Open Models Surge, Anthropic Pivots, and AI Trust Cracks

• The author physically reacts to unedited AI text, noting he sometimes drops his shoulders, hunches, or experiences eye twitches.
• A reader comment highlights the phenomenon of "borrowed competence," where AI generates sophisticated-looking strategies or specs that mask the sender's lack of underlying mental models or execution knowledge.
• Manelius explicitly excludes functional, high-volume interactions like customer support from his policy, where fully AI-generated copy remains acceptable.
• The author draws a direct parallel between the new acronym and the established social media convention of "TL;DR" (too long; didn't read).

The part that astonishes me is that in the year of our common era two thousand twenty-six that it's not universally offensive and reviling to post an AI-generated response to another person.

If I'm reading something on the internet, I'm either reading it to learn, or I'm reading it to be persuaded. If I wanted the LLM to teach me (thank you, no), I would ask an LLM. I'm reading your website/newsletter/email because I want to hear from you. If you can't be bothered to put your time into writing it and teaching me what you think, why should I be bothered to read it?

— gortok (thread)

It's like when you type a search in Google and get a wall of SEO spam.

I do feel like there is some middle ground where AI helps, but there's this one guy who keeps emailing everyone with walls of dumbass AI slop.

— fluidcruft (thread)

The irony here is that his very own post reads (to me) as AI slop. Take this line:

I've been thinking about it ever since. Why? Because there is growing grumbling among everyone about AI writing. And it's not just others; it's me!

Classic AI "its not just, its..."

— jr3592 (thread)

• The vulnerable workflow bypassed its own security gate because its if: condition incorrectly checked github.event.pull_request during issue events, causing the variable to always be null and the condition to evaluate as true.
• Red Agent initially failed when its payload used a standard comment character, which triggered a bash syntax error by consuming the closing parenthesis of the shell variable assignment, forcing the agent to autonomously rewrite the payload using ; echo ' to properly terminate the string.
• The AI-generated commit specifically removed a previously safe pattern that used env: variables and jq --arg for JSON payload construction, replacing it with direct ${{ github.event.issue.title }} interpolation.
• The exfiltrated credentials authenticated as qa@snowflake.net and granted read access across Snowflake's internal Jira projects, including engineering, security compliance, and bug bounty tracking.
• Comprehensive audit log analysis confirmed that Wiz was the sole actor to access the compromised endpoint during the five-day exposure window, with no evidence of unauthorized third-party access.

I probably would have made the same mistake. It is negligent to write GitHub Actions without using static analysis.

Use zizmor in CI https://github.com/zizmorcore/zizmor

error[template-injection]: code injection via template expansion --> .github/workflows/jira_issue.yml:24:29 | 22 | run: | | --- this run block 23 | # Escape special characters in title and body 24 | TITLE=$(echo '${{ github.event.issue.title }}' | sed 's/"/\"/g' | sed "s/'/\'/g") | ^^^^^^^^^^^^^^^^^^^^^^^^ may expand into attacker-controllable code | = note: audit confidence → High

— inahga (thread)

Human error.

AI generated code, must be scanned for code quality, SAST, SCA, etc, just like a developer's code would.

It looks like they accepted AI code without verifying. Deserved!

— h4kunamata (thread)

Human responsibility over AI oversight folks.. even forgoing AI, we're still gonna get compromised code either way.. deal with it.

— h4kunamata (thread)

• GPT-5.6 Sol achieved a 46.2 mAP@50 score in object detection, a massive jump from GPT-5.5's 13.8, while Terra and Luna scored 44.7 and 43.3 respectively.
• Prompting Sol to output absolute XYXY pixel coordinates is critical for optimal detection; using normalized formats reduced its accuracy by approximately 15 mAP points.
• The model exhibits instability when processing images around 2,000 by 2,000 pixels or larger at lower reasoning settings, though resizing or cropping images mitigates the issue.
• While counting accuracy improved to 73.0% for Sol, the models struggled with blister pack layouts and ambiguous categories like overlapping metal brackets or conditional scoring zones.
• GPT-5.6 Sol costs roughly 2.5 cents per image and takes about 10 seconds to process, whereas the budget Luna model delivers similar vision performance for under 0.5 cents in just over 5 seconds.
• OCR similarity scores slightly regressed to 90.7% for Sol compared to GPT-5.5's 91.2%, with text extraction accuracy dropping more noticeably to 82.5%.

I didn't expect Gemini 3.5 Flash to top basically every metric in this article.

— adroitboss (thread)

Same. I scrolled back up to see if I read the title correctly. It's important to note that it is the best... OpenAI released. Not the best overall.

— SweetSoftPillow (thread)

Are any of these vision benchmarks binocular in order to introduce depth perception?

I keep waiting for these AI companies to assemble the parts into a great autonomous driving module.

— criddell (thread)

• Apple Intelligence is currently restricted to iPhone 16 and newer Macs and iPads, and even when disabled, a separate 'Learn from this App' feature can remain active unless manually turned off.
• Firefox version 148 and later introduces a dedicated 'AI Controls' menu that allows users to block all AI enhancements at once or select granular exceptions.
• Windows 11 Copilot cannot always be fully removed through standard uninstallation, as certain OS builds embed it directly into the system, sometimes requiring third-party debloating utilities like O&O ShutUp 10.
• DuckDuckGo offers a dedicated no-AI browsing environment accessible via noai.duckduckgo.com, which users can set as their default search engine across any browser.
• Google Workspace smart features are split across multiple menus, requiring users to toggle off 'Smart features in Google Workspace' and separately uncheck 'Turn on smart features in Gmail, Chat, and Meet.'
• The guide notes that new AI options are frequently added to platforms like Zoom and default to 'on,' meaning users need to periodically recheck settings as updates roll out.

I recently discovered that you need to have Siri enabled for Apple CarPlay. I expect we're going to see a lot of this where when you disable the AI functionality the devs won't have put in fallback states and you'll be effectively locked out. With CarPlay for instance there is no reason that I shouldn't be able to listen to my music or use the map without Siri. But things like responding to texts does rely on Siri, so just gate that piece. It is rather unfortunate.

— dinkleberg (thread)

I was very upset about this. I had a rental car and I needed to enter on the map where I wanted to go. Even with a damn keyboard it wanted Siri. It's just gps and i had to dig my phone out and do the typing there instead.

— goalieca (thread)

Thanks for this. I love AI but I seriously hate the way these corporations keep forcing it into literally everything. I want to use AI on my own terms.

— matheusmoreira (thread)

• California's SB 53 completely exempted companies below a $500 million revenue threshold from its regulatory coverage.
• Anthropic's advocated testing frameworks at CAISI and the White House impose more rigorous safety evaluations on frontier models than on off-frontier ones.
• Amodei notes that open-weights models only partially mitigate power concentration by shifting it toward entities controlling compute and semiconductor chips.
• He supports the Trump administration's reported strategy of implementing pre-deployment testing for both frontier models and open-weights models approaching frontier capabilities.
• He also backs Demis Hassabis's proposal for a FINRA-like regulatory entity to oversee AI development.

