A cool 48k i heard? But seriously, these things take time, products don’t just invent themselves. Consider the timeline of these partnerships; for example, it’s been nearly two years with Mercedes, and we recently learned they’re still actively testing the EQXX (its at stage 2 below). In the automotive industry, especially with self-driving vehicles, every detail must be perfected. A single car crash caused by insufficient testing, particularly with new tech, could spell the end for that model line. If Akida passes the EQXX test, it might be rolled out across the fleet, it's unlikely theyll go with another piece of SNN kit that needs to be tested all over again. If it doesnt pass, well then they wont use it and we'll be left to join the dots. The same applies to sectors like healthcare and machine maintenance.
Tata Elxsi partnered with BrainChip what, just over a year ago? and Accenture included Akida in its Self-Learning Speech Recognition patent back in September 2022. So, it’s a safe bet that they plan to use Akida moving forward after they’ve had time to build, test and commercialise their tech.
I mean, they're even teaching people how to use Akida at universities because its so new, including Cornell Tech, part of the ivy league! (brilliant move btw getting into the universities)
Anyway heres a typical timeline from wo to go:
*The integration of cutting-edge technology like BrainChip's Akida neuromorphic platform into broader markets and products depends on several factors, including the technology's complexity, industry demand, and the readiness of companies to adopt it. Here’s an outline of the process and timelines:
Stage 1. Research and Development (1–3 years)
Initial trials: Early adopters, typically research labs or innovation-focused companies, test the technology for feasibility and potential use cases.
Custom development: Companies work with BrainChip to adapt Akida's neuromorphic capabilities to their specific needs.
Stage 2. Proof of Concept and Prototyping (6 months–2 years)
Prototypes: Once the technology is understood, companies develop prototypes to evaluate its integration into existing or entirely new products.
Testing: Rigorous testing is conducted to ensure functionality, reliability, and market fit.
Stage 3. Regulatory Approvals (6 months–2 years)
If the product involves sectors like healthcare, automotive, or defense, regulatory approval may add significant time.
AI technologies, especially neuromorphic ones, often require cybersecurity certifications or compliance with industry-specific standards.
Stage 4. Manufacturing and Scaling (1–3 years)
Production pipelines: Companies need to adjust or create manufacturing processes to incorporate the technology.
Supply chain readiness: Scaling neuromorphic chips into products may require partnerships with semiconductor manufacturers or suppliers.
Stage 5. Market Adoption (1–5 years)
Early adoption: High-tech sectors, such as autonomous vehicles, smart appliances, and edge AI devices, adopt the technology first.
Broader adoption: As costs decrease and the technology proves its worth, it becomes part of consumer electronics and other mainstream products.
Typical Timeline: 3–10 years
Shorter timelines (3–5 years): Industries like automotive or consumer electronics that actively seek AI advancements and already have development pipelines for smart products.
Longer timelines (5–10 years): Emerging industries or entirely new product categories enabled by Akida’s neuromorphic capabilities. These require more innovation and time to materialize.
Accelerating Factors
1. Partnerships: Collaborations with major companies (e.g., Mercedes-Benz with BrainChip's Akida for EQXX) significantly shorten the timeline.
2. Developer Ecosystem: Tools and software platforms provided by BrainChip (like AI training frameworks) can enable faster integration.
3. High Demand: Applications in industries like AI-powered medical devices, IoT, or autonomous systems can drive faster adoption.
For transformative products not yet conceived, the timeline may extend, but the enabling capabilities of Akida could inspire rapid innovation once its potential is recognized.
*GPT4o
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