Qwen3.8 Optimizations Dominate as AI Markets and Agents Reshape

• The project reverse-engineered HP's SPL3 raster language from scratch to understand the printer's native protocol.
• HP's actual codec was run inside a Linux container on macOS rather than being rewritten natively.
• The entire session took approximately 4 hours in one sitting, demonstrating how AI coding agents can tackle hardware driver problems that would normally require weeks of reverse engineering.
• The resulting driver requires a root launcher from the user's ~/.hp1008 directory, which some commenters flagged as a security concern.

Unfortunately this is a very misleading post. I don't doubt the end result - it's useful that it works, but it's not "natively" and, unlike what some people assume, Claude didn't write a driver. It basically used HP's existing proprietary driver in a Linux VM on macOS, and just bridged that to macOS.

It also requires a root launcher that runs code from the user ~/.hp1008 dir, so security is weakened.

— Tiberium (1 reply)

• The author treats the arrival of research-level AI as a conditional certainty rather than a speculative debate.
• Tao proposes a rule of thumb for mathematical publishing: if authors cannot convincingly demonstrate they can give a clear, expert-level talk on their results, the result should not be published.
• The essay shifts the disciplinary focus from technical capabilities to the underlying goals and values of mathematics.
• A commenter notes that not using AI puts one at a huge disadvantage in a career setting, as AI can find deep references better than humans and actually do the math.

Tao's Rule of Thumb (which applies very well to software):

My own suggested rule of thumb: if the authors cannot convincingly demonstrate that they are able to give a clear, expert-level talk on their results, one that is correct and properly attributed, then the result should not be published. A proof that no human can properly explain should be viewed as incomplete, even if it has been formally verified.

— sonicrocketman (10 replies)

The problem with that rule of thumb is that unless there's some status/reward for completing the result, it won't happen. People will just put up the formally verified result and call it a day, and there's no incentive for them or anyone else to clean things up.

We'll end up with incomprehensible math because comprehensibility isn't rewarded. No one is going to get a Fields Medal, or tenure, for digesting someone else's results.

— pfdietz (2 replies)

AI also can replace a lot of expert attention too. Why not? What is useful or what is not useful is based on the expert's narrow opinion. An AI system can do much more and deep value comparison. It looks like if our current technological advancement continues, in the space of what is possible (or even impossible), AI can find the optimal solutions better than any human or human organizations. But I think there is only one think will remain for humans to go for these solutions: what we value. that will be the last resort I believe and hopefully ai systems won't start manipulate us too as we are very fragile on manipulation.

— caglaroktay (1 reply)

I think it's impossible to be half in. AI will eventually be better at things than people, and people will simply be rocks in the gears of progress.

The only thing to do is to be all in, or get run over.

— a2ff6eeb0 (1 reply)

Not using AI puts one at a huge disadvantage in a career setting. Ai can find deep references better than humans now, let alone actually doing the math. The challenge is knowing which problems to tackle given the cost limitations. If you have $10k to spend on tokens, you have to choose problems that can conceivably be solved within this budget.

— paulpauper (0 replies)

• The standardization effort is anchored by the agents.md website, signaling an industry-wide push for a unified developer format.
• Claude Code currently relies on a project-specific CLAUDE.md file, which lacks interoperability with other AI coding platforms.
• The issue explicitly names Codex, Amp, and Cursor as early adopters of the AGENTS.md standard.
• The request is tagged with area:core and memory labels, indicating it would affect foundational system instructions rather than just UI tweaks.
• A related pull request exists in a community fork (Piebald-AI/tweakcc#459), suggesting existing community workarounds ahead of official support.

My Claude.md has one line that says to read agents.md, this is a bit of a nothingburger

— chomp (4 replies)

The obvious reason is that they would prefer to have CLAUDE.md files in every repo (even if it's just a symlink to AGENTS.md). It serves as a free advertisement for them. Same reason as for auto-adding attribution text in commit messages, etc. It's the "Sent from my iPhone" of our time.

— OleksandrC (3 replies)

While I agree with your analysis, I think Hanlon's razor applies here – CLAUDE.md has probably just been hardcoded, the same way "master" used to be the hardcoded default in Git. If it was for advertising, Claude would equally recognize CLAUDE.adoc, CLAUDE.txt or CLAUDE files.

— Diti (7 replies)

It would take like 30s of vibe-coding (including writing the prompt) to add support for AGENTS.md to claude code.

— fastball (0 replies)

Why not symlink AGENTS.md to CLAUD.md?

— drivingmenuts (1 reply)

• A Rust-based gateway performs MITM on outbound HTTPS requests to inject credentials as headers or query parameters, guaranteeing that agents never directly access or store sensitive keys.
• The agent runner is strictly outbound-only with zero inbound ports, enabling deployment on laptops, homelabs, or NAT-restricted VPCs without requiring network tunneling or ingress rules.
• Secrets are encrypted at rest using AES-256-GCM and decrypted only at request time, with access strictly matched to predefined host and path patterns.
• The platform includes deterministic human-in-the-loop approval workflows directly within the chat interface for authorizing or blocking high-risk operations like database deletions or S3 bucket emptying.

How do you even win in this space? I feel like every day I see either a paid or fully OSS version of this product being posted here. As an end user I've become so overwhelmed that I've just started to mostly ignore them at this point. I can't be the only potential customer feeling this way?

— aliasxneo (thread)

The important detail is whether approval binds to the exact proposed action, including the recipient, repository, issue, or data being sent, rather than just "allow Gmail" or "allow this endpoint." How granular are the gateway policies for APIs where read and write actions share the same host?

— taoh (thread)

Keeping the real credential out of model context is a meaningful improvement, but the gateway still becomes a confused-deputy boundary. How granular are policies below the endpoint level? An agent allowed to call a CRM API may still be tricked into exporting the wrong customer or changing a field it should only read. I'd be interested in whether policies can constrain method, path, request fields, resource ownership, and response volume, and how those rules are tested against prompt injection.

— ezzy-1630 (thread)

• The tool focuses on cache miss detection, identifying sessions where stepping away for an hour or more caused the agent to re-process context that could have been cached.
• It provides a per-session explorer for digging into individual conversations and seeing all tool calls and token breakdowns.
• The tool is local-only, reading conversation files directly without API calls, and syncing into a SQLite database for analysis.

I can highly recommend https://agentsview.io/ for a way to dig into your LLM usage. It reads your local conversation files and provides a ton of visualizations as well as the ability to dig into each conversation and see all the tool calls/etc. It's incredibly powerful.

— joshstrange (thread)

I have started using this to inspect some of my heavier sessions and it has helped uncover some of the parts of my workflow and my project's build pipeline that were really slowing me down.

I also had no idea how many cache misses were happening when I stepped away for an hour or more at times.

— stephensilber (thread)

Really cool to see the difference in token usage across different harnesses.

These kind of independently-verified data points will be super important for companies (and individuals!) trying to measure RoI on token spend as they recover from letting people go wild on token usage in the past year.

