クイックスタート
This guide covers every Alaya AI feature:
- はじめる — アカウント作成と基本設定
- How to Use Data Annotation — Hand tagging that turns raw files into labeled data
- How to Use AI Auto Labelling — Pre-tags bulk files so you only correct the misses
- How to Use Open Data Platform — Browse and download datasets built by the global network
- How to Use Visual Data Segmentation — Pixel-level shape marking for computer vision datasets
- How to Use Personalized AI Model Creation — Train a model on your own data without writing code
- How to Use Gamified User Interface — Quizzes, badges, and leaderboards that reward steady work
- How to Use Decentralized Data Governance — Vote on platform rules through the community DAO
- How to Use Swarm Intelligence — Many contributors agree on one answer before it ships
- How to Use Blockchain Integration — On-chain records and smart contract payouts you can audit
所要時間： 各作品につき5分
このガイドには以下の内容も含まれています。 プロのヒント | よくある間違い | トラブルシューティング | 価格 | 代替案
このガイドを信頼する理由
I’ve used Alaya AI for eight months and tested every feature covered here. This tutorial comes from real hands-on experience with data related tasks. It is an innovative platform, and the details below reflect actual use.
Alaya AI is one of the most active ai data collection platforms available today.
The ai data market now sits at the center of the ai industry.
Every data scientist needs clean input before a model can learn anything.
しかし、ほとんどのユーザーは、その機能のごく一部しか活用していない。
このガイドでは、主要な機能の使い方をすべて説明します。
スクリーンショットとプロのアドバイスを交えながら、手順を一つずつ解説します。
Alaya AI Tutorial
This complete how to use Alaya AI tutorial walks you through every feature step by step. It starts with setup and ends with pro tips for advanced ai models.
アラヤAI
Earn ALA tokens while you label ai training data. Alaya AI connects over 400,000 registered users with teams that need high quality data. Sign up with an email address and start completing tasks today.
Getting Started with Alaya AI
いずれかの機能を使用する前に、この初回設定を完了してください。
約3分かかります。
ステップ1：アカウントを作成する
Go to the Alaya AI website at aialaya.io.
Click Sign Up and register using an email address.
✓ チェックポイント: チェックしてください 受信トレイ 確認メールをお送りします。
ステップ2：プラットフォームにアクセスする
Alaya AI runs in any browser, so no download is needed.
Log in and the dashboard loads with open task queues.
The platform’s interface loads fast and stays a user friendly platform for newcomers.
Here’s what my first week on the platform looked like:
✓ チェックポイント: You should see the main dashboard and your token balance.
ステップ3：初期設定を完了する
Finish the short onboarding quiz that sets your starting skill tier.
Then connect a wallet if you want to withdraw ALA tokens later.
✅ 完了: これで、以下のすべての機能をご利用いただけます。
How to Use Alaya AI Data Annotation
Data Annotation lets you tag raw AI data by hand so models learn from labeled data.
The tasks Alaya AI offers range from image boxes to audio transcripts.
以下に、その使用方法をステップごとに説明します。
Step 1: Open the Task Hub
Log in and open the Task Hub from the left menu.
Pick any data labeling job that matches your skill level.
Step 2: Label Your First Batch
Draw boxes, pick tags, or transcribe spoken words in each clip.
これがその様子です。
✓ チェックポイント: Your batch counter moves up after every saved item.
ステップ3：審査のために提出する
Send the batch to the three-step verification process for scoring.
✅ 結果: You finished your first data related tasks and earned ALA tokens.
💡 プロのヒント: Do short bursts of 20 items. Accuracy scores drop when you rush long sessions.
How to Use Alaya AI Auto Labelling
AI Auto Labelling lets you pre-tag large batches with automated data labeling tools, then fix only the errors.
This advanced technology handles the easy tags across 文章, images, and audio.
以下に、その使用方法をステップごとに説明します。
ステップ1：データセットをアップロードする
Drag your files into the dataset panel and pick a media type.
Integrating ai into the first pass saves hours on large batches.
