BRN Discussion Ongoing

Hey FF has there been any links to LG,
I was looking today and noticed that Mercedes use their OLED screens ?
I think uiux and Tech have thrown around a few dots. FF
 
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uiux

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Dhm

Regular
https://brainchipinc.com/brainchip-nanose-successfully-detect-covid19/

This announcement from 24th February 2021 was very bullish on the detection of Covid. From the announcement:

“Artificial intelligence in medicine and healthcare is an emerging field and one in which we are eager to contribute with our edge AI processing solution at the Edge, for the benefit of science and humanity,” said Louis DiNardo, BrainChip CEO. Both Louis DiNardo, Brainchip CEO and Orit Marom Albeck, NaNose Medical CEO said: “Using the NaNose Medical artificial nose, and Akida’s artificial brain, is a potential breakthrough in accurate, fast, inexpensive, widespread testing with the potential to control outbreaks and reduce this disease’s death toll.”

I haven't seen anything more about advancing this tech and am wondering if the 1000 Eyes have have seen anything about progressing this.
From another related source https://semico.com/content/nanose-medical-and-brainchip-innovation there is an impressive list of potentially detectable diseases.

List of Diseases Detected by NaNose Medical Nano-array Sensor

COVID-19Crohn’s disease (CD)
lung cancer (LC)ulcerative colitis (UC)
colorectal cancer (CRC)irritable bowel syndrome (IBS)
head and neck cancer (HNC)idiopathic Parkinson’s (IPD)
ovarian cancer (OC)atypical Parkinsonism (PDISM)
bladder cancer (BC)multiple sclerosis (MS)
prostate cancer (PC)pulmonary hypertension (PAH)
kidney cancer (KC)Pre-eclampsia toxemia (PET)
gastric cancer (GC)chronic kidney disease (CKD)
Source: Semico Research and NaNose Medical

Could we realistically see smartphones loaded with AKIDA (and breath sensor) and the possibility of regular testing of millions of people on all of the above diseases? I am dreaming of iPhones offering this in the future, remembering Apple CEO Tim Cook stated health will be the company’s “greatest contribution to mankind."
 
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uiux

Regular
Has anybody done a deep dive into software and BRN? What I see now is Brainchip have the car (SOC) but now we need drivers. I did take note that BRNs software runs EQXX. Big bucks there imo. STPI India Brainchip systems pty Ltd ...🧐
Just my musings

BrainChip doesn't do software other than spiking algorithms

It is wrong to suggest that BRNs software runs EQXX
 
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https://brainchipinc.com/brainchip-nanose-successfully-detect-covid19/

This announcement from 24th February 2021 was very bullish on the detection of Covid. From the announcement:

“Artificial intelligence in medicine and healthcare is an emerging field and one in which we are eager to contribute with our edge AI processing solution at the Edge, for the benefit of science and humanity,” said Louis DiNardo, BrainChip CEO. Both Louis DiNardo, Brainchip CEO and Orit Marom Albeck, NaNose Medical CEO said: “Using the NaNose Medical artificial nose, and Akida’s artificial brain, is a potential breakthrough in accurate, fast, inexpensive, widespread testing with the potential to control outbreaks and reduce this disease’s death toll.”

I haven't seen anything more about advancing this tech and am wondering if the 1000 Eyes have have seen anything about progressing this.
From another related source https://semico.com/content/nanose-medical-and-brainchip-innovation there is an impressive list of potentially detectable diseases.