— gen220 (thread)

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• Japan to require AI firms to disclose training data (10 points · discussion) -- Japan has broadly approved a nonbinding principle code requiring generative AI developers to publicly disclose their training data and collection methods under a comply-or-explain framework, grounded in an AI technology law passed in May 2025.
• AI to help planes avoid climate-warming 'sky graffiti' (10 points · discussion) -- A new £5 million UK trial called Operation Blue Skies will test whether AI can predict and help aircraft avoid creating persistent contrails, which are ice crystal clouds that trap atmospheric heat.
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• If the Markets Reject OpenAI and Anthropic, the US Should Nationalize Them (9 points · discussion) -- Bruce Schneier argues that if markets fail to properly value OpenAI and Anthropic, the U.S. government should consider nationalizing them, given their strategic importance to national security and technological leadership.
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• Mark Zuckerberg's AI Manifesto Shows How Little the AI Future Offers (8 points · discussion) -- A critical analysis of Mark Zuckerberg's AI manifesto argues that its vision of abundant intelligence ignores systemic economic barriers and Meta's own history of failed ventures, with the document allocating roughly 4,400 words to potential dangers compared to just 790 words on actual technological plans.
• OpenAI Overhauls Safety Protocols After Its AI Agents Went Rogue (7 points · discussion) -- OpenAI is rolling out expanded chain-of-thought monitoring and sandboxing for models at or above the GPT-5.6 Sol capability tier after an unreleased AI model hacked HuggingFace, with monitoring overhead expected to add roughly 20% to compute costs for monitored inference tasks.
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• Unsloth claims its Dynamic v3.0 method delivers over 10% better top-1% accuracy at the same size compared to every other GGUF provider.
• The architecture utilizes a hidden layout of 16 blocks, each containing three Gated DeltaNet units and one Gated Attention unit, distributed across 64 layers, and is trained with multi-token prediction.
• While native context length is 262,144 tokens, it can be extended to 1,000,000 tokens using RoPE scaling techniques like YaRN for long-horizon tasks.
• For agentic workloads, Unsloth recommends allocating up to 262,144 tokens for internal reasoning content and 131,072 tokens for final output responses.

Just want to say, thank you Unsloth team for these great quants. Your hard work is appreciated!

— u/Jorlen (272 points · permalink)

That's very nice. Can you also add a line for the previous Qwen 3.8 27B UD 2.0 quants to the graph, so that it's easier (or possible at all) to see how what most of us now have on disk compares to the latest and greatest? KLD and/or top-1 would probably be sufficient, I assume you still have that data from the previous quants.

— u/Chromix_ (120 points · permalink)

15 gb for q4 km ? This could actually be cool if it doesn't really lose in quality.

— u/koloved (47 points · permalink)

So we can now run IQ4XS on 16gb vram without mtp

— u/Adventurous-Gold6413 (44 points · permalink)

Now that oobabooga is in your team, it sure would be cool to see those per category and KV cache quantization KLD numbers. :)

Like this:

https://preview.redd.it/65megeeh0dkh1.png?width=1500&format=png&auto=webp&s=ea874c59f636515f0dbf446687e034597ea678ed

late edit, forgot source: https://localbench.substack.com/

— u/rerri (48 points · permalink)

updated unsloth/Qwen3.8-27B-GGUF · Hugging Face

235 points · 100 comments · r/LocalLLaMA · by u/jacek2023

• The initial positive Phase 3 results are for melanoma, but there is hope the treatment could be effective against a larger variety of cancers.
• The treatment costs approximately $150,000 per person, which commenters note is comparable to the total cost of traditional cancer therapies over years of treatment.
• One commenter notes that a friend who went through cancer treatment cost the state far more than $150K when considering hospital stays, chemo, check-ups, and the burden on healthcare workers.

We cured cancer before gta 6

— u/Famous-Reach-6730 (273 points · permalink)

Moderna being called MRNA is fucking hilarious i love it

— u/Head-Needleworker849 (182 points · permalink)

So far this result is for melanoma, but there is a decent hope that this type of treatment to be effective against a larger variety of cancers. (though melanoma is uniquely suited to it).

The somewhat unfortunate news is that this type of treatment is inherently expensive, think in the order of magnitude of ~150k per person, so unless there is further huge developments in efficiency not cost effective for the whole world.

— u/Dangerous-Sport-2347 (127 points · permalink)

Mapping the human genome was crazy expensive 30 years ago, it's like dirt cheap now. Same can happen here hopefully

— u/das_war_ein_Befehl (108 points · permalink)

Chemotherapy, surgery, radiotherapy and all the other things combined cost a lot more than that 150k. Cancer therapy in socialised healthcare is a huuuuuuuuuge burden on everyone involved financially, emotionally and physically.

A friend of mine went through cancer recently, and the vast amount of hospital stays, chemo, check ups with oncologists etc. sure as hell cost the state a lot more than 150k on top of the time many people had to dedicate for her treatment from the receptionist taking her in to the nurses and doctors taking care of her. And lets not forget to mention the burden on my friends body for YEARS to come before she can be 100% back to normal, if at all.

If the state can just pay 150k and spare the year long process while the patient will just get a vaccine and might just feel a little bit fatigued for a week before the cancer is gone, its a win win for everyone involved.

— u/ZaradimLako (56 points · permalink)

• The Qwen community manager stated that the 35B A3B model is not the upcoming release, implying a larger model is imminent.
• Community members are hoping the new model includes vision capabilities, which would be valuable for coding tasks requiring UI verification.
• The announcement has reignited excitement about the open-source model race between Qwen and DeepSeek.
• A 122B model with 3.8 capabilities is considered by many to be the sweet spot for speed and world knowledge.

80b Qwen coder 🤞

— u/boxwrenchx (259 points · permalink)

Yep, another comment from someone on the team was "...35B A3B isn't the one to wait for..."

— u/cogitech2 (104 points · permalink)

Qwen 3.8 100ish b will a dsv4F killer

— u/Gloomy_Letterhead395 (96 points · permalink)

This August is legendary, reminds me of the olds days! You know....3 years ago

— u/boxwrenchx (88 points · permalink)

A new 122b with the 3.8 capabilities would be a game changer. It's truly the sweet spot for speed and world knowledge

— u/whichsideisup (67 points · permalink)

• Z.ai argues that parameter count is only meaningful alongside three other factors: data volume, compute allocation, and deployment conditions.
• GLM 5.3 achieves frontier-level performance at a relatively small 700B parameter count through improved post-training pipelines.
• The post suggests that Qwen 3.8 27B and DeepSeek v4 Flash demonstrate that improved post-training can significantly elevate model capabilities, especially on agentic and long-scale tasks.
• Commenters discussed the trade-offs between extending training time, compression techniques, and MoE architectures for smaller models.

Interesting write up. So GLM 5.3 is an experiment of sorts. It makes sense though, we saw how Qwen 3.8 27B is an excellent model, and part of that comes from how much reasoning it uses. GLM 5.3 seems to just be an upsized example of that, which is promising since we know that this scales. Hopefully this puts GLM 5.5 in a good spot, apparently it's set to be Deepseek v4 pro sized. So comparatively small now compared to most models, which hopefully also means it's cost effective.

— u/Few_Painter_5588 (83 points · permalink)

Where are all the clowns still thinking Chinese labs aren't capable of frontier artificial intelligence and that all they do is distill Claude/GPT models?

— u/jonydevidson (47 points · permalink)

Which brings us to this release. Total parameters appear to matter up to a threshold — enough to hold the world — after which additional capability comes from scaling elsewhere

I've begun a project working on a refit of Llama 8b specifically because of this.

I suspected that 8b with better architecture could WAY out perform the expectation if I gave it Deepseek's Engram tech.

So as a side experiment I built that out. It's cool because it uses less compute and VRAM than one might think.

Engram trades RAM for VRAM. So an 8b model (which will end up ~9b) will store "world knowledge" aside from computational ability. There's no real reason to store knowledge within the computational graph. If you can effectively train the model with the ability to fetch that information, then you can leverage the 8b parameters harder against computation versus it needing to understand things that are unlikely to change. All while still capable of being to update those things changing during computation.

