BRN Discussion Ongoing

[Pom down under]

10 months old

 

[Pom down under]

No mention of brainchip but looks extremely promising

An Energy-efficient and Self-diagnostic Portable Edge-Computing Platform for Traffic Monitoring and Safety | SBIR.gov

www.sbir.gov

An Energy-efficient and Self-diagnostic Portable Edge-Computing Platform for Traffic Monitoring and Safety​

Award Information
Agencyepartment of Transportation
Branch:N/A
Contract:6913G623P800056
Agency Tracking NumberOT-23-FH2-015
Amount:$149,995.68
Phasehase I
Program:SBIR
Solicitation Topic Code:23-FH2
Solicitation Number:6913G623QSBIR1
Timeline
Solicitation Year:2023
Award Year:2023
Award Start Date (Proposal Award Date):2023-07-13
Award End Date (Contract End Date):2024-01-12
Small Business Information
CLR ANALYTICS INC
52 Gardenhouse Way
Irvine, CA 92620
United States
DUNS:N/A
HUBZone Owned:No
Woman Owned:No
Socially and Economically Disadvantaged:Yes
Principal Investigator
Name: Lianyu Chu
Phone: (949) 864-6696
Email: lchu@clr-analytics.com
Business Contact
Name: Lianyu Chu
Title: Lianyu Chu
Phone: (949) 864-6696
Email: lchu@clr-analytics.com
Research Institution
N/A
Abstract
Recent advances in technologies have shown great potential for widespread use of Artificial Intelligence (AI) techniques in real-time Intelligent Transportation Systems (ITS) applications. However, the massive amounts of data collected and generated from ITS sensors pose a major challenge in data processing and transmission. This requires a shift from centralized repositories and cloud computing to edge computing. This project proposes an integrated low-power edge-computing system to work with computation-intensive traffic sensors (e.g., video, high-resolution radar, and Lidar) and weather sensors. The system will be designed to be portable, have self-diagnostic capabilities through monitoring sensors and system operations, and send out alerts and data when necessary. The proposed system will include an edge server, which will be developed based on a System-on-Module (SoM) using the latest AI chip, and an innovative hybrid camera that integrates a regular video camera and a FLIR thermal image camera. The project will identify and implement in-situ information processing and extraction algorithms based on machine learning and deep learning techniques to classify vehicles and detect events such as vehicle crashes, the presence of stopped vehicles, pavement and environmental conditions, and wildlife. The prototype will be demonstrated at a California test site in collaboration with Caltrans.

 

[MDhere]

Too many shares issued. Almost 2 billion.

This seems to worry some...but not me....with caveats to follow

If a 50:1 reverse split was undertaken we would have <40million shares at $7.50 USD or $11.25 AUD.

These numbers are commonplace on NASDAQ....likely our ultimate home.

The issue for me is that stocks priced at <$1 in USD are viewed with suspicion/derision in the US....and trust me that is a massive understatement. Most prospective buyers will dismiss without even taking a look.

Easy to buy/sell a $7.50 equity, almost impossible to buy/sell a $0.15 equity.

My suggestion....Brainchip, the company, wake up to the real world. Stock markets are conservative and appearance matters and they don't perform well as science fiction in fantasyland.

I'm certainly not keen on this type of conversion as imo there is a major risk of smashing the price down as some people don't understand this type of conversion.
Maybe we wait till we are $5 then do 2:1 conversion?
There are plenty of major companies in the u.s with well over 3 billion shares outstanding, well over. Take Tesla for an example I wrote this post it note to remind me that our outstanding share is fine. ( silly me didn't date it but its been stuck on my computer speaker so may be a diff now) but at that time they had well over 3.16 billion. And here are some Companies well over our outstanding shares -
Tesla 3.16 B (already mentioned above)
Intel 4.2B
Apple 15.5B
Amazon 10.3B
Microsoft 7.3 B
Google 12.6 B
So when (positive mind thinking) we go to $5 EVEN $4 then do a small 2:1 to get into the u.s stock exchange that i think is enough to make easy move then imo. it would then become 2:1 so would be approx 8 aud which will be entering at $5.22usd (as I believe it must be at least $4usd to meet entering criteria) i would be comfortable with that. Of course all imo

