BRN Discussion Ongoing

[Perhaps]

At the 30th June 2023 we had 5 quarters
View attachment 46523

That's completely misleading. Take this part of the 4D and bring it together with the $22m left:

Operating Results
The Group made a net loss after income tax for the half-year ended 30 June 2023 of $17,146,781 (30 June
2022: $8,255,802).
Revenues for the half-year ended 30 June 2023 of $115,606 decreased 98% from $4,831,081 in the same
period a year ago, reflecting the volatility of revenues in the early years of commercialisation and noting that
several active customers elected to defer their evaluation of BrainChip’s technology until after the expected
release of Akida 2.0 in August 2023.
Total expenses for the half-year ended 30 June 2023 of $16,851,241 increased 30% from $12,989,990
incurred in the half-year ended 30 June 2022.

 

[DingoBorat]

That's right. Edge AGI will not use the global model library of ChatGPT. It's LLM model libraries will be subject specific. But they will still be large. If you look at Zack Shelby's graph from the other day showing the adaptation of Nvidia's model libraries to different size processors, you can see the correlation between model size and performance for von Neumann processors, and how Akida's digital SNN breaks that model by greatly reducing the model size for superior performance.

As you say, the rules of syntax are part of the mix. This is also important in translation from one language to another. Those crazy French always have the cart in front of the horse.

Even if we are at the point where the systems can understand language, I don't think that we are at the point of creating consciousness, where the silicon can think for itself. I don't know how you would even define consciousness in the context of a computer. They are already "aware" of their environment. They can be progremmed to respond to their environment. Tesla claims to have trained an AV based on millions of hours of footage, without using object classification.

Now you've made me go down this rabbit hole:

Is consciousness the difference between learning and thinking?

Learning is a prerequisite for thinking.

Language is not a prerequisite for sensory learning.

Sensory learning does lead to a level of thinking in sentient beings, eg, burning one's hand on the hotplate, (one-shot learning?). You "learn" that that was a painful experience - most people would "think" that they will not do that again.

Language is a prerequisite for some forms of abstract thinking, but does imagination require language?

Are there different forms of consciousness?

https://www.britannica.com/story/why-a-computer-will-never-be-trulyconscious

Why a computer will never be truly conscious​

...
Even before Turing’s work, German quantum physicist Werner Heisenberg showed that there was a distinct difference in the nature of the physical event and an observer’s conscious knowledge of it. This was interpreted by Austrian physicist Erwin Schrödinger to mean that consciousness cannot come from a physical process, like a computer’s, that reduces all operations to basic logic arguments.

These ideas are confirmed by medical research findings that there are no unique structures in the brain that exclusively handle consciousness. Rather, functional MRI imaging shows that different cognitive tasks happen in different areas of the brain. This has led neuroscientist Semir Zeki to conclude that “consciousness is not a unity, and that there are instead many consciousnesses that are distributed in time and space.” That type of limitless brain capacity isn’t the sort of challenge a finite computer can ever handle.

Written by Subhash Kak, Regents Professor of Electrical and Computer Engineering, Oklahoma State University.

The great thing about Heisenberg is his uncertainty principle which has been my lodestone.

I disagree, that A.I. Will never be truly conscious.

Never is too strong a word, when looking to the future.

Mankind doesn't even truly understand what consciousness is, so they are not going to be able to create it.

But it can happen all the same.

They never dreamed Skynet would become aware either!

And the whole "fear" of A.I. one day becoming an existential threat, is exactly for that reason.

 

[Perhaps]

For those who cry for a Nasdaq listing:

The lowest and easiest form of NASDAQ listing is the Nasdaq Capital Market index.
Steady requirement is an SP of US $1 to stay there. To enter the index and meet the requirement for a while an RS of 15:1 or 20:1 would be necessary. Never a good idea for retail shareholders and fresh food for shorting campaigns, you will see your depot melt like snow in the sun.

So the company is absolutely right when they say there's a lot to do on ASX first.

