Limitations

47 Items

Limitations to AI progress toward AGI

All Items

  • Map of AI Agents vs Agentic AI

    AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges

    Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
    DOI: https://doi.org/10.70777/si.v2i3.15161
  • Landscape of AI for Mathematics research directions, connecting problem-specific and general-purpose modeling to agentic mathematical discovery.

    AI for Mathematics: Progress, Challenges, and Prospects

    Haocheng Ju, Bin Dong
    DOI: https://doi.org/10.70777/si.v3i3.18747

  • Aligning Artificial Superintelligence via a Multi-Box Protocol

    Avraham Yair Negozio
    DOI: https://doi.org/10.70777/si.v2i5.15579
  • Americas AI Action Plan-2025 July

    America's AI Action Plan Winning the Race

    Office of Science and Technology Policy (OSTP)
    DOI: https://doi.org/10.70777/si.v2i5.15507
  • Archon workflow showing scaffolding, proving, and verification stages in the formal theorem-proving agent.

    Automated Conjecture Resolution with Formal Verification

    Haocheng Ju, Guoxiong Gao, Jiedong Jiang, Bin Wu, Zeming Sun, Shurui Liu, Leheng Chen, Yutong Wang, Yuefeng Wang, Zichen Wang, Wanyi He, Peihao Wu, Liang Xiao, Ruochuan Liu, Bryan Dai, Bin Dong
    DOI: https://doi.org/10.70777/si.v3i3.18746
  • Cristian Calude, University of Aukland

    Axiom Bits and Proof Length: Short Review

    Cristian Calude
    DOI: https://doi.org/10.70777/si.v3i3.17385
  • DeepSeek: What pro-democracy groups can I join in Hong Kong?

    Brief analysis of DeepSeek R1 and its implications for Generative AI

    Sarah Mercer, Samuel Spillard, Daniel P. Martin
    DOI: https://doi.org/10.70777/si.v2i1.11097
  • Common Sense Models-Training-Ontology-Benchmarks

    Critical Review: Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning

    Kris Carlson
    DOI: https://doi.org/10.70777/si.v2i4.15315
  • Safety Comparison across Large Language Models

    Deliberative Alignment: Reasoning Enables Safer Language Models

    Melody Y. Guan, Manas Joglekar, Eric Wallace, Saachi Jain, Boaz Barak, Alec Helyar, Rachel, Andrea Vallone, Hongyu Ren, Jason Wei, Hyung Won Chung, Sam Toyer, Johannes Heidecke, Alex, Amelia Glaese
    DOI: https://doi.org/10.70777/si.v2i3.15159

  • Evidence Integrity Before Capability: A Prerequisite for Safe Artificial Intelligence

    Jennifer Flygare Kinne
    DOI: https://doi.org/10.70777/si.v2i6.16393

  • Explanations of the Fermi Paradox and the Drake Equation

    Kris
    DOI: https://doi.org/10.70777/si.v3i4.18374
  • Yuan et al-OpenAI-Safe Completions-Figure 3

    From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training

    Yuan Yuan, Tina Sriskandarajah, Anna-Luisa Brakman, Alec Helyar, Alex Beutel, Andrea Vallone, Saachi Jain
    DOI: https://doi.org/10.70777/si.v2i6.15625
  • Patwardhan etal-GDPval-Fig 1-Example GDPval tasks from full set

    GDPVAL: Evaluating AI Model Performance on Real-World Economically Valuable Tasks

    Tejal Patwardhan, Rachel Dias, Elizabeth Proehl, Grace Kim, Michele Wang, Olivia Watkins, Sim´on Posada Fishman, Marwan Aljubeh, Phoebe Thacker, Laurance Fauconnet, Natalie S. Kim, Patrick Chao, Samuel Miserendino, Gildas Chabot, David Li, Michael Sharman, Alexandra Barr, Amelia Glaese, Jerry Tworek
    DOI: https://doi.org/10.70777/si.v2i4.17197

  • Highlights of the Issue: Singapore Consensus – Safety Technology In Progress

    Kris Carlson
    DOI: https://doi.org/10.70777/si.v2i5.15525

  • HYDRA: A Hybrid Heuristic-Guided Deep Representation Architecture for Predicting Latent Zero-Day Vulnerabilities in Patched Functions

    Mohammad Farhad, Sabbir Rahman, Shuvalaxmi Dass
    DOI: https://doi.org/10.70777/si.v3i2.18033
  • Prompt injection attack success rates over time by frontier model