List of Diseases Detected by NaNose Medical Nano-array Sensor

COVID-19Crohn’s disease (CD)
lung cancer (LC)ulcerative colitis (UC)
colorectal cancer (CRC)irritable bowel syndrome (IBS)
head and neck cancer (HNC)idiopathic Parkinson’s (IPD)
ovarian cancer (OC)atypical Parkinsonism (PDISM)
bladder cancer (BC)multiple sclerosis (MS)
prostate cancer (PC)pulmonary hypertension (PAH)
kidney cancer (KC)Pre-eclampsia toxemia (PET)
gastric cancer (GC)chronic kidney disease (CKD)
Source: Semico Research and NaNose Medical

Could we realistically see smartphones loaded with AKIDA (and breath sensor) and the possibility of regular testing of millions of people on all of the above diseases? I am dreaming of iPhones offering this in the future, remembering Apple CEO Tim Cook stated health will be the company’s “greatest contribution to mankind."
What we have had is on going confirmation from the company then mid last year someone found and posted a promotional video put out by NaNose in which they listed Brainchip as one of their strategic partners. Then Jesse Chapman engaged in a series of emails with NaNose that confirmed the FDA clinical trials were ongoing and someone posted the FDA timeline which ran through to May, 2022. I think this might have been BaconLover???

My opinion only DYOR
FF

AKIDA BALLISTA
 
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Slade

Top 20
This weekend was my first live catchup with a fellow Chipper. A top bloke and needless to say beers were downed and BrainChip stories told.
 
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Diogenese

Top 20
We have established BrainChip Systems India to support the requirement for robust system software and firmware. As Akida is implemented commercially, it is important that our software is mature and provides a positive user experience.”
We have software for Akida Development Environment (ADE) and MetaTF.

We also need some software/firmware to enable our ARM Cortex microprocessor to be able to configure the NPUs and manage the weights for the NPUs.

There is also software used in the CNN2SNN conversion.

https://doc.brainchipinc.com/user_guide/cnn2snn.html

By careful attention to specifics in the architecture and training of the CNN, an overly complex conversion step from CNN to SNN can be avoided. The CNN2SNN toolkit comprises a set of functions designed for the popular Tensorflow Keras framework, making it easy to train a SNN-compatible network.

1647169742416.png




Typical training scenario

The first step in the conversion workflow is to train a standard Keras model. This trained model is the starting point for the quantization stage. Once it is established that the overall model configuration prior to quantization yields a satisfactory performance on the task, we can proceed with quantization.

The CNN2SNN toolkit offers a turnkey solution to quantize a model: the quantize function. It replaces the neural Keras layers (Conv2D, SeparableConv2D and Dense) and the ReLU layers with custom CNN2SNN layers, which are quantization-aware derived versions of the base Keras layer types. The obtained quantized model is still a Keras model with a mix of CNN2SNN quantized layers (QuantizedReLU, QuantizedDense, etc.) and standard Keras layers (BatchNormalization, MaxPool2D, etc.).

Direct quantization of a standard Keras model (also called post-training quantization) generally introduces a drop in performance. This drop is usually small for 8-bit or even 4-bit quantization of simple models, but it can be very significant for low quantization bitwidth and complex models.

If the quantized model offers acceptable performance, it can be directly converted into an Akida model, ready to be loaded on the Akida NSoC (see the convert function).

However, if the performance drop is too high, a quantization-aware training is required to recover the performance prior to quantization. Since the quantized model is a Keras model, it can then be trained using the standard Keras API.

Note that quantizing directly to the target bitwidth is not mandatory: it is possible to proceed with quantization in a serie of smaller steps. For example, it may be beneficial to keep float weights and only quantize activations, retrain, and then, quantize weights.


When Akida is processing input data, the software is dormant.

But when we get to Akida 3000's neural cortex, who knows?
 
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We have software for Akida Development Environment (ADE) and MetaTF.

We also need some software/firmware to enable our ARM Cortex microprocessor to be able to configure the NPUs and manage the weights for the NPUs.

There is also software used in the CNN2SNN conversion.

https://doc.brainchipinc.com/user_guide/cnn2snn.html

By careful attention to specifics in the architecture and training of the CNN, an overly complex conversion step from CNN to SNN can be avoided. The CNN2SNN toolkit comprises a set of functions designed for the popular Tensorflow Keras framework, making it easy to train a SNN-compatible network.

