more fleshed-out response:

Yes. Concepts are useless until proven otherwise, but if we want to summarize a whole field of thought and derivative applications, and if we take a reasonable heuristic that a thing can be promising if it shows potential upside without guarantee of success, I would definitively say yes.

For me the phrase is so cool but it lacks sufficient rigor. What's it really mean to take concepts from the brain and apply them, starting with where do you draw the boundary line around member approaches? Neuroscience and computing can inclusively have a lot of overlap: is any logic ‘brain-like’? Do we need to seperate brain and mind and ‘intelligent’ behavior? Your question also begs for a metric of what would be promising. Let's try economically feasible as a filter. There are clear potential benefits to the tech but it's complex and expensive and mostly early r&d, so you see government initiatives, academic projects, niche startups, and FAANG (IBM, Intel). The article citations for this pretty wide field are thorough but here's some personal highlights:

Koniku, biological neural computation start up | koniku.com

blue brain supercomputer sim project | https://www.epfl.ch/research/domains/bluebrain/blue-brain/ab...

Vicarious neuro-centric robotics startup | https://www.vicarious.com/research/

Neuropace anti-epileptic tx device | neuropace.com

Spiking net sim frameworks abound while overshadowed by contemporary ML platforms, I'll feature nengo | nengo.ai
but there's also brian, neuron, nest, spike…
Nengo is primarily maintained by academic startup ABR | appliedbrainresearch.com/about-us/

Strategic endeavors like Allen Institutes for AI and Brain, Janelia Farms neuroscience research campus, things like Brain Initiative in US and Human Brain Project in Europe, DARPA’s continued interest, plus a number of dedicated world research institutions and departments generate exponential contributions to the state of the art throughout the abstraction stack. This top down money/effort is part of the fermentation tank for future breakthroughs, a parallel to pharmaceutical drug discovery.

Two projects I find interesting if perhaps a lot to live up to
Numenta | Numenta.com
OpenCog | https://wiki.opencog.org/w/The_Open_Cognition_Project

At the top levels deepmind would define itself as a neuromorphic computing company; youtube interviews with demis hassabis support this. TPU imo is on the spectrum of a neuromorphic computing device. Elon Musk decided he needed to start a neuromorphic interface company, founded an (originally) non profit existential insurance think tank, and aspects of control dynamics and perception for spacex rockets and tesla autonomous cars all arguably fit into the concept of neuromorphic computing.

How far down the rabbit hole do we want to go? Do we need to see direct and immediate impact of r&d or can we value basic research for secondary effects? What's the goal and value prop of any particular research and what side effects might it have? It's conceivable this tech leads to such horrors and wonders as diverse as perfect digital shadows of our consciousness, which we use as back ups or slaves. It could be integral to autonomous killing robots. It could birth the first synthetic consciousness. It could cure your daughter’s disability, or your dementia. It could grow you a chicken breast without the attached chicken. It might give rise to something as menial as an ad algorithm that’s 5% better or profound as collective consciousness or the end of humanity. At this level of abstraction, tech is a double edged sword that is morally always about how you use it.

Again, promises from people and tech are both often broken, and there’s good reasons to be dismissive or pessimistic. I think there’s significant chance competing technologies win out for a lot of envisioned use cases. Momentum is behind our massive legacy development ecosystem for information processing, and maybe linear algebra brute force function approximators will prove ever sufficient and cost effective. Commercialization is a high bar. Perhaps the implications and risk is ‘too great’, and we decide to morally shun this path. Some systems or understandings of cognition could prove indecipherable and yet necessary. Instability renders the organizational complexity and resource investment required outside the scope of human ability.

Inevitably, time will weed out fledgling neuromorphic developments into whatever real-world penetration and impact they achieve, over whatever rate of adoption. Seems unlikely that nothing at all will ever come of any of it.

I need to wrap this comment but there's so many potential applications from immediate domain things like prosthetics and medical devices, bci's up to power efficient and scaling substrate for AGI or 100x improvement in robotics that it’s hard for me to not get excited about how promising this discipline is, it’s practically a holy grail of disruption. To me many macro trends like Moore's Law, AI renaissance, robotics, Theoretical + Computational + * Neuroscience, better and more medical measuring modalities and data, escalating capability and economic incentive for automation, incentive for medical knowledge and advances, the feedback loop of neuroscience developments advancing computing advancing neuroscience ...plus others… weigh in its favor. Personally this lends a lot credence to a (long term) bullish view for progress. Worth noting, time studying this topic has felt oddly - meditative? Or maybe cosmic is apt. There’s an inherent aspect of self discovery in building off of and deepening understanding of the brain mechanistically, both individually as a human research who contains/is a brain and collectively as a planet of them.

To OP, if you expand on what you mean by synthetic, environmentally embedded neuron clusters I’d be happy to associate and speculate with you.