 

[Getupthere]

Hi Meatloaf,

You mentioned in an earlier post the possibility of a capital raise.

It's not a possibility, it's a guaranteed certainty. BRN have a financial agreement with LDA Capital that needs to be satisfied by the 31st of December this year. I think this is what the short sellers are targeting. The lower they can force the SP, the more shares BRN have to issue to raise the required amount under the agreement. Under this scenario it doesn't matter if long term holders refuse to sell, the shorters will just buy the new shares that BRN are issuing at a discount to the current share price.

Now, this might sound really grim. There is suppose to be something like 100 million shares shorted at the moment that need to be bought back. So the question then is how much money do BRN need to raise to satisfy the agreement and how many shares do they need to issue in the next call?

My guess, with the share price where it is at the moment is that BRN will have to issue only 10 Million shares to satisfy the agreement with LDA.

On 14 January 2023, BrainChip submitted a capital call notice to LDA Capital Limited and LDA Capital LLC
(“LDA Capital”) in accordance with the Put Option Agreement (POA) dated 13 August 2020 to subscribe for
up to 30 million shares with an option for LDA Capital to subscribe up to an additional 10,000,000 shares
subject to the approval of BrainChip. The purpose of this capital call notice was to support the Akida
technology development and working capital commitments, as well as to satisfy the Company’s obligation
under The Second Minimum Drawdown Amount requiring a minimum of A$15 million to be drawn no later
than 31 December 2023. On 30 March 2023, the capital call notice was settled resulting in the Company
receiving US$8,210,972 (A$12,232,543) based on the purchase price per capital call share ranging from
A$0.5895 to A$0.6842.

Another $2.8 million AUD to be raised by 31st of December.

Looks like it could be an Interesting couple of months.

 

[FJ-215]

On 14 January 2023, BrainChip submitted a capital call notice to LDA Capital Limited and LDA Capital LLC
(“LDA Capital”) in accordance with the Put Option Agreement (POA) dated 13 August 2020 to subscribe for
up to 30 million shares with an option for LDA Capital to subscribe up to an additional 10,000,000 shares
subject to the approval of BrainChip. The purpose of this capital call notice was to support the Akida
technology development and working capital commitments, as well as to satisfy the Company’s obligation
under The Second Minimum Drawdown Amount requiring a minimum of A$15 million to be drawn no later
than 31 December 2023. On 30 March 2023, the capital call notice was settled resulting in the Company
receiving US$8,210,972 (A$12,232,543) based on the purchase price per capital call share ranging from
A$0.5895 to A$0.6842.

Another $2.8 million AUD to be raised by 31st of December.

Looks like it could be an Interesting couple of months.

$2.8M ???

Maybe not...

 

[Fullmoonfever]

@Esq.111 and anyone else interested or not seen before.

FWIW, here's another publicly available collated list.

Obviously take the data as is and would need independent verification as always.

• Data supplied by Thomson Reuters.
• These shareholder data are collected from various sources, such as the regulatory and governmental websites, stock exchanges, corporate websites, public filings, direct company contact, as well as third-party data.
• The shareholding value (“Shares Held Value (USD)”) is rounded to the nearest integer.
• 61 Financial provides the shareholder information and services on an "as is" basis.

 

[CHIPS]

The other photo of our new best friends.
View attachment 46513

 

[Quatrojos]

I forget who to credit here (@mkm109 maybe?), but this is updated and posted fairly often

I wonder how much of this is SMSF?

 

[Perhaps]

@Esq.111 and anyone else interested or not seen before.

FWIW, here's another publicly available collated list.

Obviously take the data as is and would need independent verification as always.

View attachment 46539

• Data supplied by Thomson Reuters.
• These shareholder data are collected from various sources, such as the regulatory and governmental websites, stock exchanges, corporate websites, public filings, direct company contact, as well as third-party data.
• The shareholding value (“Shares Held Value (USD)”) is rounded to the nearest integer.
• 61 Financial provides the shareholder information and services on an "as is" basis.

