Inside Bespoke AI: Samsung's Development Story Lands December 16, 2025
Samsung Electronics is releasing a series of videos that put the engineering behind its Bespoke AI refrigerator and Laundry Combo on display. The clips feature the planners and developers who built the core functions, offering a look at the product decisions and technical intent that shaped both appliances. Starting December 16, the videos roll out sequentially on YouTube and other social channels across 50+ countries.
Bespoke AI Refrigerator: From cold storage to data-aware
The refrigerator segment shows how AI Vision Inside identifies food items, tracks expiration dates and suggests recipes. When your hands are full, Bixby opens the door via voice command. It also highlights AI Hybrid Cooling - pairing an AI digital inverter compressor with a Peltier unit - to keep temperatures stable with smarter control logic.
Bespoke AI Laundry Combo: Wash-to-dry, end to end
The all-in-one Laundry Combo connects washing and drying in a single flow. AI Wash & Dry and the Flex Auto Dispense System analyze fabric type, weight and soil level to set cycles and detergent volumes. With Bixby, users can schedule washes by voice, while AI Vibration Reduction Technology Plus (AI VRT+) cuts vibration based on the installation environment.
"We created these videos to show the commitment and effort of Bespoke AI planners and developers working to maximize user convenience," said Jessie Song, Vice President and Head of Marketing Group, Digital Appliances (DA) Business at Samsung Electronics. "We will continue striving to deliver new value through differentiated AI features and become a trusted brand in AI appliances."
Why this matters for engineers and product teams
- On-device vision: Grocery recognition and date tracking hint at a mix of object detection and OCR. Expect region-specific datasets, edge inference constraints and a need for continual updates without breaking UX.
- Context-aware control: Hybrid Cooling and auto-dosing show how sensor data, control loops and small models can drive micro-decisions that users feel (stable temps, clean clothes) without extra steps.
- Voice as a primary action: Simple intents (open door, schedule wash) must be fast, reliable and resilient to noise. Clear intent schemas and fallback behaviors are essential.
- Environment adaptation: AI VRT+ suggests self-calibrating behavior that learns from installation conditions. Build for variance first; let the system tune itself safely over time.
- Edge reliability: These tasks live close to hardware. Design for offline operation, graceful degradation and transparent state so users trust automation.
- Lifecycle and updates: Sequential global rollout implies staged delivery and localization. Treat models, prompts and firmware as a single release unit with rigorous testing gates.
Helpful resources
- Bixby Developer Resources for voice intent design and testing.
- Curated AI courses by job role if you're upskilling a team building on-device AI and voice experiences.
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