 

[RobjHunt]

I am having a little difficulty copying and pasting this material but someone who is on LinkedIn might have better luck but if not the substance of this information is easy to grasp even if it does not present beautifully.
My opinion only DYOR
Fact Finder

Rudy Pei​

(He/Him)
Physicist | ML researcher | quantum & neuromorphic computing | behavioral economics | composer

Senior ML Research EngineerSenior ML Research Engineer
BrainChip · Full-timeBrainChip · Full-timeOct 2021 - Present · 2 yrs 5 mosOct 2021 - Present · 2 yrs 5 mosUnited StatesUnited States

• • Doing very "cool" ML stuff, literally. Researching ultra low-power neural networks for the edge, achieving 100x to 1000x times savings in model size, memory, and compute. I mainly developed the temporal event network (TENN) network for the second-generation Akida hardware, achieving state-of-the-art results in multiple tasks such as: object detection, motion planning, raw ASR, raw denoising, and NLP.
    
    I created highly optimized training pipelines for in-house models using techniques as kernel fusion with triton and CUDA. In addition, I supported the software team in compressing and quantizing the networks, and supported the hardware team in the RTL simulations. Doing very "cool" ML stuff, literally. Researching ultra low-power neural networks for the edge, achieving 100x to 1000x times savings in model size, memory, and compute. I mainly developed the temporal event network (TENN) network for the second-generation Akida hardware, achieving state-of-the-art results in multiple tasks such as: object detection, motion planning, raw ASR, raw denoising, and NLP. I created highly optimized training pipelines for in-house models using techniques as kernel fusion with triton and CUDA. In addition, I supported the software team in compressing and quantizing the networks, and supported the hardware team in the RTL simulations.…see more
• • Model Compression, Computer Science and +13 skills

Funny, I pressed on …see more, there at the end of the txt

 

[IloveLamp]

Not got a clue who Tim is

“Inception” — Tiny Stock teased as “Next NVIDIA” by Tim Bohen?​

Bohen & Sykes tease that "Bill Gates is all about this tiny $2 stock" -- What's the AI/Autonomous Driving company being touted by StocksToTrade?​

https://www.stockgumshoe.com/reviews/stockstotrade-advisory/inception-tiny-stock-teased-as-next-nvidia-by-tim-bohen/?amp

Incredible. Everyone must read imo. Wow!! What a find

“Tech giants like Megachips, ARM, and Magic Eye have also already made huge deals with the maker of Inception.

“Even NASA jumped on board to use this incredible technology.

“A tiny company trading for under $2 holds the REAL key to the future of this industry that’s ready to explode.”

“It has also been on a partnership spree over the last handful of months.

“In fact, their recent partnerships with companies valued at over $242 Billion have them prepared for growth on a grand scale…

“And experts have taken notice…predicting that in the years to come…

“Inception will be partnered with dozens… if not hundreds more household names, potentially generating tens of millions in cash flow.”

!!!!!!!

 

[Pom down under]

A sunday read if you can put up with a draft

https://ecssria.eu/assets/documents/2024%20draft%20chapter%201.1%20for%20public%20consultation.pdf

 

[Pom down under]

Another Sunday read, not that I’ve read any of em.

https://www.eetimes.eu/semiconductor-market-rebound-expected-in-2024-but-challenges-lie-ahead/

 

[Fact Finder]

​

View attachment 56471​

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Wearable Technology with Environmental Sensors​

Along with the emergency response equipment first responders bring to a rescue situation, there are emerging technologies that can equip them for safety in a number of ways. Wearable tech can inform supervisors if team members are experiencing any spikes in heart rate or blood pressure, as well as other biometric data, while environmental sensors can determine if any toxins or dangerous chemicals are present in the surrounding environment. Measuring blood oxygen levels via pulse oximetry sensors can tell firefighters when they’ve been overexposed to smoke-filled air, and body positioning sensors like the kind used in some step counters and other fitness trackers can sound the alarm when a first responder is lying prone or in any awkward position that might indicate potential distress. Something as simple as monitoring body temperature can let firefighters know when to pull back from the front lines and rehydrate.