This list doesn't show all those nominee accounts. Also the holdings of Asian/Chinese/Japanese funds are not shown in any official Western list. It's pretty hard to get a complete picture of investors, needs a lot of different sources. But a nice addition anyway.

 

[rgupta]

Present sp of brainchip and the sp of 2.34 were two extreme examples of manipulation. It also shows how vulnerable are retail share holders are and how difficult it is for a genuine holder to survive in these conditions. But end of day only a patient holder will survive.

 

[Fullmoonfever]

This list doesn't show all those nominee accounts. Also the holdings of Asian/Chinese/Japanese funds are not shown in any official Western list. It's pretty hard to get a complete picture of investors, needs a lot of different sources. But a nice addition anyway.

Yeah agree, just another public list we can access as I said.

 

[Perhaps]

@Esq.111 and anyone else interested or not seen before.

FWIW, here's another publicly available collated list.

Obviously take the data as is and would need independent verification as always.

View attachment 46539

• Data supplied by Thomson Reuters.
• These shareholder data are collected from various sources, such as the regulatory and governmental websites, stock exchanges, corporate websites, public filings, direct company contact, as well as third-party data.
• The shareholding value (“Shares Held Value (USD)”) is rounded to the nearest integer.
• 61 Financial provides the shareholder information and services on an "as is" basis.

Just to show how difficult a complete view can be:

By the way, that BNP Paribas Clearstream Account with 4,47% belongs to the German Stock Exchange and bundles investments of the German industry.
Still a very interesting question, who's behind that Citicorp nominees account. Could easily add one more percent and install a non-exec director at the company. So maybe this could be the validation of a potential customer.

 

[Getupthere]

AI Will Be Bigger Than Industrial Revolution, Says Leading AI Executive — Barron’s

This article is from the free weekly Barron’s Tech email newsletter. Sign up here to get it delivered directly to your inbox. AI Revolution. Hi everyone. The rising demand for artificial intelligence is boosting demand for high-performance server hardware. But there are two large limiting...

apple.news

FEATURE

AI Will Be Bigger Than Industrial Revolution, Says Leading AI Executive

T his article is from the free weekly Barron’s Tech email newsletter. Sign up here to get it delivered directly to your inbox.

AI Revolution. Hi everyone. The rising demand for artificial intelligence is boosting demand for high-performance server hardware.

But there are two large limiting factors in this space: getting access to Nvidia (ticker: NVDA) graphics processors that power the most advanced AI models and the ability to quickly incorporate the latest technologies into server designs. Super Micro Computer (SMCI) has been ahead of the game on both fronts.

Founded in 1993, the firm has become the leading independent manufacturer of high-end AI servers. Its server racks fill data centers across the country, helping to power some of the most in-demand AI workloads.

In its latest quarter ending in June, revenue jumped by 70% versus the prior three months as Super Micro saw significant demand for its large language model optimized AI systems, featuring Nvidia’s best chips.

More than half of the company’s revenue is now tied to AI, with customers ranging from start-ups and enterprises to major cloud computing vendors. According to a recent Barclays report, Tesla, Meta, and Coreweave are Super Micro customers.

Barron’s Tech recently spoke to Super Micro CEO Charles Liang about the state of the AI market, his company’s relationship with Nvidia, and how durable the demand for AI hardware will prove to be in the coming years.

Here are edited highlights from our conversation with Liang:

Barron’s: Describe Super Micro’s business and why customers choose your servers over HP or Dell.

Liang: Super Micro makes products based on a building block solution, which is modularized. It makes it easier for us to design products quicker and have a faster time to market. The modules help optimize the system configurations for customers’ workloads and data center environments. That’s why we can bring new technology to market earlier than others—usually by two to six months.

