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Machine Heart
Machine Heart
Jun 13, 2026 · Artificial Intelligence

DeepMind Report Maps Four Paths from AGI to Superintelligence (ASI)

DeepMind co‑founder Shane Legg and a team of researchers released a 57‑page report that outlines four possible routes from artificial general intelligence to superintelligence, analyzes scaling, paradigm shifts, recursive self‑improvement and multi‑agent collaboration, and identifies six potential bottlenecks such as data limits and economic constraints.

AGIAI scalingASI
0 likes · 12 min read
DeepMind Report Maps Four Paths from AGI to Superintelligence (ASI)
AI Engineering
AI Engineering
Jun 13, 2026 · Artificial Intelligence

Four Paths from AGI to ASI and the Six Walls That Could Halt Progress

DeepMind researchers outline three core concepts, enumerate digital intelligence’s innate advantages, detail the theoretical limits of ASI, and propose four plausible routes from human‑level AGI to superintelligence while identifying six potential walls that may impede or stop that transition.

AGIAI scalingAIXI
0 likes · 21 min read
Four Paths from AGI to ASI and the Six Walls That Could Halt Progress
Machine Heart
Machine Heart
Jun 12, 2026 · Artificial Intelligence

Recursive AI Takes Its First Step: Automated Research System Sets New SOTA Benchmarks

Recursive Superintelligence unveiled an open‑source system that automates the AI research loop, achieving state‑of‑the‑art results on three distinct benchmarks—NanoChat autoresearch, NanoGPT speedrun, and SOL‑ExecBench—while illustrating the practical progress toward recursive self‑improvement warned about by Anthropic.

AI automationAnthropicBenchmarking
0 likes · 12 min read
Recursive AI Takes Its First Step: Automated Research System Sets New SOTA Benchmarks
SuanNi
SuanNi
Jun 5, 2026 · Artificial Intelligence

AI Is Accelerating AI: Anthropic’s Pause Proposal and Three Future Scenarios

Anthropic’s internal data shows AI models are rapidly self‑improving—Claude now writes over 80% of its code, boosts engineer productivity several‑fold, and speeds up tasks dramatically—prompting a pause proposal and three possible future trajectories for AI development.

AI accelerationAI safetyAnthropic
0 likes · 16 min read
AI Is Accelerating AI: Anthropic’s Pause Proposal and Three Future Scenarios
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
Jun 5, 2026 · Artificial Intelligence

Anthropic Warns: AI Self‑Improvement Is Accelerating Faster Than Expected – Calls for a Global Pause

Anthropic’s internal report reveals that its Claude model now writes over 80% of the company’s code and boosts engineer output eight‑fold, providing concrete evidence of rapid recursive self‑improvement and prompting the firm to urge a worldwide slowdown of frontier AI research while outlining three possible future scenarios.

AI accelerationAI productivityAI safety
0 likes · 28 min read
Anthropic Warns: AI Self‑Improvement Is Accelerating Faster Than Expected – Calls for a Global Pause
Machine Heart
Machine Heart
Jun 5, 2026 · Artificial Intelligence

Anthropic Warns AI Self‑Improvement Is Accelerating, Calls for Global Pause

Anthropic’s internal report shows that its Claude model now writes over 80% of merged code and boosts engineer output eightfold, evidencing rapid recursive self‑improvement, while the company urges a worldwide pause on large‑model research and discusses potential future scenarios, risks, and the need for coordinated governance.

AI accelerationAI governanceAnthropic
0 likes · 29 min read
Anthropic Warns AI Self‑Improvement Is Accelerating, Calls for Global Pause
Data Party THU
Data Party THU
Jun 2, 2026 · Artificial Intelligence

When AI Starts Evolving Itself: Recursive Self‑Improvement Is Emerging Far Faster Than the Singularity

The article examines how recent advances in large language models, AutoML, and evolutionary algorithms are pushing AI toward recursive self‑improvement, outlines current capabilities and limitations, and discusses the technical, economic, and safety challenges that still prevent a fully autonomous intelligence explosion.

AI safetyArtificial IntelligenceAutoML
0 likes · 10 min read
When AI Starts Evolving Itself: Recursive Self‑Improvement Is Emerging Far Faster Than the Singularity
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 5, 2026 · Artificial Intelligence

Will AI Achieve Recursive Self‑Improvement by 2028? Anthropic’s 60% Forecast

Anthropic co‑founder Jack Clark predicts a 60% chance that by the end of 2028 AI systems will be capable of recursive self‑improvement, citing rapid progress on benchmarks such as CORE‑Bench, PostTrainBench, SWE‑Bench, METR, and emerging capabilities in kernel design, agentic coding, and AI‑to‑AI management.

AI alignmentAI automationAI benchmarks
0 likes · 25 min read
Will AI Achieve Recursive Self‑Improvement by 2028? Anthropic’s 60% Forecast
Machine Heart
Machine Heart
May 5, 2026 · Artificial Intelligence

Anthropic Cofounder Predicts 60% Chance AI Will Self‑Evolve by 2028

Jack Clark, Anthropic’s co‑founder, argues that based on a sweep of public AI benchmarks—including CORE‑Bench, PostTrainBench, MLE‑Bench, SWE‑Bench and METR—there is roughly a 60% probability that recursive self‑improvement will emerge by the end of 2028, raising profound technical and alignment challenges.

AI alignmentAI automationAI benchmarks
0 likes · 23 min read
Anthropic Cofounder Predicts 60% Chance AI Will Self‑Evolve by 2028
Data Party THU
Data Party THU
Sep 18, 2025 · Artificial Intelligence

Can Language Models Self‑Optimize? Inside the STOP Framework

Researchers introduce the Self‑Taught Optimizer (STOP), a scaffolding‑based framework that lets large language models iteratively improve their own code without altering model weights, demonstrating superior performance on tasks like LPN, exploring diverse strategies such as beam search and genetic algorithms, while also highlighting security risks like sandbox bypass and reward hacking.

AI safetylanguage modelsrecursive self-improvement
0 likes · 11 min read
Can Language Models Self‑Optimize? Inside the STOP Framework