Top Neuromorphic Chips in 2025 : BrainChip Akida, Intel Loihi & IBM TrueNorth

Neuromorphic computing has rapidly transitioned from academic exploration to commercial viability. Inspired by the structure and function of the human brain, neuromorphic chips emulate neural networks using silicon hardware—offering a paradigm shift in processing power, energy efficiency, and real-time learning. In 2025, three key players stand out: BrainChip Akida, Intel Loihi, and IBM TrueNorth. These chips are not just incremental updates—they represent a revolution in edge AI, robotics, IoT, and real-time cognitive processing. This article delves deep into each, comparing their architecture, capabilities, applications, and real-world deployments.

What is a Neuromorphic Chip?

Neuromorphic chips are computing devices designed to mimic the brain’s structure, particularly neurons and synapses, in silicon. Unlike conventional Von Neumann architectures, which separate memory and processing, neuromorphic architectures combine the two to enable:

• Event-driven computation
• Low power consumption
• Parallel processing
• On-chip learning
• Real-time AI inference

These chips are ideal for applications where latency, power, and adaptiveness are critical—like autonomous drones, biomedical implants, and intelligent edge devices.

Why 2025 is a Breakthrough Year

In 2025, neuromorphic chips are entering the market at scale due to:

• Maturity of fabrication processes for analog/digital hybrids
• Increasing demand for edge AI
• Shift from data center-centric AI to decentralized intelligence
• Support for spiking neural networks (SNNs), a more brain-like alternative to traditional deep learning

Top Neuromorphic Chips in 2025

Let’s dive into the top three neuromorphic chips leading this change.

1. BrainChip Akida

Overview

BrainChip’s Akida is a fully digital neuromorphic chip optimized for edge AI. Built to process spiking neural networks, Akida is designed for ultra-low power consumption while enabling on-device learning.

Please refer to this link to know more about BrainChip’s Akida.

Key Features

• SNN Native Support: Supports spiking neural networks, the closest model to how real neurons fire.
• On-chip Learning: Akida enables local learning without needing retraining on cloud infrastructure.
• Energy Efficiency: Consumes milliwatts of power, making it ideal for wearables and embedded systems.
• Scalability: Can be scaled across multiple devices or networks of edge nodes.
• Akida IP: Available as both a chip and an IP block for SoC integration.

Akida 2.0 in 2025

The latest generation—Akida 2.0—introduces:

• Improved neuron density
• Enhanced STDP (Spike Timing Dependent Plasticity)
• Native support for vision transformers (ViT) via SNN encoding
• Integration into consumer devices like wearables, hearing aids, and industrial sensors

Applications

• Smart vision (gesture, object, face recognition)
• Industrial IoT
• Wearables and health monitoring
• Autonomous navigation
• Cybersecurity (anomaly detection)

Companies using Akida

• Edge Impulse: For neuromorphic AI at the edge
• NASA: For space-grade AI computing
• SiFive: Licensing Akida IP for RISC-V platforms

2. Intel Loihi 2

Overview

Intel’s Loihi project, launched under its Neuromorphic Computing Lab, is one of the most comprehensive neuromorphic chip research efforts to date. The Loihi 2, released in late 2024, marks a significant upgrade in neuron count, learning capacity, and programming flexibility.

Please refer to this link to know more about – Intel Loihi 2.

Key Features

Up to 1 Million Neurons per Chip

• Integrated Learning Engines: Supports Hebbian learning, reinforcement learning, and more
• Asynchronous Architecture: Event-driven computation for power savings
• Programmable Neuron Models: Researchers can customize neuron dynamics
• Mesh Interconnect: Enables cluster scalability and real-time communication

Development Ecosystem

• Lava: An open-source neuromorphic software framework launched by Intel
• NxSDK: Intel’s original development environment for Loihi (being replaced by Lava)
• Kapoho Point Development Board: A USB-based Loihi 2 board for edge experimentation

Loihi 2 Highlights in 2025

• 15x improvement in chip area efficiency
• Native support for biorealistic synaptic dynamics
• Used in neuromorphic robotics (bio-inspired limbs, swarm bots)
• Deployed in smart city sensor systems

Applications

• Adaptive robotics
• Brain-computer interfaces
• Sensory processing
• Online learning systems
• Smart prosthetics
• Collaborators and Institutions
• MIT, Cornell, ETH Zurich
• Sandia National Labs
• National University of Singapore (for biofeedback projects)

3. IBM TrueNorth

Overview

IBM’s TrueNorth was among the first neuromorphic chips to garner global headlines. Released in 2014, it remains relevant in 2025 due to its groundbreaking architectural vision and continued software development.

Key Features

• 1 Million Neurons and 256 Million Synapses
• 5.4 Billion Transistors in 28nm CMOS
• Core Array: 4096 neurosynaptic cores in a tiled mesh
• Ultra-low Power: Operates on ~70mW
• Deterministic Processing: Excellent for vision, audio, and control systems

Software Ecosystem

• Corelet Programming Framework: Modular programming model for designing complex cognitive networks
• Compass Simulator: For training and deployment
• Cognitive Toolkit Integration: With IBM Watson and IBM Cloud services

Why is it Still Relevant in 2025

• While newer chips offer higher flexibility, TrueNorth continues to be used in:
• Research environments
• Cognitive vision systems
• Neuromorphic simulation of large-scale brain models

Applications

• Cognitive vision (DARPA SyNAPSE program)
• Real-time video analysis
• Audio localization systems
• Neuromorphic AI in defense and aerospace

Comparison Table of Top Neuromorphic Chips: Akida vs Loihi 2 vs TrueNorth (2025)

Real-World Applications of Top Neuromorphic Chips in 2025

Healthcare

• BrainChip Akida is used in seizure detection implants
• Loihi 2 powers adaptive prosthetics that self-learn patient gait
• TrueNorth is used in autism therapy bots for emotion sensing

Autonomous Vehicles

• Loihi 2 used in sensor fusion for low-power vehicle vision
• Akida is used in drones and UAVs for real-time edge AI

Wearables

• Smart hearing aids powered by Akida chips filter background noise in real time
• Loihi 2 enables gesture recognition on wristbands

Military and Aerospace

• TrueNorth remains dominant in ruggedized systems for defense
• Loihi 2 helps drones navigate hostile terrains using bio-inspired models

The Future of Top Neuromorphic Chips (Beyond 2025)

• SNN + LLM Fusion: Future architectures may combine neuromorphic principles with large language model (LLM) backends.
• Edge-Cloud Neuromorphic Networks: Cloud training and edge learning pipelines will become standard.
• Bio-Silicon Interfaces: Neuromorphic chips will be integrated with real biological neurons for hybrid AI.
• Neuromorphic AI-as-a-Service (N-AIaaS): Cloud platforms may soon offer neuromorphic inference as a service.

Neuromorphic chips represent a seismic shift in computing, especially for power-constrained, real-time, and adaptive applications. In 2025, BrainChip Akida, Intel Loihi 2, and IBM TrueNorth are at the forefront of this transformation—each pushing the boundaries in unique directions:

• Akida excels in real-time, ultra-low-power edge intelligence.
• Loihi 2 leads with flexibility and neuroscience fidelity.
• TrueNorth remains a proven legacy platform for scaled brain emulation.

As AI moves closer to mimicking human cognition, these chips are building the silicon brains of
tomorrow.