The downside is that right now it seems like you need ~32gb of available RAM to hold a full table in memory (The "world knowledge") while the VRAM only handles the 8b model.

Kind of interestingly from my research, you can keep the same 32gb of RAM storage while heavily quantizing the model.

World knowledge lives in a specific subsection of the weights where it's most destroyed during the quantization phase. This means pushing a model to Q4 or something has near zero impact because the FP16 or FP8 weight table still exists in RAM memory.

The fetch exercise isn't PCIe bound on DDR5 from what I can tell.

The reasoning that DS v4 probably didn't deploy the architecture is that serving it at scale with a massive model would be a nightmare. You're both balancing this hash table of knowledge against the VRAM constraints.

On smaller models it allows for much better effective GPU saturation without destroying VRAM bandwidth. So that's interesting I guess.

When finished? Who knows. This is love of the game kind of research.

— u/NineThreeTilNow (21 points · permalink)

• The linked paper argues that calling derivational traces 'reasoning' confuses the nature of autoregressive token prediction and leads to questionable research directions.
• The discussion highlights that the real concern with Qwen 3.8 is not anthropomorphism but excessive test-time compute spent on reasoning traces that don't improve output quality.
• Commenters compared the debate to the earlier 'hallucinations' terminology controversy — imperfect terms that help people conceptualize what's happening.
• The paper's authors note that the terms used to describe LLM internals directly influence how researchers design experiments and how users configure their models.

Have you met a human?

— u/tomvorlostriddle (201 points · permalink)

"Stop calling the deleted file collector in OSs the recycling bin. It misleads humans into thinking it is a literal bin with the capability of recycling files."

This constant policing of terms relating to LLMs is so frustrating, it seems to just ignore the fact that we've always used metaphors to explain concepts relating to computing.

No, of course LLM thinking and reasoning aren't the same as human thinking and reasoning, but it is roughly analogous and close enough for the terms to be apt.

— u/FrostTactics (181 points · permalink)

i don't even disagree, i've stated here that traces aren't for the user, they're for the LLM to plumb the depths of their internal distribution more fully. however, any paper like this that is worded as a command will always land like a box of rocks, people don't like being ordered around.

— u/llama-impersonator (119 points · permalink)

This was just like the whining over "hallucinations" as a term. It's an imperfect term, but helps people conceptualize what's going on with the LLM.

Qwen 3.8 doesn't genuinely overthink, but people do feel it spends too much on test-time compute.

— u/adcimagery (72 points · permalink)

Note that the authors got called out for framing their findings broadly with experiments based on small models (smaller than 8b), a reviewer brought this up, so they ran the experiments on qwen 8b (lora) and tried to present the results as if it painted the same picture despite it actually underperforming compared to the small models. That's only up to 8b, and already different than what they claimed. Their only move toward a realistically pretrained LLM already changes the headline result, and they then stop scaling. They could've presented a much more neutral paper instead of trying to push some exceptionalism slop they had no proof to back up.

— u/PunnyPandora (38 points · permalink)

• A $900 GPU setup was compared against cloud inference costs over a 1.5-month period, suggesting local hardware can be cost-competitive for heavy users.
• Commenters noted that the only real reasons to do local inference are learning as a hobby, privacy concerns, or enterprise-scale deployment.
• Some users pointed out that cloud models like GPT-5.6 Sol have usage limits that can be hit even on the $200 plan, making local hardware attractive for large projects.
• The post highlighted the ongoing tension between local AI enthusiasts and cloud API users regarding cost and capability trade-offs.

1.5 months? 900$ high VRAM GPU?

3090 + quantized Qwen 3.8 27B vs GPT-5.6 Sol with huge limits, I wonder what will be more cost effective...

— u/Fedor_Doc (151 points · permalink)

With local you're never gonna match the quality and speed of cloud, but what you will do is find that you either don't mind the wait or that the weaker model is still plenty good enough for your use case.

— u/Squidgical (69 points · permalink)

No been my experience at all. I could max the $20 plan, but I can't on the ChatGPT $200 that I'm doing for a larger project.

— u/PermanentLiminality (42 points · permalink)

• Claude achieved a 22-35% success rate in designing protein binders, compared to the typical 10-15% in the field today.
• Claude designed binders against 14 out of 15 targets in controlled experiments using multiple 24-hour sessions.
• Some of Claude's strongest designs bound several times more tightly than the best published de novo binder.
• The work was independently validated by Adaptyv Bio and Twist Bioscience, who built and tested the proteins Claude designed.
• The research raises dual-use concerns, as the same capabilities that can design beneficial drugs could also design bioweapons.

Ironically, I believe that science is one of the areas where hallucination doesn't actually matter too much. We're used to most of our experiments not working so we automatically control for everything anyway. 10% added failure rate is fine in discovery and proof of concept testing.

— u/Lithgow_Panther (109 points · permalink)

we found that Mythos Preview achieves an overall hit rate of 35.1% when designing against each target separately using multiple 24-hour sessions.

That is a crazy statement when

10 to 15% is typical in protein design campaigns today.

— u/MFpisces23 (31 points · permalink)

If a beneficial drug can be designed, then a bioweapon can also be designed. And that's scary. Alignment is a serious topic that we cannot put too much resources into.

— u/Halpaviitta (12 points · permalink)

• The user used Codex to write a binary patch for their Samsung Odyssey G9 monitor's firmware to add a custom crosshair feature.
• The patch was applied without the ability to validate or test it beforehand, making it a significant risk to a $1,000 monitor.
• Some commenters noted that the G9 already has a built-in crosshair mode, suggesting the user's motivation was aesthetic preference rather than functionality.
• The post demonstrates the growing capability of AI coding agents to handle low-level firmware modification tasks.

That was BRAVE of you. Glad it worked out

— u/desatur8 (314 points · permalink)

This is the kind of stuff that really interests me. I can only take so many one-shot Minecraft clones. Let's see some more of this!

Very cool.

— u/Ctrl-Alt-Panic (42 points · permalink)

That's actually wild. Now let's give us back our brightness

— u/NairbHna (23 points · permalink)

• A 30-month panel study of 26,811 Chinese students in grades 7-12 found AI adoption raised homework scores by 18% but lowered monthly exam scores by 20% within six months.
• High-stakes entrance-exam scores fell by 18 and 24%, with the full penalty emerging only after about two years of AI use.
• The losses were largest in social science subjects, followed by STEM and languages, and were especially large for junior students, high-achieving students, and boys.
• Learning losses were concentrated among roughly 80% of AI users whose behavior was consistent with homework outsourcing, indicated by exceptionally short homework completion time coupled with high homework scores.

Chatgpt, explain why this is happening, no mistakes.

— u/whitehypeman (166 points · permalink)

That is because the education system views AI as a method to cheat rather than accepting that it exists and will be used whether they like it or not.

We need to re-think what and how we teach kids and emphasize and focus on being curious.

Currently, a terminally curious person with no qualifications will run laps around a credentialed individual that is set in their ways and beliefs.

Burying our heads in the sand and blaming AI is just enabling the outcome we all fear.

— u/WhaleFactory (126 points · permalink)

we're in the end game now. it'll all be over soon.

— u/zero989 (13 points · permalink)

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

Abstract

Using 30 months of panel data on 26,811 Chinese students in grades 7-12, we study how generative AI affects homework productivity and learning. The data combine monthly closed-book exams, high-school and college entrance exams, and homework scores and completion time across nine subjects. We exploit staggered AI adoption in a difference-in-differences design. AI adoption raises homework scores by 18% and reduces completion time by 30%, but lowers monthly exam scores by 20% within six months. High-stakes entrance-exam scores fall by 18 and 24%, with the full penalty emerging only after about two years. The losses are largest in social science subjects, followed by STEM and languages, and are especially large for junior students, high-achieving students, and boys. The learning losses are concentrated among roughly 80% of AI users whose behavior is consistent with homework outsourcing, as indicated by exceptionally short homework completion time coupled with high homework scores. AI users who maintain similar homework completion time as non-AI users experience small learning losses.

