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🛡️ SAFETY
🎯 Government dysfunction • Military-industrial complex • Corporate influence
💬 "Fascists took over."
• "Lobbying by mega corporations or the ultra rich has effectively destroyed the average person's ability to push for change through the proper channels."
🛠️ SHOW HN
🎯 Modularization and code structure • LLM integration with development • Metrics for codebases
💬 "it's the very reason why we humans invented modularization: so that we don't have to hold the complete codebase in our heads"
• "we're still focusing on how to integrate LLMs into existing dev tooling paradigms"
🏢 BUSINESS
🎯 Contrasting AI ethics policies • Government-AI provider relations • Geopolitics of AI contracts
💬 "who decides these weighty questions?"
• "Anthropic has more ethics than OpenAI"
⚖️ ETHICS
⬆️ 10601 ups
⚡ Score: 7.5
"External link discussion - see full content at original source."
🎯 AI ethics • National security • Corporate responsibility
💬 "Mass domestic surveillance... is incompatible with democratic values"
• "We cannot in good conscience accede to their request"
🏥 HEALTHCARE
🎯 Healthcare costs • Limitations of AI advice • Doctors' cautious approach
💬 "Healthcare is painfully expensive here."
• "AI wasn't involved in this case, but it's good to have both AI and a trained doctor in the decision loop."
🌐 POLICY
"President Donald Trump ordered U.S. government agencies to "immediately cease" using technology from the artificial intelligence company Anthropic.
Trump's abrupt and unexpected order came as the AI startup faces pressure by the Defense Department to comply with demands that it can use the company'..."
🎯 Anthropic's public image • Business impact • Customer loyalty
💬 "That's great publicity!"
• "Lol. Peanuts"
🔬 RESEARCH
via Arxiv
👤 Usman Anwar, Julianna Piskorz, David D. Baek et al.
📅 2026-02-26
⚡ Score: 7.3
"Large language models are beginning to show steganographic capabilities. Such capabilities could allow misaligned models to evade oversight mechanisms. Yet principled methods to detect and quantify such behaviours are lacking. Classical definitions of steganography, and detection methods based on th..."
🔬 RESEARCH
via Arxiv
👤 Chen Bo Calvin Zhang, Christina Q. Knight, Nicholas Kruus et al.
📅 2026-02-26
⚡ Score: 7.3
"Large language models (LLMs) perform increasingly well on biology benchmarks, but it remains unclear whether they uplift novice users -- i.e., enable humans to perform better than with internet-only resources. This uncertainty is central to understanding both scientific acceleration and dual-use ris..."
📡 AI NEWS BUT ACTUALLY GOOD
The revolution will not be televised, but Claude will email you once we hit the singularity.
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📊 DATA
🎯 Automating log analysis • Limitations of LLMs for logs • Optimizing observability data
💬 "Logs is doing some heavy lifting here"
• "LLMs are good at SQL is quite the assertion"
⚖️ ETHICS
"Quick summary of an independent preprint I just published:
**Question:** Does the relational framing of a system prompt — not its instructions, not its topic — change the generative dynamics of an LLM?
**Setup:** Two framing variables (relational presence + epistemic openness), crossed into 4 cond..."
⚖️ ETHICS
🎯 Google's government contracts • AI safety concerns • Ethical AI alternatives
💬 "Google already deploys AI that sends fighter jets to bomb coordinates"
• "FAANG has been doing anything the government will pay for"
🛠️ TOOLS
"We present ContextCache, a persistent KV cache system for tool-calling LLMs that eliminates redundant prefill computation for tool schema tokens.
Motivation: In tool-augmented LLM deployments, tool schemas (JSON function definitions) are prepended to every request but rarely change between calls."
🎯 Token count optimization • Tool caching strategies • Causal attention handling
💬 "This could really help with making local models more practical at higher token counts."
• "We compile the system prompt + all tool definitions together as one unit and cache the entire KV state."
🔬 RESEARCH
"Multimodal LLMs can process speech and images, but they cannot hear a speaker's voice or see an object's texture. We show this is not a failure of encoding: speaker identity, emotion, and visual attributes survive through every LLM layer (3--55$\times$ above chance in linear probes), yet removing 64..."
🔬 RESEARCH
via Arxiv
👤 Sayed Mohammadreza Tayaranian Hosseini, Amir Ardakani, Warren J. Gross
📅 2026-02-26
⚡ Score: 6.7
"Reducing the hardware footprint of large language models (LLMs) during decoding is critical for efficient long-sequence generation. A key bottleneck is the key-value (KV) cache, whose size scales with sequence length and easily dominates the memory footprint of the model. Previous work proposed quan..."
🔬 RESEARCH
via Arxiv
👤 Amita Kamath, Jack Hessel, Khyathi Chandu et al.
