We have ChatGPT. Here’s what it will take to get to ‘InvestmentGPT’

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From a Google killer to the herald of an AI-controlled humanity, the new ChatGPT app has been making waves — and even scaring people, too — since it launched late last year.

The logical culmination of advanced machine learning technology, ChatGPT seems to know just about everything – apart from how to express itself extremely clearly and eruditely.

But while ChatGPT knows a lot, it’s not likely to be any better than any human being (or any AI system) at developing a sustainable and profitable investment strategy. That’s because ChatGPT is not trained on statistics, but on specific texts, ideas and descriptions. This means that it is unable to analyze investment data accurately enough to make confident decisions about investments, markets or the economy as a whole.

To accurately predict market trends or investment value, AI tools need to not only be trained on data, but go beyond the current capabilities of most machine learning (ML) systems. That is, developing predictive models that are trained to update themselves in response to new events that were not part of the original training models.


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regurgitated financial advice

Trained on a huge variety of databases, information sources, journalism sites and social media from around the world, ChatGPT is essentially ML on steroids. With access to so much data, neural network-based algorithms to match data patterns, and advanced natural language processing (NLP) skills to communicate your findings, ChatGPT is capable of writing essays or articles, doing homework, writing music, write and debug code, take tests (and cheat on them), woo potential boyfriends, and much more. And all this as well or even better than humans are capable of doing.

ChatGPT can also provide general financial advice. Still, according to experts, the AI ​​system’s advice is typical of human asset managers and financial advisors. When asked, “What is the best strategy to make money in the stock market?” ChatGPT replied:

“There is no single answer to this question as the best strategy for making money in the stock market will depend on many factors such as your financial goals, risk tolerance and investment schedule.”

With that, he stated that there were some basic principles that investors should follow: diversify the portfolio, invest in the long term, use dollar cost averaging and do research before investing.

“Overall, the key to making money in the stock market is having a well-thought-out strategy and being patient and disciplined in your approach,” concluded System.

AGI: The upgrade AI needs to “play the market”?

This is a far cry from what we can expect from an advanced system that has access to far more information than the average investor and the most sophisticated analytical tools on the planet. But given the current limitations of ML – especially the fact that learning models can only be built on currently available data – ChatGPT’s financial advice is in line with what one should expect from such systems.

Until ChatGPT and other ML-based analytics systems get a substantial upgrade, they are unlikely to outperform human analysts. Such an upgrade would require a much more flexible modeling system—one that would allow the system to change its predictive model in response to new events that could skew existing predictions.

Artificial general intelligence (AGI) systems, for example, can provide the upgrade that AI needs to “play the market”, providing not only more human-like thought processes, but also allowing those processes to take into account a much larger amount of data than humans could. handle at once.

Armed with massive amounts of data and advanced, flexible analytics systems designed to tweak predictive models as needed, AGI-based systems would be a much better bet for investment forecasting than current AI systems – including ChatGPT.

“What can (or will)” capabilities

AGI is still in development, but data scientists are working to improve current AI technology to enable better investment predictions. The process is, of course, incremental – but more advanced algorithms are being developed, based on the experiences of trading quantitative funds, which use complex mathematical models to make predictions.

Quant funds rely heavily on electronic trading, with millions of trades running at the same time, providing more data for ML models to develop more accurate predictions. The main difference between these technologies and ChatGPT is that the latter is based on “what is”, while AGI and ML based on advanced mathematics analyze datasets to develop models of “what can (or will)”, making it the much more appropriate ones for investment purposes.

AGI and advanced ML derived from mathematics will—eventually—allow for better and more accurate investment forecasts; it’s only a matter of time before scientists can build the advanced datasets needed to train AI to make accurate investment predictions.

Until then, let’s use current generation ML-based systems like ChatGPT for the many things it’s very good at. “InvestmentGPT” is still in the future.

Anna Becker is CEO and founder of EndoTech


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