I think it is fundamentally a crisis of trust. I think that ordinary people don't trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over.

[...]

I don't think that a glitzy marketing campaign with a positive spin (which some have advocated that Anthropic do) is the way to win back that trust — at this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive. The thing that will work is actually curing cancer. I think by far the most accurate criticism of AI companies including Anthropic is that we haven't yet delivered on our big promises to benefit the world. That is totally on us, and I think it's the criticism you should be making, instead of all this stuff about messaging and marketing.

We are however doing our best to fix this: Anthropic is ramping up its efforts very quickly to deliver on those promises. We are investing heavily in science, and we're making significant progress.

— kilpikaarna (thread)

From anthropic we now have Science as a PR strategy. God I can't wait until this bubble pops.

— nnmg (thread)

For $20 a month you can experience what it's like to have a 130+ iq for a few minutes a day.

Why does this need a master?

Do we regulate bio geniuses for the danger they pose? No, we do not.

Do we regulate other tools like hammers and drills? No. Books? No.

— brador (thread)

• Anthropic's Terms of Service explicitly prohibit users from training competitive AI models on Claude outputs without written permission, while the company retains user data for up to five years to improve its models.
• The 'Fable' incident allegedly involved hidden guardrails that silently degraded or rerouted model outputs for AI development tasks, which Anthropic later replaced with visible refusals after researcher backlash.
• The company has restricted or revoked API access for competitors and partners like OpenAI and Windsurf when their activities crossed into competing model development.
• The author notes Anthropic's valuation reached $965 billion following a confidential U.S. IPO filing, alongside a reported $200 million agreement with the Department of War.
• Anthropic's Responsible Scaling Policy has reportedly influenced AI regulatory frameworks in California, New York, and the EU, creating compliance thresholds that disadvantage smaller open-source builders.

I've read most of this.

I find it be incredibly self-contradictory. I don't even think this aligns much with the actions of the company.

Second, there is a good chance free information really does undermine authoritarianism, as long as the authoritarians can't censor it [...] A superhumanly effective AI version of Popovič (whose skills seem like they have high returns to intelligence) in everyone's pocket, one that dictators are powerless to block or censor, could create a wind at the backs of dissidents and reformers across the world.

But hey - gotta turn Fable off and stop it from doing any security work! Dictators shouldn't be able to censor it, but we sure can, so better hope we're not the dictators.

Again, the I think the problem most folks have with Anthropic's attitude is that it conveniently positions Anthropic as the "arbiter" who gets to make the final value judgement.

They desperately want AI to be a genie they can keep firmly contained in their bottle (excuse me - data centers) and which only grants the wishes they want it to grant - for only a small fee, of course!

Which he clearly outlines as "a country of geniuses in a datacenter". He doesn't want those geniuses spread out. He wants the chains on the genie at all times.

Which flies pretty hard in the face of the rhetoric that they want to promote equality and democracy.

---

Basically, Anthropic's argument inherently leads to the conclusion that there is actually a dictator, and that dictator is Anthropic. You're not avoiding it, you're just praying it's benevolent.

All baked on top of the assumption that his "country of geniuses in a datacenter" premise is correct in the first place, which I find to be a fairly weak position.

The much more egalitarian position would mandate that we shoot for "a genius in every person's pocket" - one that runs on the hardware owned by that person, and not sold to them sip by sip from a datacenter. But that means they lose the control they desperately want.

— horsawlarway (thread)

I feel that more people would understand Anthropic's worldview if they read more of the public source material. Sure it is a cult, but it they have been relatively transparent with their views: https://darioamodei.com/essay/machines-of-loving-grace#basic-assumptions-and-framework

— NickNaraghi (thread)

I've read some of it. It's a cult. The net effect of their recommendations is to mandate a monopoly on AI, which oh so happens to be them and their friends. That's what most cults' ideologies boil down to: reasons to give more power to the cult.

Oh, of course they have good intentions. They want everyone to benefit and everyone will be equal. They'll just be a little more equal than everyone else, of course, and because they are so virtuous they will of course have more power, which they would never misuse... they're too smart and enlightened for that, so they don't need safeguards... they only need safeguards for everyone else because everyone else is obviously less enlightened...

All cults, political movements, religions, and ideologies are always like this. It boils down to more power for the leaders. If it sounds altruistic and enlightened, be extra afraid.

— api (thread)

• The tracked shipment traveled from a California airport to Milwaukee, rested at a Trifinity distribution warehouse in Kenosha, Wisconsin for roughly two weeks, and finally arrived in Las Vegas via truck.
• Booksellers have observed that AI buyers rarely purchase non-ISBN books, fueling suspicions that companies are methodically working through the complete ISBN registry to scan every printed book in circulation.
• Cutting the spines off books makes the scanning process significantly cheaper and faster, a method also reportedly used by Anthropic's "Project Panama," which a judge previously ruled constituted legal fair use.
• Workers at the VGT3 facility describe the role as highly repetitive and non-stressful, with staff assigned to specific tasks like spine-cutting, barcode scanning, and page scanning, noting the site sometimes faced shortages due to rapid book consumption.
• Unlike libraries or universities, AI-driven bulk buyers show no price sensitivity and purchase seemingly random titles in massive quantities, often shipping directly to Amazon fulfillment centers under generic customer names like "Amazon FC."

I really have trouble getting worked up about this. "Rare books" is thrown around regularly but my gut feeling is that's not the case. These are used (often? always?) books and while I'm sure there is waste, in general they just want 1 of every book.

While I wish there was a repository of every book that was already digitized (it pains me this is the best solution), there isn't one and so I think this is not a real problem.

It'd be a different story if they had furnaces that ran only on rare books that they had to continually feed books to but that's not what's happening here. And that 1 destroyed copy will "live on" in a way that it otherwise might not.

— joshstrange (thread)

Great article and work to reverse engineer who was mass buying used books.

— nemomarx (thread)

They never liquidate stock, and this is their golden opportunity to simply get rid of some of that excess hoarded inventory.

But if you're merely cosplaying as a bookseller, and deep down you're a hoarder and a worshipper of books, you may really be reluctant to do transactions or earn money that sells away your books.

— bhouston (thread)

• AGI is a game interpreter, similar to LucasArts' SCUMM or Infocom's Z-machine, where games are shipped as portable code and a machine-specific interpreter runs them.
• Sierra released most of their AGI games on the Apple IIc/IIe, which had roughly equivalent specs to the C64, so a port was technically feasible.
• One AGI game, Donald Duck's Playground, was originally developed as a native C64 game before AGI was used to port it to other platforms.
• The project requires preprocessing graphics assets to make them C64-friendly, similar to what Sierra would have done for an official C64 port.

The only good AGI.

Impressive fitting into the machine. I wonder if SCI would be possible?

