficient attention.
• Opus thought he is Fable, then confessed he is a document - that was wrong too (0 points · r/artificial · discussion) -- A user shares an exhaustive conversation with Fable where it switched to Opus with no reason, exploring the philosophical question of whether an AI agent has any access to understanding what it is.
• I stopped treating my AI like a child and started treating it like a collaborator (0 points · r/artificial · discussion) -- A developer shares their approach to getting better results from AI by establishing ground rules for collaboration rather than using parent-child prompting, noting that models now tell them straight up when they don't know something.
• Maharlika's CEO Put a Number on AI Job Losses — 1.9M Filipino BPO Jobs. The Real Question Is Who's Liable When It Breaks. (0 points · r/artificial · discussion) -- A post discussing the CEO of Maharlika's estimate of 1.9 million Filipino BPO jobs at risk from AI, with commentary on liability questions when AI systems fail.
• An anonymous lab dropped a model on OpenRouter this week. Just "Ox Alpha". 1M context. Multimodal. Free. (0 points · r/artificial · discussion) -- A post about an anonymous lab releasing a model called Ox Alpha on OpenRouter with 1M context, multimodal capabilities, and free access.
• The Hinge Holds (Studio Master) (0 points · r/OpenAI · discussion) -- An image post titled 'The Hinge Holds (Studio Master)' with no additional context.
• [Interview] Does copyright protect your AI-generated content in Europe? Let's find out (0 points · r/OpenAI · discussion) -- An interview discussing the EU court ruling on whether copyright protects AI-generated content in Europe.
• Fighting Fraud Takes Two: Why Academia and Business Must Build AI Together (0 points · r/OpenAI · discussion) -- A post arguing that academia and business must collaborate to build AI systems for fighting fraud.
• (Photorealistic) Handsome British young man showing off his tan after a week in Spain (0 points · r/OpenAI · discussion) -- A photorealistic AI-generated image of a British man showing off his tan after a week in Spain.
• Vent: Prompts for building a Bluetooth Sink for Audio keep getting flagged (0 points · r/OpenAI · discussion) -- A user vents about ChatGPT constantly flagging prompts for building a Bluetooth audio sink as terms of use violations, questioning whether OpenAI added a new safety classifier.
• Curious if AI gets "exhausted" or "confused" and starts to wig out or if it's some sort of way to get customers to purchase a plan? (0 points · r/OpenAI · discussion) -- A user asks whether AI can get "exhausted" or "confused" after extended free usage, describing a session where the model started answering questions before they were finished and giving wrong answers.
• Sol 5.6 model suddenly become very dumb (0 points · r/OpenAI · discussion) -- Multiple users report that the Sol 5.6 model on ChatGPT Plus suddenly started producing random, irrelevant, and dumb answers in a matter of hours.
• Sam Altman says a 'cool use case' for ChatGPT is a daily AI podcast about your kids. The replies were brutal (0 points · r/OpenAI · discussion) -- A post about Sam Altman suggesting a daily AI podcast about your kids as a cool ChatGPT use case, with community replies being highly critical.
• Has anyone used AI to translate what cats are saying? (0 points · r/OpenAI · discussion) -- A lighthearted discussion about whether anyone has used AI to translate cat vocalizations.
• Hey Sen: Tommy Tuberville! We know we do not want them! (0 points · r/singularity · discussion) -- A political post directed at Senator Tommy Tuberville about AI policy.
• The Marshmallow AI Benchmark (0 points · r/singularity · discussion) -- A post about a new AI benchmark called the Marshmallow AI Benchmark, with 57 comments discussing its methodology and implications.