NeurIPS 2025: Biology’s Transformer Moment - Genetic Engineering and Biotechnology News
<a href="https://news.google.com/rss/articles/CBMioAFBVV95cUxQRnQ5WkJfdHlqdzBoY3hRX25yTE5hQkhITlNwSmJoaHFieU1ZYmtBenZiNEhMQVYyUDFWdWVKbENqU2xXeTEwaFZVMTduQUFZUkpaSWF6OGExbXo0d1hHVjVwUkhBTWxzVm53NUFwSXZFR1hFOXFNN1k0NGxzWVVMTm9fMEowdUN0ZklnR3cwQ01ibG1XRFpYTGJNd25URzc3?oc=5" target="_blank">NeurIPS 2025: Biology’s Transformer Moment</a> <font color="#6f6f6f">Genetic Engineering and Biotechnology News</font>
Could not retrieve the full article text.
Read on GNews AI transformer →Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
transformerneurips
Grokking Beyond Addition
Hi everyone, I’m excited to share my research paper: “Grokking Beyond Addition: Circuit-Level Analysis of Algebraic Learning in Transformers” Paper: https://zenodo.org/records/19256207 This work explores grokking across multiple algebraic structures and shows a clear result: At small model scale (d_model = 64), transformers reliably grok abelian tasks but fail to generalize on non-abelian groups , even with 100% training accuracy. It also highlights: Early circuit formation before generalization Evidence for discrete-log structure in multiplication Strong embedding similarity across different tasks (CKA) I’m opening this project for collaboration and contributions: Scaling experiments (d_model = 128 / 256) Extending to more algebraic structures Interpretability improvements Reproduction an
Any AI Agent Can Now Vibe Check LLM Outputs — No Code Required
Any AI Agent Can Now "Vibe Check" LLM Outputs — No Code Required Your AI agent just generated a customer email. It's grammatically perfect. The JSON is valid. But it accidentally threatened to cancel the customer's account instead of apologizing. No guardrail caught it because no guardrail was checking meaning . With Semantix v0.1.4 , any MCP-capable agent — Claude Desktop, Claude Code, Cursor, or your own — can validate text against semantic intents as a tool call. Zero code changes. Zero API keys. Runs locally. The Problem: Agents Don't Verify Their Own Output LLM agents are getting more autonomous. They write emails, generate reports, draft code reviews, and respond to customers. But they operate on a trust-based system: generate output, ship it, hope for the best. What if the agent cou
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!