AI Research on SoloSoft

AutoResearch: Karpathy's AI-Powered Research Assistant

Fri, 01 May 2026 00:00:00 +0000

The scientific research process is notoriously labor-intensive, with literature review, experiment design, and validation consuming months of effort before any novel contribution emerges. AutoResearch (karpathy/autoresearch on GitHub) is Andrej Karpathy’s vision for accelerating this process through an AI-powered research assistant that can autonomously read papers, perform computational experiments, and generate actionable research insights.

Created by one of the most influential figures in modern AI, AutoResearch reflects Karpathy’s deep understanding of both the research process and the capabilities of modern language models. The system operates as an autonomous loop: it reads papers in a specified domain, identifies gaps or open questions, designs experiments to address them, writes and executes code, analyzes the results, and synthesizes findings into coherent research narratives.

Beyond LLMs: AMI Labs' $1B Bet on World Models

Mon, 01 Jan 0001 00:00:00 +0000

When Yann LeCun — Turing Award winner, co-inventor of convolutional neural networks, and one of the most influential researchers in the history of AI — bets $1.03 billion against the dominant paradigm of the field he helped build, it is worth paying close attention. On March 10, 2026, AMI Labs officially launched with the largest seed round ever raised by a European startup, and a founding thesis that directly challenges the assumption powering every major AI lab in Silicon Valley: that large language models are the path to general intelligence.

LeCun disagrees. He has said so publicly, repeatedly, and with increasing specificity. His argument is not that LLMs are useless — they have proven remarkably capable for language tasks — but that they are the wrong architecture for AI that needs to reason about and operate in the physical world. Text prediction, no matter how sophisticated, does not teach an AI how objects fall, how fluids behave, or how a robot should move through uncertain terrain.

OpenAI Executive Exits 2026: What Weil and Key Departures Signal

Mon, 01 Jan 0001 00:00:00 +0000

Why is this personnel earthquake more alarming than previous ones?

Because this is not merely personal career choices, but a systematic strategic pivot. OpenAI is dismantling two key exploratory pillars: scientific research projectization (OpenAI for Science) and consumer-grade application experiments (Sora). This means the company acknowledges that at the current stage, the risks of dispersing resources to explore diverse application scenarios outweigh the benefits. When a research institution with the mission of “ensuring artificial intelligence benefits all humanity” begins cutting its science department, we must ask: has the mission changed, or has the path to achieving it been forced to become more realistic?