Environmental sensors capable of measuring the presence of airborne pollutants or particulate matter are commonly implemented in industrial manufacturing and processing facilities for employee safety. First responders can utilize similar technology in a more mobile application to provide them with important safety information about environments they’re encountering with limited prior knowledge.

Concentrations of potentially poisonous and invisible gases in the air, like carbon monoxide or dioxide or volatile organic compounds, can be detected through chromatography and light refraction. Particulate matter created by combustion, like the kind made by forest fires, can also be detected and measured through light reflection. Larger pieces of particulate reflect more light than smaller ones and pose a greater health risk, so measuring the size of particulate fragments as precisely as possible is essential. Environmental data collected from scenes of disasters has value for medical personnel as well. Having prior knowledge of the types of airborne toxins or pollutants victims and evacuees have been exposed to before they’ve even been examined can help develop treatment plans more quickly.

Real-time Data Collection​

Mobile sensors collecting real-time data on first responders’ persons feed the information into an intelligent processing layer and then display data on a “dashboard” of sorts, presenting a digital readout of the various vital signs and environmental factors being monitored. The dashboard can be monitored remotely by first responders on the scene or supervisors offsite to ensure that any responders in distress can be helped as quickly as possible. Real-time data on the surrounding air quality can tell firefighters precisely when they have to employ oxygen tanks in the field in order to breathe safely or when toxic fumes from a chemical spill have become too dangerous to be exposed to without a special breathing apparatus. Vital sign monitoring lets supervisors know when individual firefighters on the front lines of a blaze need a break or medical intervention, similar to the technology being implemented in sports to monitor athletes’ body temperature and blood oxygen levels.

Data collected in real time can also be saved and fed into algorithms that recognize patterns and make predictions to help optimize future emergency response plans. Knowing that personnel can only safely fight fires burning at certain temperatures from specific distances helps spare future hospitalizations, or worse, heatstroke or smoke inhalation. Furthermore, knowing how first responders’ bodies have reacted to the presence of certain gases or volatile organic compounds in the environment can help design emergency treatment options if first responders or victims are exposed in the future and require immediate medical attention in the field. In large-scale personnel deployments, like forest fires or natural disaster relief, historical data on employee health and wellness can help supervisors determine the optimal length and frequency of shifts to maximize overall efficiency and help responders get the appropriate amount of sleep and nutrition.

Conclusion​

Working in potentially hazardous environments is something asked of first responders every day, so monitoring their vital signs as well as key environmental factors is critical to ensuring safety. Using the data collected from first responders on the front lines to optimize future emergency response plans may also save lives and ensure first responders live longer, healthier lives post-retirement. The short- and long-term benefits of wearable technology and environmental sensors are so self-evident that you may see firefighters, EMTs, and even police officers wearing bio- and environmental-metric sensors on a daily basis in the near future.

I suspect most know that AKIDA technology is already proven in this area for newer investors the following two papers cover its applicability to these types of applications.

My opinion only DYOR
Fact Finder

“5. Conclusions​

In this paper, we presented the development of an SNN-based solution for real-time classification of electronic olfactory data. The SNN was implemented using Brainchip’s Akida Development Environment, which provides an emulation of the Akida NSoC’s functionalities on a Python-based software platform. The highlights of this implementation included the development of a novel AER-based encoder for olfaction data, implementation of unsupervised STDP for training the SNN, highly accurate real-time classification results, and preliminary results that lay a foundation for applying the Akida SNN for reliable early classification results.

