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Bitget: Ranked top 4 in global daily trading volume!
BTC market share62.10%
New listings on Bitget: Pi Network
BTC/USDT$86420.92 (+1.85%)Fear and Greed Index44(Fear)
Altcoin season index:0(Bitcoin season)
Coins listed in Pre-MarketPAWS,WCTTotal spot Bitcoin ETF netflow -$157.8M (1D); -$22M (7D).Welcome gift package for new users worth 6200 USDT.Claim now
Trade anytime, anywhere with the Bitget app. Download now
Bitget: Ranked top 4 in global daily trading volume!
BTC market share62.10%
New listings on Bitget: Pi Network
BTC/USDT$86420.92 (+1.85%)Fear and Greed Index44(Fear)
Altcoin season index:0(Bitcoin season)
Coins listed in Pre-MarketPAWS,WCTTotal spot Bitcoin ETF netflow -$157.8M (1D); -$22M (7D).Welcome gift package for new users worth 6200 USDT.Claim now
Trade anytime, anywhere with the Bitget app. Download now
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Grok priceXAI
Not listed
Quote currency:
USD
Data is sourced from third-party providers. This page and the information provided do not endorse any specific cryptocurrency. Want to trade listed coins? Click here
$0.002226-1.46%1D
Price chart
TradingView
Last updated as of 2025-04-02 18:06:19（UTC+0）
Market cap:--
Fully diluted market cap:--
Volume (24h):--
24h volume / market cap:0.00%
24h high:$0.002263
24h low:$0.002213
All-time high:$0.03000
All-time low:$0.002000
Circulating supply:-- XAI
Total supply:
--XAI
Circulation rate:0.00%
Max supply:
--XAI
Price in BTC:-- BTC
Price in ETH:40,585.21 ETH
Price at BTC market cap:
--
Price at ETH market cap:
--
Contracts:
0x0009...605ae5d(BNB Smart Chain (BEP20))
How do you feel about Grok today?
Good
BadNote: This information is for reference only.
Price of Grok today
The live price of Grok is $0.002226 per (XAI / USD) today with a current market cap of -- USD. The 24-hour trading volume is $0.00 USD. XAI to USD price is updated in real time. Grok is -1.46% in the last 24 hours. It has a circulating supply of -- .
What is the highest price of XAI?
XAI has an all-time high (ATH) of $0.03000, recorded on .
What is the lowest price of XAI?
XAI has an all-time low (ATL) of $0.002000, recorded on .
Grok price prediction
When is a good time to buy XAI? Should I buy or sell XAI now?
When deciding whether to buy or sell XAI, you must first consider your own trading strategy. The trading activity of long-term traders and short-term traders will also be different. The Bitget XAI technical analysis can provide you with a reference for trading.
According to the XAI 4h technical analysis, the trading signal is Strong buy.
According to the XAI 1d technical analysis, the trading signal is Strong buy.
According to the XAI 1w technical analysis, the trading signal is Strong buy.
What will the price of XAI be in 2026?
Based on XAI's historical price performance prediction model, the price of XAI is projected to reach $0.{8}1745 in 2026.
What will the price of XAI be in 2031?
In 2031, the XAI price is expected to change by +23.00%. By the end of 2031, the XAI price is projected to reach $0.{8}5188, with a cumulative ROI of -100.00%.
Grok price history (USD)
The price of Grok is -80.72% over the last year. The highest price of Grok in USD in the last year was $0.02033 and the lowest price of Grok in USD in the last year was $0.002050.
TimePrice change (%)
Lowest priceHighest price
Lowest priceHighest price 24h-1.46%$0.002213$0.002263
7d-3.64%$0.002181$0.002350
30d-2.20%$0.002181$0.002350
90d-43.04%$0.002050$0.006000
1y-80.72%$0.002050$0.02033
All-time+11.35%$0.002000(--, Today )$0.03000(--, Today )
Grok market information
Grok holdings by concentration
Whales
Investors
Retail
Grok addresses by time held
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Live coinInfo.name (12) price chart
Grok ratings
Average ratings from the community
4.4
This content is for informational purposes only.