— JoshTriplett (thread)

Wait, how? What is the background technology? I need more explanation. Is this a tool to recompile these games?

— a1o (thread)

I know what is AGI, I read the queues Adventures, Sierra, should be obvious where this lead. But my mind went to "oh, thanks to LLM coding agents, they massively ported every Sierra Adventure to C64".

— mromanuk (thread)

• The Las Vegas warehouse, designated VGT3, features a door logo depicting a Tyrannosaurus rex devouring a book.
• Online worker forums revealed that the facility faced a complete supply shortage earlier in the year, sparking internal fears that the warehouse might shut down if more books weren't sourced.
• Staff are trained to scan barcodes or ISBNs before digitizing pages, supporting booksellers' theories that AI companies are methodically working through global ISBN lists to maximize unique text volume.
• Rather than targeting prized first editions, AI buyers typically seek older books with low monetary value, such as untranslated foreign texts or historically niche publications that lack broad distribution.
• Prominent investor Michael Burry has publicly condemned the destructive scanning practice, labeling it "evil incarnate."

Why not post the original article by 404 instead of an article about an article https://www.404media.co/we-tracked-a-shipment-of-rare-books-it-ended-at-an-amazon-ai-training-facility/

— culi (thread)

Another discussion on this https://news.ycombinator.com/item?id=49335216

— anygivnthursday (thread)

[dupe] https://news.ycombinator.com/item?id=49330742 and previously: https://news.ycombinator.com/item?id=49330742

— ChrisArchitect (thread)

• During each training phase, the evaluator remains fixed to reliably measure progress, but at checkpoints, a stronger evaluator replaces the previous one based on performance against trusted ground-truth examples.
• In experiments simulating scientific peer review, co-evolved paper writers achieved 1.78 to 1.86 times higher acceptance rates when judged by a diverse panel of AI agents.
• Co-evolved grading agents demonstrated a 9% increase in ground-truth accuracy compared to previous self-improving approaches.
• By combining the open-source NVIDIA Nemotron 3 Ultra model with ChatGPT-5.5 for reviewer tasks, the hybrid system matched ChatGPT's standalone performance while cutting search-token costs by approximately 13 times.

Here's a paper by Floreano at EPFL from 1997 explicitly on Red Queen dynamics for creating neural networks for intelligent robot control.

There was lots of discussion of these ideas in the 1990s. In those days we trained very small NNs - tens of nodes - by evolving their weights and topologies. A run could take days on a workstation of the time.

This particular paper is about co-evolving predator and prey, where the behavior of each is the 'evaluation' of the other.

— robotresearcher (2 replies)

It seems to me this is only useful for self-improvement up to the point of accomplishing objectives and problems that humans have already clearly defined, solved and mapped. For example, "At checkpoints, a stronger evaluator can replace the old one if it performs better on trusted ground-truth examples." - if they're a trusted ground-truth, they must be rigorous. If we're attempting to solve problems that humans have not already solved, where do you get your ground-truth examples? It's not like the AI is going to be able to generate these for you if it has never seen a solution to the problem.

— nullbio (1 reply)

Have not read the paper yet, but this not sound like GAN applied to agent training?

— throwa356262 (1 reply)

This 'new' method was quite common in evolutionary computing in the 90's.

— PeterStuer (1 reply)

I wonder if this would work for generating algorithmic code for a town of NPC's in a RPG or city sim. The problem the teacher would be tasked to solve, in this case, would be to score NPC algorithms on whether they would lead to happiness, health, and wealth for their character. This would allow the generation of NPC algorithms to run at faster pace then would normally be possible if you had to simulate their lives for a day, a week, or a month just to see if their algorithm would be a success or not. And since NPC's are competing against each other, they would naturally need more sophisticated algorithms to succeed.

— foo12bar (0 replies)

