Brainchip Klassengruppe WKN: A14Z7W ISIN: AU000000BRN8 Kürzel: BRN Forum: Aktien User: Rarosch

News https://brainchip.com/brainchip-and-lorser-industries-to-develop-neuromorphic-computing-systems-for-software-defined-radio-devices/

Nvidias neues AI Model wandelt 2D Videos in 3D um https://youtu.be/PQMNCXR-WF8

https://community.gsaglobal.org/s/lt-event?id=a1U1K0000079W6vUAE

BrainChip will participate in the Global Leadership Summit. This invitation-only exclusive event brings together the leading global C-level and senior executives from the semiconductor and high technology industry. community.gsaglobal.org/s/lt-event?id=…

Danke für den tip! Bei mir war aber nichts im Ordner!🙋🏻‍♂️

Podcast mit dem Chefentwickler von SmartSense (https://www.smartsense.co/). Absatz aus dem Transscript: – [Ryan] One thing that came up in prior to us chatting was the term neuromorphic computing and that was something new to me. Can you just as to wrap this up just tell our audience what that is. – [Gil] Yeah, absolutely. If you think about your typical chipset, it hasn’t changed in eons. It’s still the same binary, one, zero. And if you think about machine learning and their capabilities, they’re basically relying on GPUs, right? So graphic processing, which can process a lot of things at the same time. Lots of RAM, lots of power. The problem with these ingredients is they don’t scale down very easily. They scale up very easily, but they don’t really scale down very easily. So it’s very difficult to take that and put it on a battery powered device that’s sitting in the middle of a desert. What neuromorphic chip design is trying to do, and by no means, I’m not an expert in that, more of a hobbyist, but what they’re trying to do is really mimic how the brain works and try to convert that into a chip that can execute commands. If you think about the brain as a computing unit, it’s actually very effective. Because it uses a network, almost like a graph database to execute very complex computations, with very little battery, very little calorie consumption. So neuromorphic chips are basically trying to take that same concept and apply it to IoT. Now they’re already companies in that space, like BrainChip that have proven that this is more than just a theory. You could basically take that and execute it. – [Ryan] Yeah, we actually spoke to somebody from BrainChip a number of weeks ago, yeah, it’s a very interesting space for sure. But yeah, thank you for coming on and talking about a lot of these different topics, the security side, the LLMs, AI, all that kind of stuff that’s going on. Very exciting stuff to think about. Considering a lot of people out there that have their solutions out there, the security is something that I think everyone- would highly recommend you think about as early as possible and as frequently as possible. Glad you came on and shed some light onto that. 🍬 https://www.iotforall.com/podcasts/e293-internet-of-things-security-what-to-know 🍬

Schau mal bei den Downloads nach. Da war bei mir die Seite hrruntergeladen

Danke bei mir geht’s auch jetzt

Bei mir auch danke

Danke, geht

Versucht mal den Link hier: https://lnkd.in/gEN3NdXt

Hab auch nen Account! Ok danke fürs Feedback 🙋🏻‍♂️

Ist ein ziemlich langer Artikel. Hier mal der relevante Teil im Wortlaut: Bridging the gap between foundational models and their real-world applications, edge computing emerges as a potent platform for deploying these models, driving AI innovation to new frontiers. Earlier this year, Qualcomm AI Research successfully deployed a popular 1B+ parameter foundation model (stable diffusion) on an edge device through full-stack AI optimization. Edge AI is becoming essential due to its capability for real-time data processing, improved privacy, and enhanced security. It is becoming increasingly significant across various verticals due to the proliferation of devices with numerous sensors producing vast amounts of data. The complexity and resource demands of foundational models pose deployment challenges on edge devices. To counter this, the focus will shift toward specialized hardware, optimization techniques, and neural processor architectures. Being able to run optimized versions of foundational models at the edge/on-device will open up endless possibilities. Recognizing these emerging requirements, BrainChip has stepped forward with innovative solutions like the Akida processor, an advanced neural processing system for edge AI. It’s important to understand and assess edge AI technology to overcome deployment challenges and explore new potentials.

Bei mir auch nicht (hab nen Account). Er leitet auch auf ne komische andere subdomain um. Ich probier’s weiter

Wenn Du bei Linkedin keinen Account hast, kann es eventuell problematisch sein, bin mir nicht sicher.

Spass bei Seite… evtl kann’s auch am Land liegen wo ich bin. Einstellungen sind normal… naja schade