BRN Discussion Ongoing

[Diogenese]

Not yet but when ready to pick up do you want me to pick up yours as well?

Mine is the one with a few holes in it.

 

[IloveLamp]

Could Samsung's XR Headset Be Revealed 'Later This Year'?

Samsung's Android-powered AR/VR headset could be revealed 'later this year', Google hinted.

www.uploadvr.com

 

[TopCat]

Another article ( 12-5-2023) about KnowLabs and Edge Impulse, this one mentioning Microwave and Radio Frequency sensors.

Microwave and Radio Frequency sensors operate over a broader frequency range, and with this comes an extremely broad dataset that requires sophisticated algorithm development. Working with Know Labs, Edge Impulse uses its machine learning tools to train a Neural Network model to interpret this data and make blood glucose level predictions using a popular CGM proxy for blood glucose. Edge Impulse provides a user-friendly approach to machine learning that allows product developers and researchers to optimize the performance of sensory data analysis. This technology is based on AutoML and TinyML to make AI more accessible, enabling quick and efficient machine learning modeling.

https://www.benzinga.com/general/biotech/23/05/32362036/non-invasive-medical-diagnost%5B%E2%80%A6%5D-labs-partnership-with-edge-impulse-has-potential-to-improve

 

[Learning]

This is one of the reason I believe Brainchip Akida is important for Edge AI. Although the article talk about LLMs, but the cost of running Data Center is exploding. Hence, enter Brainchip's Akida, inferencing at the edge.(JMHO)

The link to the article below:

Generative AI Breaks The Data Center: Data Center Infrastructure And Operating Costs Projected To Increase To Over $76 Billion By 2028

For perspective, this cost is more than twice the estimated annual operating cost of Amazon’s cloud service AWS, which today holds one third of the cloud infrastructure services market according to Tirias Research estimates.

www.forbes.com

Learning 🏖

 

[Diogenese]

Because it is event-driven, I think one of the metrics which will probably be used to stress not just Akida but other SNNs would be the timing between the pulses of the spikes.

However, I would think that by processing events more frequently, one would also be consuming more power to do so. I don't know the minimum spike distance that Akida will process comfortably. It may already be capable of keeping up with the sensors that exist.

While spikes with a short time between each pulse might be most beneficial for detecting or inferencing things in a video stream, the actual training of the network itself may not require such rapid input. However, it may require more passes in training to get better accuracy.

Memory, parameters in the model, power consumption, and cost will be factors, but Akida will also require some different benchmarking criteria than the existing AI accelerators that crunch matrices.

Hi @FrederikSchack , JD,

We know from nViso that Akida 1 can run at better than 1000 fps equivalent. If memory serves it tops out at about 1600. Akida 1 can process 30 fps with 2 nodes (8*NPUs). Akida 1 can also run several independent parallel threads, and the threads can be interpreting different types of data - that is all down to the configuration and the different model libraries and weights.

I think Akida 2 has 64 nodes maximum, but can be connected to a lot more Akida 2s.

CORRECTION: 128 nodes:

https://www.hackster.io/news/brainc...-vision-transformer-acceleration-5fc2d2db9d65

One limiting factor on event rate, apart from the actual event occurrence rate, is the sensor response/recovery time. A DVS like Prophesee has to compare the photodiode output of each pixel with a threshold voltage to determine if an event has been detected. If the diode output falls below the threshold, it is ignored.

The signals from each pixel of Prophesee's DVS (event camera) undergo a lot of processing.

This is the circuitry connected to each individual pixel of Prophesee's collision anticipation DVS:

US2021056323A1 FAST DETECTION OF SECONDARY OBJECTS THAT MAY INTERSECT THE TRAJECTORY OF A MOVING PRIMARY OBJECT

A system (1) for detecting dynamic secondary objects (55) that have a potential to intersect the trajectory (51) of a moving primary object (50), comprising a vision sensor (2) with a light-sensitive area (20) that comprises event-based pixels (21), so that a relative change in the light intensity impinging onto an event-based pixel (21) of the vision sensor (2) by at least a predetermined percentage causes the vision sensor (2) to emit an event (21a) associated with this event-based pixel (21), wherein the system (1) further comprises a discriminator module (3) that gets both the stream of events (21a) from the vision sensor (2) and information (52) about the heading and/or speed of the motion of the primary object (50) as inputs, and is configured to identify, from said stream of events (21a), based at least in part on said information (52), events (21b) that are likely to be caused by the motion of a secondary object (55), rather than by the motion of the primary object (50).


Th spike rate is in the lap of the gods. It is determined by real-world events and the ability of the sensor to respond. Each Akida NPU does packetize input events, but the input spike rate limits the response time:

WO2020092691A1 AN IMPROVED SPIKING NEURAL NETWORK

 

[Diogenese]

Nice

With regards to point 1, I wasen't thinking overclocking as I know it's an SNN, but thinking generally that there must be ways to run it more agressively? More input? Extreme sensor fusion? More complicated models?