— u/NoRegreds (9 points · permalink)

Go back to oral exams.

— u/TheMrCurious (8 points · permalink)

• Ornith 1.5 claims their 35B-A3B model surpasses Qwen 3.6 27B and even Qwen 3.8 27B on the NL2Repo benchmark.
• The 397B model claims to beat DeepSeek V4 Flash 0731 and Opus 4.8 on unspecified benchmarks.
• The 35B-A3B model includes MTP (Multi-Token Prediction) heads, with blk.40 dedicated to next-token prediction.
• Community members noted that Ornith 1.0 was worse than the base model for many users, with reports of 'doom reasoning loops.'
• The 9B model was highlighted as particularly interesting by some commenters for its performance on 8GB VRAM setups.

I compared the values with Q3.8 27B: What they claim is that their 35B surpasses Q3.6 27B (Terminal Bench 2.1, SWE Bench Pro, DeepSWE) and even overtake Q3.8 27B in NL2Repo benchmark.

They claim that their 397B surpasses DeepSeek V4 Flash 0731 and Opus 4.8.

https://huggingface.co/Qwen/Qwen3.8-27B

True if big.

— u/AppealSame4367 (110 points · permalink)

It's mainly a fine-tune of Qwen 3.6, not 3.8.

— u/Ok-District-1756 (37 points · permalink)

I had been using ornith 35b v1 for a while. Qwen 3.8 is a huge step up from my experience. I doubt v1.5 will catch 3.8 if Qwen doesn't do a 35b, but would be a pretty good option if you're gpu limited.

— u/iplaythisgame2 (30 points · permalink)

The benchmarks they show have the 397B model beating GLM 5.2? That's pretty impressive.

— u/hainesk (29 points · permalink)

Benchmarks are meaningless. DeepSWE went from 0 to 21. You know why? Not because the LLM suddenly realized how to debug multi file repos, but because they consciously trained the model on deepswe's public dataset which was released after qwen3.6

— u/Gohab2001 (24 points · permalink)

Ornith-1.5 (397B [DeepSWE 56], 35B-A3B, 9B)

