Just launched Header!
Over the last few months I’ve been obsessed with one problem: there’s so much great content to learn from… but never enough time. Everything is a 3-hour podcast, a massive newsletter, or a firehose of links that ends with 20 tabs open
Header is an AI-native learning platform for people who don’t have infinite time. I know that sounds cheesy, but bear with me
With Header, you:
1. Set a specific goal (or a bunch of goals)
2. Connect your favorite sources (YouTube channels, RSS feeds, blogs, subreddits, even paid email newsletters)
3. Let Header generate briefings instead of feeds, so you only see content that actually helps you make progress on your goals
👉 Watch our demo below or browse live public topics at https://t.co/1s5jFkvAoV (no signup required)
For folks applying to PhD programs:
I keep hearing a myth that students need to have a 1st author paper to get into a PhD program. This is definitely not true in psychology--most of the students we admit at NYU and most of the students from my own lab who have gotten into other PhD programs do not have any publications, let alone 1st author publications.
Yes, publications can help but they are not necessary and I suspect that they are actually pretty rare. If you want to build a publication record, I recommend doing an ambitious honors project, working for a lab for many years, or working as a lab manager.
Here are 10 tips to help you succeed when applying to PhD programs: https://t.co/ykn5DzSI6Z
I was ecstatic to publish my first paper in @CognitionJourn. This paper is now preceded by an *inaccurate* AI-generated Q&A.
@ElsevierConnect, stop this. You know LLMs hallucinate. You know we spend years crafting our papers to be maximally accurate. This is an insult.
At the same time, I'm having a hard time imagining people end up in those positions without experience in applying them to some sort of research project
Almost every 'researcher' position I see on LinkedIn requires experience with machine learning workflows-- do phd's in industry positions typically learn these through outside/side projects, or is it part of their research to begin with?
it just seems that there are many industry PhD's so it seems unlikely that everybody was doing data-science or ML heavy research projects throughout their graduate career.
My last "first day of school": I dropped peanut butter toast on my pants and went to my first meeting with my shirt inside out already! Channeling my inner kindergartener for starting the final year of grad school 😅
@lcdlab_uw takes #ICIS2024 ! Ishaan is presenting at Poster Session 1, and Carol and I are presenting at Poster Session 2! Come and chat to us about spatial cognition, learning, and memory!
It seems ive struck a nerve here. I have more to learn. I apologize for assuming that some of the most highly trained and educated people in the world earn more than $70k USD to perform labor that would cost almost double in any other line of work