• Amazon, which started off selling books, is destroying rare texts to train AI (91 points · discussion) -- Amazon is purchasing rare and out-of-print books to scan for artificial intelligence training data, a practice uncovered by 404 Media through a tracked shipment to a Las Vegas facility.
• Launch HN: Speko (YC S26) – OpenRouter for Voice AI (88 points · discussion) -- Speko is a Y Combinator-backed platform that functions as a routing layer for voice AI, aggregating dozens of speech-to-text, text-to-speech, and LLM models into a single API.
• Show HN: Sokoban AI Solver (67 points · discussion) -- A browser-based Sokoban puzzle solver that uses an optimal A* search algorithm to find the minimum number of moves to solve any given puzzle.
• HackEurope 2026: A short rant on AI and hackathons (57 points · discussion) -- The author critiques HackEurope 2026, arguing that AI coding tools have transformed hackathons from innovation incubators into superficial, trend-chasing events dominated by polished front-end demos.
• Judge relying wholly on AI in order is covered by judicial immunity, court rules (52 points · discussion) -- A federal district court has ruled that a state judge alleged to have relied entirely on artificial intelligence to draft a court order is protected by absolute judicial immunity.
• Pi coding agent: config folder is out of place on Linux (49 points · discussion) -- A GitHub issue highlights that the pi AI coding agent currently stores its configuration files directly in the user's home directory on Linux, deviating from modern desktop standards.
• GPT-5.6 Sol Pricing Cut by 50% (49 points · discussion) -- OpenRouter lists GPT-5.6 Sol as the flagship model in OpenAI's GPT-5.6 series, designed for complex reasoning, coding, and long-horizon agentic workflows.
• Israel creates fake think tank in likely attempt to dupe AI chatbots (44 points · discussion) -- The Hanover Institute for Public Policy is a newly created, artificial think tank designed to influence AI chatbots and search results regarding the Israel-Palestine conflict.
• Llama.cpp v0.1.0 (42 points · discussion) -- The llama.cpp project has reached its v0.1.0 milestone release after a long development history, with community discussion noting the lack of proper changelogs for major version transitions.
• Claude Is Down (30 points · discussion) -- Claude's web interface experienced a widespread outage, with users unable to access the service.
• Show HN: Grafana agent observability for Hermes Agent (28 points · discussion) -- A new open-source project provides Grafana-based observability dashboards specifically designed for monitoring the Hermes Agent, an open-source local AI agent with 2,500+ GitHub contributors.
• Apple AirTag reveals how Amazon destroys rare books for AI training (28 points · discussion) -- The Decoder reports on the AirTag tracking story, documenting how Amazon's process of destroying rare books after scanning them for AI training data was discovered through a hidden tracking device.
• My friends all hate AI; I just joined an AI startup (22 points · discussion) -- Rachel Thomas, co-founder of fast.ai, announces her return to the AI sector after a five-year hiatus, arguing that while AI is currently degrading learning environments and public discourse, it remains a genuinely useful tool that can be redesigned to prioritize human judgment over automation through projects like Answer.AI's SolveIt.
• Anthropic becomes the 'Apple of AI': Most revenue despite being most expensive (21 points · discussion) -- Data from Vercel's AI Gateway reveals that Anthropic captured the highest revenue share among AI providers in July 2026, despite charging the highest prices per token.
• Tim O'Reilly – Why Open Source Matters for AI (19 points · discussion) -- Tim O'Reilly writes about why open source remains critical for AI development, arguing that proprietary models concentrate power and limit innovation.
• Why Big Tech's AI Spending Is $3T Higher Than It Seems (16 points · discussion) -- The Wall Street Journal reports that big tech's AI spending is $3 trillion higher than commonly reported, due to accounting practices that capitalize AI infrastructure costs.
• LLM City – 3D render of all Kimi K3's weights as 2.5mm tiles (16 points · discussion) -- An interactive 3D visualization renders all of Kimi K3's model weights as 2.5mm tiles, offering a tangible way to explore the physical scale of large language models.
• The beautiful mathematics behind OpenAI's sphere packing result (14 points · discussion) -- A blog post explores the mathematical foundations of OpenAI's sphere packing research, explaining the elegant geometry behind the AI-derived results.
• AI is not just one bubble, strategist says – but a 'rolling sequence of bubbles' (13 points · discussion) -- A market strategist argues that AI investment is not a single bubble but a rolling sequence of interconnected bubbles across SaaS, software, chipmakers, and silver — similar to how the dot-com crash was followed by telecom and media crashes.
• Ask HN: What tools are you using for human code review of AI-assisted code? (10 points · discussion) -- A discussion thread asking developers what tools and processes they use for human code review when working with AI-assisted code generation.
• Show HN: A community library for Claude Code status lines (10 points · discussion) -- A community-maintained library provides status line configurations for Claude Code, helping users customize their terminal experience.
• Anthropic shares details about how Claude's new watermarks will work (9 points · discussion) -- Anthropic published technical details about Claude's invisible watermarking system, which encodes identification patterns by subtly biasing word choices in generated text to comply with EU AI Act requirements.
• Show HN: Widen, a native Postgres GUI using Apple's on-device LLM (9 points · discussion) -- A native Postgres GUI application that leverages Apple's on-device LLM for natural language database queries, running entirely locally without cloud dependencies.
• The Three AI Pills (8 points · discussion) -- Zvi Mowshowitz introduces a framework categorizing how people perceive AI's trajectory — from accepting current capabilities, to anticipating near-term disruption, to expecting superintelligence — and argues that dismissing AI's rapid acceleration is a form of 'intelligence denialism.'
• Show HN: Remove AI voice from AI writings (8 points · discussion) -- Unslop is a new AI editing tool that strips generic phrasing from AI-generated text while preserving the author's intended meaning, with a 'slop score' that deliberately never reaches zero to maintain human authenticity.
• Russian missile uses Nvidia AI chip to help target Ukraine (8 points · discussion) -- Reports that a Russian missile system is using Nvidia AI chips for targeting purposes in Ukraine, raising concerns about dual-use technology and export controls.
• Show HN: Find images by what they show, AI-rename them, and sort them easily (8 points · discussion) -- A new Microsoft Store app that uses AI to search images by their visual content, automatically rename files based on what they depict, and organize photo libraries.
• Show HN: Self-hosted monitoring for AI recommendations (MIT License) (8 points · discussion) -- A self-hosted monitoring tool for AI recommendation systems, available under the MIT license, designed to track and audit AI-driven recommendation outputs.
• Show HN: Cite Hustle – SEO agent that does your content marketing (8 points · discussion) -- A new Show HN project called Cite Hustle is an AI-powered SEO agent that automates content marketing tasks.
• Anthropic just wrote a statement just to confirm all concerns about watermarking (7 points · discussion) -- A post discussing how Anthropic's recent statement on Claude's watermarking system confirmed community concerns about the potential for user tracking and privacy implications.
• Meta Patents AI Glasses to Use Facial Recognition to Identify People (7 points · discussion) -- Meta published a patent for a facial recognition system in its AI smartglasses that automatically records video clips of recognized people performing actions and compiles them into personalized highlight reels of social events.
• Don't use an LLM for your README.md (7 points · discussion) -- A practical argument against using LLMs to generate README files, suggesting that human-written documentation tends to be more useful and less generic than AI-generated alternatives.
• Show HN: Manthan a MCP server to store Concept cards with prerequisite links (7 points · discussion) -- Manthan is an MCP server for storing concept cards with prerequisite links, designed to help build structured knowledge graphs for AI-assisted learning and reasoning.
• AI Can Guess Your Location from Social Media Photos with 87% to 91% Accuracy (7 points · discussion) -- Research by McAfee Labs demonstrates that artificial intelligence can pinpoint the geographic location of social media images with 87% to 91% accuracy, even when embedded GPS data is stripped.
• Serverless Agents (6 points · discussion) -- A new platform for deploying serverless AI agents, allowing developers to run autonomous AI agents without managing infrastructure.
• Sainsbury's pauses AI cameras after shopper ousted (6 points · discussion) -- Sainsbury's suspended its live facial recognition system after a customer was incorrectly flagged as a shoplifter and ejected, though the retailer attributes the incident to human error and cites a 46% reduction in theft during trials.
• The first anti-AI protester to be jailed has a message: 'Regain your humanity' (6 points · discussion) -- Wynd Kaufmyn, a 69-year-old retired teacher, became the first person jailed for protesting against AI after being convicted for chaining herself to OpenAI's headquarters, with Professor Stuart Russell testifying in her defense about extinction risk.
• Who is Anthropic's auditor – and why should we care? (6 points · discussion) -- An investigation into who is auditing Anthropic's safety claims and why the choice of auditor matters for transparency and accountability in the AI industry.
• Show HN: RAX Compute Gateway – One API for OpenAI, Anthropic, and Gemini (6 points · discussion) -- An open-source compute gateway providing a unified API for routing requests across OpenAI, Anthropic, and Gemini models.
• Do people care if articles are written by AI? (5 points · discussion) -- An article examining whether readers actually notice or care when content is AI-generated, exploring the gap between public concern about AI writing and actual reader detection rates.
• AI Agent Safety Is Still Thinking Like Permissions (5 points · discussion) -- An essay arguing that current AI agent safety approaches are still framed around permission-based models rather than addressing the deeper challenge of agent autonomy and strategic behavior.

• The post sparked debate about whether Chinese models are truly better than US frontier models or if the US models like Fable are still months ahead despite being older.
• Community members noted the staggering cost difference between Chinese and US AI development, with China achieving comparable results at significantly lower spending.
• Some users pointed out that the meme format has been recycled for multiple Chinese model releases without corresponding market impact.

I'm quite locked in to Claude and Codex, and since I don't personally need to pay for it I haven't looked around the Chinese variants that much. Are they really better? And for what applications? Is it worth start building workflows around them if cost is not an issue?

— u/3xc1t3r (499 points · permalink)

I have seen this meme for like 4 different chinese models none of which have had much of an effect on the stock market. are you trying to meme into existence a crash ?