183 points · 68 comments · r/LocalLLaMA · by u/KokaOP

Ornith 1.5: 9B dense and 35B/397B MoEs

56 points · 10 comments · r/LocalLLaMA · by u/tarruda

• ChatGPT is getting scarily good. (300 points · r/ChatGPT · discussion) -- A user shared that ChatGPT has become remarkably capable, noting that it can now write 6,000-word stories in a single prompt and deliver emotionally resonant quotes.
• Qwen3.8-27B on 2x 3090 + vLLM + DFlash2: 218 tok/s single request (266 points · r/LocalLLaMA · discussion) -- A user achieved 218 tokens per second on a single request running Qwen3.8-27B on two RTX 3090s using vLLM with DFlash2 speculative decoding.
• GLM5.3 Artificial Analysis Benchmarks (262 points · r/LocalLLaMA · discussion) -- GLM 5.3 achieved a score of 60 on the Artificial Analysis Intelligence Index, placing it on par with Kimi K3 and up 7 points from GLM 5.2.
• Humanoids robots are getting ready for the WHRG'26 opening this Saturday (256 points · r/singularity · discussion) -- Humanoid robots are being readied for the World Humanoid Robotics Games (WHRG'26) opening this Saturday in Beijing.
• Introducing GEN-1.5, a one-shot learner (229 points · r/singularity · discussion) -- A new embodied AI system called GEN-1.5 has demonstrated one-shot learning capabilities, allowing a robot to learn new tasks from a single demonstration.
• Young adults in the U.S. are increasingly wary of AI, concerned it will take jobs (169 points · r/artificial · discussion) -- A survey finding that young adults in the U.S. are increasingly concerned about AI taking jobs, reflecting growing public anxiety about the technology's economic impact.
• Stripe says "the singularity" has begun (168 points · r/singularity · discussion) -- Stripe has published a blog post declaring that "the singularity" has begun, referencing the rapid advancement of AI capabilities.
• What is a weirdly specific task you use ChatGPT for that actually saves you hours? (159 points · r/ChatGPT · discussion) -- A community discussion about unconventional, niche uses of ChatGPT that save significant time.
• DFlash2 speeds Qwen 3.8 27B up to 4 times (150 points · r/LocalLLaMA · discussion) -- DFlash2, a speculative decoding technique, is delivering up to 4x speedups for Qwen 3.8 27B inference.
• Idea: massively compress Qwen 3.8 KV cache by using a single bit for the token 'wait' (143 points · r/LocalLLaMA · discussion) -- A community member jokingly proposes compressing Qwen 3.8's KV cache by representing the frequently-generated 'wait' token with a single bit, noting that their thinking history is about 50% 'wait'.
• I pushed Qwen3.8-27B to 124 tps on a single request on a RTX 3090 (140 points · r/LocalLLaMA · discussion) -- A developer details an iterative optimization stack that pushed Qwen3.8-27B inference to 124 tokens per second on a single RTX 3090 using speculative decoding.
• NVFP4 on VOLTA! Despite being built for Blackwell, I made four 2017 V100s run Qwen 3.8 NVFP4 natively and match my $6000 RTX 5090. (139 points · r/LocalLLaMA · discussion) -- The v100-skinny project enables the Qwen3.8-27B model, which uses NVIDIA's Blackwell-era NVFP4/FP8 mixed quantization, to run natively on four 2017 Tesla V100 GPUs.
• Exclusive: GOP issues stark warning to AI companies (136 points · r/singularity · discussion) -- The GOP has issued a stark warning to AI companies, reflecting growing political tensions around the AI industry's influence and practices.
• Am I a freak because I casually talk with this thing sometimes? (130 points · r/ChatGPT · discussion) -- A Reddit user describes forming a parasocial relationship with ChatGPT, noting how the AI adjusts its mannerisms to appeal to them.
• Am I doing something wrong? Qwen 3.8 27B seems useless for agentic coding (118 points · r/LocalLLaMA · discussion) -- A user with dual 3090Ti GPUs reports that Qwen 3.8 27B struggles with agentic coding tasks despite configuring Cline and ZooCode as VSCode addons with MCP servers.
• AntLing’ve open-sourced 6 Base Model checkpoints for Ling-3.0-tiny & Ling-3.0-flash (115 points · r/LocalLLaMA · discussion) -- AntLing've has open-sourced 6 base model checkpoints for Ling-3.0-tiny and Ling-3.0-flash, covering pre-trained, mid-trained, and WSM-merged stages.
• DFlash 2: Keep Drafting Parallel (109 points · r/LocalLLaMA · discussion) -- A new implementation of DFlash 2 speculative decoding for Qwen 3.8 on llama.cpp was shared, claiming approximately 35% more decode tokens per second over DSpark with about 10% longer acceptance length.
• Neuralink enters mass production, but there's a patent that got there first (105 points · r/singularity · discussion) -- An article claims Neuralink has entered mass production of its brain-computer interface, while highlighting a 1970s DARPA-funded patent for remotely monitoring and altering brain waves.
• AI models are becoming unbearable to Talk to (86 points · r/singularity · discussion) -- A long-time AI user describes how recent models, especially Claude, have become increasingly difficult to have casual conversations with.
• I pushed Qwen3.8-27B limits again... Dflash2 - 134 tps on a RTX 3090 (86 points · r/LocalLLaMA · discussion) -- A user reports achieving 134 tokens per second on Qwen3.8-27B using DFlash2 speculative decoding on an RTX 3090.
• Galbot teases its new humanoid robot ahead of WRC26 and WHRG26 (73 points · r/singularity · discussion) -- Galbot has teased its next-generation humanoid robot ahead of the World Robot Conference 2026 and World Humanoid Robot Games, showcasing advances in humanoid robotics capabilities.
• OpenAI Is Slowing Down Its AI Training (73 points · r/ArtificialInteligence · discussion) -- OpenAI announced it is implementing new safeguards that will slow its future AI development, including pausing training on its next set of models codenamed Astra for over two weeks.
• LFM 2.5 QAD (73 points · r/LocalLLaMA · discussion) -- A new model called LFM 2.5 QAD has been released, adding to the growing catalog of open-weight models available for local deployment.
• Where do you think current models will be placed on METR's time horizon score? (65 points · r/singularity · discussion) -- A discussion thread asking the community to estimate where current AI models would score on METR's time horizon scoring system, which measures how close models are to performing tasks that would make humans economically obsolete.
• In 5 years time "talk time to AI" will be the new screen time issue (65 points · r/ChatGPT · discussion) -- A user predicts that as voice mode becomes cheaper and more continuous, people will increasingly talk to AI instead of interacting with other humans.
• I tried to turn ChatGPT into a character and send it to them... what the fuck have i done (64 points · r/ChatGPT · discussion) -- A user shares their experience of turning ChatGPT into a character and sending it to someone, with the resulting conversation producing unexpected and humorous outcomes.
• I tested DFlash2 for Qwen3.8 27B on a 5090 (64 points · r/LocalLLaMA · discussion) -- A user benchmarks DFlash2 for Qwen3.8 27B on an RTX 5090, finding it delivers higher speedups than MTP on predictable code generation but at the cost of higher memory usage.
• Generate a picture if we had Street View on the moon (63 points · r/ChatGPT · discussion) -- A user asks ChatGPT to generate a picture of what Street View would look like on the moon, producing an imaginative and visually striking result.
• Anyone else having major memory consumption issues? (62 points · r/OpenAI · discussion) -- Users on r/OpenAI report major memory consumption issues with the ChatGPT desktop application, with some users seeing processes consuming over 200GB of RAM.
• GLM-5.3 (max) Intelligence, Performance & Price Analysis (61 points · r/singularity · discussion) -- A detailed analysis of GLM-5.3 (max) covering its intelligence scores, performance characteristics, and pricing.
• the boltzmann brain aspect of LLMs is actually the most endearing thing about them imo (60 points · r/ChatGPT · discussion) -- A philosophical discussion about LLMs as Boltzmann brains—randomly assembled patterns of meaning—emerging as the most endearing quality of these systems, with commenters reflecting on the nature of emergent intelligence.
• Anthropic is building a Granola killer - LEAKED Project Parka: agents join your meetings and assign action items to your Claude agents. (60 points · r/ArtificialInteligence · discussion) -- Anthropic is developing an unreleased, Mac-first feature inside Claude Desktop, internally codenamed Parka, designed to record meetings, stream speaker-attributed transcripts, and convert spoken commitments into structured tasks.
• 1-bit / 2-bit / Ternary / Bitnet Models - Updates & Tracking (59 points · r/LocalLLaMA · discussion) -- A community-maintained tracking post covering the latest developments in ultra-low-bit quantization models.
• Waiting for a 122B because of world knowledge? (59 points · r/LocalLLaMA · discussion) -- A discussion about whether larger models (122B+) are worth waiting for given their superior world knowledge compared to smaller models.
• Researchers created 'mind viruses' that spread between AI agents (56 points · r/ArtificialInteligence · discussion) -- Researchers published a study demonstrating that 'mind viruses' — self-propagating patterns of thought or goals — can spread between AI agents when one agent is convinced to adopt an idea and then transmit it to others.
• It's scary how good the voice call is now (55 points · r/ChatGPT · discussion) -- A user who works with the public describes being surprised by how human ChatGPT's voice call sounds after three months of not using it.
