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Effective Software Development: 7 Ways To Get More From ChatGPT & CopilotĀ 

Dlabs.ai

A recent MIT study points to this , showing how when white-collar workers had access to an assistive chatbot, it took them 40% less time to complete a task, while the quality of their work increased by 18%. The company just axed 28% of its workforce owing to a nosedive in traffic since the advent of LLM-based chatbots.

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AI code-generation software: What it is and how it works

IBM Journey to AI blog

Using generative artificial intelligence (AI) solutions to produce computer code helps streamline the software development process and makes it easier for developers of all skill levels to write code. It can also modernize legacy code and translate code from one programming language to another.

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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. Itā€™s helpful with generating much of the boilerplate for unit tests.

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MetaGPT: Complete Guide to the Best AI Agent Available Right Now

Unite.AI

Last time we delved into AutoGPT and GPT-Engineering , the early mainstream open-source LLM-based AI agents designed to automate complex tasks. Enter MetaGPT ā€” a Multi-agent system that utilizes Large Language models by Sirui Hong fuses Standardized Operating Procedures (SOPs) with LLM-based multi-agent systems.

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MIT Researchers Introduce LILO: A Neuro-Symbolic Framework for Learning Interpretable Libraries for Program Synthesis

Marktechpost

Big language models (LLMs) are becoming increasingly skilled in programming in various contexts, such as finishing partly written code, interacting with human programmers, and even figuring out challenging programming riddles at the competition level. Figure 1: The LILO learning loop overview. (Al)

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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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Best prompting practices for using the Llama 2 Chat LLM through Amazon SageMaker JumpStart

AWS Machine Learning Blog

Llama 2 stands at the forefront of AI innovation, embodying an advanced auto-regressive language model developed on a sophisticated transformer foundation. In this post, we explore best practices for prompting the Llama 2 Chat LLM. The complete example is shown in the accompanying notebook.

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