"As soon as individual securities start to fly away from the flock, that's one signal to Wallace that says, 'Zero in on this, why is this security behaving more independently versus its peers.' And often independence of behavior is indicative of knowledge that's imprinted on the security. Often, when people don't really know anything, they tend to act in lockstep with others."
"As soon as individual securities start to fly away from the flock, that's one signal to Wallace that says, 'Zero in on this, why is this security behaving more independently versus its peers.' And often independence of behavior is indicative of knowledge that's imprinted on the security. Often, when people don't really know anything, they tend to act in lockstep with others."
Valois Franklin explains that Wallace looks at markets "like a flock of birds, that's constantly shifting and morphing," to pick up on signs of early movements driven by insider knowledge.
Like Michie's machine, Wallace maps out scenarios to pick out those that are most successful and then reinforce those winning strategies. But unlike Michie's matchbox engine, Wallace operates in the complex world of financial markets, where the parameters are always shifting.
Michie's machine, which was called the Matchbox Educable Nought and Crosses Engine - or MENACE for short - used matchboxes to represent all 304 states of play in the game of tic-tac-toe, with each small box containing beads to mark the relative advantages of each position.
In contrast, Wallace's "genetic algorithms" work to combine the individual bits of knowledge it has, to build on its own understanding and become "incrementally smarter." "What GPTs are, are clever algorithms," Bogdan said. "We have enough mimicking. We need understanding, not cleverness."
In Bogdan's view, these evolutionary processes represent the future of AI, in allowing machines to go beyond simple mimicry. Bogdan explained that neural networks, which are most prominent in the form of large language models (LLMs) like OpenAI's ChatGPT, simply "mimic the responses that a human would make given the same input."
Speaking to MarketWatch, Castle Ridge's chief scientific officer, Alex Bogdan, argued Wallace's evolutionary approach allows for a deeper level of understanding compared to the neural networks used by systems like ChatGPT, which are modeled on the human brain.
"On a daily basis, Wallace will make thousands of copies of itself, each a virtual portfolio manager with different characteristics. It will turn certain weightings and patterns up and down, or on or off, and then determine whether each portfolio manager is better or worse suited in this market environment we're in today... If it's better, it increases the probability that it breeds" Valois-Franklin said.
In simple terms, Wallace's evolutionary process sees the machine create thousands of differently-weighted virtual investment portfolios each day, which are tested and ranked according to their suitability to current market conditions, Valois-Franklin said. In a recurring eight-hour cycle, Wallace picks out its top-performing portfolios and gives them priority to "breed."
發表於 2024-3-25 21:25:48
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