Finding high-quality AI data solutions: Challenges for enterprises in the era of big models

The arrival of the big model era is accelerating the transformation of artificial intelligence development from model-centered to data-centered. Qubit Think Tank's "China AIGC Data Annotation Industry Panorama Report" pointed out that currently large model data solutions are blooming in many places, focusing on one-stop, customized services, focusing on the entire life cycle of large model development (including pre-training, supervision and fine-tuning, RLHF, red team testing, benchmark testing, etc.), professional data service providers, large model companies, AI companies and other parties have come up with relevant data solutions, most of which are one-stop, customized services.

A case study using cloud testing data for large model data solutions for vertical industries. The solution can provide high-quality and efficient data for the end-to-end process of large-scale industry models, including continuous pre-training, task fine-tuning, evaluation and joint debugging testing, and Application Release

As a data service provider with industry scenario data collection capabilities and rich data set accumulation, Cloud Measurement Data can deeply customize data collection solutions for industry customers to help obtain high-value scenario data. Using cloud measurement data to provide large-model AI data solutions for vertical industries, we can deeply customize data collection solutions for industry customers to help obtain high-value data. At the same time, when facing fine-tuning tasks, we will provide QA-instruct, Prompt and other text-based task projects and related capability support for multi-modal large models. After the fine-tuning is completed, the cloud test data accumulates evaluation systems and services through personnel and experts in vertical fields to help enterprises evaluate various vertical application areas. And through the data annotation platform with the integrated data base as the core, difficult case data is returned to complete cleaning and annotation, preparing for more efficient model tuning, and promoting the mining of more diversified AI values.

As general artificial intelligence represented by large models continues to evolve, artificial intelligence has shown a trend of moving from dedicated intelligence to general intelligence, from single point breakthroughs to collaborative innovation, and from technology research and development to leading development. The goal of large models is from decentralization to focus, and to industry-wide development.

Fundamentally speaking, the big model is based on industry applications and smart people's livelihood. Cloud Test Data actively lays out the data needs and development trends in the artificial intelligence era, based on high-quality, scenario-based AI training data services, and provides intelligent driving and smart cities through the "triple helix" of data products, data processing tools and data services. , smart IOT, smart finance and other industries provide high-efficiency, high-quality, multi-dimensional, scenario-based data services and strategies, and continue to provide high-value data support for mainstream AI technology fields such as computer vision, speech recognition, natural language processing, and knowledge graphs. .

Currently, as one of the core technologies of a new round of technological revolution, industry large models are expected to push human society towards a more intelligent era. In this new wave of science and technology, Cloud Measurement Data will actively participate in the research and development and innovation of industry large models, give full play to its advantages in the field of artificial intelligence data services, help relevant companies achieve new breakthroughs in artificial intelligence data, and create world-leading industry large model products. ,Promote the high-quality development of the large model industry

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