yoavg

Grand-master Level Chess without Search: Modeling Choices and their Implications

Yoav Golderg, February 2024.

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Researchers at Google DeepMind released a paper about a learned systems that is able to play blitz-chess at a grandmaster level, without using search. This is interesting and imagination-capturing, because up to now computer-chess systems that play at this level, either based on machine-learning or not, did use a search component.[^1]

Indeed, my first reaction when reading the paper was to tweet wow, crazy and interesting. I still find it crazy and interesting, but upon a closer read, it may not be as crazy and as interesting as I initially thought. Many reactions on twitter, reddit, etc, were super-impressed, going into implications about projected learning abilities of AI systems, the ability of neural networks to learn semantics from observations, etc, which are really over-the-top. The paper does not claim any of them, but they are still perceiv

cpursley

PostgreSQL is Enough

• Simplify: move code into database functions
• Just Use Postgres for Everything
• PostgreSQL is the worlds’ best database
• Postgres is eating the database world
• Hacker News discussion

Background and Cron Jobs

yzdbg

Automating Daily Reports, because fuck it, really...

Each day at our company, developers are required to document their activities, painstakingly jotting down their daily work and future plans. A monotonous chore that I just really dislike.

So now, there's a scribe for that :

Code

rain-1

This worked on 14/May/23. The instructions will probably require updating in the future.

llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)

Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.

It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.

• Clone llama.cpp from git, I am on commit 08737ef720f0510c7ec2aa84d7f70c691073c35d.

rain-1

The reverse turing test

I asked GPT-4 to come up with 10 questions to determine if the answerer was AI or human.

I provided my own answers for these questions and I also asked ChatGPT to answer them.

The result is that GPT-4 was able to correctly differentiate between AI and Human.

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

0xmebius

object "Contract" {
    code {
        datacopy(0, dataoffset("runtime"), datasize("runtime"))
        return(0, datasize("runtime"))
    }
    object "runtime" {
        code {
            if iszero(calledByOwner()) { revert(0, 0) }
            switch selector()
            case 0x00 {

ctsrc

Guide: Run FreeBSD 13.1-RELEASE for ARM64 in QEMU on Apple Silicon Mac (MacBook Pro M1, etc) with HVF acceleration (Hypervisor.framework)

This guide was adapted from https://gist.github.com/niw/e4313b9c14e968764a52375da41b4278#running-ubuntu-server-for-arm64

Running FreeBSD 13.1-RELEASE for ARM64

1. Install Xcode from App Store or install Command Line Tools on your Mac running on Apple Silicon.

cryptoscopia

// SPDX-License-Identifier: AGPL-3.0-or-later

// The ABI encoder is necessary, but older Solidity versions should work
pragma solidity ^0.7.0;
pragma experimental ABIEncoderV2;

// These definitions are taken from across multiple dydx contracts, and are
// limited to just the bare minimum necessary to make flash loans work.
library Types {
    enum AssetDenomination { Wei, Par }

petejkim

// SPDX-License-Identifier: MIT
// Copyright (c) 2020 petejkim

pragma solidity 0.6.12;

import { Ownable } from "https://github.com/OpenZeppelin/openzeppelin-contracts/blob/v3.2.0/contracts/access/Ownable.sol";
import { IERC20 } from "https://github.com/OpenZeppelin/openzeppelin-contracts/blob/v3.2.0/contracts/token/ERC20/IERC20.sol";
import { SafeERC20 } from "https://github.com/OpenZeppelin/openzeppelin-contracts/blob/v3.2.0/contracts/token/ERC20/SafeERC20.sol";

contract USDCFaucet is Ownable {