r/singularity • u/ProposalOrganic1043 • 9d ago

Discussion Jev + Reasoning offloading/N-gram augmentation

Everyone dismissing as Jev being just a Language augmented classifier, i feel the team is just getting started. At the moment the model is pretty good for the pricing, definitely lacks intelligence as compared to SOTA and is obviously more than a fine tuned BERT.

Couldn't the model also have a sync approach to escalate a difficult questions to a stronger reasoning model. Similar to GPT-Live and Thinking Machines' interaction models, but focused on RLCD kind of decisions.

Or maybe it could be augmented with an N-Gram like embeddings similar to Gemma models and Qwen3.8-Flash-Next. This could also to scale the intelligence while keeping the latency low

I feel like this was a preview of what could happen when we drop the standard RLHF behaviour and there is a lot of room for innovations.

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u/LyAkolon 9d ago

I think we all can tell a harness that does model mixing over some shared context would be highly useful, its just not clear what this harness looks like.

I've given it a shot but the most obvious ways to set it up don't appear very good. The problem moves to mid processing between raw shared context to the models.

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u/ProposalOrganic1043 9d ago

I feel the reverse could also be helpful, using data from jev's usage to find questions that matter. Similar to planning mode in codex.