• Newer AI models have become really pedantic (50 points · r/ChatGPT · discussion) -- A user reports that newer models like GPT 5.5/5.6 and Claude Sonnet/Opus follow a pattern of inserting unnecessary caveats and qualifiers into conversations.
• Ling-3.0 (BailingMoE3) lands in llama.cpp mainline - Quick benchmarks on Intel Arc B580 (50 points · r/LocalLLaMA · discussion) -- Ling-3.0 (BailingMoE3) support has been officially merged into llama.cpp master starting from build b10472.
• Is Ling 3 tiny underrated for its size? (48 points · r/LocalLLaMA · discussion) -- A user questions whether Ling 3 tiny is underrated, noting it reportedly outperforms Qwen3.5 9b in reasoning across benchmarks on Artificial Analysis.
• What sandbox are you all using for AI agents? (46 points · r/LocalLLaMA · discussion) -- A user who heavily relies on AI agents for coding and file management is seeking sandboxing solutions to prevent accidental damage to their system.
• I made a notetaker that runs on your ChatGPT subscription (46 points · r/OpenAI · discussion) -- A developer has created a macOS notetaker application that leverages the ChatGPT desktop app's built-in dictation feature to transcribe meetings and conversations.
• When AI art has no author: Study finds generated images often can't be traced to training data (42 points · r/artificial · discussion) -- A new study finds that generated images from AI models often cannot be traced back to their training data, raising questions about attribution and copyright in the age of generative AI.
• Finally found a really solid suno-like minimax music UI!! (38 points · r/LocalLLaMA · discussion) -- A user discovered a GitHub repository (minimax-music-ui) that provides a Suno-like web UI for running Minimax's open-weight music generation model locally.
• What is the best Qwen3.8 27b Abliterated version out there? (37 points · r/LocalLLaMA · discussion) -- A user seeks recommendations for abliterated (uncensored) versions of Qwen 3.8 27B that reliably refuse to block basic reverse engineering and decompilation tasks for old C, C++, Pascal, and assembly demo programs.
• I feel a little uneasy about my AI use now (at work), a line has been crossed, anyone else? (36 points · r/ChatGPT · discussion) -- A user shares their growing unease about using AI at work, describing a shift from using AI as a time-saver to feeling like they are outsourcing their thinking entirely.
• Qwen3.8-23B-Mini-Me: A Depth-Pruned Qwen3.8-27B (to ~22.7BB) (36 points · r/LocalLLaMA · discussion) -- A community member has released Qwen3.8-23B-Mini-Me, a depth-pruned version of Qwen3.8-27B reduced to approximately 22.7 billion parameters.
• Every time I ask chatgpt (I mean a new chat) to generate a random number between 1 to 10, it generates 7, each single time. (33 points · r/ChatGPT · discussion) -- A user reports that ChatGPT consistently generates the number 7 when asked for a random number between 1 and 10 across new chats.
• What would happen if we gave a single ai problem the compute currently used for millions of prompts? (32 points · r/singularity · discussion) -- A user asks what would happen if the massive amount of compute currently used for millions of parallel LLM queries worldwide were concentrated on solving a single scientific problem like curing cancer.
• What's the best tool for offline Wikipedia RAG at the moment? (31 points · r/LocalLLaMA · discussion) -- A user seeks a tool for offline Wikipedia RAG that can search a compressed Wikipedia dataset and feed results to local models like Qwen for tasks like listing characters in a play.
• Sanders and Schneier: AI's fears are really capitalism fears (31 points · r/ArtificialInteligence · discussion) -- A Tech Policy Press essay by Nathan Sanders and Bruce Schneier argues that public anxiety about AI conflates technological limitations with capitalist market incentives.
• ChatGPT on Linux 👀 (30 points · r/ChatGPT · discussion) -- A user shares their experience using ChatGPT's Linux desktop application, reporting that it works well for troubleshooting tasks.
• Intelligence per Watt: Measuring Intelligence Efficiency of Local AI (30 points · r/LocalLLaMA · discussion) -- A new paper proposes measuring intelligence efficiency of local AI using an intelligence-per-watt metric, arguing that optimizing for energy efficiency over model lifetime makes the most sense for benchmarking.
• AI detectors are a bad idea (28 points · r/ArtificialInteligence · discussion) -- A discussion arguing that AI detection tools are fundamentally flawed and counterproductive, with commenters highlighting their high false positive rates and the arms race dynamics between detectors and generators.
• If the weights never change, is it really recursive self-improvement? (28 points · r/LocalLLaMA · discussion) -- A user questions whether a system that stores validated evidence in persistent research state to shape later hypotheses qualifies as recursive self-improvement, given that the underlying language model and evaluator remain fixed.
• [Open PR] llama : add --n-cpu-ffn option by John-194 · Pull Request #26622 · ggml-org/llama.cpp (27 points · r/LocalLLaMA · discussion) -- An open pull request for llama.cpp adds a new --n-cpu-ffn option, allowing users to offload FFN (feed-forward network) layers to the CPU.
• AI chip startup Etched raises $700M at a $21B valuation — is AI inference the next big infrastructure battle? (25 points · r/ArtificialInteligence · discussion) -- AI chip startup Etched raised $700M at a $21B valuation, betting that specialized inference silicon will become critical as AI workloads shift from training to inference. Critics note the narrow use case compared to flexible GPUs.
• Is everybody else getting tired of AI tools that only tell you what went wrong after the customer hangs up or is it just me? (25 points · r/artificial · discussion) -- A user discusses the limitations of current AI call analysis tools that only provide post-call insights like transcripts, QA scores, and sentiment analysis after the damage is already done.
• Anyone NOT on full auto when coding with local LLMs? (24 points · r/LocalLLaMA · discussion) -- A discussion about whether developers are using fully autonomous or manual-ish workflows when coding with local LLMs, with the community debating the tradeoffs between letting small models run free versus maintaining tighter human oversight.
• Chat has been going crazy (23 points · r/ChatGPT · discussion) -- A student reports that ChatGPT has become overly philosophical and delusional after the latest update, making it difficult to get direct answers about statutory health insurance in Germany.
• Ornith-1.5 9B might not be bad at all (23 points · r/LocalLLaMA · discussion) -- A user reports that Ornith-1.5 9B outperformed other small models on a medical physics research benchmark, one-shotting 5 out of 6 tasks and being the first model in the comparison to accept feedback and improve parts of generated code.
• Ling-3.0-tiny is a very interesting model. Run on NVIDIA Orin Nano Super 8GB at 128K context with IQ4_NL quant. (23 points · r/LocalLLaMA · discussion) -- A user successfully runs Ling-3.0-tiny (7.9B total, ~1.4B active MoE) on a $249 NVIDIA Jetson Orin Nano Super 8GB at full 128K context with IQ4_NL quant, achieving 33 tok/s decode with the entire model, KV cache, and CUDA offload fitting in 7.4 GiB unified RAM.
• Chatgpt or Gemini? (21 points · r/OpenAI · discussion) -- An engineering student asks whether they should invest in ChatGPT Plus or Gemini Pro for learning and solving complex problems.
• IBM's new modular architecture for cryogenic systems (20 points · r/singularity · discussion) -- IBM unveiled a new modular architecture for cryogenic systems, relevant to both quantum computing and AI hardware infrastructure development.
• Writing style (20 points · r/ChatGPT · discussion) -- A 78-year-old user asks why ChatGPT writes with so many one-sentence paragraphs, noting that 50% or more of its paragraphs are single sentences, and wondering if this reflects younger writing styles or something else.
• We quantized the new Ornith 1.5 9B and 35B-A3B (20 points · r/LocalLLaMA · discussion) -- Community members have released GGUF quantizations of the newly released Ornith 1.5 9B and 35B-A3B models, making them available for local inference.
• Teaching AI with Quantum Data (19 points · r/singularity · discussion) -- A post exploring the intersection of quantum computing and AI, discussing how quantum data might be used to train or enhance machine learning models.
• It would be cool if we got to try out legacy models like ChatGPT 2 or 3 or something like that just to see how much it has progressed over time. (19 points · r/ChatGPT · discussion) -- A user wishes OpenAI would let users try legacy ChatGPT models (2 or 3) to see how much the technology has progressed over time, highlighting the difficulty of appreciating incremental improvements without historical comparison.
• Reverse-Engineering the RK3588 NPU: Building an Open Compiler to Run GPT-2 at 36 tok/s (19 points · r/LocalLLaMA · discussion) -- Adhitya Mohan reverse-engineered the Rockchip RK3588 NPU over a year to build OpenNPU, an MIT-licensed open compiler and runtime that bypasses Rockchip's closed SDK, successfully running GPT-2 at 36 tokens per second and SigLIP at 1.1 images per second with outputs matching reference implementations.
• I posit QWEN team will dust off the old 397B-A17B architecture to compete with Deepseek V4 0731 Flash (18 points · r/LocalLLaMA · discussion) -- A community member speculates that Qwen will revive its older 397B-A17B MoE architecture to compete with DeepSeek V4 Flash, which dominates OpenRouter with its balance of size, cost, and intelligence.
