https://kevinventullo.com/
https://www.linkedin.com/in/kevinventullo/
- kevinventulloI thought charter schools and public schools received the same $/student.
- What’s funny is the jerky animation actually communicates so much more than the smooth animation.
- I attended high school in the US in the early 00’s and cell phones were absolutely banned from classrooms. You could keep them in your locker and use them between classes, but that was it.
I attended college in the late 00’s, and I don’t think I took a single digital exam. Quizzes, sure, but for final exams even CS was pencil and paper (or a final project, which admittedly will have issues in the post-LLM era).
- FWIW there is a new-ish kind of intermediate genre between classic LAN/ranked multiplayer and single player, which is the whole “survival” genre. Generally speaking, they can be played as single player games, but also allow for small-scale co-op, synchronously or asynchronously. So even if you and a buddy have different schedules, you can make progress separately but still occasionally play together.
Valheim, Grounded, Ark, Satisfactory are a few among many others.
- Basically anything that requires a massively parallel computation on undeterminable states that are only clear in hindsight.
From https://scottaaronson.blog/ :
“If you take nothing else from this blog: quantum computers won't solve hard problems instantly by just trying all solutions in parallel.”
- What’s the best choice of free desktop PDF Viewer/Editor these days (any OS)?
On Windows I’ve been using PDF-XChange for a decade or so now, but curious if better alternatives have cropped up.
- “Don't blame me, I voted for Kodos”
- That’s a fair point. But it greatly limits the scope of human-introduced error. I think already for FLT, the surface area for error in the kernel and in axiom translation is substantially smaller than the entirety of the literature which Wiles’s proof recursively depends on.
- You need at least 45 guesses since 2^44 < 16!
- I contend it is the only way to move forward on the goal of “automating” mathematics. Although we’ve seen natural language approaches do well at IMO, the human effort required to verify higher level proofs is too great with hallucinations being what they are. With something like Lean, you don’t need a human verifier.
- Caveat: I am not an expert, so this is a semi-educated guess.
I imagine it would depend on whether DINOv3 captures the information of whether a given person is in the image, which I think is really a question about training data. So naively, I would guess the answer is yes for celebrities and no for non-celebrities. Partially for data/technical reasons, but also maybe due to the murkier legal expectation of privacy for famous people.
- To elaborate, this is a foundation model. This basically means it can take an arbitrary image and map it to a high dimensional space H in which ~arbitrary characteristics become much easier to solve for.
For example (and this might be oversimplifying a bit, computer vision people please correct me if I’m wrong) if you’re interested in knowing whether or not the image contains a cat, then maybe there is some hyperplane P in H for which images on one side of P do not contain a cat, and images on the other side do contain a cat. And so solving for “Does this image contain a cat?”becomes a much easier problem, all you have to do is figure out what P is. Once you do that, you can pass your image into DINO, dot product with the equation for P, and check whether the answer is negative or positive. The point is that finding P is much easier than training your own computer vision model from scratch.
- Perhaps you can do some pre-processing before the LLM sees it, e.g. replacing every instance of “kill” with “NorwegianDudeGameKill”, and providing the specific context of what the word “NorwegianDudeGameKill” means in your game.
Of course, it would be better for the LLM to pick up the context automatically, but given what some sibling comments have noted about the PR risks associated with that, you might be waiting a while.
- As I understand it, the most effective small models are synthesized from larger models.
- The rejection might also be random and out of your control. E.g. if they already filled the position or the higher-ups decided to save costs by taking back open headcount. Frustrating for sure, but not actionable.
From my POV, if you don’t have any strong signals about why you were rejected, I would just move on rather than trying to infer the reason.
- Is anyone else getting tired of these articles?
“Area man who had poor judgement ten years ago now has both poor judgement and access to chatbots”
- In some sense, the program itself is a ~512 byte compression of an infinite stream of bytes.