hansihe

Joined 11 years ago

Karma
353
Submissions
73
Member since
Feb 25
http://hansihe.com

[ my public key: https://keybase.io/hansihe; my proof: https://keybase.io/hansihe/sigs/PfpwSyBwKYgn8cDVS0FghzCw2sZF1N_ozR08IekKMPE ]

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Recent submissions

Comment · 1 month ago
There is exactly one manufacturer of large EPDs, E Ink Corporation.

A few have tried to compete over the years, none have really managed to ramp up production and compete from my understanding. I believe there are some chinese firms making smaller panels now, mainly used in electronic shelf labels for stores.

From my understanding most of the patents for the foundational tech have expired at this point. I believe the panels are just generally very difficult to make, with difficulty ramping up further as panel size goes up, presumably the yield is fairly low.

Comment · 1 month ago
> because the latter has shown when he ran Twitter that he will happily manipulate and censor discourse to appease the current mob mentality/political climate

Could you expand a bit on what you are referring to here?

Comment · 2 months ago
Comment · 2 months ago
Slightly relevant, I built https://mechanisms.ln.gy/ a little while ago

Indexed and filterable index of over 4000 visualised mechanisms by thang010146 on YouTube

Comment · 3 months ago
They are not really token-in token-out per se, they are embedding-in embedding-out.

When operating on text, you embed each token into the LLMs embedding space. You go from a discrete token to a point in embedding space.

Likewise, when processing images, you have a image embedding model which produces a set of embedding vectors representing the contents of the image in the LLMs embedding (latent) space.

This same concept can be extended to compaction. Instead if limiting yourself to discrete tokens, you could generate a set of embedding vectors which represent the contents of the compacted conversation in latent space.

These have the possibility of containing a lot more semantic information per vector, which is why this can be appealing.

A big downside is decreased interpretability. AI safety people are generally fairly opposed to latent space reasoning for example, it can be harder to tell what the model is actually doing and if it is trying to deceive you.

Comment · 3 months ago
It seems likely to me this was driven by the `ultra` mode in 5.6, which fans subagents to do work. This mode was previously only available in the web UI (what was previously known as pro?)

It seems possible they trained this by doing full RL rollouts of agents interacting with each other. They likely view these prompts somewhat the same as raw reasoning traces, they don't want people to train directly on them.

I am unsure if this has been confirmed, but there are some signs that the opaque "compaction blob" they return from their dedicated compaction endpoint might not be text at all, rather a latent space representation of the conversation. The fact that OpenAIs compaction seems to be much higher fidelity than a lot of other providers makes me inclined to believe this.

If this is true, it doesn't seem far fetched to infer that they might be applying similar techniques to prompting subagents.

I would be curious to see if this way of spawning subagents (encrypted blob) is used when subagents of a different model type is spawned.

Comment · 8 months ago
What do you mean? There is nothing unenforceable about this.
Comment · 10 months ago
CockroachDB does Serializable by default
Comment · 1 year ago
What makes it so great for me is the effortlessness.

I often use Python for quick one off scripts. With UV I can just do `uv init`, `uv add` to add dependencies, and `uv run` whatever script I am working on. I am up and running in under a minute. I also feel confident that the setup isn't going to randomly break in a few weeks.

With most other solutions I have tried in the Python ecosystem, it always seemed significantly more brittle. It felt more like a collection of hacks than anything else.

Comment · 1 year ago
Your dismissal of this research shows a fundamental misunderstanding of how scientific analysis works.

The study analyzed two separate phenomena - changes in engagement for Musk's posts AND changes in engagement for Republican content - occurring simultaneously. When taken together, these patterns strongly suggest algorithmic changes, not just organic user behavior from the assassination attempt.

Saying "you can't do that for the reasons I mentioned" is just wrong. Studies absolutely can point toward likely explanations without 100% certainty - that's literally how science progresses. The researchers used appropriate cautious language because they understand scientific rigor, not because their analysis is "crap."

Your argument that "if circumstances don't allow for a proper study, you don't make it" would eliminate most scientific advancement. Should we have abandoned Alzheimer's research because perfect data wasn't available? Obviously not.

What's truly absurd here is your selective skepticism. You demand impossibly high standards of proof for findings you dislike while accepting "common sense" explanations that align with your preconceptions.

Before dismissing research as "garbage" that "causes division," maybe consider whether your reaction is based on methodological concerns or simply that the evidence contradicts your preferred narrative about Musk. Your eagerness to defend him while offering nothing but personal opinion suggests it's the latter.

Comment · 1 year ago
The study analyzed two separate things:

* Change in engagement for posts by Elon Musk

* Change in engagement for republican content

It seems to me that when taken together, these two make a fair case that there was a change in algorithm on the given date?

Besides, the study you are claiming "is not science" did not even make strong claims as to there being an algorithm change. The study made an analysis, and concluded that they might point towards there being an algorithmic change.

Additionally, as you say "If the claim is that Musk tuned the algorithms at that special date, you have to prove it by other means". What other means exactly? We have no data to go on except observations of what happens on the platform. From the information we have it seems like everything points towards this being the case.

The case for manipulation happening furthered even more by Elon Musk repeatedly showing he is full of shit, and has no qualms lying and totally making stuff up. (see his repeated lies about Autopilot, his lie about being world class at video games, his lies about DOGE cuts, etc).

Before dismissing these findings, ask yourself honestly: would you apply the same rigorous standards of proof if the algorithmic changes benefited different political figures or viewpoints?

Comment · 1 year ago
Why is that laughable exactly? It was the same point in time which he endorsed Trump
Comment · 1 year ago
Comment · 1 year ago
I think it aged perfectly well.

We were talking about his son, he let the process play out in full which is beyond respectable.

When the incoming administration has shown extraordinary will to persecute political opponents, I think it would be unethical not to preemptively pardon these people.

Comment · 1 year ago
After the precedent around pardons set by his predecessor I'll give him that one.

At least Biden let the process play out before issuing the pardon so the public got to know all the details.

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