However, I would be very surprised if the conversion rate of a popup signup sheet is even 2%.

And there is a similar negative conversion effect: If any article asks me to sign up for anything, I stop reading that article immediately, and move on to an article that respects my attention.

Yes, I am in a small minority. But I also share many links with my peeps, and I never share links with popups. I hope that puts pressure on authors to share things freely.

https://www.reddit.com/r/browsers/comments/zebad6/a_few_andr...

Some highlights: - Vivaldi is suprisingly fast and has good ad blocking - Kiwi plus the Ublock Origin extension (UBO) might be /even faster/ - Firefox also allows UBO, but sadly it is relatively slow

for example, read Adrian Goldsworthy's "Pax Romana" and "How Rome Fell" for a very entertaining and up to date view of rome at its height and decline, with hundreds of little nonlinear story details. The audiobooks are on the audiobook bay. Listen to them view a Smart Audiobook reader with auto-pause for if you fall asleep, and start listening during exercise, cleaning, cooking, and commuting.

If you start doing this, you'll start listening to about 2 histories a month. In a year you'll have a much deeper understanding of history and how it's written.

Unfortunately, audiobook is the best format I've found for overcoming the size of history texts. It really helps me with my reading difficulties and tendency to get stuck on boring passages. The history is much more engaging when someone is reading for me. Also, many passages are going to go over your head, and it may put you to sleep literally - that's also fine!

The goal is to start understanding and enjoying the small little stories that historians write. History is full of millions of them, and many of them are enjoyable!

If that 10 second moment of mental space and clarity becomes enjoyable, then you will not want to reverse the friction. The author's point here is that people often add /too much/ friction.

https://news.ycombinator.com/item?id=36330900

I propose that the right amount of friction requires an amount of self control that is enjoyable and refreshing - ie, only a /very small/ amount of self control can ever be sustainable. https://news.ycombinator.com/item?id=36330900

Partnering with the incomprehensibly byzantine andcomplacent architect of the SEOpocalypse AND "late-to-the-ai-party" Google does not give faith that the solution will be more performant or private than Github's copilot.

This is just another in a series of terrible blunders in the last year that has wiped out any goodwill I had towards gitlab. WTF happened, did they get a new CEO or something?

Two Approaches: Grinding and Flow

One approach is to do the task with perfect awareness and focus. We dismiss extraneous thoughts when they arise. We and focus on doing the task perfectly and without unnecessary pain or suffering.

We could call this Grinding, since we still feel effort.

Another approach is to enter a stateless flow. In this state, your awareness and focus and identity are no longer present as you do the task. You neither feel effort nor make errors as you do the task.

We could call this Effortless Effort, or Flow.

1. The risk and threats are published

2. The audits I've seen don't evaluate the threats

3. Link me to the audits if you want to convince me

I. The risks - airgapping is not enough

1. If the software has zeroday beacons in it, it can communicate with zeroday beacon repeaters embedded in VM, OS, or hardware (see: cache side channels: https://dl.acm.org/doi/abs/10.1145/3133956.3136064 )

2. The beacons wouldn't have to look like exploit code, they could just be timing bugs sprinkled into the codebase at random. There are plenty of random little warnings and defects in the code that nobody is ever going to check or fix, see this audit: https://github.com/NationalSecurityAgency/ghidra/issues/382

3. Airgaps may be broken by ultrasound side channels; communication to compromised devices like smartphones is possible (see: speaker-to-gyroscope communication https://ieeexplore.ieee.org/abstract/document/9647842/ ; speaker-to-speaker communication https://arxiv.org/pdf/1803.03422.pdf)

4. Low bitrate data leaks, like "ghidra is running in this org, decompiling files named....." may be accumulated by the NSA

This is just zero-day warehousing and passive signals collection with embedded zerodays. It would be hard for security researchers to detect this. I'd happily change my mind if you showed me an audit that looks for beacons and other side channels.

II. The audits

Here is the one audit I could find

https://github.com/NationalSecurityAgency/ghidra/issues/382

This audit tells us that the code is janky, but doesn't tell us if it's secure. It's just a dump of thousands upon thousands of static analysis errors.

There's no threat anaylsis in this audit. But it does suggest the code has so many defects that a serious audit would be very expensive.

III. Change my mind with evidence

Please link me to the heavy audits of the code. If you can.

tldr;; I think the code is less heavily audited than you can support

Okay. I have looked at the code. Now what? Has that made me more secure?

Every person I've asked this question has had their noses so far up the NSA's pooper that they could not imagine considering the NSA an adversary.

But suppose you were running a malware honeypot operation for the CCP. Would you still use Ghidra? Why or why not?

And please don't pass the buck and say, "I probably wouldn't be allowed to use ghidra" or "I'd probably use whatever my CCP handler told me to use" or "I wouldn't be working for the CCP in the first place." That does not inform me about the security risks of using ghidra with the NSA as an adversary.

It works astoundingly well with poorly written technical manuals. Looking at you, CMake reference manual O_O. It also helps translate unix man pages from Neckbeardese into clean and modern speech.

With science papers it's a bit more work. You must copy section by section into GPT4, despite the increased token limit.

But sure. Here's how it can work:

1. Copy relevant sections of the paper

2. As questions about the jargon:

"Explain ____ like I'm 5. What is ____ useful for? Why do we even need it?"

