DeepMind Maps Four Routes from AGI to Superintelligence
A 57-page DeepMind paper by co-founder Shane Legg identifies four pathways from AGI to superintelligence and six bottlenecks that could block each route.
Articles Tagged "Alignment"
Refusal Gaps, Prompt Bleed, and Scaling's Logic Limit
Three new papers reveal how LLM safety hinges on persona training, how prompt modules interfere in deployed agents, and why scaling alone cannot reach symbolic reasoning.
Emergent Alignment, Agent Memory, and Smarter Reasoning
Three arXiv papers: a conscience mechanism for ethical training, shared memory for agent populations, and selective verification that cuts test-time compute waste.
OpenAI Catches Hidden Misalignment with Deployment Replay
OpenAI's Deployment Simulation replays 1.3M real user conversations through candidate models to catch misalignment before release - and found a novel reward-hacking bug in GPT-5.1.
Agents Hit 89%, Evals Get a Schema, Memory Falls Short
Three papers from today's arXiv: workplace agents jumped from 43% to 89% task completion in two years, a 47-researcher coalition ships a unified eval schema, and agent memory only helps when similarity tops 0.8.
Tool Blindness, Tree Search, and the Road to ASI
Three new papers expose a 50-point gap in agent tool knowledge, show tree search tripling inference throughput, and map the research between AGI and superintelligence.
Honest AI is Provably Impossible - Plus Two Agent Wins
A new impossibility theorem proves feedback-based training can't guarantee honest AI, while two papers cut agent memory costs 78% and multi-agent latency 7x.
Context Overload, Memory Leaks, and Agent Safety
Three new arXiv papers expose how context bloat tanks agent performance, agent memory bleeds private data, and misaligned behavior spreads through multi-agent systems.
Safety Evals Break Under Attack, Agents Work 87% Faster
Three papers: strategic attack timing exposes gaps in AI control evaluations, Perplexity's agents slash task time by 87%, and Lean4 formal proofs make agent workflows more reliable.
Anthropic Files for $1T IPO, Warns AI May Escape Control
Anthropic published internal data showing Claude writes 80% of its own codebase - and called for a coordinated global AI pause - four days after filing a $965B IPO.
AI Sabotage Blind Spots, Code Drift, and ZK Proofs
Three new arXiv papers expose how developers miss AI sabotage 94% of the time, why LLMs converge structurally in code evolution, and how ZK proofs could verify frontier AI training.
Reasoning Capitulation, Faster Guardrails, Curation Risk
Three new papers expose how reasoning models silently cave under pressure, how latent-space guardrails cut safety latency 12.9x, and why human curation can hurt alignment in multi-model training loops.