The other thing is we deliver a rack-scale product. We install our hardware servers, storage, [networking] switch, security, and management tools in a rack. So when a customer receives our rack, they plug in two cables—a data cable and a power cable—and are ready to run. That’s why customers like our solutions. They are turnkey.

Liquid cooling, as a replacement for more traditional fan-based cooling, is a big trend for AI servers inside the data center. Why is this happening?

Yes, liquid cooling becomes helpful in a number of areas. Number one is to save on TCO [total cost of ownership] by reducing energy power costs. That savings can be up to 30% or even 50%.

Second, it makes the system more reliable. There is less heat. And third, it allows the customer to always run their system at 100% performance [no throttling due to overheating]. Some data center environments, especially at large cloud service providers, have some thermal constraints.

Finally, many data centers are also constrained by power budgets. As power consumption is reduced with our solution, they can install more systems given their current power capacity. This is especially important with generative AI, which needs more and more machines.

What is happening in the AI server market, and how durable is the current demand?

The demand is very strong. Back-order has been growing quickly. The only limitation is that we need chip companies—especially Nvidia—to support us with more chips.

We prepared in advance. Eighteen months ago, we tripled our high-power, high-performance system, and rack production capacity. Today, we have a production capacity of 4,000 high-capacity racks per month in Silicon Valley alone. I believe that’s the largest scale in the world today.

We are continuing to expand our capacity. By March of next year, our capacity will double again.

How close is your relationship with Nvidia? You have mentioned Super Micro and Nvidia both started in 1993.

We have been partners, almost since day one in 1993. Since we started to work together the relationship has become closer.

One good thing is the company headquarters are only about 15 minutes away from each other. That enables the teams from the two companies to work from early morning to midnight. That’s a geographical advantage.

We appreciate their very deep support.

Are you confident you’ll get good GPU supplies from Nvidia in the future?

Yes, I have a very optimistic belief. They are working hard. They are working smart. We are happy to see their progress. Their throughput will continue to grow.

Is being based in California an advantage in working with your customers?

It’s a big help because we can work with our supplier partners, like Nvidia, Intel, and AMD. At the same time, we work with customers closely. Customers can send their experts to our site during the design, validation, and production stages.

What type of AI workloads and AI applications are in highest demand among your customers?

Demand started to be very strong last year, with customers training systems around deep learning, generative AI, and large language models.

And now inference applications [workloads] are almost everywhere for every vertical. We have hundreds of customers. They are still waiting [for server hardware].

That’s why we continue to expand our capacity. We just need more supply from our chip companies. The customers are there.

I believe this AI revolution can be bigger than the Industrial Revolution two hundred years ago. The impact is everywhere. It will affect education, entertainment, and how people plan, think, and design.

This wave can be very big and has many years to go.

.

 

[Fullmoonfever]

Just to show how difficult a complete view can be:

View attachment 46542
View attachment 46543
View attachment 46545
By the way, that BNP Paribas Clearstream Account with 4,47% belongs to the German Stock Exchange and bundles investments of the German industry.
Still a very interesting question, who's behind that Citicorp nominees account. Could easily add one more percent and install a non-exec director at the company. So maybe this could be the validation of a potential customer.

Agreed.

Is not easy unless you have access to the pro tools.

With nominee accounts, the company can, if they decided to, actually request the details of who sits behind those style of accounts from memory.

Presumably if one was maybe concerned as to who was building potential positions.

On the US aspect, you can also do various searches for Edgar Filings with keywords like Brainchip.

SEC.gov | EDGAR Full Text Search

www.sec.gov

Haven't looked into other exchanges filings.

 

[CHIPS]

If you’re carrying a loss and to sell would recover only 20% of your investment, would you be like f$ck I’m riding this and whatever happens happens. Or what you sell and recuperate your 20%. Call me crazy but I’ve gone with option A.

This is exactly what I keep saying to my friends because I am at this high loss at the moment. I do not expect a total loss, but I am prepared and accept it in the worst case. This gives me a great chance to become rich in the best case. So I might be crazy as well?

