Library
Current ASI papers, model drops, lab notes, benchmarks, governance frameworks, and reference code, catalogued in two tracks. Last research pass: 07 Jul 2026.
frontier map
AGI to ASI
Pathways, model releases, bottlenecks, and technical loops that can turn AI progress into compounding scientific progress.
live code
Self-improvement
DGM, Hyperagents, CodeEvolve, AI Scientist, AutoResearchClaw, and related entries link directly to public implementations where available.
practice
Fast and legible
The governance track focuses on evals, controls, assurance, and deployment norms that let ambitious systems earn trust.
technical Advancement
- ASI Technical Radar: Compounding Intelligence A curated map of the papers, model drops, benchmarks, and research systems that matter most for building ASI: post-AGI pathways, recursive self-improvement, ...
- GeneBench-Pro A genomics and biology benchmark from OpenAI for evaluating AI performance on complex scientific research tasks and datasets.
- Gemini Omni Flash Gemini Omni Flash is a public-preview multimodal model for high-speed video generation and conversational video editing through the Gemini API.
-
Claude Science
Anthropic's Claude Science is an AI workbench for scientists that integrates research tools, produces auditable artifacts, and connects to compute.
-
Claude Fable 5, Mythos 5, and Sonnet 5
Anthropic's June 2026 model wave includes Claude Fable 5, Mythos 5 for approved defensive cyber workflows, and Claude Sonnet 5 for broad agentic use.
-
GPT-5.6 Sol Preview
OpenAI's GPT-5.6 preview introduces Sol as a next-generation frontier model, with Terra and Luna positioned as lower-cost members of the same family.
-
ImprovEvolve: Basin-Hopping Meets LLM-Guided Evolutionary Search
An AlphaEvolve-inspired algorithm that decomposes LLM-guided evolutionary search into initialization, local improvement, and perturbation operators.
- A Near-Autonomous AI Chemist Improves a Challenging Reaction OpenAI and Molecule.one report a near-autonomous AI chemistry workflow in which GPT-5.4 helped improve Chan-Lam Coupling yields across tested substrates.
- From AGI to ASI A 2026 orientation report on the post-AGI frontier, defining ASI as systems more intelligent and cognitively capable than large human organizations and mappi...
- From 0-to-1 to 1-to-N: Reproducible Engineering Evidence for MetaAI Recursive Self-Design A compact evidence framework for recursive self-design, mapping public systems such as DGM, STOP, Goedel Agent, and ShinkaEvolve against criteria for inspect...
-
CodeEvolve: Open-Source Evolutionary Coding Agent for Algorithmic Discovery
An open-source evolutionary coding agent that combines LLMs, island-based search, crossover, meta-prompting, refinement, and evaluator feedback for algorithm...
-
MUSE-Autoskill
A self-evolving agent framework that treats skills as long-lived, testable assets with creation, memory, management, evaluation, and refinement.
-
AutoResearchClaw
A multi-agent autonomous research pipeline with debate, self-healing execution, verifiable reporting, human-in-the-loop modes, and cross-run evolution.
-
Gemini for Science
Google's Gemini for Science collects experimental tools for scientific literature work, code transformation, hypothesis generation, and discovery.
- Gemini 3.5 Flash and Antigravity Agent Gemini 3.5 Flash became generally available alongside Managed Agents and the Antigravity Agent preview for autonomous coding, browsing, and file work.
-
Agentic Discovery of Neural Architectures: AIRA-Compose and AIRA-Design
A 2026 paper showing LLM agents autonomously designing foundation-model architectures and training scripts, with AIRA-Compose and AIRA-Design producing model...
-
Co-Scientist: A Multi-Agent AI Partner to Accelerate Research
A Gemini-built multi-agent system for generating, debating, ranking, and evolving scientific hypotheses in life sciences and beyond.
- AIRA2: Overcoming Bottlenecks in AI Research Agents Meta AI's AIRA2 focuses on throughput, generalization, and operator limits in AI research agents for model and architecture discovery.
-
Hyperagents
Self-referential agents that combine task and meta agents into an editable program, allowing the improvement process itself to be improved across domains.
- Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents A self-improving coding-agent system that modifies its own code, validates changes on benchmarks, and keeps a growing archive of diverse agents.
-
AI Agent Systems: Architectures, Applications, and Evaluation
A 2026 survey of AI agent architectures, orchestration patterns, deployment settings, evaluation practices, and open reliability challenges.
-
Live-SWE-agent: Can Software Engineering Agents Self-Evolve on the Fly?
A live software engineering agent that evolves its own scaffold while solving real software tasks, reporting strong SWE-bench Verified and SWE-Bench Pro resu...
-
Huxley-Godel Machine: Human-Level Coding Agent Development
A self-improving coding-agent method that guides search by estimating the improvement potential of agent descendants rather than only current benchmark score.
-
AlphaEvolve: A Coding Agent for Scientific and Algorithmic Discovery
Google DeepMind's evolutionary coding-agent framework for scientific and algorithmic discovery, including infrastructure optimization and new algorithms for ...
-
The Llama 4 Herd
Meta's Llama 4 Scout and Maverick introduced open-weight natively multimodal mixture-of-experts models, distilled from the larger Behemoth teacher model.
- The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery A framework for automated scientific discovery in which frontier models generate ideas, write code, run experiments, plot results, write papers, and simulate...
governance & Practice
-
Notes Toward Sensible ASI Governance
Governance for ASI should make fast development more legible, reliable, and deployable: measurement, evaluations, incident learning, and standards that scale...
-
Google DeepMind AI Control Roadmap
Google DeepMind's defense-in-depth roadmap for securing advanced AI agents even when alignment is imperfect.
- LifeSciBench OpenAI's expert-authored benchmark for evaluating how AI systems handle realistic life-science workflows and decisions.
- A Shared Playbook for Trustworthy Third-Party Evaluations OpenAI's recommendations for independent evaluations of frontier-model capabilities and safeguards, with emphasis on harness design and validity.
- OpenAI Frontier Governance Framework A public framework explaining how OpenAI aligns safety and security practices with emerging frontier-AI legal requirements.
-
Agentic AI Scientists Are Not Built for Autonomous Scientific Discovery
A critique of autonomous AI-scientist systems, arguing that current designs miss tacit lab knowledge, diversity, physical feedback, and problem selection.
-
Measuring AI R&D Automation
A measurement proposal for AI R&D automation, tracking how much AI changes research labor, progress rates, oversight, and incident patterns.