➀ TDK has developed a spin-memristor for analog neural networks and built a network that can separate music, speech, and noise in real-time. The technology is based on a collaboration with CEA since 2020 and uses a 300mm-compatible spintronics semiconductor prototyping line at Tohoku University. ➁ The memristors are controllable, have low current leakage, and are robust against resistance drift, allowing for long-term data storage. ➂ TDK and CEA have implemented an analog algorithm that can separate the three types of sound, and the technology has a significantly lower power consumption compared to conventional digital neural network implementations.
Related Articles
- Raspberry Pi AI camera shoulders AI processing workload8 months ago
- Production-grade AI has arrived in EDA: scaling innovation in analog design and verification12 months ago
- Google’s Veo 3 AI Video Generator Will Blow Your Mind With Realismabout 19 hours ago
- Study Claims Electronic Face Tattoos Can Help Manage Stress At Work2 days ago
- Nvidia and AMD to Launch Downgraded AI GPUs in China Amid Tightened U.S. Restrictions2 days ago
- New Study Program at RUB: IT Engineering2 days ago
- Four-Legged Robot Plays Badminton With People2 days ago
- Semiconductor Market Uncertainty4 days ago
- Defence demand drives IR image sensor market to 5% CAGR 2024-302 months ago
- A Synopsys Webinar Detailing IP Requirements for Advanced AI Chips2 months ago