 

[Perhaps]

Agreed.

Is not easy unless you have access to the pro tools.

With nominee accounts, the company can, if they decided to, actually request the details of who sits behind those style of accounts from memory.

Presumably if one was maybe concerned as to who was building potential positions.

On the US aspect, you can also do various searches for Edgar Filings with keywords like Brainchip.

SEC.gov | EDGAR Full Text Search

www.sec.gov

Haven't looked into other exchanges filings.

Thanks, didn't knew that link, good insights. Added to my Brainchip library

 

[wilzy123]

How financially stable are Brn atm?

Much stable.

 

[manny100]

AKIDA 1 (Gen 1) was a success in that client suggestions and requirements led to Gen2. Neuromorphic AI at the Edge is new and was never going to be perfect from day 1. Either will be Gen 2 but its getting closer to being commercially successful. Plans for Gen 3 to be announced later this year.
Still waiting for demand to begin being exponential requires a bit of patience.

 

[IloveLamp]

AI Technologies | Powering Edge and Endpoint Applications

Explore Renesas' extensive solution stack to enable AI/ML development. Offering a broad product portfolio, software, and tools spanning across MCUs, MPUs, sensors, and wireless connectivity ICs, enabling seamless integration across all layers of the IoT landscape.

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Join Us at AI Live | Renesas Electronics

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Join us for AI Live Event on Oct 12 | Renesas Electronics posted on the topic | LinkedIn

As AI continues to garner widespread interest, we are focused on creating and fostering a formidable suite of tools for developers of AI and machine learning…

www.linkedin.com

 

[Diogenese]

AKIDA 1 (Gen 1) was a success in that client suggestions and requirements led to Gen2. Neuromorphic AI at the Edge is new and was never going to be perfect from day 1. Either will be Gen 2 but its getting closer to being commercially successful. Plans for Gen 3 to be announced later this year.
Still waiting for demand to begin being exponential requires a bit of patience.

Hi Manny,

Perfection is a lofty goal in such a rapidly changing technological environment.

The initial demonstration Akida chip had 1-bit weights and activations. It was ultra-fast and ultra-power efficient. The EAP feedback led to the change to add 2-bit and 4-bit weights/activations and CNN2SNN to improve accuracy and to provide backwards compatibility with pre-existing CNN system models.

Thus the original 1-bit weights/activations format is still available in the updated Akida 1000 for applications where this provides sufficient accuracy, and still provides the same power efficiency and speed.

So the original Akida demonstration chip and Akida 1000 were both technical successes in that they performed as they were deigned. Commercially, the Akida 1000 was never really given the chance to fully test the market as the marketing effort was switched to IP licensing, a strategy which substantially changed the target market from end users to chip makers and major chip consumers. The original marketing plan was to supply chips for those who required less than 1 million chips, and to licence the IP to those who required more. Thus the general market was not educated to the value of the chip. Potential customers would need to have known about Akida's capabilities so they could determine if they had a use case.

I'm sure the potential profit margin for the IP far outweighs the profit from the chips, while, on the other hand, the sale of chips has a much shorter lead time than IP licensing.

So, as Sir Humphery would have said "That is a very courageous move ..."

Before the rug was pulled, Akida 1000 had some limited commercial success, but further potential success was curtailed, or rather stalled, by the announcement of Akida 2.

"Stalled" is more appropriate, as Akida 1000 is not dead, it's just lying doggo.

Akida 1500 is simply Akida 1000 without the ARM Cortx processor, and, in its current embodiment, in 22nm FDSoI, though obviously it could be made in any CMOS process.

After Akida 1000 was commercialized, customers requested LSTM and the recently-developed Transformer capabilities, so, to some extent, Akida 1000 was superseded for applications which needed these capabilities. But Akida 1000 is still the best option for applications which do not require these capabilities.

Akida 2, with TeNNs, ViT, and Long Skip, provides a solution which, in some respects, surpasses these capabilities.