RaasAhsan

import java.util.concurrent.atomic.*;
import java.util.concurrent.*;

public class Main {
    private static ExecutorService executor = Executors.newFixedThreadPool(2);
    private static int iterations = 10000000;
  
    public static class Runner {
        // writes to canceled happen before a CAS on suspended
        // reads on canceled happen after a CAS on suspended

djspiewak

Understanding Comparative Benchmarks

I'm going to do something that I don't normally do, which is to say I'm going to talk about comparative benchmarks. In general, I try to confine performance discussion to absolute metrics as much as possible, or comparisons to other well-defined neutral reference points. This is precisely why Cats Effect's readme mentions a comparison to a fixed thread pool, rather doing comparisons with other asynchronous runtimes like Akka or ZIO. Comparisons in general devolve very quickly into emotional marketing.

But, just once, today we're going to talk about the emotional marketing. In particular, we're going to look at Cats Effect 3 and ZIO 2. Now, for context, as of this writing ZIO 2 has released their first milestone; they have not released a final 2.0 version. This implies straight off the bat that we're comparing apples to oranges a bit, since Cats Effect 3 has been out and in production for months. However, there has been a post going around which cites various compar

jenningsanderson

What are the Daylight OpenStreetMap Parquet Files?

Listed on the registry of Open Data on AWS, the Daylight OpenStreetMap Parquet files contain the latest Daylight Map Distribution of OpenStreetMap in an analysis-ready format. This dataset is optimized for cloud-based queries with Amazon Athena, meaning anyone can access the entire dataset with SQL queries in the browser, without the need to download or access the files directly.

The Daylight Map Distribution of OpenStreetMap is always openly available for download in the standard OSM PBF format (find it at daylightmap.org). The parquet files, however, were first made available alongside Daylight release v1.9. They contain fully resolved geometries and additional metadata including areas, lengths, and quadkeys, not present in the PBF.

In total, the OSM features files contain nearly 1B features including 178M+ nodes, 816M+ ways, and 5M+ relations. These are all _renderable f

yoavg

Some remarks on Large Language Models

Yoav Goldberg, January 2023

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.

Intro

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