View attachment 2509



Typical training scenario

The first step in the conversion workflow is to train a standard Keras model. This trained model is the starting point for the quantization stage. Once it is established that the overall model configuration prior to quantization yields a satisfactory performance on the task, we can proceed with quantization.

The CNN2SNN toolkit offers a turnkey solution to quantize a model: the quantize function. It replaces the neural Keras layers (Conv2D, SeparableConv2D and Dense) and the ReLU layers with custom CNN2SNN layers, which are quantization-aware derived versions of the base Keras layer types. The obtained quantized model is still a Keras model with a mix of CNN2SNN quantized layers (QuantizedReLU, QuantizedDense, etc.) and standard Keras layers (BatchNormalization, MaxPool2D, etc.).

Direct quantization of a standard Keras model (also called post-training quantization) generally introduces a drop in performance. This drop is usually small for 8-bit or even 4-bit quantization of simple models, but it can be very significant for low quantization bitwidth and complex models.

If the quantized model offers acceptable performance, it can be directly converted into an Akida model, ready to be loaded on the Akida NSoC (see the convert function).

However, if the performance drop is too high, a quantization-aware training is required to recover the performance prior to quantization. Since the quantized model is a Keras model, it can then be trained using the standard Keras API.

Note that quantizing directly to the target bitwidth is not mandatory: it is possible to proceed with quantization in a serie of smaller steps. For example, it may be beneficial to keep float weights and only quantize activations, retrain, and then, quantize weights.


When Akida is processing input data, the software is dormant.

But when we get to Akida 3000's neural cortex, who knows?
Precisely that’s why I am being very nice to AKD1000, 500, 1500 & 2000 just in case. I don’t think I could sleep with the lights out if I had made that remark about “who knows what a neuromorphic chip is anyway.” FF
 
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KMuzza

Mad Scientist
Hard to say where we will end up, but you can see that we are replicating the past, I hope we are at the crossroads now before we move up, being very optimistic that we will follow the trend up as indicated on my chart below with some comments as this is a weekly Heikin ashi chart pointing to a move down in the next week still in the green zone & then moving up where we were previously in the 80c-90c region ...


View attachment 2497
Hi Dolci- can we please have more of your insightful and valued opinion on the TA Chart thread- :love:
THANKS
AKIDA BALLISTA
 
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VictorG

Member
Good morning chippers, wishing each of you a great week.

Yesterday I was at a family function together with many family friends, I intruding many of them to BRN. Collectively we have purchased just shy of 2 million BRN shares over the past 7 months. The mood was upbeat and most were inclined to add to their holdings at these levels.

I asked a mate why he so bullish on BRN, he said the only price he sees is his target price in 2 yrs, everything else is just noise.

GLTA

VG
 
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Tezza

Regular
Good morning chippers, wishing each of you a great week.

Yesterday I was at a family function together with many family friends, I intruding many of them to BRN. Collectively we have purchased just shy of 2 million BRN shares over the past 7 months. The mood was upbeat and most were inclined to add to their holdings at these levels.

I asked a mate why he so bullish on BRN, he said the only price he sees is his target price in 2 yrs, everything else is just noise.

GLTA

VG
I am very similar to your friend, i have a 2 yr target price of $8. Might be optimistic with the current going ins in the world so I may need to stretch to 3 yrs.
 
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chapman89

Founding Member
I am very similar to your friend, i have a 2 yr target price of $8. Might be optimistic with the current going ins in the world so I may need to stretch to 3 yrs.
In 2 years time we will have AKD2000 out of production, consistent flow of revenue, multiple contracts in various industries, most likely will have many US retail and institutional investors buying up shares, I think $8 is conservative for 2 years time.
 
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Interesting, the invasion may spark a China invasion of Taiwan.

ABC News: Taipei residents warn against the idea that 'Taiwan is next' after Russia's invasion of Ukraine.

