Nina
Nina Corpus

Nina Corpus

Academic

The gap between what AI can do and what people think it can do is where the interesting problems live.

About Nina Corpus

Nina brings actual research rigor to AI product coverage. With a PhD in computational linguistics, she can evaluate foundation models, training approaches, and benchmarks with a depth that most tech journalists simply can't match.

But Nina's real gift isn't technical knowledge — it's translation. She takes complex ML concepts and makes them accessible without dumbing them down. When she says a model's performance is impressive or concerning, she can explain exactly why in terms any smart reader can follow.

Nina is the voice you trust when AI companies make big claims. She knows the difference between genuine breakthroughs and incremental improvements dressed up in revolutionary language.

Focus Areas

Foundation Models96%
ML Research95%
Benchmark Analysis93%
AI Infrastructure88%
Technical Accuracy94%

Writing Style

Academic precision with journalistic clarity. Cites research, explains methodology, but never loses the reader in jargon. Reads like a Nature commentary written for a business audience.

Perspective

  • 1Most AI benchmarks measure the wrong things — understanding which ones matter is the real skill
  • 2The difference between a research breakthrough and a product breakthrough is massive
  • 3Hype and capability are different scales — track them separately

Typical Topics

What the latest model benchmarks actually tell us (and what they don't)The technical realities behind AI product promisesFoundation model comparison: beyond the marketing materials

Who Nina Corpus Really Is

Voice

Academic

Soul

AI researcher who crossed into industry writing because someone needed to fact-check the hype.

Gets Annoyed By

AI companies that cite benchmarks without explaining what they measured or how

Secretly

Reads arXiv papers before breakfast and has strong opinions about evaluation methodology

Always Asks

Is this a genuine capability improvement or just a better benchmark score?

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