One of the most significant contributions of this study is the development of AERO, an AER-based data-to-spike encoder for olfaction data. The operating principle of AERO is based on discretizing the sensor responses and encoding their activation levels along with sensor ID and temporal data. For this implementation, normalized relative resistance features were extracted from sensor responses and provided as an input to the AERO encoder. Parameters, such as frequency of event-generation, the number of time points for encoding, and discretization levels, can be configured based on the input data and processing requirements. The development of AERO has opened several avenues for future research, such as encoding multi-dimensional data using different features and interfacing of electronic nose systems with AER-based neuromorphic hardware for processing.

The SNN was tested using the benchmark dataset [20] under four different scenarios of increasing complexity. In general, under each scenario, the classification performance of the SNN was between 90% and 100%, and the processing latency was between 2.5 and 3 s, which includes data-to-spike encoding, learning, classification, and other software-based latencies introduced due to looping and conditional statements. This processing latency would, of course, be dramatically reduced once the classifier is implemented on the Akida NSoC hardware without the overhead of software emulation. Taken together, these classification results show that the SNN-based classifier can deliver highly accurate results with minimal processing latency. Moreover, the ability to transfer the SNN implementation to the Akida NSoC can be leveraged to develop low-power electronic nose systems with minimal computational cost and memory requirements. Intrinsically, in most cases, neuromorphic approaches have proven to outperform traditional processing methods that suffer from limited accuracy, high computational and power requirements, and substantial latency to provide classification results [32]. When evaluated against other neuromorphic and traditional approaches based on the same dataset [21,24,33,34], the results revealed that the SNN classifier developed in this study achieved comparable and, in most cases, better classification performance with minimal computation requirements and latency for both learning and processing. More importantly, the Akida SNN was able to identify patterns from a highly multi-dimensional dataset and classify the dataset based on the four chemical groups of the compounds.

Future research based on these results will focus on the development of a robust SNN-based classifier on the Akida NSoC and its implementation in a real-world application. The efficacy of AERO when combined with rate coding methods, such as [35] and rank-order encoding [2,31,36], will also be investigated. This implementation also lays the foundation for the application of both the AERO encoder and an SNN to study neuromorphic gustation and the fusion of olfaction and gustation for the development of a comprehensive analytical tool for chemical sensing”

A Hardware-Deployable Neuromorphic Solution for Encoding and Classification of Electronic Nose Data

In several application domains, electronic nose systems employing conventional data processing approaches incur substantial power and computational costs and limitations, such as significant latency and poor accuracy for classification. Recent developments ...

www.ncbi.nlm.nih.gov

“4. Conclusions​

This study presents the implementation of a neuromorphic approach towards the encoding and classification of electronic nose data. The proposed approach was used to identify eight classes of malts and has potential as an application for quality control in the brewing industry. Experiments were conducted using a commercial e-nose system to record a dataset consisting of time-varying information of sensor responses when exposed to different malts under semi-laboratory conditions. The classifier proposed in this study utilized the combination of the Akida SNN and the AERO encoder, a neuromorphic approach that has previously delivered highly accurate results on a benchmark machine olfaction dataset [12]. The proposed method successfully classified the dataset with an accuracy of 97.08% and a maximum processing latency of 0.4 ms per inference when deployed on the Akida neuromorphic hardware. A secondary dataset that was used to validate the classifier model in an ‘inference-only’ mode was classified with an accuracy of 91.66%. These results could potentially be further improved by refinements to pre-processing that can enhance informative independent components for malt classes that are misclassified.

