BRN Discussion Ongoing

Tezza

Regular
To make your disappointment more perfect, they will drop a notification for unquoted securities at the same time! BOOM TAKE THAT
Yay
 
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7für7

Top 20
Yeah come on!…just smash it down… 18…17… I don’t care!! Wohooooo
 
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Rskiff

Regular
Market expectations seem to be low. We live in hope, not the ideal investment policy.
 
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Rskiff

Regular
Market expectations seem to be low. We live in hope, not the ideal investment policy.
Is BRN the only AI company that is missing the AI bubble?
 
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overpup

Regular
At least we don’t have a nonsense pump this time… 😵‍💫 maybe it will skyrocket after all…

Can you believe it? I’m happy for the dipp 😂🙌
Maybe if we start wishing for BRN to fail the Irony of the Universe will kick in and it will skyrocket!
 
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With the SP not doing the normal pump before the quarterly

1753766777094.gif



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HopalongPetrovski

I'm Spartacus!
Shorter's taking a punt on another crap 4C hoping to drive down the price for a quick trade.
Que Sera sera.
 
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Diogenese

Top 20
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Bravo

If ARM was an arm, BRN would be its biceps💪!


Shouldn't they do a pump first?

It used to get pumped, then ceremoniously thumped
Now it’s getting dumped… and royally humped 😝 🐫
 
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CHIPS

Regular
Here are five high-revenue, Fortune 500-aligned examples where the Akida neuromorphic chip can provide or secure an innovative competitive advantage through integration into core product offerings or internal infrastructure. Each case includes the company's strategic needs, how Akida helps, and the competitive edge it introduces:

1. Apple Inc. – Next-Gen Smart Hearing & Spatial Audio Devices


Use Case: On-device adaptive hearing personalization in AirPods or future wearable audio devices
Akida’s Role: Ultra-low power neural processing for real-time noise filtering, hearing profile adaptation, and spatial sound tracking using spiking audio data
Strategic Need: Apple seeks tighter integration of personalized, health-linked audio and real-time spatial computing (e.g. Vision Pro ecosystem)
Competitive Edge:
  • Differentiates AirPods with on-device auditory intelligence
  • Enhances privacy (no audio sent to cloud)
  • Adds value to Apple's broader Health & Accessibility offerings
    Revenue Potential: >$20B segment (Wearables/Home/Accessories)

2. Amazon – Intelligent Edge for Echo & Warehouse Robotics


Use Case: Decentralized AI for Echo devices and Kiva robotics, enabling faster and more private local decisions
Akida’s Role: Integrate into Echo speakers and warehouse robots to reduce cloud inference latency and power draw
Strategic Need: Amazon wants to improve energy efficiency and reduce server-side compute costs for Alexa and fulfillment operations
Competitive Edge:

  • Faster local response = better UX
  • Lower cost of compute per user interaction
  • Scalable privacy-respecting smart home ecosystem
    Revenue Potential:

  • ~$200B+ logistics operations savings at scale

3. Tesla – Ultra-Efficient Perception for Autonomous Driving Edge Cases


Use Case: Low-power, always-on perception for vision-based driver monitoring systems (DMS) or secondary sensors
Akida’s Role: Run SNN models on driver behavior, in-cabin motion, and fatigue without taxing the main FSD chip
Strategic Need: Tesla’s Dojo and FSD stack are high-powered; offloading low-level, safety-critical perception to an Akida co-processor improves energy and redundancy
Competitive Edge:
  • Compliance with EU/US driver monitoring regs
  • Reduced thermal/power burden in vehicles
  • Can use temporal learning to personalize driver responses
    Revenue Potential: FSD & Hardware upgrades = $12B+ annually

4. Johnson & Johnson – Neuromorphic Edge in Smart Medical Devices


Use Case: Smart surgical instruments, diagnostics, or wearables for post-op monitoring that adapt to patient-specific signals
Akida’s Role: Embedded SNN chip for ultra-low power real-time bio-signal classification (e.g., tremor, ECG, EMG)
Strategic Need: J&J is investing in digital surgery (e.g., OTTAVA) and patient-connected devices
Competitive Edge:
  • Enables battery-efficient, real-time closed-loop systems
  • Devices learn from patient baselines and adjust responses (e.g., haptic feedback)
  • Minimizes cloud dependency = faster FDA path
    Revenue Potential: Surgical & Interventional segment >$25B

