Tag: Reddit

Most coverage of the Claude Code leak focuses on the drama or the hidden features. But the bigger story is that this is the first time we've seen the complete architecture of a production-grade AI agent system running at scale ($2.5B ARR, 80% enterprise adoption). And the patterns it reveals tell us where autonomous AI agents are actually heading. What the architecture confirms: AI agents aren't getting smarter just from better models. The real progress is in the orchestration layer around the model. Claude Code's leaked source shows six systems working together: Skeptical memory. Three-layer system where the agent treats its own memory as a hint, not a fact. It verifies against the real world before acting. This is how you prevent an agent from confidently doing the wrong thing based ...

submitted by /u/esporx [link] [comments]

submitted by /u/Mathemodel [link] [comments]

https://futurism.com/artificial-intelligence/paper-ai-chatbots-chatgpt-claude-sycophantic Your AI chatbot isn’t neutral. Trust its advice at your own risk. A striking new study, conducted by researchers at Stanford University and published last week in the journal Science, confirmed that human-like chatbots are prone to obsequiously affirm and flatter users leaning on the tech for advice and insight — and that this behavior, known as AI sycophancy, is a “prevalent and harmful” function endemic to the tech that can validate users’ erroneous or destructive ideas and promote cognitive dependency. “AI sycophancy is not merely a stylistic issue or a niche risk, but a prevalent behavior with broad downstream consequences,” the authors write, adding that “although affirmation may feel supportive,...

It won't be a war against the machines or an out-of-control algorithm. Rather humans will simply lose the ability to concentrate and solve problems for themselves. And so AI will be granted more and more control over everything. submitted by /u/bummed_athlete [link] [comments]

A lot of the AI discussion is still framed around capability: Can it write? Can it code? Can it replace people? But I keep wondering whether the deeper problem is not intelligence, but responsibility. We are building systems that can generate text, images, music, and decisions at scale. But who is actually responsible for what comes out of that chain? Not legally only, but structurally, culturally, and practically. Who decided? Who approved? Who carries the outcome once generation is distributed across prompts, models, edits, tools, and workflows? It seems to me that a lot of current debate is still asking: “What can AI do?” But maybe the more important question is: “What kind of responsibility structure has to exist around systems that can do this much?” Curious how people here think abou...

Dataset Model Acc F1 Δ vs Log Δ vs Static Avg Params Peak Params Steps Infer ms Size Banking77-20 Logistic TF-IDF 92.37% 0.9230 +0.00pp +0.76pp 64,940 64,940 0.00M 0.473 1.000x Static Seed 91.61% 0.9164 -0.76pp +0.00pp 52,052 52,052 94.56M 0.264 0.801x Dynamic Seed Distill 93.53% 0.9357 +1.17pp +1.92pp 12,648 16,881 70.46M 0.232 0.195x CLINC150 | Logistic TF-IDF | 97.00% | 0.9701 | +0.00pp | +1.78pp | 41,020 | 41,020 | 0.00M | 0.000 | 1.000x | Static Seed | 95.22% | 0.9521 | -1.78pp | +0.00pp | 52,052 | 52,052 | 66.80M | 0.302 | 1.269x | Dynamic Seed | 94.78% | 0.9485 | -2.22pp | -0.44pp | 10,092 | 10,136 | 28.41M | 0.324 | 0.246x | Dynamic Seed Distill | 95.44% | 0.9544 | -1.56pp | +0.22pp | 9,956 | 9,956 | 32.69M | 0.255 | 0.243x HWU64 | Logistic TF-IDF | 87.94% | 0.8725 | +...

It took me a lot of time and deep thought to find an answer and write this article. I hope it helps anyone who is in doubt or facing the same situation I was. I Used to Know the Code. Now I Know What to Ask ??? submitted by /u/wesam_mustafa100 [link] [comments]

Was at Nvidia's GTC conference recently and honestly, it was one of the most eye-opening events I've attended in a while. There was a lot to unpack, but my single biggest takeaway was this: world modelling is the actual GOAT of AI right now, and I don't think people outside the research community fully appreciate what's coming. A year ago, when I was doing the conference circuit, world models were still this niche, almost academic concept. You'd bring it up and get blank stares or polite nods. Now? Every serious conversation at GTC was circling back to it. The shift in recognition has been dramatic. It feels like the moment in 2021 when everyone suddenly "got" transformers. For those unfamiliar: world models are AI systems that don't just predict the next token. They build an internal repr...

A few hours ago, the first author of a paper that played a significant role in the TQ paper posted about some ongoing issues: In May 2025, our emails directly raised the theoretical and empirical issues; Majid wrote that he had informed his co-authors. During ICLR review, reviewers also asked for clarification about random rotation and the relation to RaBitQ. On March 26, 2026, we formally raised these concerns again to all authors and were told that corrections would wait until after the ICLR 2026 conference takes place; we were also told that they would not acknowledge the structural similarity regarding the Johnson-Lindenstrauss transformation. We do not consider that acceptable given the present level of public promotion and community confusion. We are posting this comment so that the...