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🤖 Polymarket in the AI Era: Claude Helps Ordinary Traders Earn Up to $800 Daily
The prediction market is undergoing a transformation right before our eyes. If creating trading bots was once a privilege of programmers, now, thanks to artificial intelligence, the barrier has been significantly lowered.
Expert frostikk reveals how the combination of neural network Claude and Polymarket changes the game. The main points are as follows:
🔹 Code is no longer a barrier. Traders without a technical background are using Claude to write Python scripts. Simply describe the strategy in natural language, and the AI will provide ready-made logic with API connections.
🔹 Popular strategies:
Arbitrage: Searching for price differences between Polymarket and other platforms. Following 'whales': Automatically copying the trades of large holders. Micro scalping: Participating in the 15-minute BTC market.
💰 Impressive numbers:
A simple arbitrage bot can earn about $25 per hour. Advanced market-making strategies can yield between $500 and $800 daily. Monthly case: Through high-frequency small trades, capital increased from $20,000 to $215,000 in 30 days.
⚠️ Important reminder: Automation is not a "printing press." Success depends on discipline and the correctness of logic. Errors in the bot's code can drain your account faster than you can hit the "stop" button.
The future of prediction markets lies in algorithms. The only question is whose bot is smarter. 🚀
#Polymarket #AI #Claude #CryptoNews
#Arbitrage
The prediction market is undergoing a transformation right before our eyes. If creating trading bots was once a privilege of programmers, now, thanks to artificial intelligence, the barrier has been significantly lowered.
Expert frostikk reveals how the combination of neural network Claude and Polymarket changes the game. The main points are as follows:
🔹 Code is no longer a barrier. Traders without a technical background are using Claude to write Python scripts. Simply describe the strategy in natural language, and the AI will provide ready-made logic with API connections.
🔹 Popular strategies:
Arbitrage: Searching for price differences between Polymarket and other platforms. Following 'whales': Automatically copying the trades of large holders. Micro scalping: Participating in the 15-minute BTC market.
💰 Impressive numbers:
A simple arbitrage bot can earn about $25 per hour. Advanced market-making strategies can yield between $500 and $800 daily. Monthly case: Through high-frequency small trades, capital increased from $20,000 to $215,000 in 30 days.
⚠️ Important reminder: Automation is not a "printing press." Success depends on discipline and the correctness of logic. Errors in the bot's code can drain your account faster than you can hit the "stop" button.
The future of prediction markets lies in algorithms. The only question is whose bot is smarter. 🚀
#Polymarket #AI #Claude #CryptoNews
#Arbitrage
Grok-3: Is Elon Musk's New AI Worth Comparing to ChatGPT, Claude, Gemini?
Elon Musk caused a stir again with the launch of #grok3 , the latest AI product from xAI, aiming to compete with giants like GPT-4o, Claude 3.5 Sonnet, Gemini, and DeepSeek. But how powerful is Grok-3 really? Let's compare!
1. Creation: Grok-3 beats Claude
Grok-3 excels in storytelling, surpassing #Claude 3.5 Sonnet with rich content, quality characters, and engaging storytelling. However, the content is still not perfect, with some details that may feel restrictive to the reader.
1. Creation: Grok-3 beats Claude
Grok-3 excels in storytelling, surpassing #Claude 3.5 Sonnet with rich content, quality characters, and engaging storytelling. However, the content is still not perfect, with some details that may feel restrictive to the reader.
🤖 The #AI race is heating up: #ChatGPT , #Claude , #Grok , #Cursor ... and dozens more. Just 3 years ago, 90% of this stuff didn’t exist.
Now it's not about whether AI works; it's which AI works best for what.
Some write like copywriters, some code like senior developers, and some organize like ops leads.
What’s in your stack? And what’s still missing from the perfect AI toolkit?
Now it's not about whether AI works; it's which AI works best for what.
Some write like copywriters, some code like senior developers, and some organize like ops leads.
What’s in your stack? And what’s still missing from the perfect AI toolkit?
📛 Anthropic have created a "microscope" for LLM - now you can see how AI thinks
Anthropic have been working on the interpretability of neural networks for a long time. Their past SAE (Sparse Autoencoder) method has already been adopted by OpenAI and Google, and now they offer a new way to "parse" AI into thoughts - Circuit Tracing.
🟢 How does it work?
🍒 They take an off-the-shelf language model and select a task.
😘 Replace some components of the model with simple linear models (Cross-Layer Transcoder).
😘 Train these replaced parts to mimic the original model, minimizing the difference in output.
🍒 Now you can see how information "flows" through all the layers of the model.
😘 Based on this data, an attribution graph is built - it shows which attributes influence each other and form the final answer.
🟢 What interesting things were discovered in Claude's brain?
🟠 The LLM "thinks ahead." For example, when she writes a poem, she plans the rhyme scheme in advance, even before she starts a new line.
🟠 Math is not just about memorization. Turns out the model is actually calculating, not just retrieving memorized answers.
🟠 Hallucinations have a cause. A specific "answer is known" trigger is found. If it is triggered in error - the model starts making things up.
🟠 Fun fact: if you tell the model the answer to a problem right away, it will think backwards - come up with a plausible path to that answer.
#claude #AI
🟢 How does it work?
🍒 They take an off-the-shelf language model and select a task.
😘 Replace some components of the model with simple linear models (Cross-Layer Transcoder).
😘 Train these replaced parts to mimic the original model, minimizing the difference in output.
🍒 Now you can see how information "flows" through all the layers of the model.
😘 Based on this data, an attribution graph is built - it shows which attributes influence each other and form the final answer.
🟢 What interesting things were discovered in Claude's brain?
🟠 The LLM "thinks ahead." For example, when she writes a poem, she plans the rhyme scheme in advance, even before she starts a new line.
🟠 Math is not just about memorization. Turns out the model is actually calculating, not just retrieving memorized answers.
🟠 Hallucinations have a cause. A specific "answer is known" trigger is found. If it is triggered in error - the model starts making things up.
🟠 Fun fact: if you tell the model the answer to a problem right away, it will think backwards - come up with a plausible path to that answer.
#claude #AI
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