# Configuration for n8n | |
# Make sure to adjust: server_name, SSL certificate paths, and proxy_pass settings | |
############################################################################## | |
# HTTP Server Block - Redirects all HTTP traffic to HTTPS | |
############################################################################## | |
server { | |
# Listen directives | |
listen 80; # IPv4 | |
listen [::]:80; # IPv6 |
javascript:(function(){try{navigator.clipboard.readText().then(function(t){if(t){var e=window.open("","_blank","width=800,height=600");e.document.open(),e.document.write(t),e.document.close()}else alert("Clipboard is empty. Please copy some text to the clipboard first.")}).catch(function(t){console.error("Failed to read clipboard contents: ",t),alert("An error occurred while trying to access the clipboard. Please ensure your browser allows clipboard access.")})}catch(t){console.error("An error occurred:",t),alert("An error occurred while trying to open the new window with the clipboard content.")}})();//bookmarklet_title: HTML Preview from Clipboard |
Begin by enclosing all thoughts within <thinking> tags, exploring multiple angles and approaches. | |
Break down the solution into clear steps within <step> tags. Start with a 20-step budget, requesting more for complex problems if needed. | |
Use <count> tags after each step to show the remaining budget. Stop when reaching 0. | |
Continuously adjust your reasoning based on intermediate results and reflections, adapting your strategy as you progress. | |
Regularly evaluate progress using <reflection> tags. Be critical and honest about your reasoning process. | |
Assign a quality score between 0.0 and 1.0 using <reward> tags after each reflection. Use this to guide your approach: | |
0.8+: Continue current approach | |
0.5-0.7: Consider minor adjustments | |
Below 0.5: Seriously consider backtracking and trying a different approach |
Audience: I assume you heard of chatGPT, maybe played with it a little, and was imressed by it (or tried very hard not to be). And that you also heard that it is "a large language model". And maybe that it "solved natural language understanding". Here is a short personal perspective of my thoughts of this (and similar) models, and where we stand with respect to language understanding.
Around 2014-2017, right within the rise of neural-network based methods for NLP, I was giving a semi-academic-semi-popsci lecture, revolving around the story that achieving perfect language modeling is equivalent to being as intelligent as a human. Somewhere around the same time I was also asked in an academic panel "what would you do if you were given infinite compute and no need to worry about labour costs" to which I cockily responded "I would train a really huge language model, just to show that it doesn't solve everything!". We
As part of a holiday D&D one-shot session where Santa Claus's toy factory had been sabotaged, our dungeon master presented to us, a group of Christmas elves, a riddle to solve.
9 cards, labeled with the names of Santa's reindeer were presented to us. The instructions indicated that we had to find the order reindeer were in, according to this riddle:
Vixen should be behind Rudolph, Prancer and Dasher, whilst Vixen should be in front of Dancer and Comet. Dancer should be behind Donder, Blitzen and Rudolph. Comet should be behind Cupid, Prancer and Rudolph. Donder should be behind Comet, Vixen, Dasher, Prancer and Cupid. Cupid should be in front of Comet, Blitzen, Vixen, Dancer and Rudolph. Prancer should be in front of Blitzen, Donder and Cupid. Blitzen should be behind Cupid but in front of Dancer, Vixen and Donder. Rudolph should be behind Prancer but in front of Dasher, Dancer and Dond
rdx_en_date | rdx_en_stamp | vhash | version | |
---|---|---|---|---|
2018-08-25 03:29:12 | 1535167752 | 12.1-49.23 | ||
2018-10-16 17:54:20 | 1539712460 | 12.1-49.37 | ||
2018-11-28 08:56:26 | 1543395386 | 26df0e65fba681faaeb333058a8b28bf | 12.1-50.28 | |
2019-01-18 17:41:34 | 1547833294 | d3b5c691a4cfcc6769da8dc4e40f511d | 12.1-50.31 | |
2019-02-13 06:11:52 | 1550038312 | 1ffe249eccc42133689c145dc37d6372 | ||
2019-02-27 09:30:02 | 1551259802 | 995a76005c128f4e89474af12ac0de66 | 12.1-51.16 | |
2019-03-25 22:37:08 | 1553553428 | d2bd166fed66cdf035a0778a09fd688c | 12.1-51.19 | |
2019-04-19 11:04:22 | 1555671862 | 489cadbd8055b1198c9c7fa9d34921b9 | ||
2019-05-13 17:41:47 | 1557769307 | 86b4b2567b05dff896aae46d6e0765bc | 13.0-36.27 |
console.log("[*] SSL Pinning Bypasses"); | |
console.log(`[*] Your frida version: ${Frida.version}`); | |
console.log(`[*] Your script runtime: ${Script.runtime}`); | |
/** | |
* by incogbyte | |
* Common functions | |
* thx apkunpacker, NVISOsecurity, TheDauntless | |
* Remember that sslpinning can be custom, and sometimes u need to reversing using ghidra,IDA or something like that. | |
* !!! THIS SCRIPT IS NOT A SILVER BULLET !! |
For fun, I had ChatGPT take the free response section of the 2022 AP Computer Science A exam. (The exam also has a multiple-choice section, but the College Board doesn't publish this.) It scored 32/36.
- For each question, I pasted in the full text of the question and took the response given.
- I tried each question once and took the response given: no cherry-picking. For readability, I've added indentation in some cases, and included method signatures where they were provided in the question and ChatGPT only provided a body. I've added question numbers; any other comments are ChatGPT's.
- Many questions have examples containing tables or diagrams; because those don't translate well to plain text, I excluded those tables/diagrams and any text that referenced them.
- I excluded the initial instructions at the top of th