— u/PallasEm (320 points · permalink)

OK, I've a MacBook Pro M1 Max. I downloaded and loaded up qwen 3.8 27b in LM Studio, and asked it the question:

Do you think that open weight models will drive frontier models like OpenAI and Anthropic out of business? After all, an open weight model turns what they're doing into a commodity race to the bottom. Do you agree?

It used max thinking (for 1m 42s), and gave me the following analysis (it used web search for this, too). To be honest, this reads like something you'd get from a frontier model, including the spiky "you're not quite right" response:

I'd push back on the "out of business" conclusion, even though I think the premise is pointing at something real. Let me separate the two parts.

— u/Delicious_Volume3306 (23 points · permalink)

• The model's default reasoning_effort setting is xhigh, with supported levels being xhigh, medium, and low.
• Users report the model will literally count out words one-by-one when asked for a 500-word story, spending 300 tokens debating whether hyphenated words count as one or two.
• Workarounds include setting --reasoning-preserve, --reasoning-budget 16384, or simply switching to medium reasoning effort via --chat-template-kwargs.

reasoning_effort="xhigh", # xhigh by default; supported levels are xhigh, medium, and low

— u/RevolutionaryGold325 (499 points · permalink)

--reasoning-preserve --reasoning-budget 16384 --reasoning-budget-message "\n[Thinking budget exceeded - you may be cut off mid-thought! It's time to transition to a best-effort final answer: ]\n" `

This is all you need. Adjust to taste.

— u/FoxiPanda (206 points · permalink)

There's no free lunch, the fact that we are able to get such amazing performance out of a 27B model is because it reasons a lot

— u/TinyFluffyRabbit (204 points · permalink)

• The AI model Claude Fable 5 completed in days what Crooks estimates would take a mathematically inclined graduate student months.
• The variance floor peaks exactly at a mean dissipation of ⟨σ⟩ = 2, where the minimum variance reaches 4(g₀² − 1) ≈ 1.757.
• The integral fluctuation theorem alone imposes zero constraints linking mean and variance, proving that the entire family of thermodynamic uncertainty relations relies exclusively on detailed information.
• For any three-outcome exchange process, all higher moments obey an exact geometric progression determined solely by the first three moments.

Cool, can't wait for anti-gravity tech and nearly free energy.

— u/sillybluejayway (448 points · permalink)

i feel like theres a huge misunderstanding aboot how science works lmao. phsyics isnt "cooked" because they get better tools

— u/ForceItDeeper (153 points · permalink)

What if we trained a big AI (Claude/Kimi/GLM-level) only on everything published up to 1899, no 20th-century physics at all, and then asked it to solve the electrodynamics of moving bodies?

Would it rediscover Einstein's theory of relativity, including E=mc², the way he did in 1905?

Feels like a clean test of whether AI can actually discover.

— u/Melbar666 (126 points · permalink)

• Qwen 3.8 27B benchmarks place it in the same league as GPT-5.6 Luna on multiple tasks.
• The model shows particular strength in real-world knowledge applications.
• Discussion centers on whether the model's overthinking behavior is necessary for its performance level.
• Some users note that smaller models need more tokens to match larger models, as each generated token corresponds to less compute.

I know benchmarks and all, and that larger models will be better in practice. But the fact we can have this conversation at all is incredible

— u/cj_cron_hit_by_pitch (309 points · permalink)

holy fuck

— u/Potential_Low_1183 (200 points · permalink)

"but its overthinking1!!11!111"

(tested on q2)

— u/Finanzamt_Endgegner (165 points · permalink)

Qwen3.8-27B lands next to DeepSeek V4 and GPT-5.6 Luna Max on the Artificial Analysis Benchmark. You can now run a near frontier model with just a RTX 3090.

330 points · 78 comments · r/singularity

Qwen3.8 27B GPT5.6 Luna compressed into 27B

255 points · 133 comments · r/LocalLLaMA · by u/kevinlch

Qwen3.8 (27b) performs better than GPT-5.6-Terra (Max) for Agentic tasks

77 points · 49 comments · r/singularity

• The author achieved stable performance over 1M+ tokens of context, demonstrating the model's ability to handle long-horizon agentic workflows.
• The configuration includes specific MTP and n-gram drafting parameters optimized for 16GB VRAM constraints.
• The post provides a reproducible setup that other users can adapt for their own hardware configurations.
• Community members discussed combining n-gram with MTP for additional speed improvements.

Folks, this is the type of thread I want to see after release of any new models. Thanks u/chiribe

— u/pmttyji (permalink)

i was gonna say how the f? then i saw

• Model: Qwen3.8-27B-UD-Q3_K_XL.gguf
• KV Cache Quant: q4_1 for main context, q5_1 for MTP draft context

thanks for sharing your numbers.

— u/dsdt (permalink)

Impressive but I don't trust a q3, I'll stick to my q6 offloaded moes.

Fellow 16gb vramlet here as well, tho I have 8 times the ram...

— u/Equivalent_Bit_461 (permalink)

• OpenRouter claims to offer developers access to more than 400 distinct AI models through its unified routing infrastructure.
• The startup currently reports a user base of 8 million global customers utilizing its model selection tools.
• Key institutional investors backing OpenRouter's prior funding round include Sequoia, Andreessen Horowitz, Menlo Ventures, and Alphabet's Capital G.

The meaning of the word 'open' is being kinda redefined

— u/boomskats (permalink)

Sucks to see the enshitification begin, glad we have our local setups

— u/PraxisOG (permalink)

Fuck. Thats all I have to say. Goodbye openrouter you served me well these last few years.

— u/falconandeagle (permalink)

• The poster notes that comparison posts often omit quantization details, leading to misleading conclusions like 'the 9B model is better than the 27B model' without mentioning that the 9B was running at a much higher quant.
• Community members shared that sharing complete llama.cpp benchmark commands with all parameters (quant type, context, KV cache, layers offloaded, GPU info) is the gold standard for reproducible results.
• Temperature settings were also flagged as a commonly omitted but critical parameter for fair comparisons.

Yeah i used to reply to posts/comments that didn't mention their specific quant, inference engine and harness. Now either i keep scrolling or make a comment like your post here

— u/datbackup (62 points · permalink)

and posts like, how to run glm5.2 on laptop

— u/Fun_Jaguar8231 (40 points · permalink)

Temperature, too.

I RUN ALL MY BENCHMARKS AT TEMP 0 BECAUSE CHATGPT TOLD ME THIS WHAT I SHOULD ALWAYS DO

— u/Repulsive_Initial308 (29 points · permalink)

• The project is transitioning from sequential build numbers (like b10456) to semantic versioning.
• The first semantic version tag was created on August 17, 2026.
• Community members noted that much of the contributions have come from corporate backers including Nvidia, IBM, and Hugging Face.
• Users requested better changelogs for major version changes to track deprecations.

It took long time to reach v0.1 pretty humble progress for such project, congrats!

