# Build the hybrid model inputs = tf.keras.Input(shape=(28, 28, 1)) x = model(inputs) outputs = quantum_classifier(x) hybrid_model = tf.keras.Model(inputs, outputs)
Enter , the first commercially available compact quantum‑accelerated processor that can sit comfortably on a standard 2 U server rack or even be embedded in a rugged industrial enclosure. Developed by QuantumFlux Systems , JUQ‑253 is poised to make quantum‑level speed‑ups accessible to any organization that needs real‑time, low‑latency AI at the edge. juq-253
import tensorflow as tf import qatf
All tests run on a standard 2 U server with 256 GB RAM, using the latest QATF 2.1 release. # Build the hybrid model inputs = tf
# Build the hybrid model inputs = tf.keras.Input(shape=(28, 28, 1)) x = model(inputs) outputs = quantum_classifier(x) hybrid_model = tf.keras.Model(inputs, outputs)
Enter , the first commercially available compact quantum‑accelerated processor that can sit comfortably on a standard 2 U server rack or even be embedded in a rugged industrial enclosure. Developed by QuantumFlux Systems , JUQ‑253 is poised to make quantum‑level speed‑ups accessible to any organization that needs real‑time, low‑latency AI at the edge.
import tensorflow as tf import qatf
All tests run on a standard 2 U server with 256 GB RAM, using the latest QATF 2.1 release.
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