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

Of google killer at the announcement of an AI-controlled humanity, the new ChatGPT app has been making waves – and even freaking people out too – since its introduction late last year.

The logic culmination of advanced machine learning technology, ChatGPT seems know almost everything — as well as the way of expressing oneself in an extremely clear and erudite manner.

But although ChatGPT knows a a lot, it is unlikely to be better than any human (or any AI system for that matter) at developing a sustainable and profitable investment strategy. Indeed, 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 reliable decisions about investments, markets or the economy as a whole.

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

Regurgitated financial advice

Trained on a vast array of databases, news sources, journalism sites, and social media 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) capabilities to communicate its results, ChatGPT is able to write trials Or articlesto do one’s homework, write music, write and debug code, to pass tests (And deceive them), woo the beautiful potentials, and much more. And all of this as well, if not better, than humans are capable of.

ChatGPT can also provide general financial advice. Yet, according to experts, the advice from the AI ​​system is typical of human asset managers and financial advisors. When asked, “What is the best strategy for making 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 a number of factors, such as your financial goals, risk tolerance and trading schedule. investment.”

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

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

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

This is far from what we can expect from an advanced system that has access to far more information than the average investor and to the most sophisticated analytical tools on the planet. But given the current limitations of ML – specifically the fact that learning models can only be built from 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 will remain unlikely to outperform human analysts. This upgrade would require a much more flexible modeling system, one that allows the system to change its predictive model in response to new events that could skew existing forecasts.

Artificial general intelligence (AGI) systems, for example, could provide the upgrade AI needs to “play the market”, not only providing more human thought processes, but also enabling those processes to consider a much larger amount of data than humans could. process at once.

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

Capacities “what can (or will)”

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

Quantitative funds rely heavily on e-commerce, with millions of trades executing 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 relies on “what is”, while AGI and advanced math-based ML analyze datasets to develop models of “what can ( or will) be”, which makes them much more suitable for investment purposes.

AGI and advanced math-derived ML will – eventually – enable better and more accurate investment forecasting; it’s only a matter of time before scientists are able to create the advanced datasets needed to train AI to make accurate investment predictions.

In the meantime, let’s use current generation ML-based systems like ChatGPT for the Several things it’s very good. “InvestmentGPT” is still in the future.

Anna Becker is CEO and Founder of EndoTech