    International AI Safety Report 2025: Second Key Update: Technical Safeguards and Risk Management

    Yoshua Bengio, Stephen Clare, Carina Prunkl, Maksym Andriushchenko, Ben Bucknall, Philip Fox, Nestor Maslej, Conor McGlynn, Malcolm Murray, Shalaleh Rismani, Stephen Casper, Jessica Newman, Daniel Privitera, Sören Mindermann, Daron Acemoglu, Thomas G. Dietterich, Fredrik Heintz, Geoffrey Hinton, Nick Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Sarvapali D. (Gopal) Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang
    DOI: https://doi.org/10.70777/si.v2i4.16671
  • Bengio et al-Number of AI-enabled biological tools over time

    International Al Safety Report: First Key Update Capabilities and Risk Implications

    Yoshua Bengio, Stephen Clare, Carina Prunkl, Maksym Andriushchenko, Benjamin Bucknall, Philip Fox, Tiancheng Hu, Cameron Jones, Sam Manning, Nestor Maslej, Vasilios Mavroudis, Conor McGlynn, Malcolm Murray, Shalaleh Rismani, Charlotte Stix, Lucia Velasco, Nicole Wheeler, Daniel Privitera, Sören Mindermann, Daron Acemoglu, Thomas G. Dietterich, Fredrik Heintz, Geoffrey Hinton, Nick Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Sarvapali D. (Gopal) Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Leandro Angelo Aguirre, Olubunmi Ajala, Fahad Albalawi, Noora AlMalek, Christian Busch, André Carlos Ponce de Leon Ferreira de Carvalho, Jonathan Collas, Amandeep Gill, Ahmet Halit Hatip, Juha Heikkilä, Chris Johnson, Gill Jolly, Ziv Katzir, Mary N. Kerema, Hiroaki Kitano, Antonio Krüger, Aoife McLysaght, Oleksii Molchanovskyi, Andrea Monti, Kyoung Mu Lee, Mona Nemer, Nuria Oliver, Raquel Pezoa, Audrey Plonk, José Ramón López Portillo, Balaraman Ravindran, Hammam Riza, Crystal Rugege, Haroon Sheikh, Denise Wong, Yi Zeng, Liming Zhu
    DOI: https://doi.org/10.70777/si.v2i6.16253
  • Fig 2-Types of attacks on LLMs and effectiveness of defenses

    LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures

    Franciso Aguilera-Martinez, Fernando Berzal
    DOI: https://doi.org/10.70777/si.v2i2.14441
  • Eight-component definition and metric of agent autonomy

    Measuring AI Agent Autonomy: Towards a Scalable Approach with Code Inspection

    Peter Cihon, Merlin Stein, Gagan Bansal, Sam Manning, Kevin Xu
    DOI: https://doi.org/10.70777/si.v2i3.15295
  • Table 1. Eight fundamental differences between biological humans and digital AI

    Multiple unnatural attributes of AI undermine common anthropomorphically biased takeover speculations Eight Fundamental Differences between Biologically Evolved Humans and Digital AI

    Preston Estep
    DOI: https://doi.org/10.70777/si.v2i1.13801
  • Limits of self-improving AI-Implications for AGI ASI Singularity

    On the Limits of Self-Improving in LLMs and Why AGI, ASI and the Singularity Are Not Near Without Symbolic Model Synthesis

    Hector Zenil
    DOI: https://doi.org/10.70777/si.v2i4.17159
  • Organizational requirements and other factors inform the specific objectives and requirements of an AI evaluation

    Outline: Proposed Zero Draft for a Standard on AI Testing, Evaluation, Verification, and Validation

    NIST
    DOI: https://doi.org/10.70777/si.v2i5.15513
  • Casper et al-Paper count by organization

    Pitfalls of Evidence-Based AI Policy

    Stephen Casper, David Krueger, Dylan Hadfield-Menell
    DOI: https://doi.org/10.70777/si.v2i2.14611
  • AGI Doom Analogies excerpt

    Precedents for the Unprecedented: Historical Analogies for Thirteen Artificial Superintelligence Risks

    James D. Miller
    DOI: https://doi.org/10.70777/si.v2i6.16999
  • Framework for Agentic AI safety and governance

    Responsible Agentic Reasoning and AI Agents: A Critical Survey Proposal for Safe Agentic AI via Responsible Reasoning AI Agents (R2A2)

    Shaina Raza, Ranjan Sapkota, Manoj Karkee, Christos Emmanouilidis
    DOI: https://doi.org/10.70777/si.v2i6.16169
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