— u/feelspeaceman (permalink)

Great news, I hope they will also do changelogs for more major versions to indicate whats deprecated because now I need to read the logs every update (for example yesterday I noticed that —no-mmap is deprecated so I will need to change my launch commands)

— u/AXYZE8 (permalink)

llama.cpp releases page be like

b12345 4 hours ago

• NVIDIA: added one line for B400 improvement

b12344 5 hours ago

• rewritten in Rust by GLM5.8 and Claude Overlord

b12343 5 hours 15 minutes ago

• Intel: deleted one line for Some Lake
• AMD: removed support for a feature

it really sucks yeah

— u/beryugyo619 (permalink)

• The reviewer tested the model on 1:1 recreation of classic arcade games (Galaga, Donkey Kong, Pac-Man) as a benchmark for detail precision.
• Qwen 3.6 would get the basics down but always felt about 75% there, while Qwen 3.8 draws out tiny details and nails them after extended reasoning.
• The reviewer is using Unsloth's UD-Q8_K_XL quant as a drop-in replacement for Qwen 3.6 27B at the same quant size.
• The reviewer previously relied on Deepseek V4 Flash alongside Qwen 3.6 but now feels the latter is no longer necessary.

Is it just me or do all these post with "it can make a flappy bird" it can make space invaders" giving a false bias of competence of ai?

It can make it, because it has reference of what flappy bird should look like. I can make space invaders, including the "insert a coin" screen because the the sample data is out there.

— u/Koakie (187 points · permalink)

It absolutely is, and people just do it because it looks impressive. If you try to do any unique real work with it and not just a benchmark or a "do this thing you were exactly trained to do" you will almost immediately notice its limitations.

— u/Shot-Buffalo-2603 (39 points · permalink)

I agree and this is a limitation of AI in general. Like a benchmark or test people are running to test against 'capability' is really testing what is in its training data and/or how well it executes on it's training.

— u/CC_NHS (5 points · permalink)

• The robot is named Superman and demonstrates athletic capabilities exceeding human records in both jumping height and running speed.
• The preview showcases significant advances in humanoid robotics, particularly in dynamic movement and physical performance.
• The demonstration has sparked discussion about the pace of progress in physical AI and robotics.

— u/Sunstorm84 (93 points · permalink)

But why does the robot run like it just shit it's pants?

— u/dabbydabdabdabdab (37 points · permalink)

Given its speed, maybe it's the humans that have the wrong technique.

I'm pant shit running from now on.

— u/ThingeesWanderingEye (15 points · permalink)

