Hi Bravo, Its new tech and everyone was excited what it could do except when it came to the crunch no one or very few wanted to risk their job or business via adopting AKIDA.
Management and investors underrated the time it takes to progress to move from the Innovation stage 1 through to Early Adopters Stage 2 (us now) and then on to the next stage 3 Majority Adopters.
Everyone got caught up in the excitement of what AKIDA can do but did not understand that in 2021/22 no product actually existed that could use AKIDA quickly. Megachips just started demonstrating robots in Sept'25 and still no sales after 5 plus years.
There is the lenghty engagement to commercial product timeframe as well - although now shortened by AKIDA Cloud and Hubs with pre trained models.
Investors in more recent years should have been aware of the above via research.
Some relief for many Early risk taker investors is the very low price paid at entry.
The other issue is that there is no such thing as a management team that does not 'talk up the company'. That is part of investors DD - buy/avoid/hold/sell/add.
It is what it is and there is never any shortage of excitement over new tech and never any shortcuts to commercial success.
If i dwell on the past i will lose faith in the journey to the future.
Are you still confident of BRN success? I am.
Hi Manny,
Thanks for your response.
I’ve never doubted the technology. My point was simply that we are still (as you say) in the Early Adopter phase, despite management having, for many years, made statements that in hindsight appear overly optimistic. I don’t believe that helps anyone - neither investors nor management themselves.
Phrases like “explosions of sales”, “watch us now”, and even Antonio’s comment in a previous AGM that a five-year licence would make us profitable overnight are powerful statements. At the time, I assumed they must have been grounded in something tangible or at least realistically within reach. But with the benefit of time and still no meaningful licence wins of that nature, it’s hard not to question whether those scenarios were ever genuinely close.
We’re now sitting around 13-14 cents and many of us are trying to reconcile the gap between what felt imminent and what has actually materialised. That disappointment doesn’t mean the tech is broken, but I do think it means expectations were perhaps set poorly.
You mentioned that “there is no such thing as a management team that does not talk up the company.” I understand that to a point. But enthusiasm should be balanced with some sense of realism otherwise it erodes trust. Management commentary materially influences investor behaviour and therefore carries responsibility. Communicating transparency when timelines stretch or challenges arise is, in my view, just as important as communicating optimism when things look promising.
You also referred to the lengthy commercialisation timeframe and suggested that investors in recent years should have understood this through research. Bu the issue here as I see it, is that those timelines were also shaped by management’s own commentary (references to looking toward financials, imminent traction, accelerating pipelines, etc.). That kind of messaging can't help but shape expectations.
I should clarify that I’m not absolving investors of our own responsibility (i.e. research/due diligence). But I don’t think management can be completely absolved either because communication matters.
My original point was simply that what once felt like we were on the cusp of explosive revenue now appears to be a much longer road which is a bitter pill for many of us to swallow.
Having said that, I fully appreciate there are reasons beyond management’s control as to why commercial traction has taken longer than expected (even if those reasons haven’t always been clearly articulated to shareholders).
Some likely factors (to name a few) include:
- The issues Jonathan Tapson outlined in his recent presentation, some of which are outlined in this post #110,044
- Lengthy semiconductor adoption cycles
- The disruptive nature of the tech itself and the difficulty of shifting developers from conventional ML frameworks to neuromorphic approaches
- Limited SNN engineering talent globally
- Customers unwilling to share proprietary datasets needed for optimisation
- Competition from established players integrating NPUs into MCUs (e.g. Arm’s M85 NPU)
- Larger players bringing edge AI silicon in-house
- Customers demanding full ecosystem maturity (toolchains, software stacks, long-term support) before committing
- Lack of regulatory pressure around energy efficiency that might otherwise accelerate adoption
In a nutshell, I question whether it would have been \ prudent for management to have been a little more transparent about the hurdles earlier, instead of allowing enthusiastic messaging to set an expectation of near-term traction that hasn’t materialised.
