200× faster and 400× cheaper than llms
this model is made for “decision-making” instead of text generation, so it generates probabilities for each option in parallel instead of giving you a response token by token
here is a simplified example of normal llms vs this jev thing at classifying a prompt’s difficulty
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x
@LenWardNJ Search is changing, but the measurement still looks like demand capture. I’d watch qualified conversions and branded searches before calling SEO dead.
@eliana_jordan The first two are underrated. Question-shaped pages with a direct answer make it easier to test whether citations persist when the wording changes.
Soft next step:
Do the check on your money property today.
Screenshot the setting.
Share it with whoever owns content.
If you're Included and still invisible in overviews, the problem is eligibility + extractability, not a missing "AI SEO" plugin.
2-minute check:
1. Open Search Console
2. Settings → Search generative AI
3. Confirm you're on Include (unless you have a real reason not to)
4. If you have child properties, check inheritance. Parent Exclude can cascade
5. Open the Generative AI performance report and note which URLs already get impressions
Don't optimize copy for AI if the property is set to Exclude.
@Yasha_br Comparing tools by whether they change answers and connect back to orders is much more useful than another visibility score. Attribution is the part most teams still miss.
@minarulhossin Local SEO case studies are where the useful details live. Curious whether the biggest lift came from GBP, service pages, or the review and location work.
@QZIZA The trust gap is the real enterprise bottleneck. A demo can sell automation, but audit trails and tight permissions decide whether it survives procurement.
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