The article discusses the resurgence of programming languages designed specifically for AI development, highlighting Mojo as a promising example. It explores the historical context of AI-focused languages, the limitations of Python for AI, and the features and benefits of Mojo and other emerging AI languages.
- Demonstrates how to improve two pretrained models' proficiency in the Dafny verified programming language.
- Uses 178 programming problems from the MBPP dataset for prompting GPT-4 and PaLM-2 to generate methods in Dafny.
- Three types of prompts were used: a direct contextless prompt, one that includes a signature of the method and test cases, and a third one that decomposes the problem into steps and includes dynamically chosen similar examples.
- GPT-4 was able to generate verified (and human-evaluated) Dafny methods in 58% of the cases with the third prompt.
- Contributes a collection of 153 MBPP problems implemented and formally verified in Dafny, 50 written by authors and 103 synthesized by GPT-4.
Just wanted to poke this issue since it has been over a year since a comment was left and this issue still exists. I have recently been struggling with getting my custom shadow task to include the dependencies in the thick jar until I changed my configuration to use
project.configurations.implementation.canBeResolved = true
configurations = project.configurations.implementation »
Prior to this build, my team used Gradle 6 and used the deprecated compile and runtime dependency declarations. We had also pointed our custom shadow task to use configurations = project.configurations.runtime » After upgrading to Gradle 7 and v7.1.2 of this plugin, we began running into issues with our jars missing dependencies.
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sourceSets.main.scala.srcDir "src/main/java"
sourceSets.main.java.srcDirs = »
sourceSets.test.scala.srcDir "src/test/java"
sourceSets.test.java.srcDirs = »