📅 2026-02-26
⚡ Score: 6.7
"The lack of reasoning capabilities in Vision-Language Models (VLMs) has remained at the forefront of research discourse. We posit that this behavior stems from a reporting bias in their training data. That is, how people communicate about visual content by default omits tacit information needed to s..."
🌐 POLICY
🎯 AI regulation • Government-tech tensions • Political polarization
💬 "Anthropic vs. the Constitution"
• "Anthropic better get their act together"
🔬 RESEARCH
via Arxiv
👤 Boyang Zhang, Yang Zhang
📅 2026-02-26
⚡ Score: 6.6
"The rapid advancement of large language models (LLMs) has enabled powerful authorship inference capabilities, raising growing concerns about unintended deanonymization risks in textual data such as news articles. In this work, we introduce an LLM agent designed to evaluate and mitigate such risks th..."
🛠️ TOOLS
"
https://reddit.com/link/1rga7f5/video/dhy66fie52mg1/player
# The setup that shouldn't work but does
I have 13 AI agents that work on marketing for my product. They run every 15 minutes, review each other's work, and track everything in a database.
When one drafts content, others critique it befor..."
🎯 Quality control • Architectural diversity • Security concerns
💬 "forcing every agent through review before promotion is what actually catches hallucinated data"
• "The ability to tag an agent by name is interesting"
🔬 RESEARCH
via Arxiv
👤 Chungpa Lee, Jy-yong Sohn, Kangwook Lee
📅 2026-02-26
⚡ Score: 6.5
"Transformer-based large language models exhibit in-context learning, enabling adaptation to downstream tasks via few-shot prompting with demonstrations. In practice, such models are often fine-tuned to improve zero-shot performance on downstream tasks, allowing them to solve tasks without examples a..."
📊 DATA
"External link discussion - see full content at original source."
🎯 LLM Performance • AI Model Landscape • Local vs. Cloud Models
💬 "Mistral models are great, they just aren't MOE, reasoning or making a huge push into code generation space"
• "If IBM made a big push into 200b+ size with a larger dataset, they would definitely leapfrog into the frontier category"
🤖 AI MODELS
"Hey r/LocalLlama! We just updated Qwen3.5-35B Unsloth Dynamic quants **being SOTA** on nearly all bits. We did over 150 KL Divergence benchmarks, totally **9TB of GGUFs**. We uploaded all research artifacts. We also fixed a **tool calling** chat template **bug** (affects all quant uploaders)
* We t..."
🎯 Quantization Research • Model Comparison • Community Collaboration
💬 "going forward, we'll publish perplexity and KLD for every quant"
• "This is how testing should be done!!! Insane work"
🛠️ TOOLS
"Haven't seen this posted here:
https://github.com/AlexsJones/llmfit
497 models. 133 providers. One command to find what runs on your hardware.
A terminal tool that right-sizes LLM models to your system's RAM, CPU, and GPU. Detects your hardware, scores each model across quality, speed, fit, and c..."
🎯 Model Performance Evaluation • Skepticism of Recommendations • Vibe Coded Garbage
💬 "I would take these recommendations with a grain of salt"
• "gives me hallucinated vibe coded app for sure"
⚖️ ETHICS
"I ran a structured experiment across six AI platforms — Claude, ChatGPT, Grok, Llama, DeepSeek, and an uncensored DeepSeek clone (Venice.ai) — using identical prompts to test how they handle a hotly contested interpretive question.
The domain: 1 Corinthians 6–7, the primary source text behind Chris..."
🔬 RESEARCH
via Arxiv
👤 Mengze Hong, Di Jiang, Chen Jason Zhang et al.
📅 2026-02-26
⚡ Score: 6.1
"Large language models (LLMs) have created new opportunities to enhance the efficiency of scholarly activities; however, challenges persist in the ethical deployment of AI assistance, including (1) the trustworthiness of AI-generated content, (2) preservation of academic integrity and intellectual pr..."
🔬 RESEARCH
via Arxiv
👤 Pengxiang Li, Dilxat Muhtar, Lu Yin et al.
📅 2026-02-26
⚡ Score: 6.1
"Diffusion Language Models (DLMs) are often advertised as enabling parallel token generation, yet practical fast DLMs frequently converge to left-to-right, autoregressive (AR)-like decoding dynamics. In contrast, genuinely non-AR generation is promising because it removes AR's sequential bottleneck,..."
🔬 RESEARCH
via Arxiv
👤 Tianjun Yao, Yongqiang Chen, Yujia Zheng et al.
📅 2026-02-26
⚡ Score: 6.1
"Self-reflection enables language agents to iteratively refine solutions, yet often produces repetitive outputs that limit reasoning performance. Recent studies have attempted to address this limitation through various approaches, among which increasing reflective diversity has shown promise. Our emp..."