Skeet: Towards a Lightweight Serverless Framework Supporting Modern AI-Driven App Development
- URL: http://arxiv.org/abs/2405.06164v1
- Date: Fri, 10 May 2024 01:00:20 GMT
- Title: Skeet: Towards a Lightweight Serverless Framework Supporting Modern AI-Driven App Development
- Authors: Kawasaki Fumitake, Shota Kishi, James Neve,
- Abstract summary: Skeet was recently released to general use, alongside an initial evaluation.
Skeet provides an app structure that reflects current trends in architecture, and tool suites that allow developers with minimal knowledge of AI internals to easily incorporate such technologies into their apps and deploy them.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The field of web and mobile software frameworks is relatively mature, with a large variety of tools in different languages that facilitate traditional app development where data in a relational database is displayed and modified. Our position is that many current frameworks became popular during single server deployment of MVC architecture apps, and do not facilitate modern aspects of app development such as cloud computing and the incorporation of emerging technologies such as AI. We present a novel framework which accomplishes these purposes, Skeet, which was recently released to general use, alongside an initial evaluation. Skeet provides an app structure that reflects current trends in architecture, and tool suites that allow developers with minimal knowledge of AI internals to easily incorporate such technologies into their apps and deploy them.
Related papers
- CRUD-Capable Mobile Apps with R and shinyMobile: a Case Study in Rapid Prototyping [0.0]
"Harden" is a Progressive Web Application (PWA) for Ecological Momentary Assessment (EMA) developed mostly in R.
It leverages the shinyMobile package for creating a reactive mobile user interface (UI)
This paper outlines the methodology used to create the Harden application, and discusses the advantages and limitations of the shinyMobile approach to app development.
arXiv Detail & Related papers (2024-09-01T02:27:36Z) - OpenHands: An Open Platform for AI Software Developers as Generalist Agents [109.8507367518992]
We introduce OpenHands, a platform for the development of AI agents that interact with the world in similar ways to a human developer.
We describe how the platform allows for the implementation of new agents, safe interaction with sandboxed environments for code execution, and incorporation of evaluation benchmarks.
arXiv Detail & Related papers (2024-07-23T17:50:43Z) - Inference Optimization of Foundation Models on AI Accelerators [68.24450520773688]
Powerful foundation models, including large language models (LLMs), with Transformer architectures have ushered in a new era of Generative AI.
As the number of model parameters reaches to hundreds of billions, their deployment incurs prohibitive inference costs and high latency in real-world scenarios.
This tutorial offers a comprehensive discussion on complementary inference optimization techniques using AI accelerators.
arXiv Detail & Related papers (2024-07-12T09:24:34Z) - OS-Copilot: Towards Generalist Computer Agents with Self-Improvement [48.29860831901484]
We introduce OS-Copilot, a framework to build generalist agents capable of interfacing with comprehensive elements in an operating system (OS)
We use OS-Copilot to create FRIDAY, a self-improving embodied agent for automating general computer tasks.
On GAIA, a general AI assistants benchmark, FRIDAY outperforms previous methods by 35%, showcasing strong generalization to unseen applications via accumulated skills from previous tasks.
arXiv Detail & Related papers (2024-02-12T07:29:22Z) - Securely extending and running low-code applications with C# [0.0]
Low-code development platforms provide an accessible infrastructure for the creation of software by "citizen developers"
Since citizen developers are usually not specifically trained in software development, they require additional support when writing code.
An approach to leverage the Roslyn compiler platform to implement custom static code analysis rules for low-code development platforms using the.NET platform is demonstrated.
arXiv Detail & Related papers (2023-07-12T09:32:31Z) - Disappearing frameworks explained [0.0]
Disappearing frameworks show their meaning as an emerging topic within the space of web application development.
The purpose of this short book is to give a quick introduction to disappearing frameworks and show their meaning as an emerging topic within the space of web application development.
arXiv Detail & Related papers (2023-05-29T07:21:38Z) - A comparison between traditional and Serverless technologies in a
microservices setting [0.0]
This study implements 9 prototypes of the same microservice application using different technologies.
We use Amazon Web Services and start with an application that uses a more traditional deployment environment (Kubernetes)
Migration to a serverless architecture is performed by combining and analysing the impact (both cost and performance) of the use of different technologies such as AWS ECS Fargate, AWS, DynamoDBDB.
arXiv Detail & Related papers (2023-05-23T10:56:28Z) - YMIR: A Rapid Data-centric Development Platform for Vision Applications [82.67319997259622]
This paper introduces an open source platform for rapid development of computer vision applications.
The platform puts the efficient data development at the center of the machine learning development process.
arXiv Detail & Related papers (2021-11-19T05:02:55Z) - Federated and continual learning for classification tasks in a society
of devices [59.45414406974091]
Light Federated and Continual Consensus (LFedCon2) is a new federated and continual architecture that uses light, traditional learners.
Our method allows powerless devices (such as smartphones or robots) to learn in real time, locally, continuously, autonomously and from users.
In order to test our proposal, we have applied it in a heterogeneous community of smartphone users to solve the problem of walking recognition.
arXiv Detail & Related papers (2020-06-12T12:37:03Z) - FastReID: A Pytorch Toolbox for General Instance Re-identification [70.10996607445725]
General Instance Re-identification is a very important task in the computer vision.
We present FastReID as a widely used software system in JD AI Research.
We have implemented some state-of-the-art projects, including person re-id, partial re-id, cross-domain re-id and vehicle re-id.
arXiv Detail & Related papers (2020-06-04T03:51:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.