Jinglianwen Technology: current situation and solutions of data annotation industry

In recent years ,⼈⼯ Intelligence is rising rapidly ,AI Have entered rapidly ⼊ We ⽣ Living . stay ⼈⼯ Intelligent response ⽤ In the background of increasing scenes , As ⼈⼯ The upstream foundation of intelligence ⾏ trade , Data annotation is developing rapidly . At present, the commercialization of artificial intelligence is in computing power 、 The algorithm and technology have basically reached stage maturity , Want to be more grounded , Solve industry specific pain points , It requires a large number of relevant data after annotation processing to support algorithm training , It can be said that the data decide AI The landing degree of .

The industry white paper released by iResearch consulting shows , expect 2025 The market size will break through 113 One hundred million yuan , The compound annual growth rate of the industry reached 23.5%. However , The data annotation industry is also facing many difficult situations behind its vigorous development .

Current situation of data annotation industry

1、 For data service providers Scene annotation capability Ask for promotion

Different should ⽤ Scenarios correspond to different annotation requirements ,⽐ Such as ⾃ The field of mobile driving mainly includes ⾏⼈ distinguish 、 Vehicle identification 、 Traffic light recognition 、 Road recognition and so on ,⽽ The field of intelligent security mainly involves ⾯ Department identification 、⼈ Face detection 、⼈ Face key information points extraction and license plate recognition , This requires a higher level of professionalism for the customized annotation of data service providers .

2、 High threshold callout items Labor costs are too high

Data annotation is still a labor-intensive industry in essence .⼀ Something special ⾏ trade , Such as ⾦ melting 、 Medical care 、 Language 、 The law requires more professionalism for data annotation ⾼, Through traditional annotation ⽅ The law has been difficult to be satisfied ⾜ Current ⾏ Industry demand . therefore , Want to meet the current industry needs , There must be more professional ⼈ Just lose ⼊, This is directly related to the high labor cost .

3、 Labeling efficiency To be improved

When the labor cost cannot be reduced , Improve the proficiency of data annotators , Or the use of efficient annotation tools can effectively improve the annotation efficiency . However, highly skilled taggers are still scarce in the industry , And efficient annotation tools are scarce in the industry .

4、 mark data Of The accuracy needs to be improved

The quality of the data set directly determines the quality of the final model . Machine learning relies on the feeding of massive labeled data , The quality of these data will affect AI Whether it can finally land smoothly will have an important impact . therefore , With the continuous development of science and technology , The industry requires higher and higher accuracy of labeled data , At present, the accuracy of labeled data needs to reach 99%, Even 99.99% To meet the needs of the industry .

5、 Data security cannot be guaranteed

Data security has always been the focus of attention . For example, in the field of security , Because it involves the need to collect private data such as multiple faces , Therefore, ensuring the security of data has become a hard demand of many companies . Many teams do not have their own independently developed annotation platform or data storage server , This makes it difficult to ensure that data is being collected 、 There is no leakage in the three links of marking and storage .

For the above problems , Jinglianwen technology provides corresponding solutions ：

1、 It has a wealth of customized scene building capabilities .

2、 Cultivate the 930 Professional full-time labeling team of , Service costs are reduced 25% above .

3、 An advanced data annotation platform and mature annotation platform are established for data customized annotation services 、 to examine 、 Quality inspection mechanism , Support computer vision （ Pull frame dimension 、 Semantic segmentation 、3D Point cloud annotation 、 Key point marking 、 Line marking 、2D/3D Fusion annotation 、 Target tracking 、 Picture classification, etc ）、 Speech Engineering （ Speech cutting 、ASR Voice transcribe 、 Voice emotion judgment 、 Voiceprint recognition and marking, etc ）、 natural language processing （OCR Transcribe 、 Text information extraction 、NLU Statement generalization ） Multi type data annotation . Under the support of pre marking technology , Marking efficiency can be improved 3 More than times .

4、 Have a comprehensive quality inspection process , Real time accurate estimation and AI Supplementary Examination , The data is accurate to 99% above .

5、 Set strict data privacy security measures , The core principle is that data should never be reused , Set data isolation at the same time 、 Privatization deployment and other security processes and technologies .