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Stefanie Hausman

Created on April 7, 2026

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Discover more than 1500 professional designs like these:

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Momentum: Onboarding Presentation

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Natural Language Processing (NLP): DAX Co-pilot

Where It Falls Short

What It Does Well

Struggles with heavy accents, multiple speakers, and patients who describe symptoms in everyday language instead of medical terms. Can't read body language. A patient wincing while saying 'I'm fine' gets documented as 'feeling fine.'

Listens to doctor-patient conversations and writes clinical notes automatically in real time. Doctors using it spend up to 50% less time on paperwork and can finally make eye contact with patients instead of staring at a screen.

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Computer Vision (CV): John Deere See & Spray

Where It Falls Short

What It Does Well

The equipment costs hundreds of thousands of dollars, putting it out of reach for most small and mid-size farms. Doesn't work well when crops look similar to local weeds or in poor lighting. Misses everything below the soil.

Cameras on the sprayer photograph every single plant in a field and identify each one as either a crop or a weed in real time. It then sprays herbicide only where the weeds are, reducing overall chemical use by an incredible 77%.

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

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Recommendation Engines (RE): Alie by Muvi

Where It Falls Short

What It Does Well

Creates a filter bubble where users only see more of what they already like instead of discovering something genuinely new. Struggles with new users who have no history yet. Can only recommend what's already in the system.

Analyzes what each user watches, clicks, and searches on websites and apps in real time, then recommends personalized content based on those patterns. No manual setup required. It learns and improves on its own over time.

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Anomaly Detection (AD): Feedzai

Where It Falls Short

What It Does Well

Flags a lot of legitimate transactions as suspicious. Buying a gift in another state might freeze your card. Every false positive needs a human to review it, creating a bottleneck. Also weak against brand new fraud tactics.

Monitors millions of bank transactions in real time and catches suspicious activity by comparing each one to the customer's normal spending patterns. Can flag fraud in milliseconds, protecting customers before any damage is done.

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Generative AI (Gen AI): Adobe Firefly

Where It Falls Short

What It Does Well

Can't keep the same character consistent across multiple images. Doesn't follow brand guidelines without heavy prompting. Still makes errors with hands, text, and fine details. It creates visuals but doesn't understand design intent.

Built right into Photoshop and Illustrator, designers can type 'add a mountain range' and Firefly generates it seamlessly. It expands images, creates variations, and generates textures on demand using Adobe's licensed library.

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Predictive Analytics (PA): Google DeepMind WeatherNext2

Where It Falls Short

What It Does Well

Only predicts based on patterns from the past. As climate change creates unprecedented weather events, predictions get less reliable. It also can't account for local context not in the data like new construction in a flood zone.

Predicts weather up to 10 days out more accurately than traditional methods, and does it in under a minute instead of hours on a supercomputer. Trained on decades of global data, it beat standard forecasts on over 90% of tests.

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

Use this side of the card to provide more information about a topic. Focus on one concept. Make learning and communication more efficient.

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