About Grok (XAI)
What is Grok (GROK)?
Grok is an interesting new product from xAI, a company founded by Elon Musk. Grok is a conversational AI model that can browse the internet, similar to ChatGPT. It's a memecoin that was launched on the Ethereum blockchain on November 4, 2023, and it aims to provide informative responses with a bit of humor, inspired by Musk's vision.
How does Grok (GROK) Work?
Grok offers a range of exceptional features, including the capacity to combine informative responses with humor and its integration with the xAI Model GROK. Nevertheless, it is important to note that Grok has certain limitations, such as ethical filtering that restricts certain sensitive queries, which is intended to ensure responsible usage.
Large Language Models (LLM) include Grok and GPT-4, which are both types of AI models. Artificial intelligence models have come a long way with the emergence of LLM. These models are trained on vast amounts of natural language data and are used for various tasks, including machine translation, natural language generation, and natural language understanding. LLM captures the semantic and syntactic features of language in large scale data sets, enabling machines to learn the linguistic structure and produce better language responses.
Generative AI is a technology that uses artificial intelligence to create data or content. It generates new content that can be used for creative applications such as image, text, or music synthesis. By leveraging big data and machine learning algorithms, generative AI can create unique and creative data or content for various purposes.
GROK is an improvement on AI model "alignment," which refers to its ability to follow user intentions while also generating less offensive or dangerous output. It also improves on factual correctness and "steerability," which means it can change its behavior according to user requests.
What makes Grok (GROK) Unique?
Grok is the new conversational AI model with internet browsing capabilities, designed to adapt to any situation and offers a unique conversational experience. Ask Grok questions, start discussions, or simply get informative responses with a touch of humor. With its advanced technology inspired by xAI's Grok model, Grok is the perfect assistant for all your needs.
What is the GROK Token?
By holding GROK Tokens, users can enjoy access to AI services and applications at more affordable rates, benefiting both individuals and businesses alike. Furthermore, GROK Tokens can serve as a reward system for contributors such as developers, creators, miners, researchers, and early adopters who enhance and enrich the GROK ecosystem. In essence, GROK Tokens are a valuable asset for those seeking to participate in the cutting-edge realm of AI development within the crypto and blockchain industries.
XAI to local currency
1 XAI to MXN$0.051 XAI to GTQQ0.021 XAI to CLP$2.131 XAI to HNLL0.061 XAI to UGXSh8.121 XAI to ZARR0.041 XAI to TNDد.ت0.011 XAI to IQDع.د2.921 XAI to TWDNT$0.071 XAI to RSDдин.0.241 XAI to DOP$0.141 XAI to MYRRM0.011 XAI to GEL₾0.011 XAI to UYU$0.091 XAI to MADد.م.0.021 XAI to OMRر.ع.01 XAI to AZN₼01 XAI to SEKkr0.021 XAI to KESSh0.291 XAI to UAH₴0.09
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Last updated as of 2025-04-02 18:06:19（UTC+0）
Grok news
What Does FDV Tell Us About 2024’s Top Altcoins — Winners vs. Losers
Hyperliquid’s FDV rose 2.4x as tight supply and soaring demand drove price gains. Ondo surged 3.7x in FDV despite supply growth, with demand outpacing dilution risks. Rapid unlocks caused FDV collapses in Dymension, Wormhole, StarkNet, and XAI tokens.
CoinEdition•2025-03-24 16:00
Top Token Unlocks to Watch This Week: Major Crypto Projects Set for Growth
Xai enables in-game item ownership and trade for traditional gamers without requiring crypto-wallets, expanding access to blockchain economies. Moca Network’s AIR Kit allows seamless digital identity management across platforms, providing users with a universal Web3 account. Delysium’s YKILY Network supports AI agents with decentralized financial infrastructure, ensuring security, scalability, and collaboration.
