Yeah I can’t fully agree with axioma #2. While people learn when you challenge them, every person reacts differently when they struggle. And there is this thing, anxiety, that makes people insecure. Mathematics anxiety is even a thing [1].
So I think this axioma is based on a previous one: everyone wants to be challenged, which I believe is not true. You have to give people a reason for that motivation first, to be able to challenge them. Otherwise you will make people feel insecure, because they will think that they’re not smart enough, and we are taught that maths = smart. (Maybe we have to tackle this social construct first.)
Well, my guess is that updates and inserts are much more frequent than searches in their use case. You're assuming a balanced frequency for these operations and it hardly ever happens.
ipv4 space is very limited and you can easily compute all the hashes. There is salting and combined with rotating salts it could work but no one guarantees that you’re not storing them
But the idea that the brain functions on a basis of complex statistical processes doesn't imply that statistics created the brain itself, it just suggests that the brain's processes can be modeled/understood through the lens of statistical methods. Statistics is just how we describe a tool we invented to analyze observable data, the brain could be a similar tool and it doesn't need to be the same tool.
It's akin to saying that we created the concept of "physics", yes we created it, and physics govern, for example, how a car moves, but it doesn't mean our concept of physics created the car or physics itself, we just use physics to describe and understand the car's movement.
Maybe statistics can't generate anything, but if you imagine everything we can do as very complex, unimaginable multi-dimensional functions that can generate outputs based on inputs, we can use statistics to find functions that fit any real (ground truth) function in the observable universe.
When you fine-tune it, do you train just the head/last few layers or do you also unfreeze the model afterwards and retrain the whole model with a very small LR for a few epochs?
10% of the population in spain was using netflix before this, as a reference 12% in germany, not that much difference. We'll see, but I think it has more to do with the decline in quality of the content and people sending a message than anything else.
My experience is similar but tbh I feel it's mainly due to the fact that oauth is implementing an important security layer (authentication/authorization) and that's hard by definition. There are lots of steps and things you can't afford to overlook or you'll be vulnerable to multiple different attacks
IMO if your app is less secure than your competition by default, the app is less secure, period.
Telegram is said to have been given authorities access to user data [1], despite the fact that they advertise the opposite. I guess that’s what happens when your app is not encrypted E2E by default.
Also, they have used their own encryption algorithm in the past (I don’t know now) instead of the well known and proven algorithms out there. Something highly criticized by experts, back then [2]
As a software engineer this all is very inspiring. I’m tickled and excited to do things again. I’m also learning deep learning and statistics and having a blast with toy projects.
I’ve noticed that bing chat is better if you instruct it not to search anything, that way it will use the model knowledge. I’ve learned to use the model knowledge or the web search results summary depending on what I want. But ChatGPT is still way better for model knowledge because it has fewer restrictions.
I wish they would make this distinction clearer in the UI. Most of the time it can answer without resorting to search, I think it would be better if the user explicitly specifies that they need web results.
> Actually nowadays I bet higher percentage of Swedes know English than know Swedish.
Is that hyperbole? Because that would be very sad if true, culturally speaking. There are 5 different official languages in my country (Spain) and there are several laws to prevent them from becoming extinct for this very reason.
It's only useful when you have some cognitive work that you want to automate so it saves you time and you can do it on a large scale, but I don't think writing massive amounts of viruses is the goal here. The objective is to code very specific and particular viruses or exploits for very specific targets.
Also, writing code is only a small part of hacking, especially when it is against specific targets.
The idea is interesting but I still don’t get how it works.
Also, what are the benefits for me, as a user? I could give you ideas for the challenges but I’m missing a “search” or “explore” feature to find solutions for my problems in an engaging way that would encourage me to contribute my own
Jeez, I don’t think I’ll ever understand the american thing with Apple. It must be a social thing, I’ve seen people humiliate and even shun people who have Android (“the green bubble”) or other non-Apple devices.
I feel that they're always very biased in these comparisons.
Yeah, but to be fair GPT 2 is open source and Whisper (a high-quality speech recognition and multilingual translation model) is also open source. A few years ago I needed a good model for transcription for a project and I couldn’t find anything decent. They really have contributed to the open source community.
If they keep releasing older models and keep their cutting-edge technology for profit I’m fine with it.
So I think this axioma is based on a previous one: everyone wants to be challenged, which I believe is not true. You have to give people a reason for that motivation first, to be able to challenge them. Otherwise you will make people feel insecure, because they will think that they’re not smart enough, and we are taught that maths = smart. (Maybe we have to tackle this social construct first.)
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[1] https://en.m.wikipedia.org/wiki/Mathematical_anxiety