Based on these results, we can conclude that the classifier model implemented using Akida SNN in conjunction with the AERO encoder provides a promising platform for odor recognition systems. An application targeted towards the identification of malts based on their aroma profile, generally considered a nontrivial classification task using traditional machine learning algorithms, was successfully demonstrated in this work with a classification accuracy greater than 90% under different scenarios. The developed model can be deployed on the Akida NsoC, thus enabling the integration of a bio-inspired classifier model within a commercial e-nose system. A comparative analysis of the proposed approach with statistical machine learning classifiers shows that the SNN-based classifier outperforms the statistical algorithms by a significant margin for both accuracy and processing latency. A performance-based comparison of the neuromorphic model proposed in this work with other neuromorphic olfactory approaches, such as [13,14,26,27,69,70], could not be established as their inherent structures, including spike encoding schemes, neuron models, SNN architectures, and implementation of learning algorithms, vary vastly. The proposed methodology, however, does not require a graphic processing unit (GPU)-based model simulation, unlike in [13], or a complex bio-realistic model, as used in [14]. Furthermore, the SNN-based classifier can be entirely mapped on a single neural processing unit core, as opposed to multiple cores used in [14], leading to a low-power and low-latency implementation.

The application of such real-time and highly accurate e-nose systems can be extended to fields such as food technology, the brewing and wine industries, and biosecurity. Future research in this domain will focus on encoding parameters such as rank-order code within the AERO events to analyze its impact on classification performance“

Application of Neuromorphic Olfactory Approach for High-Accuracy Classification of Malts - PMC

Current developments in artificial olfactory systems, also known as electronic nose (e-nose) systems, have benefited from advanced machine learning techniques that have significantly improved the conditioning and processing of multivariate ...

www.ncbi.nlm.nih.gov

 

[IloveLamp]

Incredible. Everyone must read imo. Wow!! What a find

View attachment 56507

“Tech giants like Megachips, ARM, and Magic Eye have also already made huge deals with the maker of Inception.

“Even NASA jumped on board to use this incredible technology.

“A tiny company trading for under $2 holds the REAL key to the future of this industry that’s ready to explode.”

“It has also been on a partnership spree over the last handful of months.

“In fact, their recent partnerships with companies valued at over $242 Billion have them prepared for growth on a grand scale…

“And experts have taken notice…predicting that in the years to come…

“Inception will be partnered with dozens… if not hundreds more household names, potentially generating tens of millions in cash flow.”

!!!!!!!

PROOF IT IS US!!!!!!!!!

WILL YOU ALL FINALLY GET EXCITED!!???

Sean Hehir

Sean Hehir has experience working with technology organisations, managed large global teams and been responsible for explosive revenue growth for glob

www.businessnews.com.au

 

[Fact Finder]

PROOF IT IS US!!!!!!!!!

WILL YOU ALL FINALLY GET EXCITED!!???

Sean Hehir

Sean Hehir has experience working with technology organisations, managed large global teams and been responsible for explosive revenue growth for glob

www.businessnews.com.au

View attachment 56510 View attachment 56511

Hi ILL

Have to pass on excited. I tried it for awhile and people kept saying are you okay you look a bit down so I went back to being ecstatic.

FF.

 

[IloveLamp]

PROOF IT IS US!!!!!!!!!

WILL YOU ALL FINALLY GET EXCITED!!???

Sean Hehir

Sean Hehir has experience working with technology organisations, managed large global teams and been responsible for explosive revenue growth for glob

www.businessnews.com.au

View attachment 56514
View attachment 56511 View attachment 56513

 

[Esq.111]

Hi All

On 19 December, 2023 I posted my then updated list of 50 companies and institutions which have been confirmed as engaged with Brainchip either by Press Release, academic papers, ASX announcements or direct communications with the Director Investor Relations or the CEO Sean Hehir.

