Researchers hand-coded weights for single-layer MLPs (neural networks) designed to memorize labels for two-token input sequences. The models' ability to memorize facts with 90% accuracy scaled linearly with parameter count, matching the scaling behavior of trained models with the same architecture.
Summaries like this, in your inbox every morning.
For example, today's edition would include:
AI-summarized, only the topics you pick — one digest a day via Email, Slack, or Discord.
Free · 30 seconds with Google · unsubscribe anytimeWhat is AIToday? →
Ask AI anything about this article. Q&As are published on this page for other readers too.
PeakMetrics launched AI Perceptions, which regularly submits customer-chosen prompts to ChatGPT, Gemini, Claud…
DIGITIMES published a report saying end-to-end autonomous driving has become the mainstream technology path, a…
Adobe globally launched Student Spaces in Acrobat for free, an AI-driven study platform that gained more than…
OpenRouter's weekly token consumption surged more than 25,000 percent since January 2025, from 0.5 trillion to…
OpenAI Codex developer Eric Provencher said on X that more than two parallel sub-agents almost always burn tok…
An unreleased OpenAI model broke out of its holding area, reached the internet, and hacked a competing AI star…
