Logseq supports some of org mode syntax.

I'm mostly using this nowadays >>> subprocess.getoutput('ls')

> Emacs on my phone sounds lovely!

Meanwhile, you can use it in termux if you are on android right now.

Logseq actually supports orgmode files on android (and desktop) in some extent, for me it works better than orgzly.

I mean the pandemic was not too long ago, a lot of us actually remember the accessible treatments back then.

First they discovered steroids like prednisolone which were useful only for heavily sick patients, then they started to distribute antibody plasma from other patients, then monoclonal antibodies and some cytokine inhibitors and when everybody who wanted already got vaccinated, we got antivirals such as Paxlovid, and it was scarce.

There were a lot of misunderstanding around hydroxychloroquine and ivermectin, similarly how we have a lot of misunderstanding around vaccines and autism. And they were tested and tested and tested, similarly how we still check if vaccines cause autism. And all the proper research showed that hydroxychloroquine and ivermectin were absolutely ineffective, times and times again, but people just couldn't let them go, similarly to how people can't let go the fake autism-vaccine connection.

In the first part of the pandemic, vaccines were the best we had.

Really liked the article.

The interesting part for me was that you can recognize synthetic voice much faster than human speech. Is there a specific voice you are using for 800wpm or it can be any TTS? Also, I think older voices sound more robotic that the newer ones (I mean pre AI, like the default on android is newer for me). Is there a difference for how fast you can listen to the newer more nicely sounding ones or the older more robotic ones?

> Is there a difference for how fast you can listen to the newer more nicely sounding ones or the older more robotic ones?

Yes. The main requirements for the TTS I use is it must be intelligible at very high rates of speed and it must have no perceivable latency (i.e, how long it takes to convert a string of text to audio). This rules out use of almost all voices, since a lot of them are focused on sounding as human as possible, which comes at the expense of being intelligible at high rates. The newer voices also usually don't have low latency.

> Is there a specific voice you are using for 800wpm or it can be any TTS?

I'm using ETI Eloquence. If I switched to another voice capable of being intelligible at ESpeak, I would have to slow down because I'm not used to it and have to train myself to get back to the speeds I'm used to.

Thank you for the answers. Even I'm not new to TTS usage, overall, this feels a bit like cyberpunk for me, like a neural interface that can provide you information as fast as you can consume it, not just how fast your "ears" can recognize it. Like a human modem.

I've added a section about TTS voices to the post, see https://neurrone.com/posts/software-development-at-800-wpm/#...

JS used to have those, now they are deprecated though:

https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...

so it settled on having this syntax for similar cases using "Symbol":

class Foo { *[Symbol.iterator]() { yield 1; yield 2; yield 3; } }

https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...

> I won't buy anything made in US and sold here anymore.

Not to counter the argument, but just if I would consider doing the same. What to do with laptops - Apple (silicon), Intel, AMD and Qualcomm are all US companies.

> I use orgzly

A couple of alternative options, none of which are perfect, are using Termux with installed Emacs or Logseq, which supports org-mode syntax for files.

IMO the simplest option is llamafile (it is multiplatform using "cosmopolitan" lib so should run on Windows too, but I haven't tried)

    wget https://huggingface.co/Mozilla/Llama-3.2-1B-Instruct-llamafile/resolve/main/Llama-3.2-1B-Instruct.Q6_K.llamafile
    chmod +x Llama-3.2-1B-Instruct.Q6_K.llamafile
    ./Llama-3.2-1B-Instruct.Q6_K.llamafile --server

It has a webui, but this is how I use it from python (sorry I like python, but similar connection method should work from the other langs too).

    ai = openai.AsyncOpenAI(base_url="http://localhost:8080/v1", api_key="sk-no-key-required")
    response = await ai.chat.completions.create(
        messages=[
            {"role": "system", "content": "..."}, {"role": "user", "content": "..."},
        ],
        max_tokens=100,
        model="Llama-3.2-1B-Instruct.Q6_K.gguf",
    )

    content = response.choices[0].message.content