taskylizard

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► System Tools

joaocruz04

Enabling FTS4 on an Android project with Room

You can do a SQL text query by using the LIKE operator. The issue is that using it requires a lot of computation, as a complete string query is done. Also if you want to have more search options (more fields), your query will grow a lot in complexity. To solve this issue, there's a concept of virtual tables for full text search (FTS).

We will build our solution using Room (already set in the project). We're using version 2.2.0-rc01 for that.

Step 1 - Create new Virtual Table

With Room, the only thing we need is to create the new class with @FTS4 notation. By specifying contentEntity to be the Route class, it means that it will reuse the values from the Route table instead of populating this one with copies. The fields in question should match the ones from the Route table. In this example we only need the title.

veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

yoavg

Reinforcement Learning for Language Models

Yoav Goldberg, April 2023.

Why RL?

With the release of the ChatGPT model and followup large language models (LLMs), there was a lot of discussion of the importance of "RLHF training", that is, "reinforcement learning from human feedback". I was puzzled for a while as to why RL (Reinforcement Learning) is better than learning from demonstrations (a.k.a supervised learning) for training language models. Shouldn't learning from demonstrations (or, in language model terminology "instruction fine tuning", learning to immitate human written answers) be sufficient? I came up with a theoretical argument that was somewhat convincing. But I came to realize there is an additional argumment which not only supports the case of RL training, but also requires it, in particular for models like ChatGPT. This additional argument is spelled out in (the first half of) a talk by John Schulman from OpenAI. This post pretty much

thesamesam

FAQ on the xz-utils backdoor (CVE-2024-3094)

This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.

Background

On March 29th, 2024, a backdoor was discovered in xz-utils, a suite of software that

gtallen1187

"A little bit of slope makes up for a lot of y-intercept"

01/13/2012. From a lecture by Professor John Ousterhout at Stanford, class CS140

Here's today's thought for the weekend. A little bit of slope makes up for a lot of Y-intercept.

[Laughter]

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

objcode

/* Copyright 2019 The Android Open Source Project
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   https://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

varemenos

Get Git log in JSON format

git log --pretty=format:'{%n  "commit": "%H",%n  "abbreviated_commit": "%h",%n  "tree": "%T",%n  "abbreviated_tree": "%t",%n  "parent": "%P",%n  "abbreviated_parent": "%p",%n  "refs": "%D",%n  "encoding": "%e",%n  "subject": "%s",%n  "sanitized_subject_line": "%f",%n  "body": "%b",%n  "commit_notes": "%N",%n  "verification_flag": "%G?",%n  "signer": "%GS",%n  "signer_key": "%GK",%n  "author": {%n    "name": "%aN",%n    "email": "%aE",%n    "date": "%aD"%n  },%n  "commiter": {%n    "name": "%cN",%n    "email": "%cE",%n    "date": "%cD"%n  }%n},'

The only information that aren't fetched are:

• %B: raw body (unwrapped subject and body)
• %GG: raw verification message from GPG for a signed commit

72lions

/**
 * Creates a new Uint8Array based on two different ArrayBuffers
 *
 * @private
 * @param {ArrayBuffers} buffer1 The first buffer.
 * @param {ArrayBuffers} buffer2 The second buffer.
 * @return {ArrayBuffers} The new ArrayBuffer created out of the two.
 */
var _appendBuffer = function(buffer1, buffer2) {
  var tmp = new Uint8Array(buffer1.byteLength + buffer2.byteLength);