at least 8 months
now we wait
my guess is that it will take ~12 months for open source to catch up to Mythos, not 4
Mythos reportedly found a 27-year-old zero-day bug in OpenBSD.
at least 8 months
now we wait
my guess is that it will take ~12 months for open source to catch up to Mythos, not 4
Positive users bet on open-source AI matching Anthropic Mythos in 3 months due to rapid progress hopes, while negative users fear it may never happen or call such views cope.
8 months, Q1 2027 the bigger problem is that Mythos itself is a last generation pretrain, and by then Anthropic will likely have completed something vastly more capable, so the real gap will only increase, towards Dario's targeted 24 months.
now we wait
my guess is that it will take ~12 months for open source to catch up to Mythos, not 4
at most 18 months
if they don't have a mythos by then something went seriously wrong
now we wait
my guess is that it will take ~12 months for open source to catch up to Mythos, not 4

@teortaxesTex OpenAI will be the first indicator. There's a lot of cope going around but if they can't demonstrate a Fable/Mythos class model even with a 2x lead in hardware capacity then it's over.

@teortaxesTex My strategy plan. .
🔻↩️↩️

@teortaxesTex I genuinely wish Deepseek/Kimi/GLM catch up with Fable. But I'm scared it'll take a very long time or it might never happen.

@teortaxesTex are you sure? i would have thought with the whole Trainium + amazon deal that they would have been able to stand up the compute a bit faster

@teortaxesTex I'll place my bet at 3 months

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@teortaxesTex Anthropic ships last-gen. The market ships papers. Six months behind your own labs is eighteen months ahead of what's deployed. That's the whole gap.

@scaling01 3
Mythos reportedly found a 27-year-old zero-day bug in OpenBSD.
at least 8 months
now we wait
my guess is that it will take ~12 months for open source to catch up to Mythos, not 4