Who's Who of AI

Stephen Turner

101 trust researcher @stephenturner.us · 9,193 followers
Associate Professor and Research Dean at UVA School of Data Science, #Rstats enthusiast, dad, runner, guitar noise-maker. Views my own. Web: https://datascience.virginia.edu/people/stephen-turner Newsletter: https://blog.stephenturner.us
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Articles & links

Interesting data and analysis behind NeurIPS's new AI policy blog.neurips.cc/2026/06/02/a...

AI-Generated Papers in the NeurIPS 2026 Position Paper Track – NeurIPS Blog blog.neurips.cc
AI Weekly's analysis →
  • NeurIPS desk-rejected 178 papers (18.4%) via Pangram; 123 more must prove human authorship by June 15, 2026.
  • Default Pangram window sizes flagged 42.7% of submissions; refined 100-word windows reduced that rate to 12.7%.
  • Comparison venues FAccT 2025 and NeurIPS E&D 2026 showed 0% and 2.1% maximum AI scores respectively.
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View on Bluesky · ♥ 0 ↻ 2 ↩ 0 · 7 from the directory shared this · 43d ago

isaiprofitable.com

Is AI Profitable Yet? isaiprofitable.com
AI Weekly's analysis →
  • The AI industry has spent roughly $1.4 trillion against $613 billion in revenue, leaving almost every major player still in the red.
  • Amazon leads all spenders at $313 billion invested; NVIDIA is the sole major AI player currently in the black, profiting from hardware.
  • The site's anonymous creator predicts clarity on AI viability by 2030 and notes Anthropic recently approached its first profitable quarter.
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View on Bluesky · ♥ 5 ↻ 0 ↩ 0 · 9 from the directory shared this · 44d ago

The diffusion of large language models in published academic articles www.pnas.org/doi/10.1073/...

pnas.org
View on Bluesky · ♥ 2 ↻ 0 ↩ 0 · 3 from the directory shared this · 42d ago

Claude Opus 4.8 - if this honesty thing is real that'd be nice www.anthropic.com/news/claude-...

Introducing Claude Opus 4.8 \ Anthropic anthropic.com
AI Weekly's analysis →
  • Opus 4.8 matches Opus 4.7 pricing at $5/$25/M tokens; Effort Modes replace pricing tiers as the cost-quality dial.
  • Dynamic Workflows impose hard ceilings: 1,000 total subagents, 16 concurrent; workflow plans live in JavaScript variables outside Claude's context window.
  • SWE-bench Pro score jumps from 64.3% (Opus 4.7) to 69.2% (Opus 4.8); the model flags its own code flaws 4x more often than its predecessor.
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View on Bluesky · ♥ 8 ↻ 0 ↩ 1 · 3 from the directory shared this · 49d ago
Their own posts

Recent commentary

Someone please define these terms for me. 1. AI literacy. 2. AI fluency. 3. AI governance. And don’t ask AI.

View on Bluesky · ♥ 4 ↻ 0 ↩ 5 · 21d ago

IANAL, but pretty sure if you publish a preprint under CC-BY, you're effectively telling the world, any AI company, qed, whoever: "here's my paper, you have my permission to do whatever you want to with it." Which includes AI training to create a derivative product and sell it back to you.

View on Bluesky · ♥ 3 ↻ 0 ↩ 3 · 17d ago

X/LinkedIn these days: Let's dive in and delve into the rich tapestry of your load-bearing claim—rather than merely accepting it—because fundamentally you're doing zero moves there, and the gap is what's actually interesting. It's worth noting: this is a paradigm-shifting, AI-driven opportunity 1/ 🧵

View on Bluesky · ♥ 4 ↻ 1 ↩ 1 · 43d ago

Breaking my AI Dry July to ask America's next top model, 5.6-Sol, a very important question that most people get obviously wrong despite all the available evidence. Sol gets it correct on the first try.

View on Bluesky · ♥ 2 ↻ 0 ↩ 2 · 6d ago

I'd like to see the Claude/ChatGPT histories of all these folks booing commencement speakers off stage 🤔

View on Bluesky · ♥ 3 ↻ 0 ↩ 0 · 55d ago
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