Google's sign language model beat every previously reported score on the benchmark. Google wrote the benchmark.
The model is probably the real thing. The superlative was graded on a Google-built exam, and the 'on your phone' feature phones a server with every sentence you sign.
"Google DeepMind says SL2T is the most capable sign language translation model to date, scoring 70 BLEURT zero-shot on FLEURS-ASL, significantly higher than any previously reported score, and ships it as sign-to-text dictation in Gboard and Live Transcribe on Pixel 11" [SOURCE ↗]

Start with the genuinely good part: Pixel 11 owners who sign can now dictate into Gboard and Live Transcribe in ASL. Gloss-free translation trained on 100,000 hours across 50-plus sign languages is a real research result aimed at people software has ignored for decades.
Now the claim. 'Most capable sign language translation model to date' rests on FLEURS-ASL, where SL2T's 70 BLEURT is 'significantly higher than any previously reported score'. FLEURS-ASL was introduced by a Google researcher, and the paper that introduced it supplied the baselines it just beat. Google is valedictorian of a school it founded, in a class very few others attend.
And the phone feature is less on-the-phone than the framing suggests. By DeepMind's own blog, the on-device part is a pose tracker; the geometric coordinates of your signing are 'sent to the server for translation'. The video stays local. The content of everything you say does not.
Best-in-class is plausible. Measured-by-us, graded-on-our-benchmark, running-on-our-server is the context.
On August 12, Google DeepMind launched SL2T, a sign-language-to-text model, as a working feature: ASL dictation inside Gboard and Live Transcribe on the Pixel 11. The launch blog stakes the flag plainly: 'SL2T is the most capable sign language translation model to date according to key benchmarks li
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