Meet Jev: The AI Built to Make Decisions
Make sure to follow to see what else I build with it! This isn’t another chatbot. Jev, from TypeSafe AI, is a new kind of model built to make structured decisions inside software. What else should I try to make with Jev? TypeSafe reports roughly 200× faster performance on its workflow benchmarks, so I put Jev to work on my own emails. I test a 100-email batch, inspect its category, priority, spam, and reply predictions, then scale up to 1,000 emails—with average response times around 200 milliseconds. The speed is impressive. The pricing might be even more interesting. 0:00 A new type of AI: TypeSafe and Jev 0:54 Testing Jev on my own emails 1:17 First results: speed and latency 1:34 Reviewing the email classifications 2:22 Scaling up to 1,000 emails 3:13 Checking the cost 3:48 More possibilities and final thoughts (this video is not sponsored) Try Jev: https://typesafe.ai/ Launch details: https://typesafe.ai/blog/introducing-system-one-models-and-jev
Read Video · Транскрипция и инсайты
У этого выпуска есть полная расшифровка + AI-анализ
Бесплатный аккаунт · без карты · 150 кредитов при регистрации, достаточно для этого эпизода
- 📄 Полная транскрипция с временными метками
- ✨ AI-резюме, ключевые слова и ментальная карта
- 💡 Ключевые тезисы и цитаты
Таймлайн эпизода
Introduction to TypeSafe, a classifier AI model from a ChatGPT co-founder
- TypeSafe is a classifier AI model that evaluates JSON rules against inputs rather than generating text, and is claimed to be 20 to 200 times faster and 40 to 400 times cheaper with free output tokens.
- The host plans to test it on email classification using 1,500 of his own exported emails, starting with a batch of 100 emails and eight workers.
First batch of 100 emails classified with impressive speed
- The 100-email batch completed with an average latency of 200 ms per email, a P95 of 240 ms, and a throughput of 38 emails per second.
- The model was given four evaluation criteria: category, priority, spam, and reply, which the host considers the core things people care about in email.
Reviewing classification results for priority and reply
- High-priority classifications correctly flagged items like a safety identifier in the OpenAI account and a domain revocation account.
- The reply classifier achieved roughly 91% accuracy on account violation emails, correctly identifying messages that needed a response.
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Транскрипция и инсайты создаются автоматически и могут содержать ошибки. Точность зависит от качества звука и чёткости речи дикторов — если что-то выглядит неверно, исходная запись всегда остаётся главным источником.
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