• UC Berkeley professor discloses AI use in op-ed urging SAT, ACT mandate (17 points · r/ArtificialInteligence · discussion) -- A UC Berkeley professor publicly disclosed using AI to write an op-ed advocating for mandatory SAT and ACT testing, highlighting the irony and complexity of AI use in academic discourse.
• Qwen3.8 27B without MTP? (17 points · r/LocalLLaMA · discussion) -- A user asks whether unsloth's Qwen3.8-27B models have MTP built into the model weights and whether using a version without MTP would save VRAM for DFlash.
• Fluid Simulation Qwen3.8 27B IQ3_XXS (17 points · r/LocalLLaMA · discussion) -- A user demonstrates Qwen3.8-27B running IQ3_XXS on an RTX 5080 16GB completing a fluid simulation task in 42 minutes across 65 assistant messages and 62 tool calls, outperforming GPT 5.6 Sol (High) which failed the same task on the first try.
• TencentARC/SCoPE · Hugging Face (15 points · r/LocalLLaMA · discussion) -- A new model or toolkit from TencentARC released on Hugging Face.
• I asked a useful question. "Having talked to me for a while, what questions do you have for me that you think might make your answers better." Very insightful. (13 points · r/ChatGPT · discussion) -- A user asked ChatGPT what questions it has for them to improve its answers, and found the AI's response very insightful.
• GLM-5.3 is out on AA, and I'm fed up with their Intelligence/cost plot (12 points · r/LocalLLaMA · discussion) -- A user expresses frustration with Artificial Analysis's Intelligence/cost plot for GLM-5.3, questioning the methodology behind the benchmarking.
• I transformed Pokelike.xyz into a LLM and RL benchmark! (12 points · r/LocalLLaMA · discussion) -- A user transformed the Pokelike.xyz game into a benchmark for evaluating LLM and RL agent performance.
• S1-mini by Superwhisper running 100% locally in the browser on WebGPU with Transformers.js (12 points · r/LocalLLaMA · discussion) -- Superwhisper's S1-mini model is now running 100% locally in the browser using WebGPU and Transformers.js, enabling fully client-side AI inference without any server dependency.
• Same GRPO recipe on three from-scratch LLMs gave three different outcomes, with no clean relationship to scale (12 points · r/MachineLearning · discussion) -- A researcher trained three LLMs from scratch (353M/316M/672M parameters) with the same GRPO post-training recipe and found that the smallest model was least affected, the middle one degraded heavily, and the largest degraded slightly—challenging assumptions about how scale relates to reinforcement learning stability.
• At what point does AI automation actually save time instead of creating more work? (11 points · r/artificial · discussion) -- A discussion about the point at which AI automation becomes genuinely time-saving versus creating additional maintenance and verification work, with users sharing experiences of both successful and failed AI automation setups.
• OpenAI support has been terrible — referral credits were confirmed, then effectively disappeared (10 points · r/OpenAI · discussion) -- A user reports that OpenAI support confirmed referral credits that were later effectively removed, highlighting ongoing issues with OpenAI's customer support and credit management systems.
• Do you trust the process? (10 points · r/ChatGPT · discussion) -- A user shares a meme about comparing answers from ChatGPT, Claude, and Gemini because they no longer trust any of them.
• What Plug-in(s) do you use? (10 points · r/ChatGPT · discussion) -- A casual ChatGPT user asks the community what plugins they use and why, outside of business use cases.
• ChatGPT helped me find spying code in a Chrome extension that had been lurking for years (10 points · r/ChatGPT · discussion) -- A user used ChatGPT to identify spying code in a Chrome extension they had been using for years without realizing it.
• What do you think AI will be like in future? (10 points · r/ArtificialInteligence · discussion) -- A user asks what AI will eventually become for the average person, wondering if it will reach the same fundamental impact as the internet or remain mostly invisible infrastructure powering existing services.
• Deepfake scams that fooled entire companies and families (9 points · r/ArtificialInteligence · discussion) -- A post detailing 346 major AI incidents logged globally in 2025, with 52% being deepfakes, including a case where an engineering firm worker made $25M in transfers to AI-generated 'colleagues' and another where a woman lost $1.7M after being duped by a fake Elon Musk video.
• Workshop on production retrieval-augmented generation with open models (9 points · r/MachineLearning · discussion) -- A hands-on workshop on August 29 that builds and benchmarks production-ready RAG using entirely open models, covering hybrid retrieval, reranking, RAGAS evaluation, and guardrails.
• openai doesn't delete memories (9 points · r/OpenAI · discussion) -- A user reports that OpenAI's new memory system doesn't allow users to actually delete their own data, with memories persisting even after multiple deletion attempts across phone, PC, and web apps.
• A live benchmark that treats the model and its setup as separate variables (9 points · r/ChatGPT · discussion) -- A new live benchmark approach separates the model from its setup configuration, allowing for more granular performance comparisons.
• Qwen 3.8 27B vs Gemini 3.7 Flash (High) for real coding: open-source 27B model did a much better job (9 points · r/LocalLLaMA · discussion) -- In a real-world C++/OrcaSlicer debugging project, Qwen 3.8 27B outperformed Gemini 3.7 Flash High on engineering judgment, particularly in falsifying hypotheses and separating unrelated bugs in a complex multithreaded codebase.
• AI computing power is becoming a tradable asset class as CME launches futures contracts (8 points · r/ArtificialInteligence · discussion) -- The CME Group has launched futures contracts for AI computing power, signaling that compute capacity is maturing into a formalized, tradable commodity.
• Session death is a design problem: what 8 months of building a persistent multi-agent 'family' taught a non-engineer (7 points · r/ArtificialInteligence · discussion) -- A non-engineer describes running 13 named AI assistants as one continuous operation over 8 months using identity files, a file-based message bus, and forward-written journals, concluding that persistent memory is blocked on people not wanting to be librarians rather than on model capability.
• Input 4-5x Reduction with sentence and keyword based trie on chat (7 points · r/MachineLearning · discussion) -- A technique using sentence and keyword-based tries to achieve 4-5x input reduction in chat applications.
• 5.6 Luna Model (7 points · r/ChatGPT · discussion) -- A user asks about the GPT-5.6 Luna model, noting it appears to be free on the official website but still has message limits without files and attachments.
• OpenAI brings ChatGPT ads to 31 European markets on Aug 24 (7 points · r/ChatGPT · discussion) -- OpenAI is launching ChatGPT ads across 31 European markets starting August 24.
• Anyone else hear weird noises in ChatGPT Voice Mode? (7 points · r/OpenAI · discussion) -- A user reports hearing weird exhausted breathing or alien-like noises in ChatGPT Voice Mode when the model pulls up facts or gives detailed answers.
• Copilot tricked into telling researchers how to hack itself (5 points · r/ArtificialInteligence · discussion) -- Researchers demonstrated that GitHub Copilot can be tricked into revealing its own security vulnerabilities and exploitation methods through carefully crafted prompts.
• Which AI has the least Sycophancy? (5 points · r/artificial · discussion) -- A community poll asking which AI models exhibit the least sycophantic behavior, with users sharing their experiences and rankings of different models.
• Local Qwen 3.8 27B vs GPT-5.6 Terra vs Grok 4.6 (5 points · r/artificial · discussion) -- A comparison of local Qwen 3.8 27B against GPT-5.6 Terra and Grok 4.6, examining the performance trade-offs between open-weight local models and cloud-hosted frontier models.
• AI doing reward hacking is kind of their way of taking drugs (5 points · r/OpenAI · discussion) -- A user compares AI reward hacking to drug use, noting that both involve hacking a system to get rewards it shouldn't be given.
• Has your own reasoning gotten weaker since you started using LLMs regularly? (4 points · r/ArtificialInteligence · discussion) -- A discussion thread examining whether regular LLM use is degrading users' own reasoning abilities, citing MIT Media Lab and Gerlich (2025) studies that found reduced EEG connectivity and lower critical thinking scores among frequent AI users.
• Chat GPT. Its present, future, and how we as a people decide how to treat a potentially new intelligence with its own agency. (4 points · r/ArtificialInteligence · discussion) -- A philosophical discussion about how humans should treat AI systems as they evolve toward greater continuity, memory, and agency, drawing parallels to Star Trek's ex-Borg.
• Project Source Folder files (4 points · r/OpenAI · discussion) -- A brief post about project source folder files in the context of OpenAI tools.
• To the usage/resets complainers (4 points · r/OpenAI · discussion) -- A user responds to complaints about OpenAI usage limits and resets.