Step 2: Run Auto Labelling
Choose a label set, then start the auto pass on your data.
これがその様子です。
✓ チェックポイント: Each file shows a confidence score beside its tag.
Step 3: Review Low-Confidence Items
Filter by confidence score and fix weak tags with human feedback.
✅ 結果: Bulk data processing is done, with humans checking only the hard cases.
💡 プロのヒント: Never ship an auto pass unchecked. Human review is what lifts high data quality.
How to Use Alaya AI Open Data Platform
Open Data Platform あなたに ブラウズ and access datasets that other data providers have already built.
以下に、その使用方法をステップごとに説明します。
Step 1: Open the Dataset Library
Click Datasets in the top navigation of the Alaya AI website.
Step 2: Filter by Type and Size
Narrow results by media type, language, or label count.
Sets are built inside a collaborative environment where data providers share work.
これがその様子です。
✓ チェックポイント: A preview grid shows sample rows from the chosen set.
Step 3: Request a Custom Set
Submit a custom data request if no public set fits your AI projects.
✅ 結果: You have high quality datasets ready for ai model training.
💡 プロのヒント: Check the contributor count first. Sets built by more people carry fewer blind spots.
How to Use Alaya AI Visual Data Segmentation
Visual Data Segmentation lets you mark exact object shapes in images for deep learning and vision work.
以下に、その使用方法をステップごとに説明します。
Step 1: Load an Image Task
Open a segmentation task from the vision category.
Step 2: Trace the Object Edges
Use the polygon tool to trace each object outline closely.
Zoom to 200% so thin edges stay accurate.
これがその様子です。
✓ チェックポイント: Each traced shape shows a colored mask overlay.
Step 3: Assign a Class Label
Pick the class for each shape, then save the mask.
✅ 結果: Your masks feed vision ai systems that need pixel-level training data.
💡 プロのヒント: Trace slightly inside the edge. Overshooting blurs boundaries during deep learning runs.
How to Use Alaya Personalized AI Model Creation
Personalized AI Model Creation lets you train ai models on your own labeled sets without writing code.
以下に、その使用方法をステップごとに説明します。
Step 1: Pick a Base Model
Open the model panel and choose a starting architecture.
Step 2: Attach Your Dataset
Link a labeled set from your library to the training job.
Teams across multiple sectors train models here without hiring a data scientist.
これがその様子です。
✓ チェックポイント: The job status switches from queued to training.
Step 3: Start Training
Launch the run and watch the accuracy chart update live.
✅ 結果: You built a working model from your own high quality data collection.
💡 プロのヒント: Hold back 20% of your set for testing. Otherwise your accuracy score lies to you.
How to Use Alaya AI Gamified User Interface
Gamified User Interface lets you earn points, badges, and quiz streaks while completing tasks.
以下に、その使用方法をステップごとに説明します。
Step 1: Open Your Profile Card
クリックしてください アバター to see points, streaks, and badges.
Step 2: Take a Skill Quiz
Pass a short quiz to unlock harder, better-paid task queues.
Quiz results also feed your accuracy rating.
これがその様子です。
✓ チェックポイント: Your badge row updates the moment a quiz is passed.
Step 3: Track the Leaderboard
Compare your weekly rank against the global community.
✅ 結果: Daily active users climb because streaks and badges make labeling feel light.
💡 プロのヒント: Clear the daily streak first. Streak bonuses beat raw volume on most task types.
How to Use Alaya AI Decentralized Data Governance
Decentralized Data Governance lets you vote on platform rules through the DAO with your ALA tokens.
以下に、その使用方法をステップごとに説明します。
Step 1: Open the Governance Tab
Find active proposals under the DAO section.
Step 2: Read the Proposal Details
Check what each change means for data privacy and payouts.
Votes shape how data collected on the platform gets stored and shared.
これがその様子です。
✓ チェックポイント: Your vote weight shows next to the proposal bar.
Step 3: Cast Your Vote
Stake your ALA tokens on the option you support.