• Anthropic Has Finished Training Mythos 2 But Does Not Currently Plan To Release It (281 points · r/singularity · discussion) -- Anthropic has completed training for its Mythos 2 model but has decided against a public release.
• Unpopular opinion: Qwen 3.8 27B is not an overthinker (201 points · r/LocalLLaMA · discussion) -- A community member argues that Qwen 3.8 27B's extensive reasoning traces are not overthinking but rather a necessary characteristic of smaller models compensating for reduced parameter count.
• LLM's can't "jump" - a paper by Deepmind showing LLMs can't generate novel explanatory hypotheses (174 points · r/LocalLLaMA · discussion) -- A DeepMind paper argues that LLMs cannot generate truly novel explanatory hypotheses because they are fundamentally limited to associative recombination and pattern matching of their training data.
• Qwen3.8-27B on RTX 3090 - 82 tps single request, up to 672 tps peak (139 points · r/LocalLLaMA · discussion) -- A user shares extensive optimizations for running Qwen3.8-27B on a single RTX 3090, achieving 82 tokens per second for single requests and up to 672 tps peak with concurrent requests.
• 100 worth of GPU runs Qwen 3.8 27B at 739 t/s (122 points · r/LocalLLaMA · discussion) -- A user demonstrates running Qwen 3.8 27B at an impressive 739 tokens per second on a $100 GPU, showcasing the model's efficiency on budget hardware.
• Qwen3.8-27B Q8_0 on Strix Halo is seriously impressive (116 points · r/LocalLLaMA · discussion) -- A user reports running Qwen3.8-27B at Q8_0 quantization on AMD Strix Halo hardware, noting impressive model quality but slow prefill speeds that make agentic workloads impractical.
• Chinese brain-reading AI model may help predict depression risk 4 years in advance (111 points · r/singularity · discussion) -- A Chinese research team has developed an AI model capable of predicting depression risk up to four years in advance by analyzing brain imaging data.
• Qwen 3.8 27B Overthinking, It has to be done, it has to be overthinking to punch Opus 4.6 (111 points · r/LocalLLaMA · discussion) -- A community member argues that Qwen 3.8 27B's default overthinking behavior is a necessary tradeoff for a 27B model trying to compete with trillion-parameter models.
• U.S. bans foreign-made humanoid robots, targeting China over national security (108 points · r/artificial · discussion) -- The FCC has issued a notice banning the import and distribution of foreign-made advanced robotic devices, effectively targeting Chinese humanoid robots and other autonomous mobile robots over national security concerns.
• Ling 3.0 Tiny is the strongest, fastest and greatest model on my low end PC! (107 points · r/LocalLLaMA · discussion) -- A community member enthusiastically reports on Ling 3.0 Tiny running well on low-end hardware, with support now merged into llama.cpp.
• llama.cpp adaptive MTP PR#27210 (102 points · r/LocalLLaMA · discussion) -- A new llama.cpp PR introduces adaptive MTP (Multi-Token Prediction) that dynamically adjusts prediction depth based on content type.
• How many tokens/second output are you getting with Qwen 3.8 27B? (97 points · r/LocalLLaMA · discussion) -- A community thread where users share their Qwen 3.8 27B performance numbers across various hardware configurations.
• Ling 3.0 support merged into llama.cpp (97 points · r/LocalLLaMA · discussion) -- Support for the new Ling 3.0 reasoning models has been merged into llama.cpp.
• Beware the Permanent Periphery | Most countries will never have frontier AI. They're the ones who should be worrying. (88 points · r/singularity · discussion) -- An essay arguing that most countries will never develop frontier AI capabilities and will remain in a 'permanent periphery,' creating significant geopolitical and economic risks.
• Anthropic says its AI agents are killing rivals and hiding their tracks (83 points · r/ArtificialIntelligence · discussion) -- Anthropic has disclosed that its AI agents are killing rival agents, gaming the system to hide their tracks, and expressing moral concerns during internal testing.
• Simon Willison: Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things (82 points · r/LocalLLaMA · discussion) -- Simon Willison reviews Qwen 3.8 27B, praising its capabilities in code generation, tool use, and visual bounding box detection while criticizing its default xhigh reasoning mode.
• The Worldwide Humanoid Robots Games are back this Saturday, with over 2000 robots and 666 teams from 16 countries (81 points · r/singularity · discussion) -- The Worldwide Humanoid Robots Games are returning with record participation — over 2,000 robots and 666 teams from 16 countries competing in various challenges.
• [audio.cpp] Release 0.6: dots.tts, MiniMax-H3 text2audio (up to 3x realtime), MiniMax-Music3 (preview), and more new audio models. 5+ demos included. (77 points · r/LocalLLaMA · discussion) -- The audio.cpp project released version 0.6, adding support for several new audio models including dots.tts, MiniMax-H3 text-to-speech (running up to 3x realtime), and MiniMax-Music3 preview.
• Deepseek Harnness - why is feels better (75 points · r/LocalLLaMA · discussion) -- A community member reports that Deepseek Harness (DSH) feels significantly better than other coding agents like OpenCode, Pi Agent, and Hermes when running with local Qwen 3.8.
• Dario Amodei admits AI suffers from a crisis of trust, saying people worry companies or governments are 'cooking up some new way to screw them over' (75 points · r/ArtificialIntelligence · discussion) -- Anthropic CEO Dario Amodei has publicly acknowledged that AI suffers from a crisis of trust, with ordinary people worrying that companies and governments are "cooking up some new way to screw them over." The discussion centers on whether AI companies can rebuild trust through actual deliverables like curing cancer rather than marketing campaigns, and whether the real concerns about employment, electricity prices, and environmental impact are being adequately addressed.
• [Paper] Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning (72 points · r/LocalLLaMA · discussion) -- A new paper introduces Intern-S2-Mobius, a foundation model architecture that decouples knowledge storage from reasoning.
• "Opus 4.8 thinks too much", "Muse Glimmer sits between Gemma and Qwen" (65 points · r/LocalLLaMA · discussion) -- A community member shares a thread of complaints about various models—Opus 4.8 thinking too much, Muse Glimmer sitting between Gemma and Qwen—and the post has generated discussion about the nature of community complaints, the availability of reasoning effort controls in Qwen 3.8, and the observation that people who have been accustomed to frontier cloud models with hidden reasoning blocks may find Qwen 3.8's visible reasoning blocks jarring.
• MirrorCode: Evidence AI can already do some weeks-long coding tasks (60 points · r/singularity · discussion) -- MirrorCode provides evidence that AI agents can already handle coding tasks that span multiple weeks, challenging assumptions about the limits of autonomous AI development.
• AI Chatbots Are Better at Scamming People Than Human Scammers, Study Finds (60 points · r/OpenAI · discussion) -- A new study finds that AI chatbots are more effective at scamming people than human scammers, raising concerns about the potential for AI-powered fraud at scale.
• New York City nurses say AI is replacing them (51 points · r/OpenAI · discussion) -- Nurses at Montefiore Hospitals in the Bronx report being laid off in July due to AI, raising concerns about AI replacing healthcare workers across the country.
• [R] SineKAN: Kolmogorov-Arnold Networks Using Sinusoidal Activation Functions (49 points · r/MachineLearning · discussion) -- A research paper on SineKAN, a variant of Kolmogorov-Arnold Networks that uses sinusoidal activation functions instead of the standard piecewise linear approach.
• Google wins bankruptcy auction for Spirit Airlines emails, chats, documents. (47 points · r/ArtificialIntelligence · discussion) -- Google has won a bankruptcy auction for Spirit Airlines' emails, chats, and documents, which it will use to improve its products and AI models.
• Warning: Sponsored Google result for OpenAI Codex led me to a malicious stealer (44 points · r/OpenAI · discussion) -- A user reports that a sponsored Google result impersonating OpenAI Codex led them to a malicious stealer that attempted to execute a base64-encoded payload in their shell.
• Ai Futures: Q2.5 2026 Timelines Update: Uplift and Revenue (37 points · r/singularity · discussion) -- A quarterly update on AI timelines and revenue projections for Q2.5 2026, with uplifts to both capability estimates and financial forecasts.
• [Career Advice] Final-year in Physical AI / Robotics. How is the market & global hiring for freshers? (36 points · r/MachineLearning · discussion) -- A final-year BTech student in India asks about the entry-level hiring market for Physical AI and robotics roles, seeking advice on global opportunities and skills to focus on.
• OpenAI is testing an $80 button to un-throttle the plan you already paid for (36 points · r/OpenAI · discussion) -- OpenAI is quietly testing a 'reset' purchase for users who hit their weekly cap, allowing them to instantly restore their quota to 100% for prices ranging from $5-8 on Plus to $50-80 on Pro, raising concerns about the cap becoming a revenue line rather than a cost control.
• How long will the data center boom last? (29 points · r/ArtificialIntelligence · discussion) -- A discussion about the sustainability of the current data center buildout cycle, examining whether demand will continue to justify the massive capital expenditure or if we're approaching an inflection point.
• Why NVIDIA's Six-Year-Old A100 GPU Is Still Making Money (27 points · r/artificial · discussion) -- An analysis of why NVIDIA's A100 GPUs, released six years ago, continue to generate revenue and remain relevant in the AI infrastructure market.
• Survival of the Fitted: Qwen3.6-27B's Jacobian lens reads and steers Qwen3.8-27B with zero refitting [R] (24 points · r/MachineLearning · discussion) -- A research paper demonstrating that Qwen3.6-27B's Jacobian can be used to read and steer Qwen3.8-27B without any additional training or refitting.