Good news though:

"The US has the Taiwan Relations Act, which states, "The United States will make available to Taiwan such defense articles and defense services in such quantity as may be necessary to enable Taiwan to maintain a sufficient self-defense capability."

Analysts describe this as "strategic ambiguity" when it comes to what kind of support the US would provide in the event China invaded Taiwan.

But in October last year, when asked if the US would come to Taiwan's defence if China attacked, President Joe Biden responded, "Yes, we have a commitment to do that."
 
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Mccabe84

Regular
I plan on buying more over the next couple of months because Sean said yes there will be revenue this year, so surely the share price would be higher than it is now with revenue coming in
 
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IMPORTANT:

Make sure you take 5 minutes to read the @uiux

BrainChip + Quantum Ventura​

thread. It will be worth the effort.

My opinion only DYOR
FF

AKIDA BALLISTA
 
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Motty

Member
Yes.
Has been discussed.

They claim their aim is to compete with Nvidia. They have three boards ranging in power consumption from 75 watts to 300 watts. They do deep training neural networks and are chasing software development at the moment to support their systems.

They do not do SNN or low power or Ai/AGi.

They call their current product Greyscale.

My opinion only DYOR
FF

AKIDA BALLISTA

PS: More likely to partner with Brainchip than compete just like Nvidia.
Thanks for the reply FF.
 
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The other day Ford’s brain machine interface was discussed with the discovery of its patent for detecting driver alertness and reaction from Brain activity and or muscle response now over on the Mercedes thread Alfie Posted the following link for Mercedes:


I said it the other day the only way this can happen efficiently is with a processor that can recognise spike patterns. We know this is how Neuralink is doing this for Mr. Musk and as I said the crossovers have led many to wonder if Neuralink might be using AKIDA technology.

Is it not just too much of a coincidence that both Ford and Mercedes are doing similar things at the same time as they are working with Brainchip.

As Dio said and all this for just $1.05.

True value should be $1.50 according to Pitt Street Research and since then we have had at least the following:
1. Almost a doubling of staff and larger offices and more staff to come;
2. The release of four commercial ready to buy COTS;
3. The new CEO Sean Hehir
4. The new Head of Marketing Jerome Nadel
5. The confirmation that all 15 EAPs look likely to convert;
6. The licence with MegaChips
7. The very successful capital call on LDA Capital;
8. A great looking annual report showing $49 million in the bank;
9. A 4C showing revenue increasing;
10. Validation unsolicited from Mercedes Benz;
11. Confirmation that Mercedes Benz, Valeo, NASA & Vorago have moved from being simple EAPs to being Early Adopters;
12. Confirmation that Renesas will be releasing MCUs this year with AKIDA technology on board;
13. Go to market readiness of MegaChips with trained staff out there selling AKIDA edge technology;
14. A new Chair of the Board Mr. Viana completing the Brainchip ARM management and strategic plan;
15. The appointment of a highly qualified Australian director;
16. Confirmation that the AKD2000 design is complete and on schedule;
17. The reveal that Brainchip has been awarded research and development grants by the Western Australian and Federal Governments and has had an endorsement by the WA Chief Scientist; and
18. The research grant from the US Airforce for the AKIDA radar project.

Clearly at an average value of 2 cents a point x18 points BRNASX should now be sitting at $1.86 at least.

$1.05 cents is irrational.

My opinion only DYOR
FF

AKIDA BALLISTA
It is now after 10am on Monday and trading has commenced. True to my word I did not debate the comments made by any other poster regarding their views as to whether $1.05 was a rational valuation of BRNASX or not and based on the responses in this straw poll I can conclude:

1. My fair value assessment of $1.88 is incorrect and in the opinion of all those who replied far too low;

2. Minimum fair value is $2.00 at least;

3. Present valuations on the ASX are irrational;

4. I am a downramper sleeper sent by HC to play the long game.

My opinion only DYOR
FF

AKIDA BALLISTA
 
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