The Limits of Artificial Intelligence
The Limits of Artificial Intelligence
Blog Article
Amid the warm Manila breeze, in a university hall buzzing with intellect, tech entrepreneur and investment icon Joseph Plazo made a striking distinction on what machines can and cannot do for the economic frontier—and why understanding this may define who wins in tomorrow’s markets.
Tension and curiosity pulsed through the room. Students—some furiously taking notes, others capturing every word via livestream—waited for a man known not only as an AI visionary, but also a contrarian investor.
“Machines will execute trades flawlessly,” Plazo opened with authority. “It won’t tell you when not to trust them.”
Over the next hour, Plazo delivered a fast-paced masterclass, intertwining machine logic with human flaws. His central claim: AI is brilliant, but blind.
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Bright Minds Confront the Machine’s Limits
Before him sat students and faculty from prestigious universities across Asia, assembled under a pan-Asian finance forum.
Many expected a victory lap of AI's dominance. Instead, they got a reality check.
“There’s too much blind trust in code,” said Prof. Maria Castillo, an Oxford visiting fellow. “This lecture was a rare, necessary dose of skepticism.”
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When Algorithms Miss the Mark
Plazo’s core thesis was both simple and unsettling: machines lack context.
“AI is fearless, but also clueless,” he warned. “It finds trends, but not intentions.”
He cited examples like machine-driven funds failing to respond to COVID news, noting, “By the time the algorithms adjusted, the humans were check here already positioned.”
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The Astronomer Analogy
He didn’t bash the machines—he put them in their place.
“AI is the telescope—but you are still the astronomer,” he said. It sees—but doesn’t think.
Students pressed him on sentiment tracking, to which Plazo acknowledged: “Sure, it can flag Reddit anomalies—but it can’t feel a market’s pulse.”
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A Mental Shift Among Asia’s Finest
The talk sparked introspection.
“I believed in the supremacy of code,” said Lee Min-Seo, a quant-in-training from South Korea. “Now I realize it also needs wisdom—and that’s the hard part.”
In a post-talk panel, faculty and entrepreneurs echoed the caution. “This generation is born with algorithmic reflexes—but instinct,” said Dr. Raymond Tan, “is not insight.”
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What’s Next? AI That Thinks in Narratives
Plazo shared that his firm is building “co-intelligence”—AI that blends pattern recognition with real-world awareness.
“No machine can tell you who to trust,” he reminded. “Capital still requires conviction.”
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Standing Ovation, Unfinished Conversations
As Plazo exited the stage, the hall erupted. But more importantly, they started debating.
“I came for machine learning,” said a PhD candidate. “But I left understanding myself better.”
In knowing what AI can’t do, we sharpen what we can.