DataHive AI

We’re looking for Hive Calls users in the US 🇺🇸 Call friends, earn rewards, and help improve AI voice technology. Conversations are recorded with both participants’ consent. 👉 Join here: https://dhive.app

Some users were unable to withdraw their earned USDC due to an issue on a third-party provider's side.

The problem has now been resolved, and withdrawals are working normally.

We apologize for the inconvenience and appreciate your patience ❤️🐝

🐝 DataHive AI keeps delivering strong Vote Rank results on 🪙 Solana. We're now part of ⚙️ Shinobi Performance Pool, where validators earn their place through performance. Stake SOL with DataHive AI and earn staking rewards!

🐝 Install Hive Calls. Complete the quest. Become a Buzzer! Our Hive Calls quest is live on Galxe! Complete it to unlock the Buzzer role in the DataHive Discord. How to participate: 1. Open the quest on Galxe. 2. Install Hive Calls on Android or iPhone and connect your DataHive account. 3. Complete the quest tasks and claim your Buzzer role. 📞 Keep talking, earn points together Invite a friend and call each other to earn DataHive points for a future airdrop. Both participants earn points for approved minutes. Your conversations help improve voice AI. Calls are recorded only after both participants agree. 🌍 Open worldwide. Talk in any language. Download: Google Play | App Store 👉 Join the Galxe quest: https://app.galxe.com/quest/DataHiveAI/GCXkbtZsd5

Ukrainian Mission Payouts Are Ready 🇺🇦 If you completed one of our Ukrainian paid missions, approved earnings are now available for withdrawal in your DataHive AI Wallet. You can choose between: 🔵USDC — sent directly to your crypto wallet 🔵Tremendous — with payout options available for supported countries and locations Important information about Tremendous

If you are currently located in Ukraine, we strongly recommend choosing USDC. Tremendous currently does not support reward redemption for recipients located in Ukraine, and having a foreign or international bank card alone does not bypass this restriction. If you are currently living or staying in another supported country and have a suitable bank account there, Tremendous may show payout methods available for your location. Please use only the options displayed on your Tremendous redemption page and carefully check the requested banking details before confirming. If you choose an unsupported bank or card option and the payout becomes stuck, DataHive cannot reverse, reroute, or recover the payment through Tremendous. In that situation, contacting DataHive support will unfortunately not help, so please check your available payout options before confirming. If Tremendous is not clearly available for your location, choose USDC instead.

Log in to your DataHive AI Wallet and claim your earnings!

Hive Calls is now available on iOS! 🍎📞 Download the app, call your friends, have real conversations, and earn points together. Now available on the App Store: https://apps.apple.com/by/app/hive-calls/id6812719492?l

A quick note to the DataHive community 🐝 We’re continuing to build real speech and conversation datasets, expanding Hive Calls, and preparing more ways for contributors to earn through actual data work. That includes more paid missions in USD, new languages, and language-specific dialogue tasks inside Hive Calls. Hive Calls for iOS is also coming very soon, opening the app to even more users and conversations. Keep participating, keep your points, and stay with us. There’s much more ahead for DataHive. https://play.google.com/store/apps/details?id=app.dhive.calls

Thank you for all the conversations you’ve been having through Hive Calls. 🐝📞 One small update: starting from now, calls focused mainly on Hive Calls, DataHive, points, rewards, or how to earn may no longer be eligible, because these topics are less useful for the real-world conversational datasets AI companies are looking for.

Don’t worry — calls you’ve already completed before this update can still be eligible.

To help your future calls qualify, we’ve put together a short guide with practical tips and examples of better conversation topics. Read it before your next call: https://datahive.ai/blog/2026/10/06/how-to-get-your-hive-call-approved/

Romanian & Hungarian Mission Payouts Are Ready 💰 If you completed one of our Romanian or Hungarian paid missions, your submission may now be approved and ready for withdrawal. Log in to your DataHive AI dashboard, open your Wallet, and check your available balance. You can now cash out using: 🔵Tremendous — choose from available payout options in your country, such as gift cards, prepaid cards, PayPal, bank transfers, and other supported methods. 🔵USDC — fast, low-fee payouts directly to your crypto wallet. If your mission has been approved, your earnings are waiting for you. Log in, check your Wallet, and claim your payout.

What Makes a Call Eligible? 📞 For a Hive Call to qualify, it should meet a few simple requirements:

• Two real people must join the call

An eligible call is a conversation between two different participants.

• Both people should actively participate

The call should include a real back-and-forth dialogue, not one person doing all the talking.

• The conversation should be meaningful

You can talk naturally, but the dialogue should make sense and feel like a real conversation.

• One person cannot speak from both phones

Switching between two devices and pretending to be both participants will not qualify.

• Any language is allowed

You can speak in the language that feels most natural to both of you.

• Any topic is allowed

There are no fixed themes. Talk about daily life, work, hobbies, travel, plans, or anything else.

• Audio should be clear enough to understand

Studio quality is not required, but heavy background noise, distortion, or unclear speech may prevent the call from qualifying.

• No prerecorded or AI-generated audio

The conversation should happen live between the participants.

