Large Language Models of Code Fail at Completing Code with Potential Bugs paper page: https://
huggingface.co/papers/2306.03
438
… Large language models of code (Code-LLMs) have recently brought tremendous advances to code completion, a fundamental feature of programming assistance and code
MACHINE LEARNING
-
Large Language Models Struggle With Code Containing Potential Bugs
By
–
-
Static Evaluation of Code Completion by Large Language Models
By
–
A Static Evaluation of Code Completion by Large Language Models paper page: https://
huggingface.co/papers/2306.03
203
… Large language models trained on code have shown great potential to increase productivity of software developers. Several execution-based benchmarks have been proposed to -
Deductive Verification of Chain-of-Thought Reasoning in Large Language Models
By
–
Deductive Verification of Chain-of-Thought Reasoning paper page: https://
huggingface.co/papers/2306.03
872
… Large Language Models (LLMs) significantly benefit from Chain-of-Thought (CoT) prompting in performing various reasoning tasks. While CoT allows models to produce more comprehensive -
UntetherAI Joins MLCommons to Accelerate ML Innovation
By
–
@UntetherAI has joined @MLCommons to accelerate #ML innovation! We are thrilled to collaborate and contribute to their renowned MLPerf benchmarks in our commitment to providing high-performance, energy-efficient #AI inference acceleration. Press Release: https://
tinyurl.com/4yswn2n7 -
Free Deep Learning Course with Lightning AI: Fundamentals and Modern Approaches
By
–
Deep Learning Fundamentals – Lightning AI This is a free deep learning course that covers foundational techniques and algorithms in deep learning and modern approaches. I like the way course is conducted: 10 units with bit-sized videos, quizzes, and exercises. Super
-
Real-time performance challenges in multi-thousand GPU clusters
By
–
Is anyone doing real time work on the multi-thousand GPU clusters that are popping up? It should be possible with the right software, but I generally see step times measured in seconds rather than milliseconds.
-
GPT Demonstrates Strong Performance in Feed Ranking Systems
By
–
GPT is Rather Good at Feed Ranking https://
bit.ly/3MznMBO #MachineLearning #AI #DataScience #DeepLearning -
Apple Frameworks Need Optimization for ML Model Development
By
–
Of course, Apple frameworks are far from optimized for ML model development. They're actually pretty bad! But the bar is ridiculously low for Apple here to improve on, and it seems like it's starting to do a lot of foundational work here to own those workflows.
-
Apple’s ML Strategy: Fine-tuning and Quantizing Models for Production
By
–
Based on the announcements, as well as some descriptions from WWDC sessions, we can see a potential ML development route Apple is targeting: fine-tuning and quantizing ML models to put into prod.
-
Apple Uses Transformers for Autocorrect, Positions Mac Studio for ML
By
–
There were two essentially throwaway lines from WWDC yesterday. First, it's using a transformers-based approach for autocorrect, of all things. And the second was it wanted to semi-position its new Mac Studio with a comically large level of memory for ML training workflows.