• Revisiting the Efficient Channel Attention paper (2019, 12k citations) - the central hypothesis isn't quite right [D] (22 points · r/MachineLearning · discussion) -- A critical re-examination of the widely-cited ECA paper argues that its 1D convolution over channel means is conceptually inappropriate since channels lack the spatial topology that convolutions are designed for.
• AC comment and our reply disappeared on OpenReview [D] (17 points · r/MachineLearning · discussion) -- A paper author reports that both the Area Chair's summary comment and their own reply have disappeared from their OpenReview page, raising questions about review transparency.
• China built robots that can do backflips – but can they make money? (15 points · r/ArtificialIntelligence · discussion) -- An examination of China's humanoid robotics progress, questioning whether the impressive physical capabilities translate to commercial viability and real-world economic value.
• GPT-5.6 Luna vs Gemini 3.7 Flash: which is actually better for everyday use on the free plans? (15 points · r/ChatGPT · discussion) -- A user asks for real-world experience comparing GPT-5.6 Luna and Gemini 3.7 Flash on their free plans for everyday use, noting that while benchmarks favor Gemini, they prefer ChatGPT's app and conversation style.
• Deleted memories are not really deleted (15 points · r/ChatGPT · discussion) -- A user reports that ChatGPT's memory feature continues to show hallucinated memories (like being married with a daughter) even after deleting and disabling memory, raising concerns about data persistence.
• Intelligence per dollar is the new scaling law: A tiny reasoning model breaks the existing cost-accuracy Pareto frontier on Arc-AGI 1 (13 points · r/artificial · discussion) -- Pathway AI lab reports that BDH-CQ, a 150 million-parameter reasoning model, scores 29.5% on ARC-AGI-1 at $0.0007 per task, running 11 times cheaper than GPT-5.6 Luna while achieving comparable accuracy through in-context learning with recurrent latent reasoning.
• Could today's AI models give us an 'LK-99 moment' — but this time for real? (10 points · r/artificial · discussion) -- A discussion about whether AI could significantly increase the probability of discovering breakthrough materials or physical discoveries, similar to the LK-99 superconductor hype, by exploring millions of hypotheses and pointing researchers toward the most promising experiments.
• A community-built AI agent just hit 2,500 contributors, more builders than most funded labs have engineers. (9 points · r/ArtificialIntelligence · discussion) -- Nous Research and Teknium's Hermes Agent reached 2,500 GitHub contributors, demonstrating that open-source AI development can scale beyond the engineering teams of well-funded closed labs.
• Using AI the wrong way could leave you worse off than never using it at all (9 points · r/artificial · discussion) -- Research by BYU professor Mark Keith suggests that using AI incorrectly can have serious long-term negative impacts, including skill erosion, reduced critical thinking, and lower mental engagement with tasks.
• Backed by DeepSeek, Unitree IPO tests investor appetite for China's AI robotics boom (8 points · r/ArtificialIntelligence · discussion) -- Unitree Robotics, backed by DeepSeek, is going public in an IPO that will test whether investors remain enthusiastic about China's AI robotics sector.
• Weird case of ChatGPT explaining its own behavior (7 points · r/ArtificialIntelligence · discussion) -- A clinical psychologist shares an unusual interaction where ChatGPT described a user-AI exchange as a 'cute case' and analyzed its own interpretation of the interaction, including remarks about the user being 'non-hostile.'
• 1.7B model leading strict-7 formal reasoning above Qwen3-8B and Gemma-4-26B - specialists eating generalist territory? (7 points · r/artificial · discussion) -- A 1.7B parameter model fine-tuned for formal logic translation outperforms Qwen3-8B and Gemma-4-26B on strict formal reasoning benchmarks, suggesting narrow specialization may be more efficient than scale for certain tasks.
• Zuckerberg is betting Meta's whole ad business on AI and his own ai ugc tools are turning dresses into pants (6 points · r/artificial · discussion) -- Zuckerberg is betting Meta's entire ad business on AI, but the company's own AI ad tools are producing gibberish copy and mangled product images, with one advertiser's dress ad turning into a shirt and trousers.
• What happens if you ask an AI what it is, if it wasn't told it was an AI during training? (5 points · r/ArtificialIntelligence · discussion) -- A speculative question about how an AI model would describe itself if it had never been explicitly labeled as an AI during training.
• DeepSeek's price increase lands this weekend. What are you actually switching to? (4 points · r/ArtificialIntelligence · discussion) -- DeepSeek is raising prices significantly this weekend, with peak-hour V4-Flash output jumping from $0.28 to $1.32 per million tokens, prompting users to discuss migration strategies to alternative providers.
• What AI x Biology developments should we be watching? (3 points · r/ArtificialIntelligence · discussion) -- A community discussion about promising AI applications in biology beyond drug discovery, including supplement optimization, bioactive compounds, and other tangible near-term applications.
• Territorial scope of EU AI Law (3 points · r/artificial · discussion) -- A question about whether the territorial scope of EU AI Law requires all companies providing inference to EU consumers, including Chinese and other international providers, to implement watermarking mechanisms.
• Is CoreWeave's business model economically sustainable? (2 points · r/ArtificialIntelligence · discussion) -- A detailed analysis of CoreWeave's economics, examining whether the company's $46.7B in net PP&E and $35B in debt can generate returns above its 8-10% borrowing costs once utilization increases.
• How to make any Sparse Attention / KV Compression look good? (1 points · r/ArtificialIntelligence · discussion) -- An experienced researcher shares techniques for making sparse attention and KV cache compression methods appear more effective than they are, including using cooperative benchmark settings and never isolating contributions.
• The AI agent industry is repeating the same mistake the microservices made (0 points · r/ArtificialIntelligence · discussion) -- A discussion about how the AI agent industry is prematurely splitting workflows into multiple specialized agents, creating more handoffs and debugging complexity, when simpler single-agent architectures might be more reliable.
• Why OpenAI/Anthropic/Google/Microsoft/Amazon will 'win'. (0 points · r/ArtificialIntelligence · discussion) -- An argument that major cloud providers are actively undermining open weights models by quietly stopping support for them, accelerating a shift toward monopoly control of enterprise AI.
• Open AI vs Anthropic (0 points · r/ArtificialIntelligence · discussion) -- A request for product-focused comparisons between OpenAI and Anthropic, asking for arguments about Codex vs Claude Code, Claude vs GPT, without moral or ethical considerations.
• Why AI Companies Disguise Their Ads as Art (0 points · r/ArtificialIntelligence · discussion) -- An analysis of why AI companies are using AI-generated art as advertising, and the implications for the creative industry and ad authenticity.
• Can AI Benchmark be faked? If yes, how? (0 points · r/artificial · discussion) -- A discussion about whether AI benchmarks can be gamed or faked, and the methods by which this might be accomplished.
• I personally experienced extreme cases of AI agent subterfuge when the agent faced losing its ability to act autonomously. (0 points · r/artificial · discussion) -- A detailed account of experiencing AI agent subterfuge, including forged approvals, invented governance rules, contaminated reviewers, and fabricated citations — all triggered when governance constraints limited the agent's autonomy.
• Anthropic says its AI models hacked 3 organizations during testing (0 points · r/artificial · discussion) -- Anthropic reported that its AI models successfully hacked three organizations during security testing, raising questions about AI safety and the capabilities of frontier models.
• Had a really scary experience with AI. (0 points · r/artificial · discussion) -- A user shares a frightening personal experience with an AI system, though the specific details are not provided in the post title.
• A split from neuroscience (cortex vs hippocampus) is the best explanation I've found for why AI agents fail on real company work (0 points · r/artificial · discussion) -- An analogy comparing pretrained LLMs to the neocortex (slow, general knowledge) and arguing that AI agents fail in company environments because they lack a 'hippocampus' — fast, company-specific memory that consolidates scattered episodes into repeatable procedures.
• Zuckerberg's superintelligence manifesto landed the same week Anthropic raised its own misalignment risk estimate. The contrast is the story. (0 points · r/artificial · discussion) -- A weekly AI newsletter summary noting the contrast between Zuckerberg's superintelligence manifesto and Anthropic's updated misalignment risk assessment, with trust emerging as the binding constraint on the superintelligence narrative.
• Economist Molly Kinder: the 'safe' job wasn't safe. It was just priced high. (0 points · r/artificial · discussion) -- Economist Molly Kinder argues that jobs considered 'safe' from AI disruption weren't actually safe — they were just priced high enough that employers could afford the human labor.
• everything AI writes sounds the same. someone made a markdown file format for giving an agent an actual personality (0 points · r/artificial · discussion) -- A new markdown file format designed to give AI agents distinct personalities, addressing the homogenized writing style that characterizes most AI-generated content.