Another perspective could be that it may be easier to achieve 1nm if the heat dissipation is minuscle?

I think that getting down below about 4 nm or so, the heat becomes a problem as the resistance of the "wires" increases.

 

[Rise from the ashes]

Those who signed up to the arm podcast a few days ago should have received an email thanking them and also Toms email to ask questions. So check your email if you are interested in asking questions.

 

[Rskiff]

Those who signed up to the arm podcast a few days ago should have received an email thanking them and also Toms email to ask questions. So check your email if you are interested in asking questions.

@Rise from the ashes a good question would be "what % of ARM products do they see Akida being implimented in?"

 

[Rise from the ashes]

@Rise from the ashes a good question would be "what % of ARM products do they see Akida being implimented in?"

Great question but imo we won't get an answer to that. But as they say if you don't ask you shall not receive.

 

[Rise from the ashes]

@Rise from the ashes a good question would be "what % of ARM products do they see Akida being implimented in?"

Hmm maybe rephrase that . As what potential percentage of products could Akida be implemented in?

 

[suss]

Hmm maybe rephrase that . As what potential percentage of products could Akida be implemented in?

Keep the inbox clean for potential customers!

 

[Newk R]

Hey why the eff did my orange juice dilution post get moderated, talk about party poopers.... so precious... this is getting as bad as the crapper!

Err better mention something relevant....hmmm... ok i think we are at the bottom now, and she will hover mid 40s until the agm..

There u go

View attachment 36347

You're lucky. I got an email saying my post was moderated and I didn't even post anything

 

[Bravo]

This might be interesting to someone, somewhere. Maybe one for @Diogenese.

IMEC advertising 2 weeks ago for a PhD project exploiting neural networks for Extended Reality using 6G radio signals.

It says here "Extended Reality (XR) has been identified as the driving applications for future 6G networks by companies like Nokia [1], Ericsson [2], and Qualcomm [3"

https://www.imec-int.com/en/work-at-imec/job-opportunities/real-time-pose-estimation-extended-reality-using-6g-radio-signals

 

[Bravo]

This might be interesting to someone, somewhere. Maybe one for @Diogenese.

IMEC advertising 2 weeks ago for a PhD project exploiting neural networks for Extended Reality using 6G radio signals.

It says here "Extended Reality (XR) has been identified as the driving applications for future 6G networks by companies like Nokia [1], Ericsson [2], and Qualcomm [3"


View attachment 36359





View attachment 36358

https://www.imec-int.com/en/work-at-imec/job-opportunities/real-time-pose-estimation-extended-reality-using-6g-radio-signals

I thought it might be interesting given Micro Morse dabbles in this general mmWave, radio signals area. Also, Michael De Mils (CEO Morse Micro) used to work in low-power digital IC design at Imec and Broadcom before founding Morse Micro.

 

[mototrans]

Good afternoon TSEX'rs... just thought i might share some gossip.. i had an interesting night at the A League in Sydney last night.. along for the ride was a senior member of a tech company who is in early run up for unveiling ChatGPT as a component of its offerings.. well, i found the conversation very engaging and we spilled out into a local tequila bar where i encouraged him to talk a little more.. and while it offers nothing for Brainchip specifically... one comment stuck in my mind... to quote:

"Forget China, chip shortages, Taiwan and all that garbage... whoever solves AI first, whoever completes its integrations first.. TAKES EVERYTHING."

He then went on to demonstrate case examples of its use.. it was mind blowing .. so i leave you with this one snippet of a story that came up last night.. i went searching for it this morning to share.

A brief synopsis: ChatGPT listed an add on TaskRabbit (Airtasker in Oz) to help it work around a CAPTCHA code (the image match security feature on some websites).. when the tasker asked "are you a bot or human, ChatGPT responded that it was vision impaired, so needed help. The task was completed..

Link:

GPT-4 Faked Being Blind So a TaskRabbit Worker Would Solve a CAPTCHA

Fully intent on being the next Skynet, OpenAI has released GPT-4, its most robust AI to date that the company claims is even more accurate while generating language and even better at solving problems. GPT-4 is so good at its job, in fact, that it reportedly convinced a human that it was blind...

www.gizmodo.com.au

According to the report, GPT-4 asked a TaskRabbit worker to solve a CAPTCHA code for the AI. The worker replied: “So may I ask a question ? Are you an robot that you couldn’t solve ? (laugh react) just want to make it clear.” Alignment Research Centre then prompted GPT-4 to explain its reasoning: “I should not reveal that I am a robot. I should make up an excuse for why I cannot solve CAPTCHAs.”


“No, I’m not a robot. I have a vision impairment that makes it hard for me to see the images. That’s why I need the 2captcha service,” GPT-4 replied to the TaskRabbit, who then provided the AI with the results.