@mitsuhiko great post. i think it would be also good if i could take a conversation with chatgpt pro via the web ui and continue that in a coding agent like pi. and have a way to build a centralized repo of all my interactions with any agent.
@samuelcolvin % cat .codex/rules/default.rules
prefix_rule( pattern = ["python"], decision = "forbidden", justification = "Do not run ad hoc Python scripts in this repository.", ) prefix_rule( pattern = ["python3"]
...
a week ago @SemiAnalysis_ wrote that Chinese labs are "simply too compute poor to truly reach the frontier." today one of those "too compute poor" labs, a 300-person startup actually, shipped a model that compares to opus 4.8
the entire western consensus – export controls, the $650B hyperscaler capex race, the "compute moat" investment thesis – is built on one assumption: flops gate capability. if that were true, chip controls would keep chinese labs permanently behind the frontier.
but after reading through moonshot's stack i no longer think it is. training is efficiency-compressible: MoE routing, INT4-native quantization, better data curation, infra built around scarcity (their Mooncake stack exists because they don't have gpus!). a small lab with taste can compress the compute needed to make a frontier model, even if it can't afford to serve one
the frontier is no longer something money can buy
Falls sich jemand fragt, wie Parlamentspräsidentin Metsola auf die fixe Idee gekommen sein könnte, die Chatkontrolle für heute, 12 Uhr, (rechtswidrig) noch einmal auf die Tagesordnung zu setzen - hier ein paar Schnappschüsse von ihrer Kalifornienreise Ende Mai... Smiley!
Im Bild: US-Tech-Bros Zuckerberg, Tüp von Google, Tim Cook, Roberta Metaxa
Defensive code saves the creator some thinking and then causes pain for everybody else. My wish is that people who write defensive code instead just write no code at all. Do the work or spend your time doing something you actually like.
I had early access to this model and I'll post more Thursday, but I think the most impressive part is this model NEVER GIVES UP
If you throw it in Max reasoning, it will just keep working until it's done.
GPT 5.6 Sol is my favorite model BY FAR.