French courts have been imposing disproportionately severe sentences for minor offenses, including 10 months in prison for stealing a can of Red Bull and one year for a homeless boy with schizophrenia caught looting a luxury store. The overwhelmed courts rush cases, provide minimal time for defendants, and prioritize punishment under the instruction of the Justice Minister. Furthermore, the French government is censoring social media and justifying it by claiming to protect public order, but it infringes upon free speech and mirrors tactics used by authoritarian regimes. The justice system exhibits a double standard, favoring the privileged, and creates a class divide, leading to unrest. Ironically, the government compares itself to oppressive nations while undermining democratic principles.

[YANDHI - WAR WITH THE MATRIX (KANYE AI X BIG BABY GANDHI)](https://youtube.com/watch?v=CGyPqImBOjY

Imagine an AGI (Artificial General Intelligence) that could perform any task a human can do on a computer, but at a much faster pace. This AGI could create an operating system, produce a movie better than anything you've ever seen, and much more, all while being limited to SFW (Safe For Work) content. What are the first things you would ask it to do?

I thought it was a great idea when I read it in this comment. That way, if you didn't want to hear about Reddit, you wouldn't have to.

Maybe I've installed too many plugins? I have close to 20.

Edit: It was just an issue on Arch Linux.

No, I am 40 plugins all active and they have not changed my browser load time almost at all.

Make sure there are no other issues. If you are on Arch Linux, there is a problem with xdg-desktop-portal-gnome that if installed will slowdown loading of many programs.

Both platforms offer unique features, but also come with limitations. While Lemmy offers diverse content, it lacks robust tag metadata for organizing and searching images. On the other hand, boorus excel at categorizing images with tags but lack the discussion and the diverse content from Lemmy. Why haven't we seen a platform that combines the best of both worlds? How do you envision it would be like?

Last month, I developed a script because lemmy.ml had become too slow. Unfortunately, I have the same problem again, but this time there are too many instances to evaluate, causing the script to take an excessively long time to complete. I'm seeking advice on how to enhance the script to simultaneously ping multiple instances. Are there any alternative scripts available that might provide a more efficient solution?

git clone https://github.com/LemmyNet/lemmy-stats-crawler
cd lemmy-stats-crawler
cargo run -- --json > stats.json

#!/usr/bin/env python3
import json
import time
import requests
import requests.exceptions

from typing import List, Dict

TIME_BETWEEN_REQUESTS = 5  # 10 * 60 = 10 minutes
TIME_TOTAL = 60  # 8 * 60 * 60 = 8 hours


def get_latency(domain):
    try:
        start = time.time()
        if not domain.startswith(("http://", "https://")):
            domain = "https://" + domain
        requests.get(domain, timeout=3)
        end = time.time()
        return end - start
    except requests.exceptions.Timeout:
        return float("inf")


def measure_latencies(domains, duration):
    latencies = {}
    start_time = time.time()
    end_time = start_time + duration
    while time.time() < end_time:
        latencies = measure_latencies_for_domains(domains, latencies)
        time.sleep(TIME_BETWEEN_REQUESTS)
    return latencies


def measure_latencies_for_domains(domains, latencies):
    for domain in domains:
        latency = get_latency(domain)
        latencies = add_latency_to_domain(domain, latency, latencies)
    return latencies


def add_latency_to_domain(domain, latency, latencies):
    if domain not in latencies:
        latencies[domain] = []
    latencies[domain].append(latency)
    return latencies


def average_latencies(latencies):
    averages = []
    for domain, latency_list in latencies.items():
        avg_latency = sum(latency_list) / len(latency_list)
        averages.append((domain, avg_latency))
    return averages


def sort_latencies(averages):
    return sorted(averages, key=lambda x: x[1])


def get_latency_report(domains, duration):
    latencies = measure_latencies(domains, duration)
    averages = average_latencies(latencies)
    return sort_latencies(averages)


def get_instances(data: Dict) -> List[Dict]:
    instances = []
    for instance_details in data["instance_details"]:
        instances.append(instance_details)
    return instances


def get_domains(instances: List[Dict]) -> List[str]:
    return [instance["domain"] for instance in instances]


def load_json_data(filepath: str) -> Dict:
    with open(filepath) as json_data:
        return json.load(json_data)


def main():
    data = load_json_data('stats.json')
    instances = get_instances(data)
    domains = get_domains(instances)
    report = get_latency_report(domains, TIME_TOTAL)
    for domain, avg_latency in report:
        print(f"{domain}: {avg_latency:.2f} seconds")


if __name__ == "__main__":
    main()

We could have AI models in a couple years that hold the entire internet in their context window.