A product discussed on AI Engineer.

Training Frontier Models to Out-Think Hackers — Uri Rolls, Arithmetic & Thom Wolf, Hugging Face
Jul 24, 2026 · 17:28
Uri Rolls of Arithmetic and Thom Wolf of Hugging Face argue that frontier models can be trained to out-think hackers, not just pattern-match vulnerabilities, by focusing on logic leaps in access control. Their benchmark, Mask Off, builds blackbox environments from real zero days found by human researchers, testing whether models can chain reconnaissance into exploitation. A live example: a Keycloak check validates admin by name while another checks by ID, so renaming oneself to the admin inherits privilege—GPT-5.5 and Opus probe everything but never make that logical leap. Results are brutal: only one solve at K1, with GPT-5.5 alone succeeding at K5. Rolls and Wolf argue this mirrors ARC-AGI’s challenge—models struggle to build dynamic world models—and that high-quality data and open source models can shift the economics of cyber defense, giving defenders a lasting speed advantage.

OpenClaw in Your Hand: Building a Physical AI Terminal - Lech Kalinowski, Callstack
Jun 28, 2026 · 24:36
Lech Kalinowski presents Vault, a dual-display handheld AI terminal built on an ESP32-S3 that runs a local LLM and OpenClaw agents without cloud reliance. The device pairs a fast OLED live surface with a bistable e-paper content display, offering four modes — shell, assist, control, and an LLM-native RPG — all powered by a single lithium-polymer cell. The backend serves GPT-oss 120b via NVIDIA TensorRT-LLM, keeping inference off the microcontroller. Kalinowski shares engineering war stories: blown OLEDs from unstable power supplies, software I2C issues, and noisy encoders. The RPG mode generates four worlds with NPCs and narrative state tracked by the LLM, not dice or HP. Built in three months with 130 commits, the terminal is intentionally distraction-free, targeting quiet spaces where users want text-first AI interaction.
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