An engineering and math graduate asks how to maximize impact, weighing a career in robotics research against founding low-sophistication hard-tech startups. They lean toward startups, arguing that academic research positions are capacity-constrained and their marginal impact there would be near zero, whereas a startup could at least potentially create some impact.
Background
- The poster is an engineering/math grad choosing between academic robotics research (on "zero-shot learning" — AI that handles tasks without being trained on them) and founding simple hardware startups that can be prototyped in a makerspace.<br>- "Counterfactual impact" comes from effective altruism: you measure your personal contribution by asking what would happen without you. The poster thinks academia is "capacity-constrained" — if they don't take a research position, someone equally capable will, so their marginal impact is near zero. A founder, by contrast, may create something that wouldn't otherwise exist.<br>- This tradeoff is debated in tech-adjacent EA/rationalist circles: prestigious research may have low personal leverage compared to entrepreneurship, even if the startup involves less sophisticated tech.
Max Weinbach says he had early access to OpenAI's new model GPT-5.6 Sol, calling it his favorite model by far. He highlights that it never gives up and will keep reasoning until it's done. OpenAI announced that GPT-5.6 Sol, along with Terra and Luna, will launch publicly on Thursday, with preview access expanding globally now.
The US government ordered Anthropic to suspend access to its Fable 5 and Mythos 5 models for all customers, citing a potential jailbreak technique that involved asking the model to review a codebase for vulnerabilities—a capability Anthropic says is available in other public models. Access was abruptly cut off on June 12.
Andrej Karpathy announces the release of Claude Fable 5, the same underlying model as Mythos but with added safeguards. He calls it a major step forward, particularly for long problem-solving sessions on difficult tasks, and describes it as state-of-the-art on nearly all benchmarks with exceptional performance in software engineering, research, and vision.
Roman Storm warns that the legal theory in his case could set a precedent making open-source developers liable for how others use their code, potentially criminalizing the mere publication of privacy, messaging, or crypto tools. He notes that developer Michael Lewellen cannot publish lawful code due to prosecution fears, and argues this chilling effect extends beyond any single case.
Meta's engineering culture is deteriorating under Mark Zuckerberg and Scale AI CEO Alexandr Wang, who have introduced keyboard tracking, reassignments to data labeling, and AI-centric performance metrics. Critics argue this incentivizes performative AI use, drives away experienced engineers, and contributed to a major Instagram hijacking incident caused by AI-written and AI-reviewed code.