GPT-4

Evidence in the last complete seven days

Source mentions

1

Previous seven days 0

Distinct sources

1

Previous 0

Comparable growth

Not comparable

Ranking appearances

0

Collection observations and undated records are separate from dated publication counts. Observed in 7d：1 · Undated records：0

Daily history · up to 90 days

Bars show dated source mentions. The latest UTC day may be incomplete. Zero mentions and missing collection coverage are different conditions.

Dotted markers indicate days with no record. They are not counted as zero mentions.

Source evidence

Sources in the evidence shown：Hacker News 1 · arXiv 1 · Ask HN 1

1. Hacker News · Published Nov 4, 2026

   Ask HN: How to Keep the Edge as an Engineer?

   Hi, for the past few months I've been thinking a lot about my work as a software engineer and how I'll be able to provide benefits to companies I work for in the coming years, given the fast pace of progress of LLMs Every time I think I found an edge that will help me stay I relevant, AIs seem to get really good at it in a few weeks/months. I'll give a few e

   View source record →

2. arXiv · Published Oct 20, 2026

   Translating in style: An open-weight alternative to GPT-4 for culturally aligned machine translation

   View source record →

3. Ask HN · Published Jul 4, 2024

   Ask HN: Algorithm for searching text with similar meaning

   For example, I have a long text that says, "I have to change the screw number 1234," and a short one that says, "screw number 1234 changed." Both were inserted by different people, referring to the same thing. I thought of using an LLM (GPT-4), however, my dataset is too large (millions of entries) and it would be expensive. Is there any

   View source record →

Review priority 38 / 100

This score orders research candidates. It is not search volume, a forecast or verified commercial demand.

• Evidence

  8 / 30

  Distinct dated articles or first observations; repeat crawling adds nothing.

• Publisher diversity

  8 / 25

  Conservative owner grouping; syndicated copies count once.

• Comparable change

  0 / 20

  Comparable complete weeks only; no percentage from a zero baseline.

• Recent evidence

  14.7 / 15

  Latest publication or first observation, not repeated fetch time.

• Name specificity

  7.2 / 10

  Explicit entities and technical concepts outrank ambiguous acronyms.

Limitations and interpretation

• First observation is a collection milestone, not proof that a word or product is new to the world.
• Counts describe monitored public sources, not the whole web or search demand.
• First observed here is not the invention date of a name or idea.
• Candidates come from public titles, summaries and entity URLs, not verified full-text analysis.
• Owner grouping is conservative; undisclosed syndication may remain.
• Both weeks need adequate, comparable collection coverage.
• Sources behind this term changed or lack a comparable baseline.
• The previous week is too small for a reliable percentage change.
• Current evidence comes from one publisher or owner.