Well the fact that BRN are at CES and working from a hotel suite is pretty poor IMO. While it may be normal (to a point) that this happens as there may not be enough room on the floor for them. Nothing about the setup is inspiring whatsoever.
The feel (and I may be wrong) is tucked away, hard to find and not worthy of a place with the real CES showrooms. As much as we try to stay positive about the company, more and more they seem unable to get the tech over the line. The longer they take, that 3 year advantage is slowly dwindling away. 3 years ago AKIDA 1000 had a 3 year lead. Sales?
More and more we see these types of AI appearing.
Use Cases:
- Image and Video Analysis: Edge AI is commonly used for tasks like object detection, facial recognition, and image classification directly on cameras or smartphones.
- Predictive Maintenance: IoT devices equipped with Edge AI can predict equipment failures by analyzing sensor data locally.
- Voice Recognition: On-device voice assistants leverage Edge AI for natural language processing without continuous internet connectivity.
In summary, Edge AI empowers devices to perform AI tasks locally, leading to faster response times, improved privacy, and efficient use of resources. The technical implementation involves deploying optimized models, preprocessing data, and leveraging hardware acceleration on edge devices.
******* has introduced the Vision Pro augmented reality headset, ushering in a new era of immersive experiences. Paired with the integration of Edge AI into iOS, this dynamic duo promises to redefine how users engage with technology, seamlessly blending the real and virtual realms.
Reading this you'd get excited about this thinking, who is using AKIDA? But I have removed the company name with ***** but you've likely already guessed with the operating system IOS. Yes, this is from Apple.- Full article here. Apple Plans to Integrate EDGE AI into Upcoming iOS Release (themarketinfo.com)
I am aware that this is not saying anything about spiking networks and using neuromorphic computing, However, is this showing us that while our tech may even be better, companies are saying the power saving for these processes aren't big enough to use BRN tech? They can get the job done other ways and saving 5x, 20x the power while great, in the average use during the day to day of a phone (for example) doesn't warrant the need for AKIDA.
More and more (IMO) this looks like a cool toy people are impressed with, but doing it like that, cool but not needed.
I suppose look at it like this. Batteries are getting better, the new phones last over 24 hours for years. At the end of a full day do you care if your phone when you plug it back in is at 34% or 25%?
Cars, you save enough overall power to get an extra mile today for the day, because your key word spotting is 5x 10x more efficient? I am aware this is dumbing it down, but IMO that is where BRN are at. A gimmick that people are amazed at but we can do it another way with our current partners or in house tech. So thanks for the sideshow, but we are good.
(20min delay)