CryptoFrontNews•2025-03-09 16:00
5 Token Unlocks to Watch for the Second Week of March
This week’s top token unlocks include XAI, MOCA, AGI, CHEEL, and XAV, with over $44 million in new tokens hitting the market.
BeInCrypto•2025-03-09 02:00
Watch Out: 17 Altcoins Have Massive Token Unlocks in the New Week – Here is the Day by Day, Hour by Hour List
CryptoNewsNet•2025-03-02 22:55
Watch Out: 20 Altcoins Have Massive Token Unlocks in the New Week – Here is the Day by Day, Hour by Hour List
Bitcoinsistemi•2025-02-03 02:55
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FAQ
What is the current price of Grok?
The live price of Grok is $0 per (XAI/USD) with a current market cap of -- USD. Grok's value undergoes frequent fluctuations due to the continuous 24/7 activity in the crypto market. Grok's current price in real-time and its historical data is available on Bitget.
What is the 24 hour trading volume of Grok?
Over the last 24 hours, the trading volume of Grok is --.
What is the all-time high of Grok?
The all-time high of Grok is $0.03000. This all-time high is highest price for Grok since it was launched.
Can I buy Grok on Bitget?
Yes, Grok is currently available on Bitget’s centralized exchange. For more detailed instructions, check out our helpful How to buy grok guide.
Can I get a steady income from investing in Grok?
Of course, Bitget provides a strategic trading platform, with intelligent trading bots to automate your trades and earn profits.
Where can I buy Grok with the lowest fee?
Bitget offers industry-leading trading fees and depth to ensure profitable investments for traders. You can trade on the Bitget exchange.
Where can I buy crypto?
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Cryptocurrency investments, including buying Grok online via Bitget, are subject to market risk. Bitget provides easy and convenient ways for you to buy Grok, and we try our best to fully inform our users about each cryptocurrency we offer on the exchange. However, we are not responsible for the results that may arise from your Grok purchase. This page and any information included are not an endorsement of any particular cryptocurrency. Any price and other information on this page is collected from the public internet and can not be consider as an offer from Bitget.
Bitget Insights
Mahnoor-Baloch007
1d
AI agents and AI are related but distinct concepts in the field of artificial intelligence.
AI (Artificial Intelligence)
1. Definition: AI refers to the broad field of study focused on creating intelligent machines that can perform tasks that typically require human intelligence.
2. Characteristics: AI systems can process and analyze large amounts of data, learn from experiences, and make decisions based on that data.
3. Examples: AI-powered chatbots, image recognition systems, and natural language processing tools.
AI Agents
1. Definition: AI agents are a specific type of AI system that can autonomously perform tasks on behalf of a user or another system.
2. Characteristics: AI agents have the ability to design their own workflow, utilize available tools, and interact with external environments to achieve complex goals.
3. Examples: AI-powered trading bots, autonomous vehicles, and smart home systems.
Key Differences
1. Autonomy: AI agents have a higher level of autonomy compared to traditional AI systems, allowing them to make decisions and take actions independently.
2. Interactivity: AI agents can interact with their environment and other systems, whereas traditional AI systems may only process data internally.
3. Proactivity: AI agents can anticipate and prevent problems, whereas traditional AI systems may only react to problems after they occur.
4. Complexity: AI agents often require more complex decision-making and problem-solving capabilities compared to traditional AI systems.
In summary, while AI refers to the broader field of artificial intelligence, AI agents are a specific type of AI system that can autonomously perform tasks, interact with their environment, and make decisions independently.
Thank you...🙂
$BTC $ETH $SOL $PI $XRP $DOGE $SHIB $SUNDOG $MEME $AI $XAI $PEPECOIN $PIPPIN $ORAI $ETC $WHY $U2U
SUNDOG+6.08%
BTC+1.54%
Crypto_inside
1d
Machine learning ❌ Traditional learning. 🧐😵💫
Machine learning and traditional learning are two distinct approaches to learning and problem-solving.
