mythic.ai: Power-Efficient AI Acceleration for Edge and Enterprise

mythic.ai is a pioneering AI compute platform company specializing in high-performance, power-efficient analog computing for edge and enterprise AI inference. Leveraging groundbreaking technologies like Compute-in-Memory, Dataflow Architecture, and Analog Computing, mythic.ai delivers unmatched efficiency and speed through its Mythic Analog Matrix Processor (AMP™) and AI Workflow. Designed for real-world deployment, the platform enables deterministic execution with guaranteed accuracy, frame-rate, and power profiles—ideal for applications in smarter cities, intelligent robotics, smart homes, AR/VR, and aerospace. With solutions like the M1076 AMP chip and MM1076/ME1076 M.2 cards, mythic.ai empowers developers and engineers to run complex DNN models on-device without external DRAM, drastically reducing latency and power consumption.

Key Features:

• Compute-in-Memory Architecture: Executes AI computations directly within memory arrays, eliminating data movement bottlenecks.
• Analog Computing: Uses analog signals to perform matrix multiplications with ultra-low power and high efficiency.
• Mythic AMP™ (Analog Matrix Processor): Delivers up to 25 TOPS in a single chip with 3–4W power consumption.
• Mythic AI Workflow: Streamlined two-stage process combining optimization and compilation for seamless DNN deployment.
• Mythic Optimization Suite: Converts 32-bit models to 8-bit (ANA8) with preserved accuracy; supports 4-bit quantization and retraining flows.
• Mythic Graph Compiler: Automates machine code generation, mapping, and packing for efficient execution on AMP tiles.
• Low Latency Inference: Always runs with batch size 1 for real-time responsiveness.
• Scalable Design: Supports deployment from single edge devices to server-class systems in data centers.
• On-Chip Weight Storage: Up to 80 million weight parameters stored directly on the chip—no external DRAM needed.
• Support for Major AI Frameworks: Fully compatible with PyTorch, TensorFlow 2.0, and Caffe.
• Lightweight Host Drivers: Simplified integration with embedded and server operating systems like Ubuntu and NVIDIA L4T.
• Pre-Qualified DNN Models: Ready-to-use models for object detection, classification, scene segmentation, and human pose estimation (e.g., YOLOv3, YOLOv5, ResNet-50, SegNet, OpenPose Body25).
• High-Throughput NoC Router: On-chip network-on-chip interconnects tiles for efficient dataflow across cores.
• Deterministic Performance: Ensures predictable latency, power, and accuracy for mission-critical applications.
• Privacy-First Analytics: Enables in-camera AI processing for instant face redaction and enhanced data privacy.
• Compact Form Factors: Products like the MM1076 and ME1076 M.2 cards fit into space-constrained devices.

Pricing: mythic.ai offers a product inquiry process for potential customers, indicating a tailored, enterprise-focused pricing model. While no public pricing tiers are listed, the availability of inquiry options and specialized hardware suggests a paid or subscription-based approach for commercial deployments. Given the enterprise-grade nature and lack of public free options, the best fit is paid.

Conclusion: mythic.ai is a transformative force in AI hardware, redefining edge and server inference with its analog compute-in-memory technology. Its combination of unmatched power efficiency, high performance, and real-world reliability makes it an ideal solution for developers and organizations building intelligent systems in robotics, smart cities, and beyond—setting a new standard for AI deployment where power and speed matter most.