Remove Auto-complete Remove Explainability Remove Software Development
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AI and coding: How Seattle tech companies are using generative AI for programming

Flipboard

Diamond Bishop , CEO and co-founder at Augmend , a Seattle collaboration software startup Diamond Bishop, CEO of Augmend. Augmend Photo) “AI is making it so small startups like ours can accelerate all aspects of the software development lifecycle. It’s helpful with generating much of the boilerplate for unit tests.

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Top 50+ AI Coding Assistant Tools in 2023

Marktechpost

GitHub Copilot GitHub Copilot is an AI-powered code completion tool that analyzes contextual code and delivers real-time feedback and recommendations by suggesting relevant code snippets. Tabnine Tabnine is an AI-based code completion tool that offers an alternative to GitHub Copilot.

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Deploy Meta Llama 3.1-8B on AWS Inferentia using Amazon EKS and vLLM

AWS Machine Learning Blog

8B model With the setup complete, you can now deploy the model using a Kubernetes deployment. Complete the following steps: Check the deployment status: kubectl get deployments This will show you the desired, current, and up-to-date number of replicas. AWS_REGION.amazonaws.com/${ECR_REPO_NAME}:latest Deploy the Meta Llama 3.1-8B

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Boost inference performance for Mixtral and Llama 2 models with new Amazon SageMaker containers

AWS Machine Learning Blog

This version offers support for new models (including Mixture of Experts), performance and usability improvements across inference backends, as well as new generation details for increased control and prediction explainability (such as reason for generation completion and token level log probabilities).

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Improve performance of Falcon models with Amazon SageMaker

AWS Machine Learning Blog

The decode phase includes the following: Completion – After the prefill phase, you have a partially generated text that may be incomplete or cut off at some point. The decode phase is responsible for completing the text to make it coherent and grammatically correct. The default is 32.

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How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch

AWS Machine Learning Blog

In this post, we explain how we built an end-to-end product category prediction pipeline to help commercial teams by using Amazon SageMaker and AWS Batch , reducing model training duration by 90%. The project was completed in a month and deployed to production after a week of testing.

BERT 119
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HARPA AI Review: How I Finally Tamed My Tab Overload

Unite.AI

Developers can use HARPA AI for writing and inspecting code, answering programming questions, and automating repetitive tasks related to software development. It explains why something might need changing! Immediately, HARPA explained what I had put into Google with related queries! But it doesn't just flag issues.