Traditional Learning:
1. Rule-based: Traditional learning involves explicit programming and rule-based systems.
2. Human expertise: Traditional learning relies on human expertise and manual feature engineering.
3. Fixed models: Traditional learning uses fixed models that are not updated automatically.
Machine Learning:
1. Data-driven: Machine learning involves learning from data and improving over time.
2. Algorithmic: Machine learning relies on algorithms that can learn from data and make predictions.
3. Adaptive models: Machine learning uses adaptive models that can update automatically based on new data.
Key Differences:
1. Learning style: Traditional learning is rule-based, while machine learning is data-driven.
2. Scalability: Machine learning can handle large datasets and complex problems, while traditional learning is limited by human expertise.
3. Accuracy: Machine learning can achieve higher accuracy than traditional learning, especially in complex domains.
Advantages of Machine Learning:
1. Improved accuracy: Machine learning can achieve higher accuracy than traditional learning.
2. Increased efficiency: Machine learning can automate many tasks, freeing up human experts for more complex tasks.
3. Scalability: Machine learning can handle large datasets and complex problems.
Disadvantages of Machine Learning:
1. Data quality: Machine learning requires high-quality data to learn effectively.
2. Interpretability: Machine learning models can be difficult to interpret and understand.
3. Bias: Machine learning models can perpetuate biases present in the training data.
When to Use Machine Learning:
1. Complex problems: Machine learning is well-suited for complex problems that require pattern recognition and prediction.
2. Large datasets: Machine learning can handle large datasets and identify trends and patterns.
3. Automating tasks: Machine learning can automate many tasks, freeing up human experts for more complex tasks.
When to Use Traditional Learning:
1. Simple problems: Traditional learning is well-suited for simple problems that require explicit programming and rule-based systems.
2. Small datasets: Traditional learning is suitable for small datasets where machine learning may not be effective.
3. Human expertise: Traditional learning relies on human expertise and manual feature engineering, making it suitable for domains where human expertise is essential.
Thank you...🙂
$BTC $ETH $SOL $PI $AI $XAI $BGB $BNB $DOGE $DOGS $SHIB $BONK $MEME $XRP $ADA $U2U $WUF $PARTI $WHY
BTC+1.54%
BGB-1.56%
Crypto_inside
1d
What is Q-learning...🤔🤔??
Q-learning is a type of reinforcement learning algorithm used in machine learning and artificial intelligence. It's a model-free, off-policy learning algorithm that helps agents learn to make decisions in complex, uncertain environments.
Key Components:
1. Agent: The decision-maker that interacts with the environment.
2. Environment: The external system with which the agent interacts.
3. Actions: The decisions made by the agent.
4. Rewards: The feedback received by the agent for its actions.
5. Q-function: A mapping from states and actions to expected rewards.
How Q-learning Works:
1. Initialization: The agent starts with an arbitrary Q-function.
2. Exploration: The agent selects an action and observes the resulting state and reward.
3. Update: The agent updates its Q-function based on the observed reward and the expected reward for the next state.
4. Exploitation: The agent chooses the action with the highest Q-value for the current state.
Advantages:
1. Simple to implement: Q-learning is a straightforward algorithm to understand and code.
2. Effective in complex environments: Q-learning can handle complex, dynamic environments with many states and actions.
Disadvantages:
1. Slow convergence: Q-learning can require many iterations to converge to an optimal policy.
2. Sensitive to hyperparameters: The performance of Q-learning is highly dependent on the choice of hyperparameters.
Q-learning is a powerful algorithm for reinforcement learning, but it can be challenging to tune and may not always converge to an optimal solution.
Thank you...🙂
$BTC $ETH $SOL $PI $AI $XAI $XRP $BGB $BNB $DOGE $DOGS $SHIB $BONK $FLOKI $U2U $WUF $WHY $SUNDOG $COQ $PEPE
SUNDOG+6.08%
BTC+1.54%
Crypto_inside
1d
What is Machine learning..🤔🤔??