• Do not leave the call running in silence

Only real conversation time counts. The idea is simple: have a genuine conversation with another person, in any language, about any topic, and make sure both voices can be clearly heard. Join Hive Calls 🐝

Start with a Welcome Hive Call 🐝📞 New to Hive Calls? Your first conversation can be with AI. Welcome Hive Call is a built-in AI conversation designed to help you get started. You can ask how Hive Calls works, learn about calls, rewards, and the app itself, or simply have a casual conversation and see how the experience feels. By completing your Welcome Hive Call, you can also earn your first welcome points before calling other users. No preparation is needed. Just open the app, start the Welcome Hive Call, ask questions, and talk naturally. Your first Hive Calls conversation is already waiting for you.

Why Hive Calls is different 📞 Most voice datasets are built from isolated recordings: one person reads a sentence, submits it, and moves on. Useful, but real conversations are much more complex. With Hive Calls, two people actually talk to each other. That means the audio contains natural pauses, quick reactions, interruptions, laughter, changes in tone, unfinished thoughts, and all the small details that make human conversation feel real. There are no fixed scripts or predefined topics. You can call friends or other DataHive users and talk about whatever comes naturally: your day, work, travel, hobbies, plans, or anything else. With everyone’s consent, qualifying calls may be recorded and used to create datasets for training and improving voice AI systems. The goal is simple: help AI learn not just what people say, but how real conversations actually happen. Download Hive Calls and start talking 🐝

Hive Calls is Live! 📞🐝 Our new mobile app is here. With Hive Calls, you can call other DataHive users, have real conversations, and earn rewards for qualifying calls. Both participants can earn if they’re eligible and the conversation meets the quality requirements. You can currently earn rewards for up to 40 qualifying minutes per day. Calls must be natural two-way conversations, so silence, prerecorded audio, scripts, or AI voices don’t count. With everyone’s consent, qualifying calls may be recorded and used to create datasets for training and improving voice AI systems. You can also invite friends through your referral link and earn additional rewards after they qualify and complete the required call activity. Download Hive Calls, invite someone you know, and start talking.

P.S. iOS App coming soon 🚀

Hive Calls is coming soon. 📞🐝 A new way to connect, talk, and contribute through real conversations is almost here. Stay tuned. More details are coming shortly.

We’re building a feature that will change how you chat with each other and how you interact with the platform. New ways to engage, new ways to earn. The reveal is getting closer. 🐝

What Audio Compression Does to an AI Dataset 🐝 A WAV file and an MP3 can sound almost identical to us. But for an AI model, they are not always the same. When audio is compressed, some parts of the original signal are removed to make the file smaller. Humans may barely notice the difference, but AI systems can react to those changes differently. This matters because audio often goes through several processing steps before it reaches a dataset. A recording can be captured on a phone, compressed by an app, uploaded to a platform, processed again, and then converted into another format. The words are still there, but the audio itself has changed. That becomes important when a model is trained on one type of audio and later has to work with another. For example, a system trained mostly on clean recordings may perform worse when it starts receiving compressed phone calls or low-quality voice messages. There is another risk too. If most recordings in a dataset come from the same codec or processing pipeline, the model may start learning patterns created by that technology, not just patterns in human speech. This is why a good audio dataset is not only about different speakers, languages and accents. It also needs to reflect the different devices, formats and real-world conditions the model will encounter after deployment. Compression is not automatically bad. In many cases, good-quality compressed audio works perfectly well. The bigger problem is mismatch. If training audio sounds very different from real-world audio, model performance can drop. So file format is not just a storage choice. The way audio is recorded, compressed and processed becomes part of the dataset itself. Extension | Android App

Audio Codecs Are Becoming the Tokenizers of Speech AI Text models don't read sentences as we do. They first break text into smaller pieces called tokens. Modern speech AI is starting to work in a similar way. Instead of processing every tiny point in an audio waveform, neural audio codecs compress speech into smaller digital units, or audio tokens. This makes audio much easier for AI models to process and generate. Early systems such as SoundStream and EnCodec were mainly designed to compress audio while keeping it sounding natural. But researchers realized that the compressed representation could also be used directly by AI models. This creates an interesting challenge: speech contains much more than words. It also carries tone, emotion, rhythm, pauses, accent and information about the speaker. If an audio codec compresses speech too much, some of those details disappear. If it keeps too much information, the model becomes slower and more expensive to run. Newer systems try to find the balance. SpeechTokenizer, for example, separates more language-related information from the acoustic details needed to recreate the voice. Kyutai's Moshi goes even further. Its Mimi codec compresses speech into a relatively small number of audio tokens, allowing the model to listen and speak in real time instead of constantly converting speech into text and back again. This also changes how we should think about speech datasets. If training data contains only clean, scripted recordings, the codec may become good at representing clean speech but worse at capturing laughter, hesitation, emotion, overlapping voices or real-world background noise. And once that information is lost during compression, the model built on top may never get a chance to learn it. So audio codecs are becoming much more than compression tools. They increasingly decide which parts of human speech an AI model can actually understand and reproduce.