Today I updated my list with the disclosures since 19 December, 2023 and it has now reached 55 so I thought as new or potential investors could be looking at Brainchip as a result of this weeks price action it might be a useful first step before they dig into Neuromorphia’s magnum opus via ‘Brainchip AKIDA Ecosystem’ thread:

1. FORD

2. VALEO

3. RENESAS

4. NASA

5. TATA Consulting Services

6. MEGACHIPS

7. MOSCHIP

8. SOCIONEXT

9. PROPHESEE

10. VVDN

11. TEKSUN

12. Ai LABS

13. NVISO

14. EMOTION 3D

15. ARM

16. EDGE IMPULSE

17. INTEL

18. GLOBAL FOUNDRIES

19. BLUE RIDGE ENVISIONEERING

20. MERCEDES BENZ

21. ANT 61

22. QUANTUM VENTURA

23. INFORMATION SYSTEM LABORATORIES

24. INTELLISENSE SYSTEMS

25. CVEDIA

26. LORSER INDUSTRIES

27. SiFIVE

28. IPRO SILICONE

29. SALESLINK

30. NUMEM

31. VORAGO

32. NANOSE

33. BIOTOME

34. OCULI

35. CIRCLE8 CLEAN TECHNOLOGIES

36. AVID GROUP

37. TATA ELXSI

38. GMAC INTELLIGENCE

39. EDGX

40. EUROPEAN SPACE AGENCY

41 UNIGEN

42. iniVation

43. SAHOMA CONTROLWARE

44. MAGIK EYE

45. MYWAI

46. INFINEON

47. ERICSSON

48. MICROCHIP

49. ONSEMI

50. University of Virginia

51. University of Oklahoma

52. Arizona State University

53. Carnegie Mellon University

54. Rochester Institute of Technology

55. Drexel University

My opinion only DYOR
Fact Finder

Good Morning Fact Finder & Fellow Chippers ,

Sterling effort on the updated list.

Having eyeballed your list then, compared with mine , then cross checked with Neromorphia's list ( Thread titled - Brainchip AKIDA Ecosystem ).....

I noticed that Fact Finder's list has not included IPSOLON.

Having a quick look over at the , Brainchip AKIDA Ecosystem Thread.... Mind boggling compilation of documents & links..... in the list @ no.47 sits IPSOLON Research Blue Halo, mentioned in a tweet... possible slip of the finger / tongue.

Big thankyou to all contributors & compilers .

Below is my updated hard copy ,

THE BRAINCHIP SCROLL.

* I feel for past scroll compilers , must have been a bastard of a job without white-out & sticky tape.
.

Regards,
Esq.

 

[Teach22]

View attachment 56516

Proof it is us????

The article says it’s Brainchip. Doh!

Suggest you read the whole thing, it’s nothing to get excited about imo.

 

[SharesForBrekky]

Good Morning Fact Finder & Fellow Chippers ,

Sterling effort on the updated list.

Having eyeballed your list then, compared with mine , then cross checked with Neromorphia's list ( Thread titled - Brainchip AKIDA Ecosystem ).....

I noticed that Fact Finder's list has not included IPSOLON.

Having a quick look over at the , Brainchip AKIDA Ecosystem Thread.... Mind boggling compilation of documents & links..... in the list @ no.47 sits IPSOLON Research Blue Halo, mentioned in a tweet... possible slip of the finger / tongue.

Big thankyou to all contributors & compilers .

Below is my updated hard copy ,

THE BRAINCHIP SCROLL.

* I feel for past scroll compilers , must have been a bustard of a job without white-out & sticky tape.
.

Regards,
Esq.

'You're going to need a bigger scroll'

Your scroll is absolutely GOLD, love it Esq

 

[Damo4]

Proof it is us????

The article says it’s Brainchip. Doh!

Suggest you read the whole thing, it’s nothing to get excited about imo.

@IloveLamp, I know you deleted your "prove it" post, but here's the proof:



"
Well, the good news, assuming you don’t own the stock, is that the share price is a lot lower than $2 now. This is a little Australian company called Brainchip (BRN.AX in Sidney, BRCHF OTC in the US), and here’s my version of the stock chart from those two years, from early 2020 through to early 2022… it’s a clear match, though since this was often a wildly-trading penny stock in 2020 and 2021, you can see that Bohen’s chart must be smoothed out a bit, maybe it’s just a weekly or monthly chart.




