In today’s Smart Money, I’ll look at a company that highlights the limits of legacy AI Appliers struggling to adapt as A-AI accelerates. Then, I’ll break down an AI Applier that can successfully leverage A-AI to strengthen its core business and gain a competitive advantage.
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Hello, Reader.
In machine learning – the type of AI that teaches computers to learn from examples – not all data is created equal.
“Hurtful data,” be it mislabeled, misleading, or biased, can degrade AI models. That’s like a photo of a cat being labeled “dog.” Other data is “useless” because it is repetitive, low quality, or adds no meaningful new information.
If the examples are wrong, the model learns the wrong patterns.
Longtime Digest readers know how bullish we are on the AI Megatrend. We’ve tried hard to keep our readers in profitable trades…
OpenAI Sora video backlash, Taiwan’s rare earth retort, Apple smart glasses. Plus: Browser wars, “cobots,” crypto crash, Qantas…
Executives at Fortune’s Brainstorm Tech warned that you need to start with fundamentals before rolling out a complex new AI…
Average performance figures may not tell us what we really want to know about how AI systems operate.
Honeywell and Caterpillar both say AI can ease skills gaps but workers need training to use it effectively
Today, Tom Yeung will consider the dangers of the latest AI mania – and the safer investing path to follow instead.
