Show HN: Academa – Long-form STEM lecture videos generated by LLMs (academa.ai)
Hi HN, we are Sina Atalay and Abdullah Geduk, co-founders of Academa. We are both PhD students.
We thought: what if lecture videos were written as code and compiled into video using computer graphics and TTS?
Then LLMs could write them, and lectures could be fixed with code edits instead of video production.
On correctness: LLMs may make mistakes. But these videos are code sitting in our repository, and we can maintain them. Every report and review becomes a fix in the source, and everyone who watches after that gets the corrected lecture. Every recorded lecture on the internet is stuck with its mistakes. Ours will continuously improve.
Each video also comes with an AI chat that understands everything said and shown in the lecture.
There is a longer write-up at the bottom of the page.
Happy to answer any questions.
24 comments
[ 0.28 ms ] story [ 33.4 ms ] threadModels change. Models are unpredictable. The assumption that we can constrain them between prompt bumpers has not been proven and seems unlikely to be provable given how these model works.
Beyond that, how do you know if the reports and reviews are even correct? Are you just gonna rely on the kindness of others to provide that value? Of all things that LLM’s have killed, I’m pretty sure the open sharing of knowledge and understanding are the first on the chopping block. I don’t care whether or not you’re pro or anti LLM, publishing knowledge for reputation is now a dead end for anyone wanting to make a living.
Wrapping others’ knowledge in a black box that may or may not accurately represent that knowledge is basically enshitification on steroids. The reason we hold folks like Lovelace, Sagan, or Feynman in high regard is because they weren’t wrong when they shared their understanding and knowledge.
But the best of luck to everyone involved! I’m sure everything will work out!
You wrote it well. This aspect irks me, too.
That's such an excellent argument against letting humans teach other humans! You should start a petition.
I'm curious, what are the economics of producing this longer form content?
Actually, the economics are quite good.
We’re not using video generation models. We ask an LLM to write the lecture as code, then render it deterministically with computer graphics and TTS.
So the main costs are the LLM call, TTS, and some cloud GPU time for rendering. That ends up being much cheaper than generating long form video directly with video models.
Just assign years worth of reading homework every week, and I am sure all the students will fullfill their assignments of reading every token that went into each video, no matter how many, rather than watch an LLM generated video.
Students simply need to learn how to read text as fast as an LLM can, and have an enormous token budget to use the LLMs directly themselves.
And while you're at it, increase their tuition by the amount those tokens cost, so each student can pay for feeding the same tokens in to their own LLM instead the school doing it once and paying out of their own pocket immediately. Because the idea of schools producing reusable courseware is unprecidented! That way they can fold the token cost into their student loans.
Also, you’re not chatting with the transcript; you’re chatting with the video. The AI has much more than the transcript in its context. See this, for example: https://academa.ai/lectures/diffusion-models-learning-to-den...
And in the coming months, we’ll make the answers themselves real-time videos, which is kind of trivial for us at this point. We’ll ask the LLM to answer by writing code, and our software will render that code and show you the response directly as a video.
I've rarely, if ever, seen this. And if I had, I think most of the class would have just been annoyed, which you probably didn't notice.
Universities have made the mistake of competing with YouTube (video lectures), whereas what they can actually offer is direct access to domain experts.
I am skeptical that any other solution has much of a moat. So if the creators of this are after any feedback, I would offer that their best bet is to be competitive on User Experience, rather than underlying technology.
The future of humanity is dire if this is what's round the corner.
Thanks for making everything worse, you soulless bastards.
It suddenly starts talking about URLs, but it never really sets up the idea that we're using some kind of URL lookup service as an example. The way it introduces the memory limit feels similarly strange. At some point, it just says that we have 8GB of memory, but it does that halfway through the explanation, not as part of the setup of the problem we're actually solving.
The idea of using LLMs to write out a script and storyboard for the video is interesting, but I think it needs intermediary work to better instruct the speech and graphics on how to perform.