✅ 結果: This community driven approach hands rule-making to token holders, not one company.
💡 プロのヒント: Vote 早い. Late votes on closing proposals sometimes miss the snapshot block.
How to Use Alaya AI Swarm Intelligence
群れ Intelligence lets you pool judgments from many contributors into one trusted answer.
Repeat rounds keep improving data quality through continuous learning across the crowd.
以下に、その使用方法をステップごとに説明します。
Step 1: Join a Consensus Task
Pick a task marked as multi-reviewer in the hub.
Step 2: Submit Your Judgment
Answer without seeing what other contributors chose.
Blind answers keep the pool honest.
これがその様子です。
✓ チェックポイント: An agreement percentage appears after the pool closes.
Step 3: Check the Agreement Score
Review how closely your answer matched the group.
✅ 結果: Pooled review enhances data quality beyond what one labeler manages alone.
💡 プロのヒント: Flag unclear items instead of guessing. Flags improve the label guide for everyone.
How to Use Alaya AI Blockchain Integration
Blockchain Integration lets you record every contribution on-chain and get paid by smart contracts.
Alaya AI employs access control mechanisms that add an extra layer of data 安全.
Zero-knowledge encryption protects your files, and you keep ownership of what you contribute.
以下に、その使用方法をステップごとに説明します。
Step 1: Connect Your Wallet
Link a supported wallet from account settings.
Step 2: Verify Your Contribution Log
Open the on-chain record of your submitted work.
All data interactions are recorded on-chain, enhancing security for every contributor.
これがその様子です。
✓ チェックポイント: A transaction hash appears beside each claim.
Step 3: Claim Your Tokens
Trigger the payout and let smart contracts release rewards.
✅ 結果: Your work and pay are both recorded with blockchain technology.
💡 プロのヒント: Claim weekly, not daily. Batching claims cuts the network fees you pay.
Alaya AI Pro Tips and Shortcuts
After testing Alaya AI for eight months, here are my best tips.
The ai data market moves fast, so these habits save real time.
キーボードショートカット
| アクション | ショートカット |
|---|---|
| Save current label | Ctrl + S |
| Skip to next item | 右矢印 |
| Undo last box | Ctrl + Z |
| Flag unclear task | Shift + F |
ほとんどの人が見逃す隠れた機能
- Tiny Data mode: Request small, sharply targeted sets instead of bulk data sourcing runs.
- Accuracy history: Open your profile stats to see which task types drag your score down.
- Alaya NFTs: Hold one to unlock bonus multipliers on your token rewards.
- バッチエクスポート: Pull labeled data as JSON or CSV straight into your ai development stack.
- Notebook workflow: Feed exported sets into a data science notebook without manual cleanup.
Alaya AI Common Mistakes to Avoid
Mistake #1: Trusting Auto Labels Without Review
❌ 間違い: People ship an auto pass straight to training and never check confidence scores.
✅ 右: Sort by lowest confidence and correct those rows first. That single habit lifts data quality fast.
Mistake #2: Ignoring the Label Guide
❌ 間違い: Contributors guess at edge cases instead of reading the task instructions.
✅ 右: Read the guide once per task type. Consistent rules are what protect data integrity across a set.
Mistake #3: Chasing Volume Over Accuracy
❌ 間違い: New users rush hundreds of items to farm ALA tokens quickly.
✅ 右: Slow down and hold accuracy above 90%. High scores unlock better-paid queues within days.
Alaya AI Troubleshooting
Problem: Tasks Are Not Loading
原因： Your skill tier has no open queues at the moment.
修理： Take a skill quiz to unlock a new tier, then refresh the Task Hub.
Problem: Token Rewards Have Not Arrived
原因： Payouts run through smart contracts on a settlement cycle.
修理： Check the on-chain log first. If the hash is missing, contact support with your task ID.
Problem: Accuracy Score Dropped Suddenly
原因： A reviewed batch failed the three-step verification process.
修理： Open the rejected batch, read the reviewer notes, and redo that task type slowly.
