Whatever AI is integrated into the retail trader's Robinhood platform, rest assured that it will be dumber than the AI that Goldman Sachs is using. The best way to compete is to go completely in the opposite direction in your trading: no algo, no mechanical rules, no AI, go full discretionary.
We shouldn't even have trading platforms, banks, clearing houses etc involved. We should be trading on a peer to peer network that was originally planned back in the 80's.
With everything new, there is always an initial phase of excitement, and it just starts ruining everything. Nothing feels like it used to, everything is losing the human touch and trading won't be any different. I hate the way this is all going.
Well I think they have it with defi or something but it should be a huge peer network like napster...no fees, no market makers, no clearing houses. If the big boys can't get naked fills then they can't manipulate.
Stop day trading or scalping and you won't even notice AI. Let AI fight it out every day/minute/second while you sit back and follow the larger patterns outside of the noise. btw I just scalped the other day for $400, didn't even notice any difference...easy to get in and out, and the swings are even bigger so don't know what everyone is complaining about. Like they say you make your profit trading when you buy, not when you sell. Those who get that statement will get it.
I mean it does really help make things a lot easier sure, but nothing is the same, that was my only point on it.
I did a search to try to understand/distinguish AI from other rules-based software systems. The capabilities most relevant to trading would appear to be "Learn from large datasets" and "Use neural networks", but I wonder if software really has to be considered AI to do those things well (not my field of expertise). Question for those knowledgeable in this area: What does AI bring to trading system development and testing that is different from other sophisticated data analysis software that is not AI? -------- "What discriminates ChatGPT's capabilities from mere rule-based systems, warranting its classification as Artificial Intelligence? Based on the provided search results, ChatGPT is considered AI due to its ability to: Generate human-like responses: ChatGPT uses natural language processing (NLP) and generative pretrained transformers (GPT) to produce responses that mimic human conversation. This capability is a hallmark of artificial intelligence. Learn from large datasets: ChatGPT is trained on massive amounts of text data, allowing it to learn patterns and relationships between words and concepts. This ability to learn from data is a key aspect of AI. Demonstrate advanced conversational capabilities: ChatGPT can engage in back-and-forth conversations, understand context, and adapt to user input. These conversational abilities are a result of its AI-driven NLP and machine learning algorithms. Produce novel, coherent responses: ChatGPT can generate original text that is coherent and meaningful, rather than simply regurgitating pre-existing information. This ability to create new content is a characteristic of AI systems. Use neural networks: ChatGPT’s architecture is based on neural networks, which are a fundamental component of many AI systems. These networks enable the model to learn complex patterns and relationships in data. While some sources, like the Reddit thread, clarify that ChatGPT is not “true AI” in the sense of achieving human-level intelligence or self-awareness, the consensus among the search results is that ChatGPT is indeed an AI system due to its advanced language processing capabilities and ability to generate human-like responses. Key points: ChatGPT’s NLP and GPT architecture enable human-like conversation and response generation. It learns from large datasets and adapts to user input. Neural networks are a core component of its architecture. While not “true AI” in the sense of human-level intelligence, ChatGPT is considered an AI system due to its advanced language processing capabilities."