covering AI news, working on @voxelbench
Joined October 2018
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Argon is out on VoxelBench
its performance is very uneven; sometimes producing clean and detailed builds, while also often making much less detailed and smaller builds
overall im underwhelmed, but I hope they recognize this gap and improve it fast
one similarity I found interesting (and annoying) between this model and Fable 5.0 is that they both prefer to make smaller builds
but unlike Fable, Argon made no effort to verify that the blocks it placed weren't overlapping or clipping into other blocks
on average, Argon spent 2 minutes per VoxelBench prompt; far below the average of models like Opus and Fable, and even Astra or Sol
Legit retweeted
Business Insider is reporting that Google is internally testing a new Gemini 4 checkpoint named Carbon that matches Opus 5.5 in coding.
Legit retweeted
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
Legit retweeted
anthropic is testing haiku 5.5 too
been using fable 5.5 for the last few days but noticed something weird
some outputs from fable 5.1 that knows tibo the reset guy were way worse than sonnet 5.5
but why would it give worse outputs?
so i can only think of one thing that team is routing some prompts to haiku 5.5 through fable 5.1 too and testing it that way
which makes me think we might see haiku 5.5 in next week or two
here's one weird output i got
just look at how different these outputs are even tho both were run on fable 5.1 xhigh that knows tibo the reset guy
Legit retweeted
Apparently, the same OpenAI models may get way more reasoning budget through the API than through Codex.
So even if you’re using OpenAI’s own Codex harness, you could still be getting a more constrained version of the model compared to someone just paying for the API directly.
For example, GPT-6 Astra is reportedly around 832 “juice” on Max via API, vs 128 through Codex.
(If this is true, and the measurements suggest it might be, then OpenAI is basically holding these models back on its own plans while API users get the real monsters.)
Legit retweeted
Google will launch an experimental AI satellite on Oct. 1 as part of Project Suncatcher, its effort to eventually build AI data centers in space.
The satellite will carry 4 $GOOGL TPUs and enough compute to answer simple Gemini queries from orbit while testing whether AI chips can reliably operate in space.
Google plans two more satellite launches in 2027 and is already designing potential fleets of 80+ satellites that could work together as an orbital AI data center.
Google estimates space-based data centers could become cost-competitive with terrestrial facilities by the mid-2030s.
Source: NYT