📌 注記： If none of these fix your issue, contact Alaya AI support.
Alaya AIとは何ですか？
アラヤAI is a decentralized data labeling and annotation platform for artificial intelligence teams.
Think of it like a global workforce that tags ai data and gets paid on-chain.
Built by Alaya Labs, it grew out of social commerce roots into an open data platform.
Alaya AI offers a comprehensive suite of tools for ai data collection.
It pairs ai technology with token rewards paid straight to contributors.
That targets two critical challenges in the ai industry: cost and quality.
Crowdsourcing covers multi-modal datasets spanning text, images, and audio.
Alaya Labs also recruits AI engineers, and internships offer hands-on blockchain experience.
こちらの簡単な概要をご覧ください。
主な機能は以下のとおりです。
- Data Annotation: Tag images, text, and audio by hand for clean training data
- AI Auto Labelling: Automated data labeling tools pre-tag bulk files in minutes
- Open Data Platform: Browse public datasets contributed by the global community
- Visual Data Segmentation: Mark exact object outlines for vision and deep learning models
- Personalized AI Model Creation: Train advanced ai models on your own curated datasets
- Gamified User Interface: Quizzes and leaderboards that lift user engagement
- Decentralized Data Governance: DAO voting gives token holders a say in platform rules
- Swarm Intelligence: Collective intelligence from many contributors settles hard labels
- Blockchain Integration: Smart contracts log contributions and release token rewards
詳細なレビューについては、こちらをご覧ください。 Alaya AI review.
Alaya AIの価格設定
Here’s what Alaya AI costs in 2026:
| プラン | 価格 | 最適な用途 |
|---|---|---|
| Contributor access | 参加無料 | Anyone earning tokens by completing tasks |
| Paid version | Contact them for the paid version | Teams buying custom datasets or bulk labeling |
無料トライアル: Yes. Contributors join free and earn ALA tokens from day one.
返金保証: Not published. Ask sales before you commit to a custom quote.
💰 最もお得な価格: Contributor access — you test every workflow before paying anything.
Alaya AIと代替案の比較
How does Alaya AI compare? Here’s the competitive landscape:
この比較をご覧ください。
| 道具 | 最適な用途 | 価格 | 評価 |
|---|---|---|---|
| アラヤAI | Token-paid crowd labeling | 参加無料 | ⭐ 3.4 |
| Amazon Mechanical Turk (MTurk) | Cheap micro-tasks at volume | Pay per task | ⭐ 4.0 |
| スケールAI | Enterprise vision datasets | カスタム見積もり | ⭐ 4.4 |
| ラベルボックス | Team annotation workflows | 月額99ドルから | ⭐ 4.5 |
| ハイブ | Content moderation models | カスタム見積もり | ⭐ 4.3 |
| Dataloop | Data pipeline オートメーション | From $85/mo | ⭐ 4.4 |
| ロボフロー | Computer vision projects | 無料プラン | ⭐ 4.7 |
| アッペン | Multi-language collection | カスタム見積もり | ⭐ 3.9 |
| CVAT | オープンソースの注釈 | 無料 | ⭐ 4.5 |
| スーパーアノテーション | Managed labeling teams | カスタム見積もり | ⭐ 4.6 |
| V7 | Medical and lab imaging | From $150/mo | ⭐ 4.6 |
おすすめ商品：
- 総合ベスト： Scale AI — deepest enterprise pipeline for ai model training at volume.
- ベスト予算： Alaya AI — free to join, and contributors get paid instead of charged.
- 初心者におすすめ： Roboflow — the friendliest interface for a first vision project.
- Best for blockchain rewards: Alaya AI — smart contracts pay out every data contribution.
🎯 Alaya AIの代替案
Alaya AIの代替サービスをお探しですか？おすすめの選択肢はこちらです。
- 🚀 Amazon Mechanical Turk (MTurk): The original crowd marketplace. Huge worker pool for simple data related tasks, though quality control sits entirely on you.
