← Jev

What podcasts say about Jev

Every statement, with the speaker, the exact quote and the moment it was said.

What experts have said about Jev

21 statements · 16 positive · 3 negative · 2 neutral

  1. Jev is currently among the most talked-about AI models.

    “Jev is one of the buzziest models we've had in a long time”

    Listen at 0:00

    Open the episode · How People Are Actually Using Jev
  2. Jev is fundamentally different from conventional large language models.

    “It is something fundamentally different.”

    Listen at 0:09

    Open the episode · How People Are Actually Using Jev
  3. Users are finding many use cases that exploit Jev’s distinctive capabilities.

    “people are discovering and sharing a slew of different use cases that take advantage of what makes Jev unique”

    Listen at 0:20

    Open the episode · How People Are Actually Using Jev
  4. Jev can select the best-fitting option from up to 255 choices.

    “Jev can find the best fit.”

    Listen at 3:31

    Open the episode · How People Are Actually Using Jev
  5. Jev can place an item on a user-defined rating scale.

    “Jev can answer where something falls.”

    Listen at 3:52

    Open the episode · How People Are Actually Using Jev
  6. Jev can classify whether a stated proposition is true or false probabilistically.

    “it simply answers, is this true?”

    Listen at 4:09

    Open the episode · How People Are Actually Using Jev
  7. Jev performs its limited classification tasks extremely quickly.

    “it can do it incredibly fast”

    Listen at 5:02

    Open the episode · How People Are Actually Using Jev
  8. Jev cannot write code, draft contracts, or make nuanced non-quantifiable decisions.

    “It's not gonna write code, it's not gonna draft contracts, and it's not gonna make nuanced decisions that involve a variety of factors that aren't quantifiable and clear.”

    Listen at 6:42

    Open the episode · How People Are Actually Using Jev
  9. Jev is suited to high-volume, small-scale judgments.

    “It's going to be used for small judgments at volume.”

    Listen at 6:49

    Open the episode · How People Are Actually Using Jev
  10. Jev can perform semantic matching despite differing wording.

    “it can find what you mean even when the words don't match”

    Listen at 9:54

    Open the episode · How People Are Actually Using Jev
  11. Jev detected six planted writing mistakes faster than Claude Fable 5.1.

    “Jev, however, caught its 6 in 0.35 seconds as compared to 8.83 seconds for Fable 5.1.”

    Listen at 18:09

    Open the episode · How People Are Actually Using Jev
  12. Jev performed the writing check at approximately 580 times lower cost than Fable 5.1.

    “it did so at about 580 times cheaper”

    Listen at 18:15

    Open the episode · How People Are Actually Using Jev
  13. Jev is probably unsuitable for tasks requiring sentences or calculations as answers.

    “If the answer is a sentence or a calculation, that's probably not a good fit for JEV's sort of judgment model.”

    Listen at 23:18

    Open the episode · How People Are Actually Using Jev
  14. Jev should not be used alone when classification errors have serious consequences.

    “you don't want to leave things up to its judgment alone if getting it wrong has big consequences”

    Listen at 23:39

    Open the episode · How People Are Actually Using Jev
  15. Jev progressed rapidly from an exciting concept to valuable production use cases.

    “we've gone from buzzy exciting concept to actually valuable production use cases extremely quickly”

    Listen at 25:12

    Open the episode · How People Are Actually Using Jev
  16. It will take time to determine how broadly Jev can be integrated into applications.

    “I think it's going to take some time for us to really figure out just how deeply we can weave this into all sorts of different use cases.”

    Listen at 25:27

    Open the episode · How People Are Actually Using Jev
  17. Typesafe’s Jev produces probabilities for specific questions rather than long-form text.

    “these judgment models like the one we're discussing today, Jev from Typesafe, produce probabilities around specific questions”

    Listen at 0:18

    Open the episode · Why a New Class of AI “Judgment Models” Could Have Big Business Implications
  18. Typesafe claims Jev is 20–200 times faster and 40–400 times cheaper than alternatives.

    “Jev is 20 to 200 times faster, 40 to 400 times cheaper with output tokens free, frontier composable intelligence optimized for decisions”

    Listen at 12:52

    Open the episode · Why a New Class of AI “Judgment Models” Could Have Big Business Implications
  19. Jev processed 37 documents and 777 judgments in under 0.7 seconds for about $0.0025.

    “In less than 0.7 seconds, Mike said, Jev quote unquote read all 37 documents and answered all 21 questions for each. Returning 777 judgments for an estimated quarter of a cent.”

    Listen at 19:18

    Open the episode · Why a New Class of AI “Judgment Models” Could Have Big Business Implications
  20. Jev could function like a code linter for knowledge work.

    “it could act as a kind of code linter for knowledge work”

    Listen at 19:57

    Open the episode · Why a New Class of AI “Judgment Models” Could Have Big Business Implications
  21. Jev can apply conditional workflow logic to messy human context.

    “Jev is basically asking, what if those if statements could understand messy human context?”

    Listen at 20:16

    Open the episode · Why a New Class of AI “Judgment Models” Could Have Big Business Implications

Statements are attributed to the speaker as said on the episode and reflect their view at the time, not PodLume's. They are not advice.

Jev: what podcasts say · PodLume