Tag: LLMs
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LoRA and QLoRA: Fine-Tuning Large Models on One GPU
LoRA fine-tunes 70B models on one GPU using low-rank weight updates. The intrinsic dimension proof, rsLoRA scaling fix, and where LoRA falls short.
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Speculative Decoding: How LLMs Generate 3x Faster
Speculative decoding achieves 3-4x LLM speedup with zero output quality loss. The math proof, EAGLE-2’s 4.26x result, and when it does not help.
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LLMs in Veterinary Clinical Practice: What the Evidence Actually Shows
ChatGPT-4.5 scored 90% on feline eye disease cases vs 96.7% for experienced veterinary ophthalmologists and significantly outperformed novices (56-67%). Where LLMs add clinical value in veterinary practice, where…
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Poisoning the Medical Brain: RAG Attacks and Security in Clinical AI Systems
Clinical LLMs failed prompt injection at 94% in JAMA testing. RAG systems face a harder attack: poisoned retrieved documents that the LLM cannot distinguish from legitimate sources. How…
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Radiology Foundation Models: What Merlin, the 22% Hallucination Rate, and ED Fracture Data Tell Us
Stanford published Merlin in Nature (2026): a 3D vision-language foundation model for abdominal CT trained on 15,331 scans and over 6 million images, evaluated across 752 tasks. How…
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Prompt Injection Succeeds 94% of the Time Against Clinical LLMs
A JAMA Network Open study found prompt injection attacks succeed 94.4% of the time against clinical LLMs, including 91.7% in high-harm pregnancy drug scenarios. Based on PubMed-indexed research,…
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LLMs Give Novice Biologists 4x Uplift on Dangerous Tasks
A 2026 study measured LLM access giving novice biologists a 4.16x accuracy boost on biosecurity-relevant tasks, including beating expert baselines. Here is the mechanism and what it means…
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MiniMax M2.7 Optimized Its Own Training Harness 100 Times. Here Is the Loop.
MiniMax M2.7 ran an internal agent that modified its own training scaffold 100 times in a row without human input and gained 30% on internal evaluations. Here is…
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M-Trends 2026: Exploits Now Arrive Before Patches. The Mean Time-to-Exploit Is Negative 7 Days.
Mandiant M-Trends 2026 documents a mean time-to-exploit of negative 7 days. 28.3% of CVEs are being exploited within 24 hours of disclosure. Here is the AI attack chain…
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KellyBench: 8 AI Models Bet the Premier League. All Lost Money.
General Reasoning put 8 frontier AI models through a full Premier League season with a 100k bankroll each. Every model lost money. The benchmark reveals three distinct failure…
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DeepSeek V4’s Hybrid Attention Cuts KV Cache by 10x. Here’s the Architecture.
DeepSeek V4-Pro processes one million tokens using 10% of the KV cache V3.2 needed. The mechanism is Hybrid Attention: two complementary compressors interleaved across 61 layers. Here’s how…
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30 Days After QJL: What’s Actually Compressing the KV Cache
After QJL failed, three approaches own the KV cache frontier: TriAttention’s pre-RoPE selection, LRKV architectural compression, and adaptive bit-width.
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Open-Weight LLM Rankings, April 2026: MMLU Is Saturated, Here’s What to Use Instead
MMLU is saturated. In April 2026, the metrics that matter are SWE-bench Verified, GPQA Diamond, and RULER’s effective context window. Chinese labs hold 4 of the top 5…
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ARC-AGI-3 Is Live. Here’s Why Current Models Score in the Low Double Digits.
ARC-AGI-3 launched on Kaggle with a $1M prize and current leaders in low double digits. The benchmark adds Exploration, Modeling, and Planning that test-time compute scaling cannot solve.…
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ICLR 2026 Outstanding Papers: What They Actually Found, and the Review Crisis Around Them
ICLR 2026 named two outstanding papers: LLMs Get Lost In Multi-Turn Conversation and Transformers are Inherently Succinct. The conference also documented a 45% identity leak and 21% AI-generated…
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Agent Memory Architecture: Four Patterns, Four Tradeoffs
Agent memory is not one thing. It is four distinct patterns: full context window, hierarchical summarization, external vector store, and episodic log. Each has different performance, cost, failure…
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OpenAI Codex at 3 Million Users: How It Differs from Claude Code
Codex has 3M weekly users. Claude Code runs in your terminal. The architectural difference between cloud loop and local execution determines which tasks each tool handles well —…
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Why 86% of Enterprise AI Agent Pilots Never Reach Production
Multiple independent studies in 2026 put the enterprise AI agent pilot failure rate at 86-89%. Six failure modes account for the losses. Here’s what they are, what causes…
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Amazon Bedrock AgentCore: What Each Layer Does and Why It Matters
Amazon Bedrock AgentCore is six infrastructure services in one name. Here’s what each layer does: Runtime for serverless execution, Memory’s four tiers, Tool Execution’s sandboxing, Action Gateway’s enterprise…
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Know Your Agent: The First Regulated AI Agent Governance Standard
MetaComp’s StableX KYA Framework, published April 21, 2026, is the first governance standard for AI agents from a licensed financial institution. Here’s what its four pillars cover, how…
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