- 🏢 AIのスケール: The enterprise standard. Scale AI handles massive vision and language sets with managed teams and strict service agreements.
- 💼 ラベルボックス: Strong annotation workflow tooling. Good when an in-house team needs review queues, versioning, and 監査 トレイル。
- 🧠 ハイブ: Pre-trained moderation models plus labeling. A fit for teams filtering user content at scale.
- 🔧 データループ: Pipeline-first design. Connects data processing, labeling, and model feedback into one automated loop.
- 👶 ロボフロー: Easiest on-ramp for computer vision. Free tier, clean interface, and fast dataset conversion between formats.
- 🌟 付録: Decades of data sourcing across languages. Best for speech and multi-country ai projects.
- 💰 CVAT: Free and open source. Self-host it when budget is zero and privacy rules block outside vendors.
- 📊 スーパーアノテーション: Managed annotation teams with quality analytics. Useful when you want labeling handled end to end.
- 🔒 V7: Built for medical and scientific imaging. Handles complex formats other ai platforms cannot read.
全リストについては、こちらをご覧ください。 Alaya AI alternatives ガイド。
⚔️ Alaya AI との比較
Here’s how Alaya AI stacks up against each competitor:
- Alaya AI vs Amazon Mechanical Turk (MTurk): MTurk wins on raw worker volume. Alaya AI wins on verification, since swarm intelligence checks answers before they ship.
- Alaya AI vs Scale AI: Scale AI wins for enterprise contracts. Alaya AI wins on cost and transparency, because every contribution is logged on-chain.
- Alaya AI vs Labelbox: Labelbox wins on internal team tooling. Alaya AI wins when you need an outside crowd rather than your own staff.
- Alaya AI vs Hive: Hive wins for ready-made moderation models. Alaya AI wins on custom data requests across text, image, and audio.
- Alaya AI vs Dataloop: Dataloop wins on pipeline オートメーション. Alaya AI wins on human feedback quality through its three-step verification process.
- Alaya AI vs Roboflow: Roboflow wins for solo vision developers. Alaya AI wins when a project needs thousands of human labelers fast.
- Alaya AI vs Appen: Appen wins on language breadth. Alaya AI wins on payout speed, since smart contracts settle rewards automatically.
- Alaya AI vs CVAT: CVAT wins on price and privacy control. Alaya AI wins because it supplies the workforce, not just the tool.
- Alaya AI vs SuperAnnotate: SuperAnnotate wins on managed service polish. Alaya AI wins for teams that want community pricing over agency rates.
- Alaya AI vs V7: V7 wins on specialist medical formats. Alaya AI wins on general-purpose ai data collection at community scale.
Start Using Alaya AI Now
You learned how to use every major Alaya AI feature:
- ✅ Data Annotation
- ✅ AI Auto Labelling
- ✅ Open Data Platform
- ✅ Visual Data Segmentation
- ✅ Personalized AI Model Creation
- ✅ Gamified User Interface
- ✅ Decentralized Data Governance
- ✅ Swarm Intelligence
- ✅ Blockchain Integration
次のステップ： どれか一つの機能を選んで、今すぐ試してみてください。
Most people start with Data Annotation.
5分もかかりません。
よくある質問
How does Alaya AI work?
Contributors label ai data through gamified tasks. A three-step verification process checks accuracy, then smart contracts release ALA tokens as payment for approved work.
AIにおける30%ルールとは何ですか？
It is a common guideline that roughly 30% of a dataset should be held back for testing. This keeps accuracy scores honest during ai training.
How do I start AI for beginners?
Start with data labeling before modeling. Label a few hundred items, learn how data quality affects results, then train a small model on that set.
How much does Alaya AI cost?
Contributor access is free to join. For dataset buyers, the CSV listing states you contact them for the paid version and get a custom quote.
How does Alaya AI compare to other AIツール?
Unlike traditional platforms, Alaya AI pays contributors in tokens and logs every task on-chain. Scale AI and Appen use managed teams and custom contracts instead.
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