"Ah, now I understand _____. But I'm still confused about _____. Why do you mean when you say _____?"

"I'm starting to get it. One final question. What does it mean when ______?"

"I am now enlightened. Please lay down a sick beat and perform the Understanding Dance with me. Dances"

This actually works surprisingly well.

That's not what's happening in the parent comment. They're talking about projects like

https://github.com/ZrrSkywalker/LLaMA-Adapter

https://github.com/microsoft/LoRA

https://github.com/tloen/alpaca-lora

and specifically the paper: https://arxiv.org/pdf/2106.09685.pdf

Lora is just a way to re-train a network for less effort. Before we had to fiddle with all the weights, but with Lora we're only touching 1 in every 10,000 weights.

The parent comment says GPT4all doesn't give us a way to train the full size Llama model using the new lora technique. We'll have to build that ourselves. But it does give us a very huge and very clean dataset to work with, which will aid us in the quest to create an open source chatGPT killer.

But AI workers mainly develop and use jargon because it is an easy and natural way to consolidate concepts.

Sure, there is a kind of conspiracy caused by publish or perish. Researchers may use jargon to make their work harder to reject on review; laborious speech and jargon can make statements sound more profound. However, no technical field is immune to this. We'll need to systematically change science before we can eliminate that problem.

Until we manage that, if you care about the concepts enough to want to understand them before there are good plain speech descriptions, just pop the jargon into google scholar and skim read a few papers, and you're good to go. If you don't care about the concepts that much, then don't worry about the jargon. The important concepts will get their own non-technical explanations in time.

As it stands, AI jargon is not that bad. It tends to be pretty fair and easy to understand, compared to jargon in, say, biochemistry or higher math.

1. Identify the jargon terms you don't understand

2. Lookup papers that introduce the jargon terms

3. Skim-read the paper to get the gist of the jargon

If you don't want to do this, then you don't have to feel uneducated. You can simply choose to feel like your time is more important than skimming a dozen AI papers a week.

But for example, here's what I did to understand the parent comment:

1. I had no idea what lora is or how it relates to alpaca.

2. I looked up https://github.com/tloen/alpaca-lora

3. I read the abstract of the Lora paper: https://arxiv.org/pdf/2106.09685.pdf https://github.com/tloen/alpaca-lora

4. Now I know that Lora is just a way of using low rank matrices to reduce finetuning difficulty by a factor of like 10,000 or something ridiculous

5. Since I don't actually care about /how/ Lora does this, that's all I need to know.

6. TLDR; Lora is a way to fine-tune models like Llama while only touching a small fraction of the weights.

You can do this with any jargon term at all. Sure, I introduced more jargon in step 4 - low rank matrices. But if you need to, you can use the same trick again to learn about those. Eventually you'll ground yourself on basic college level linear algebra, which if you don't know, again you should learn.

The sooner you evolve this "dejargonizing" instinct rather than blocking yourself when you see new jargon, the less overwhelmed and uneducated you will feel.

Saying he gives talks to philosophers, or saying this pushes philosophy to its limits doesn't fix the problem that lecun does a poor job - in this presentation - of philosophically motivating the proposal.

Perhaps I am wrong, and you can point out exactly how lecun explicates the philosophy in the presentation - perhaps it's really embedded in the maths, which I have not appreciated.

Appealing to lecun's authority won't fix the opacity of the presentation. But interpreting it can help! Are you up for it?

That's an ethically bankrupt position, and I reject it.

You're simply wrong here. Any teacher who starts to be paranoid about the ineptitude of their students will be MISERABLE. Instead, teachers must establish better boundaries, and better materials and methods for their students.

For instance, I've /been/ the hapless student, and you probably have been too. I've asked silly X-Y questions. I've refused to read the docs before asking questions that have been asked millions of times before. And what helped me was people linking me to articles on how to ask good questions and how to get good answers and generally how to help and be helped.

Throwing in the towel and saying "man these students are just too lazy and expect too much" is not going to help the community, and it's not going to make the students magically ask more insightful and considerate questions. In my experience working with tutors, professors, mentors, and students in both professional, open source, and academic contexts, no skilled and happy teacher thinks or talks this way about their students.

So if you want to relate to students this way, just realize that it's no better than haplessly trying to help everyone in the first place:

- It still burns you out and makes you miserable (in fact, it's the one of the end stages of burnout)

- It still fails to make your students more self-reliant

If that's what you want, please continue to denigrate people who, after all, simply want to be helped and don't know how to be helped.

When a helper fails to advocate for these people, it's wrong to conclude that they didn't want the help - a moral judgement. The help being offerred might not have been good enough, or the person might not have been ready for help.

In the end, whenever we do get to help someone we should be happy (since that improves the work. But when we fail someone - or we think someone has failed themselves - we should not be bitter, but become better at finding those who we can help, and improving what we offer to those we help.

I don't think you would doubt any of what I said. Instead, I think you're here to defend a morally negative view of students and others who "do not want to work" for the help. And I think that's wrong.

I feel you've helped too many people, with too little reward, and for that matter with too little progress in your ability to help.

That's not the fault of the people needing help, though, now is it? So why are you characterizing them as vampires?

IMO rather than embittering people against helping others, you should retire from helping ppl that aren't paying for your help. That way, you'll stop embittering and misguiding helper volunteers, whose jobs literally ARE to help people who don't seem to "get" the docs.