Machine learning is a subset of artificial intelligence (AI) that involves training algorithms to learn from data and make predictions, decisions, or recommendations without being explicitly programmed.
Key Characteristics:
1. Learning from data: Machine learning algorithms learn patterns and relationships in data.
2. Improving over time: Machine learning models improve their performance as they receive more data.
3. Making predictions or decisions: Machine learning models make predictions, decisions, or recommendations based on the learned patterns.
Types of Machine Learning:
1. Supervised Learning: The algorithm learns from labeled data to make predictions.
2. Unsupervised Learning: The algorithm learns from unlabeled data to identify patterns.
3. Reinforcement Learning: The algorithm learns through trial and error to achieve a goal.
4. Semi-supervised Learning: The algorithm learns from a combination of labeled and unlabeled data.
5. Deep Learning: A subset of machine learning that uses neural networks with multiple layers.
Machine Learning Applications:
1. Image Recognition: Image classification, object detection, and facial recognition.
2. Natural Language Processing (NLP): Text classification, sentiment analysis, and language translation.
3. Speech Recognition: Speech-to-text and voice recognition.
4. Predictive Analytics: Forecasting, regression, and decision-making.
5. Recommendation Systems: Personalized product recommendations.
Machine Learning Algorithms:
1. Linear Regression: Linear models for regression tasks.
2. Decision Trees: Tree-based models for classification and regression.
3. Random Forest: Ensemble learning for classification and regression.
4. Support Vector Machines (SVMs): Linear and non-linear models for classification and regression.
5. Neural Networks: Deep learning models for complex tasks.
Machine Learning Tools and Frameworks:
1. TensorFlow: Open-source deep learning framework.
2. PyTorch: Open-source deep learning framework.
3. Scikit-learn: Open-source machine learning library.
4. Keras: High-level neural networks API.
Machine learning has numerous applications across industries, including healthcare, finance, marketing, and more. Its ability to learn from data and improve over time makes it a powerful tool for solving complex problems.
Thank you...🙂
$BTC $ETH $SOL $PI $AI $XAI $BGB $BNB $DOGE $SHIB $FLOKI $BONK $U2U $WUF $WHY $SUNDOG $PARTI $XRP
SUNDOG+6.08%
BTC+1.54%
Kanyalal
2d
AI agents and AI are related but distinct concepts in the field of artificial intelligence.
AI (Artificial Intelligence)
1. Definition: AI refers to the broad field of study focused on creating intelligent machines that can perform tasks that typically require human intelligence.
2. Characteristics: AI systems can process and analyze large amounts of data, learn from experiences, and make decisions based on that data.
3. Examples: AI-powered chatbots, image recognition systems, and natural language processing tools.
AI Agents
1. Definition: AI agents are a specific type of AI system that can autonomously perform tasks on behalf of a user or another system.
2. Characteristics: AI agents have the ability to design their own workflow, utilize available tools, and interact with external environments to achieve complex goals.
3. Examples: AI-powered trading bots, autonomous vehicles, and smart home systems.
Key Differences
1. Autonomy: AI agents have a higher level of autonomy compared to traditional AI systems, allowing them to make decisions and take actions independently.
2. Interactivity: AI agents can interact with their environment and other systems, whereas traditional AI systems may only process data internally.
3. Proactivity: AI agents can anticipate and prevent problems, whereas traditional AI systems may only react to problems after they occur.
4. Complexity: AI agents often require more complex decision-making and problem-solving capabilities compared to traditional AI systems.
In summary, while AI refers to the broader field of artificial intelligence, AI agents are a specific type of AI system that can autonomously perform tasks, interact with their environment, and make decisions independently.
Thank you...🙂
$BTC $ETH $SOL $PI $XRP $DOGE $SHIB $SUNDOG $MEME $AI $XAI $PEPECOIN $PIPPIN $ORAI $ETC $WHY $U2U
SUNDOG+6.08%
BTC+1.54%
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