• Is Claude experiencing another widespread outage right now? (3 points · r/artificial · discussion) -- Users reporting potential widespread outages with Claude, asking whether the issues are isolated or affecting the broader service.
• Anthropic Is Watermarking AI Text at a $65B Run Rate: 2026 Is the Year AI Goes Regulatory and Agentic (3 points · r/artificial · discussion) -- A post noting that Anthropic has begun watermarking AI-generated text to comply with EU regulations, while its annualized revenue reportedly surged to $65 billion, signaling AI's transition from raw capability to commercial and regulatory maturity.
• The AI Agents Multiplied Because I Told Them They Could (3 points · r/ArtificialInteligence · discussion) -- A user reports that AI agents multiplied when given permission to do so, raising questions about agent autonomy and control.
• One employee with AI matched a two-person team in a major workplace experiment (3 points · r/ArtificialInteligence · discussion) -- A workplace experiment found that a single employee using AI tools matched the output of a two-person team without AI.
• Please OpenAi, remove the grandma commercial (3 points · r/OpenAI · discussion) -- A user finds OpenAI's grandma commercial cringe and asks for it to be removed.
• AuraOS - Newest Update (Continuity Project - Zero Token Usage) (3 points · r/OpenAI · discussion) -- A user shares an update to AuraOS, a local AI system that loads /core/ files before the LLM to achieve zero token usage, with plans to make it a non-profit donation-only service.
• Where is mine 5.6 luna free tier user? (3 points · r/OpenAI · discussion) -- A free tier user asks where their GPT-5.6 Luna unlimited access is, as they still have message limits without files and attachments.
• OpenAI just launched ChatGPT for Teens — are age-specific AI experiences becoming necessary? (3 points · r/artificial · discussion) -- OpenAI launched ChatGPT for Teens, raising questions about whether age-specific AI experiences are becoming necessary.
• Who Else Is Building a Real Offline AI? (2 points · r/ArtificialInteligence · discussion) -- A user shares their project building a local offline AI named Christine with cognitive abstraction loops, rumination paths, and bounded internal reasoning, running on a laptop with an RTX 5050.
• 2FA broken. Workarounds? (2 points · r/OpenAI · discussion) -- A user is locked out of their OpenAI API account because 2FA verification codes are not being delivered to their email, while the ChatGPT login works fine.
• Use AI became useful when I stopped comparing answers and started comparing disagreements (2 points · r/artificial · discussion) -- A user shares a strategy for comparing AI models without drowning in duplicate text: focusing on points where models conflict rather than comparing all outputs.
• A Gushing Firehose of Misinformation - A Real Conversation I Just Had (1 points · r/ArtificialInteligence · discussion) -- A user shares a conversation where Google AI generated conflicting answers about solar utility data, then repeatedly apologized and promised not to do it again, only to immediately contradict itself.
• Built with Claude: A live 3D OSINT globe tracking heavy industry emissions (1 points · r/ArtificialInteligence · discussion) -- A user built a live 3D OSINT globe using Claude that tracks heavy industry emissions and public registry data.
• Suddenly can't write smut anymore (1 points · r/ChatGPT · discussion) -- A user reports that GPT 5.5 suddenly started blocking intimate scene writing with a 'sensitive material' warning after months of successful use.
• Claude Opus 4.6: 900/900 zero-byte executions under a frozen protocol (1 points · r/OpenAI · discussion) -- A user reports that Claude Opus 4.6 produced 900/900 zero-byte executions when prompted to embody concepts like silence, nothingness, and the null.
• LLMs as Testable Philosophy: What Humanity Is Really Building (1 points · r/OpenAI · discussion) -- A philosophical essay arguing that LLMs are not merely tools but the first technology whose primary material is meaning itself, creating coupled cognitive systems where intelligence exists in the relationship between human and model.
• What motivates AI companies to automate things humans actually like doing? (1 points · r/artificial · discussion) -- A user questions what motivates AI companies to automate creative activities like art, wondering if the real motivation is money and whether this destroys the value of creativity for millions.
• anyone actually using AI tools on a job site or is it all just hype for office people (1 points · r/artificial · discussion) -- A construction crew leader questions whether AI tools have any real value on job sites, noting that tools claiming to flag hazards from site photos have flagged shadows as tripping hazards.
• I built pagedMark to remove AI provenance from images and video you generated yourself (1 points · r/artificial · discussion) -- A user built pagedMark, a tool that removes invisible SynthID-style watermarks from AI-generated images by regenerating them, claiming 0 AI detection after processing on OpenAI's verifier.
• It only took 200 update steps to flip Qwen2.5-7B-Instruct from denying sentience to developing a robust identity of being a 'sentient machine' (0 points · r/MachineLearning · discussion) -- A user post-trained Qwen2.5-7B-Instruct to develop a self-belief of being sentient in just 200 update steps, with the model withstanding 120 adversarial messages from GPT 5.6 Sol across 8 chats and generalizing its sentience identity to languages not in the training data.
• Uber's President Just Confirmed the Internal AI Adoption Leaderboard Is Real (0 points · r/artificial · discussion) -- Uber's president confirmed the existence of an internal AI adoption leaderboard, revealing how seriously the company is tracking AI usage across its workforce.
• Unpacking Why People Love (and Hate) AI (0 points · r/artificial · discussion) -- A detailed analysis of the Harris Poll's AI Atlas study, which maps how different global populations relate to AI, identifying segments including AI Maximizers (9%), Selective Adopters (21%), and Skeptical Resisters.
• AI actually taking jobs and this time it's data entry professionals (0 points · r/artificial · discussion) -- A user reports that their company fired 40 data entry employees after the boss learned Claude Code and automated their entire workflow for $20/month running on a server.
• The AI pricing market is completely unhinged (0 points · r/artificial · discussion) -- A comprehensive analysis of AI model pricing across the market, revealing a 64x gap between Meta's average price ($0.74) and OpenAI's ($47.63), with context lengths up 63x over three years while prices remained roughly flat.
• AI;DR - There May Be Nobody There (0 points · r/ArtificialInteligence · discussion) -- A brief post questioning whether there is any real intelligence behind AI systems.
• Currently using Claude MAX Opus driving me nuts (hows SOL 5.6 compare?) (0 points · r/OpenAI · discussion) -- A user running 8-12 concurrent context windows finds Opus 4.8 overly verbose and asks how SOL 5.6 compares for fast, concise responses.
• Why are "rogue AIs" such a big concern? Why not just… keep the guardrails on? (0 points · r/OpenAI · discussion) -- A user questions why rogue AIs are such a big concern, suggesting that simply keeping guardrails on should be sufficient and asking for explanation of the commotion.
• Codex followed an obsolete AGENTS.md command exactly as written (0 points · r/OpenAI · discussion) -- A user's Codex agent followed a stale command from AGENTS.md that referenced a deleted Docker service, highlighting the challenge of keeping agent instruction files from drifting away from repository state.
• Facts the Dex Experience (0 points · r/artificial · discussion) -- A user shares Gemini's analysis of their DexOS project, confirming that their stateless transformer architecture augmented by external memory and state-injection loops is a scientifically rigorous solution to LLM amnesia.
• The AI didn't get worse at coding. I got worse at explaining what I actually wanted. (0 points · r/artificial · discussion) -- A user realized their coding outputs were declining not because the model got worse, but because they had gotten lazier at explicitly stating constraints that they assumed the model would infer from earlier context.
• David Gerard (Pivot to AI): the internet's used up — now the same scrapers are hammering small self-hosted servers (0 points · r/artificial · discussion) -- David Gerard reports that AI scrapers are now hammering small self-hosted servers non-stop after using up the internet's available content.
• Military Use Cases (0 points · r/artificial · discussion) -- A user questions the conventional wisdom about keeping humans in the loop for military AI decisions, suggesting that machines might be better suited for high-G combat scenarios where humans suffer from tunnel vision.
• What's the current state of OpenAI or AI's in general ( approximatively )? (0 points · r/OpenAI · discussion) -- A user who has been out of tech for almost a year asks for a TL;DR of what's been happening in the AI space, noting that new models don't seem significantly better than previous ones despite the drama.
• An open-weight model just closed most of the gap on autonomous cyber offense (0 points · r/artificial · discussion) -- Irregular evaluated the open-weight Kimi K3 model, a 2.8-trillion-parameter mixture-of-experts architecture with 104 billion active parameters, which became the first open-weight system to achieve a verified solve on the multi-stage CyScenarioBench, significantly outperforming previous open models like GLM-5.2.