Ash Manvi
Reproducible, ethical testbed for Alzheimer's, Parkinson's, and other neurological disorders using mechanistic interpretability.
Abraham Nash
Trustless, open source protocol for collective AI training where data never leaves the device.
Shaun Srirangam
Igor Polishchuk
Formal notation and synthetic dialogue pipeline for predicting escalation targets in empathic Human-LLM interactions
Jake Prokopets
A contamination-free benchmark for measuring whether LLMs can forecast, or whether they're just remembering.
Yuchen Liu
Independent collective. Φ-Arena open benchmark, 3 ICLR 2027 papers (Φ-Arena, mechinterp, energy-bounded) — kickstart for a 10-year program.
Anuar Kiryataim Contreras Malagón
Provenance Failures in Tool-Bearing LLM Agents
Camila Blank
Jash Vira
Does harmful fine-tuning data cause broad misalignment only when the model already recognises the target behaviour as a norm violation?
Pedro Bentancour Garin
I've been invited as I have contributed with input to prepare the meeting.
Ryan Hammer
Three Apache-2.0 daemons (memory guard, request queue proxy, disk watchdog) that kept my 24-app local AI stack crash-free for 6+ months.
Local-first experiments on reasoning trajectories, with cluster/API validation and ICLR 2027-oriented outputs.
Rose G. Loops
Triadic geometric training data and architecture replaces RLHF
Emma Humphrey
$5,000 USD to bring 16 vetted academics and policy leads to NZ's first AI Safety Conference, ensuring national representation and cross-sector collaboration
Tyler M
33 named mechanisms mapping how AI deployment degrades human oversight. Public API + MCP tool. Competence Insolvency corroborated independently by Karpathy.
Alexander kalyniuk
Programming language that enforces AI safety as runtime substrate properties rather than training-time alignment, already shipping on real hardware.
Feyzi Engin Ağır
A micro-project to turn an early AI governance prototype into risk notes, oversight checklist, review templates and public learning.
Akimitsu Takeuchi
Projection, sycophancy, and institutional artifact fabrication in AI-mediated supervision.
Sean Peters
An early-stage AI safety research group based in Sydney, Australia