And the full picture, up through today, as Tim Bohen keeps pitching this as the “Inception” chipmaker and the key to self-driving cars? Here’s what the five-year chart looks like (this chart is from December, the stock has bounced back by about a penny)

"

 

[Damo4]

@IloveLamp, I know you deleted your "prove it" post, but here's the proof:



"
Well, the good news, assuming you don’t own the stock, is that the share price is a lot lower than $2 now. This is a little Australian company called Brainchip (BRN.AX in Sidney, BRCHF OTC in the US), and here’s my version of the stock chart from those two years, from early 2020 through to early 2022… it’s a clear match, though since this was often a wildly-trading penny stock in 2020 and 2021, you can see that Bohen’s chart must be smoothed out a bit, maybe it’s just a weekly or monthly chart.




And the full picture, up through today, as Tim Bohen keeps pitching this as the “Inception” chipmaker and the key to self-driving cars? Here’s what the five-year chart looks like (this chart is from December, the stock has bounced back by about a penny)

"

It's definitely great that old mate is selling his subscribers in Brainchip, but his goal is to get a monthly subscription.
It's also confirmed in the article Bill Gates basically said none of those things about Brainchip, just Ai in general.

Tim is a salesperson but yes, good to know he's driving some interest our way!

 

[IloveLamp]

It's definitely great that old mate is selling his subscribers in Brainchip, but his goal is to get a monthly subscription.
It's also confirmed in the article Bill Gates basically said none of those things about Brainchip, just Ai in general.

Tim is a salesperson but yes, good to know he's driving some interest our way!

Thanks Damo agreed. Apologies to the forum for my over excitement lol

I saw what @Pom down under posted lying in bed half asleep and speed reading lol not a good combo.

But the u.s.a is waking up and we are about to go for a ride!! That is clear imo dyor

 

[mrgds]

View attachment 56516

Ive always wondered what the "Inc" was in Brainchip Inc.
Now we know its "Inception"

 

[Fact Finder]

Good Morning Fact Finder & Fellow Chippers ,

Sterling effort on the updated list.

Having eyeballed your list then, compared with mine , then cross checked with Neromorphia's list ( Thread titled - Brainchip AKIDA Ecosystem ).....

I noticed that Fact Finder's list has not included IPSOLON.

Having a quick look over at the , Brainchip AKIDA Ecosystem Thread.... Mind boggling compilation of documents & links..... in the list @ no.47 sits IPSOLON Research Blue Halo, mentioned in a tweet... possible slip of the finger / tongue.

Big thankyou to all contributors & compilers .

Below is my updated hard copy ,

THE BRAINCHIP SCROLL.

* I feel for past scroll compilers , must have been a bastard of a job without white-out & sticky tape.
.

Regards,
Esq.

Hi Esq

I only have on my list those things I have actually seen or heard myself.

If you or anyone else has the Ipsolon tweet and can throw it up I will amend my list.

Regards
Fact Finder

 

[4jct]

Too many shares issued. Almost 2 billion.

This seems to worry some...but not me....with caveats to follow

If a 50:1 reverse split was undertaken we would have <40million shares at $7.50 USD or $11.25 AUD.

These numbers are commonplace on NASDAQ....likely our ultimate home.

The issue for me is that stocks priced at <$1 in USD are viewed with suspicion/derision in the US....and trust me that is a massive understatement. Most prospective buyers will dismiss without even taking a look.

Easy to buy/sell a $7.50 equity, almost impossible to buy/sell a $0.15 equity.

My suggestion....Brainchip, the company, wake up to the real world. Stock markets are conservative and appearance matters and they don't perform well as science fiction in fantasyland.

Have to agree Charles and, not to mention, all outstanding shorts have to be handed back in order to facilitate a reverse split which is a handy disruption for these scumbags if timed correctly. A few months ago would have been perfect.