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ヒューマン・イン・ザ・ループとは何ですか?

Human-in-the-loop (HITL) is a critical process in data annotation that blends human expertise with machine automation. This hybrid approach is highly effective in ensuring high-quality labeled datasets, particularly for machine learning models that power AI (artificial intelligence) applications.

Benefits of human-in-the-loop

Increased accuracy

Combining human expertise with machine automation ensures the highest possible data quality

Efficient handling of edge cases

Machines may struggle with ambiguous or rare cases, but human annotators can provide the necessary context for accurate labeling

Cost efficiency

While human involvement is necessary, the automation of simple tasks reduces the overall cost, making the process efficient and scalable

The HITL process explained

Human-in-the-loop involves a cycle where machines first attempt to label the data using automated techniques. Human annotators then review and correct the results. Here's a breakdown of the HITL process:

  • Machines attempt to label a dataset using pretrained models. This is particularly effective for large volumes of data that contain well-known patterns.

  • Human experts step in to audit and correct any errors or inconsistencies. This is crucial for edge cases where machine predictions might fail.

  • Once human corrections are made, their outcomes are fed back into the ML model to help it improve its future labeling accuracy. The system becomes more intelligent over time, gradually reducing the reliance on human intervention for repetitive tasks.

How Uber AI Solutions can help with human-in-the-loop

We’re uniquely positioned to enhance the HITL process with our comprehensive data annotation services. As AI and ML models become more complex, HITL becomes an essential component for ensuring accurate, reliable data labeling. Here’s how Uber AI Solutions can help streamline and optimize your HITL workflows:

結論

Uber AI Solutions is your trusted partner for scaling human-in-the-loop processes. By combining a global human workforce with advanced tools like uLabel, Uber ensures that your machine learning models are trained with the highest quality data. With scalable, customizable, and cost-efficient HITL workflows, Uber AI Solutions can help you optimize your data annotation pipeline and enhance the performance of your AI applications.

Uber AI ソリューション

大規模なデータのラベリング業務を管理する 9 年以上の専門知識を活かし、画像と動画のアノテーション、テキストのラベリング、3D 点群処理、意味セグメンテーション、意図のタグ付け、感情検出、文書の転記、統合データなど、30 を超える高度な機能を提供しています。生成、物体の追跡、LiDAR アノテーションが含まれます。

Uber の多言語サポートは、ヨーロッパ、アジア、中東、中南米の言語を含む 100 以上の言語をサポートし、多様なグローバルアプリケーションに対応する AI モデルの包括的なトレーニングを提供します。

Uber のソリューションには次のようなものがあります。

  • データの注記とラベリング: テキスト、音声、画像、動画などのさまざまなテクノロジーに対応する、エキスパートによる正確なアノテーションサービス

  • サービスのテスト: 柔軟な SLA、多様なフレームワーク、3,000 以上のテストデバイスにより、効率的なプロダクトテストを実施

  • 言語とローカライゼーション: どこにいても快適に利用できる世界基準のユーザー エクスペリエンス