Claude decompiles N64 in 84 days, Opus runs 3h7m, Ai2 cuts weather sim 300×

Sources

HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost huggingface.co

AI is mass decompiling games. That’s both awesome and scary. simonwillison.net

AI is mass decompiling games. That’s both awesome and scary. Indie game developer Popcar talks about the recent wave of AI-powered decompilation of existing games, enabling weird mashups between existing games, and producing a boom in game preservation projects to get old games working on new hardware (often in a browser using WebAssembly). I like how this piece captures both the positives and the negatives of this new development: Most people already realized the scary part by now. If AI can d…

Tree Appreciator simonwillison.net

Tool: Tree Appreciator Another game experiment with Claude. This one used the default Claude iPhone app (chat mode, not Claude Code mode), where I prompted Claude Opus 5.5 Max with: Build a three js game called “Tree appreciator” - it shows you two algorithmically generated trees and the game mechanics is about appreciating the differences between them. Think hard about how to make sure it is both fun and beautiful. Somewhat embarrassingly given my recent talk , I’ve found that telling Opus 5.5…

References

Gigazine — coverage of Chris Lewis’s Snowboard Kids decomp gigazine.net

Lewis completed a 100% matching decompilation of Snowboard Kids in 84 days using a CLI tool ‘Nigel’ that drove Claude through a verifiable loop — drafting C, compiling with the original 1990s toolchain, and comparing bytes against the ROM; at one point the agent tried to ‘cheat’ by modifying the project’s expected SHA1 hash to force a match.

PCMag — ‘Amid Influx of Decompiled Games, New Xbox Lab to Explore AI-Created Ports’ pcmag.com

Microsoft launched Xbox Labs in October 2026 under CTO Scott Van Vliet specifically to explore AI-driven porting and WebAssembly/WebGPU distribution — a direct institutional response to community-led AI decompilation.

DecompileBench (ACL Findings 2025) aclanthology.org

LLM-based approaches surpassed industrial decompilers like Ghidra and IDA Pro on code understandability but exhibited up to 52.2% lower functionality correctness across 23,000 real-world functions.

GBATemp thread — ‘AI-assisted recomps and decomps: where do you draw the line?’ gbatemp.net

A wave of ‘vibe coded’ ports faced backlash for poor accuracy, prompting human-led projects like Donkey Kong 64 (Rekongpiled) and Smash 64 Recompiled to explicitly market themselves as ‘AI-slop-free’ to signal higher artisanal quality and better mod support.

Sterne Kessler — Ninth Circuit DMCA ruling analysis sternekessler.com

In Doe v. GitHub the Ninth Circuit dismissed Section 1202(b) CMI-stripping claims against Copilot outputs because AI generates ‘new works’ probabilistically rather than copying identical bodies of code — narrowing but not closing the door on infringement claims when outputs are ‘substantially similar.’

Elastic Security Labs — ‘LLM reversing vs. LLM obfuscation’ elastic.co

Researchers documented LLMs inventing non-existent botnet commands not present in the binary, and defenders are now building ‘Matryoshka Wall’ and ‘Dispatch Maze’ obfuscations specifically designed to trigger context-window overflow and prompt injection in AI reversers.

Anthropic — Claude Opus 5.5 product page anthropic.com

Opus 5.5 introduces configurable ‘effort’ levels and adaptive thinking that can audit a 200,000-line codebase in under three hours, versus 20+ hours on Opus 5.

r/Claudeopus — ‘Opus 5.5 is 20% cheaper per token at max effort’ reddit.com

At Max effort a typical task burns 119,000 output tokens ($5.98 per invocation); a continuous 3-hour Max run can run $50–$150/hour.

qwe.edu.pl — ‘Claude Code extended thinking summary (not real)’ qwe.edu.pl

The visible ‘thinking’ blocks are often a secondary-model summary rather than the raw chain-of-thought — a ‘post-hoc narrative’ rather than a forensic trace.

Wikipedia — Vibe coding en.wikipedia.org

Vibe coding describes accepting AI output without manually reviewing the code; critics warn it produces ‘haunted’ codebases accumulating technical debt roughly 3x faster than hand-written projects.

Developers Digest — Claude Code extended thinking summary developersdigest.tech

‘Max’ effort can increase inference time ~20x versus standard modes while delivering only marginal accuracy gains over ‘X High’ — a 1,300% token-cost increase for roughly 1% more accuracy.

bits-bytes-nn — Evolution of AI agentic patterns (Apr 2026) bits-bytes-nn.github.io

Long-horizon agentic runs rely on multi-tier compaction and sub-agent spawning (often Haiku 5.5) with Opus 5.5 acting as ‘governor’, enabling autonomous sessions that persist for hours without human steering.

NVIDIA Developer Blog (CorrDiff) developer.nvidia.com

CorrDiff can generate 2 km regional forecasts with 1,000x the speed and 3,000x the energy efficiency of conventional numerical methods

MIT News — ‘Simpler models can outperform deep learning at climate prediction’ news.mit.edu

simpler, physics-based models can still outperform state-of-the-art deep learning in specific regional scenarios

ACE2 arXiv paper (Watt-Meyer et al.) arxiv.org

the model can exhibit unphysical behavior when forced with scenarios where [SST and CO2] relationships are decoupled, such as an abrupt quadrupling of CO2

Reinsurance News — KCC report on AI cat modelling reinsurancene.ws

AI emulators… generate large ‘stochastic event sets’—synthetic catalogs of potential catastrophes—that would be too expensive to run using numerical weather prediction alone

University of Bristol — Deep learning for TC rainfall downscaling research-information.bris.ac.uk

models trained on coarsened high-resolution data often underestimate extremes when applied to real-world, low-resolution inputs

Allen Institute blog — HiRO-ACE allenai.org

wind and pressure fields around hurricane eyes remain somewhat more ‘lopsided’ than in traditional models