5. Walmart – Edge AI for Loss Prevention and Shelf Management


Use Case: Store-edge Akida-enabled cameras for shoplifting detection, shelf stock prediction, and employee activity classification
Akida’s Role: Low-cost edge deployment of computer vision at scale; Akida’s SNN excels at temporal events (e.g., repeated suspicious behavior)
Strategic Need: Walmart needs low-cost, privacy-compliant smart retail systems across thousands of stores
Competitive Edge:
  • Real-time shrinkage detection without adding cloud expense
  • Improve restocking response with adaptive shelf analysis
  • Supports high-scale IoT rollout at marginal cost
    Revenue Potential: Loss prevention impact >$3B annually; Inventory efficiency could save >$5B

Summary Table​


CompanyUse CaseAkida FunctionRevenue DomainCompetitive Advantage
ApplePersonalized hearing + spatial audioAdaptive SNNs for audio$20B+ wearablesHealth+privacy differentiation
AmazonSmart devices + robotsEdge inference, energy saving$200B infraLatency + cost reduction
TeslaDriver monitoring + sensor fusionIn-cabin perception, low power$12B+ FSDRedundancy + compliance
J&JSmart medical systemsBio-signal adaptation$25B medtechFDA-aligned, personalized AI
WalmartTheft & stock controlOn-device CV at scale$8B+ operationsRetail AI at low TCO

Where does this come from??? AI or some article? Then post the link or mark it as AI-generated.
 
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HopalongPetrovski

I'm Spartacus!
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MDhere

Top 20
Didn't you get the memo?
This qtr they are just making do with that bot at .1975. 🤣
well i have a spare measly grand in the bank to splash on something,what shall it be??
 
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TheDrooben

Pretty Pretty Pretty Pretty Good
well i have a spare measly grand in the bank to splash on something,what shall it be??
I'm with you MD......
giphy (28).gif


HAPPY AS LARRY
 
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Derby1990

Regular
Bought into BRN 5 years ago, thinking it might fast track my retirement.
Luckily, I didn't need it, since I did everything (else) right, and I'm retiring in December anyway.
Maybe my nibblings (my sole beneficiaries) will get something out of it in 30 years time 🤣
 
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Maybe if we start wishing for BRN to fail the Irony of the Universe will kick in and it will skyrocket!
That will only happen if you sell all your shares. 😂
I reckon most of us here will either be rich or poor🙈
I'm with TechMan, wait until June 2026.
Then I'll reassess and wait for Sept 2027. Then I'll..............🙂
**This post has not been AI generated.
 
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CHIPS

Regular
That will only happen if you sell all your shares. 😂
I reckon most of us here will either be rich or poor🙈
I'm with TechMan, wait until June 2026.
Then I'll reassess and wait for Sept 2027. Then I'll..............🙂
**This post has not been AI generated.

Maybe we all should sell a few shares? :unsure: If it helps, I am ready to give it a try. :geek:

Shopping Selling GIF by Pudgy Penguins
Penguin Talking GIF by Pudgy Penguins
Sale Cash Out GIF by Pudgy Penguins
Penguin Talking GIF by Pudgy Penguins
 
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Mt09

Regular
That will only happen if you sell all your shares. 😂
I reckon most of us here will either be rich or poor🙈
I'm with TechMan, wait until June 2026.
Then I'll reassess and wait for Sept 2027. Then I'll..............🙂
**This post has not been AI generated.
I’ll reassess June 2053.. I’m running out of optimism to be honest.
 
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DK6161

Regular
Hello all. Have not been here in a while. How's everyone going? Any news of revenue yet? The wife wants to know before we sign the divorce papers. Thanks in advance
 
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Earlyrelease

Regular
Not expecting anything unfortunately. But still happy with the small bits of hope that some fantastic researchers keep finding and posting. Whilst frustrating as …. I can say in my mind the sentiment for product adoption has definitely improved and we just need some of the use cases and product development cycles to align. Like Derby 1990 I bought these to end work early (early release) but that hasn’t happened but too many friends and work colleagues have passed and so my retirement won’t be as flamboyant as first thought but will pretend I am 19 yrs old and moved out of home and live on noodles until I can touch my super in 2 yrs time.
 
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