BRN Discussion Ongoing

[7für7]

Low volume today ..

 

[Tothemoon24]

 

[manny100]

"Jesse ChapmanJesse Chapman • 3rd+3rd+Verification EngineerVerification Engineer1w • 1 week ago • Visible to anyone on or off LinkedIn
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BrainChip & Parsons Corporation Join Forces to Bring Neuromorphic AI to the Tactical Edge

In a significant step for edge AI and defense technology, BrainChip Holdings Ltd (ASX: BRN) has announced a multi-year strategic partnership with Blue Ridge Envisioneering (BRE), a Parsons company (NYSE: PSN). The collaboration aims to integrate BrainChip’s Akida™ hashtag#neuromorphic technology into Parsons’ mission-ready edge-AI platforms, delivering real-time, low-power hashtag#intelligence in environments where cloud connectivity is limited or unavailable.

The partnership will leverage Akida’s event-based, energy-efficient architecture and on-device learning capabilities, enabling adaptive AI performance in constrained, dynamic defense scenarios. Notably, Parsons gains access to BrainChip’s AKD1500 processor, which recently commenced tape-out for volume production, positioning the chip for deployment in both defense and broader commercial applications."
The 'secret sauce' for Parsons is the neuromorphic on line learning capabilities - see bold above. That is why we are set for a big future in defense.

 

[Bravo]

This is also an interesting development!

Airbus, Leonardo and Thales have now signed an MOU.They aren’t just collaborating. They’re actually planning to form a new combined company (a new European space player) with a target of being operational by 2027 (pending approvals).

As we know, BrainChip already has an entry point with Airbus. In an October 2024 quarterly update, BrainChip reported agreements amounting to €190,000 with Frontgrade Gaisler and Airbus Defence & Space, intended for ultra-low-power AI in space applications.

If Airbus adopts neuromorphic edge AI for a particular sensor role, even at small volume in the beginning, then once this new 2027 company exists, that architecture has a pathway not just to Airbus, but to Leonardo and Thales via this new company as well.

It says " The combined entity will employ around 25,000 people across Europe. With an annual turnover of about 6.5bn€ (end of 2024, pro-forma) and an order backlog representing more than three years of projected sales, this new company will form a robust, innovative and competitive entity worldwide.Ownership of the new company will be shared among the parent companies, with Airbus, Leonardo and Thales owning respectively 35%, 32.5% and 32.5% stakes. It will operate under joint control, with a balanced governance structure among shareholders."

Airbus, Leonardo and Thales sign Memorandum of Understanding to create a leading European player in space

Airbus, Leonardo and Thales have signed a Memorandum of Understanding (“MoU”) aimed at combining their respective space activities into a new company.

www.airbus.com

 

[Newk R]

I am not fluent in English but….. could it be that there are several grammatical errors on that flyer

„mims nimos“, „ayschonnotus“ ?? “mimics … asynchronous“.??

„instany / localy locally / rel-tiime“ … „instantly / locally / real time“.??

„devices that smart“ … „devices that are smart“.

„do’t“ … „don’t“??


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Is this real or somebody's BS

 

[7für7]

Not even 20 I see the big news coming from tomorrow any time now

 

[manny100]

We all know that devices can communicate with each other, eg i see my phone messages on my lap top. Edge chips whether Neuromorphic or not in devices can communicate with each other if connected via some type of network not necessarily connected to the cloud. For Edge devices the network would mostly not be cloud connected (why would you bother).?
This where AKIDA shines with its on chip learning capabilities compared to other neuromorphic or traditional 'dumb' chips with no on chip learning capabilities.
Chips in autos, robots etc need to communicate. Robots in a team may need to send each other signals .
Its easy to see why Parsons see our on chip learning adaptability as so important. Great for space and commercial applications. Care would need to be taken in defense with networks even though will not be could connected.
Its also easy to how AKIDA well ahead of the pack.
I ask Chat GPT to summarise. Its common sense but saved me typing it.

Comparison Table: With vs. Without On‑Chip Learning​

Aspect	Akida with On‑Chip Learning	Chips without On‑Chip Learning
Adaptability	Can learn new patterns locally (e.g., new anomalies, new commands) and immediately use them in communication.	Limited to pre‑trained models; cannot adapt on their own. Must be retrained in the cloud or offline and redeployed.
Communication Content	Sends newly learned events or adapted patterns to other devices (e.g., “new anomaly detected”).	Sends only pre‑defined outputs from its fixed model (e.g., “class = 2”).
Collaboration	Devices can share discoveries: one node learns something new and alerts others, enabling system‑wide adaptation.	Devices can only share fixed detections; if one encounters a new pattern, others won’t recognize it until all are updated externally.
Autonomy	High — devices can self‑improve and coordinate without cloud or human intervention.	Lower — devices depend on external retraining and updates to handle new situations.
Resilience	Ideal for remote or disconnected environments (spacecraft, autonomous vehicles, industrial plants) where cloud updates aren’t possible.	Vulnerable in disconnected environments — performance degrades if new patterns appear that weren’t in the original training.
Efficiency of Communication	Communicates only meaningful, newly learned events, reducing bandwidth.	Communicates fixed outputs, which may include irrelevant or incomplete information if the model is outdated.
System Intelligence	Creates a distributed, adaptive network — like a “nervous system” that learns and shares in real time.	Creates a static network — devices can coordinate, but only within the limits of their pre‑trained knowledge.