BRN Discussion Ongoing

[Rise from the ashes]

Lol chappy beat me to it

 

[buena suerte :-)]

Great to see World markets having a healthy run........Well needed!! and BRN picking up the pace!​

​

BCHPY​

Brainchip Holdings Ltd.​

Sponsored ADR (1 ADS : 40 Ordinary)

31.14​

4.14
15.33%
27.87 / 31.98 (200 x 560)

BRCHF​

Brainchip Holdings Ltd.​

Ordinary Shares

0.76522​

0.06022
8.54%
0.76 / 0.7774 (9500 x 1000)

BRAINCHIP HOLDINGS LTD​

ISIN: AU000000BRN8 | WKN: A14Z7W | Symbol: 24Y | Type: Equity
OverviewChartsNewsKey DataPrice HistorySustainability
Frankfurt
WatchlistPortfolio
BuySell

► Chart analyses

	13/05/22 16:42:55
Last price	0.73
Change to prev. day	+7.35%

MARKETS​

see all

DOW​	32,196.66	466.36	1.47%
S&P 500​	4,023.89	93.81	2.39%
NASDAQ​	11,805.00	434.04	3.82%

London FTSE 100​

+2.55%7,418.15+189.53

Germany DAX​

+2.10%14,027.93+294.34

​

Japan NIKKEI 225​

+2.64%26,427.65+696.83

Hong Kong HANG SENG​

+2.71%19,906.20+540.13

 

[Foxdog]

Just read the latest Motley Fool article on our company. I'm not a fan of these guys (was a subscriber years ago when they were much smaller and 'nicer'). It does appear as though they are starting to accept us as a serious player, without actually saying it. This speaks volumes for me as the Fool are major down- rampers for any stocks not on their buy list. I'm looking forward to them eating humble pie in the very near future.

 

[Foxdog]

Can robots get drunk

 

[Investig8ed]

Please don't forget GPS controls on Earth Moving Machinery , Civil Construction, especially in remote areas. Mine sites especially

My money is on Caterpilla as they have teamed up with NASA to build autonomous machinery hopefully for their 2024 moon mission

 

[Rise from the ashes]

Sorry if this has been posted as I’m camping down in Tilba Tilba.
But pretty sure the CEO of NVISO is telling us something…..

View attachment 6541

Glad I use a pseudonym. R.W

 

[HopalongPetrovski]

Scott North, 32, is an active member of ASX Stock Tips Group Facebook page and has also shorted stocks as part of his investment strategy. The Sydneysider posted earlier in the Facebook group about shorting tech darling Brainchip.

“I thought it was overvalued, the tech sector as a whole was selling off and it had such a retail following and very little insto support”, says North, who trades his own capital full time. But North says he’s also, at other times, bet that Brainchip’s share price would go up. “Two weeks ago I went long Brainchip and held for a week.”

“Two weeks ago I went long Brainchip and held for a week.”........What a fucktard!

 

[David holland]

"C"....that's my personal vision at this point, but I do know that it's been discussed, I believe all or very close to all hurdles have been cleared, but ultimately I don't sign documents, 2025 maybe a little target to aim for in my opinion, I think pressure will mount to list on the Nasdaq as more US Institutions and partners emerge, I'm pretty confident some major players can see the writing on the wall, whatever their approach towards Brainchip, whether that be taking a % sub 50% or going for an outright takeover, market cap will never be as cheap as it is now...smart visionaries already know that...my future guess would be the likes of Nvidia...I speak for myself, not that of the company..

Why wouldn't they go all the way, Takeovers don't favour shareholders

 

[Deleted member 118]

“Two weeks ago I went long Brainchip and held for a week.”........What a fucktard!

 

[Fox151]

“Two weeks ago I went long Brainchip and held for a week.”........What a fucktard!

A week is long? That's like calling 2 inches big.

 

[Fox151]

Not sure if this posted before but a neat demo by Renesas

I'm so conflicted by this. I despise those self serve checkouts.... but if they're using BRN, I'm gonna have to support them.

 

[Fact Finder]

What really annoys me is someone constantly telling me what I already know. It is just soooo annoying.

My opinion only DYOR
FF

AKIDA BALLISTA

Just so it’s clear I am referring to Tim at Nviso. Will he ever shut up about using AKIDA and how much better it is than other Ai semiconductors. He is like a big kid who is the first one in his class to get a mobile phone.

My opinion only DYOR
FF

AKIDA BALLISTA

 

[Diogenese]

Scott North, 32, is an active member of ASX Stock Tips Group Facebook page and has also shorted stocks as part of his investment strategy. The Sydneysider posted earlier in the Facebook group about shorting tech darling Brainchip.

“I thought it was overvalued, the tech sector as a whole was selling off and it had such a retail following and very little insto support”, says North, who trades his own capital full time. But North says he’s also, at other times, bet that Brainchip’s share price would go up. “Two weeks ago I went long Brainchip and held for a week.”

LSTM (long-short-term-money)

 

[Moonshot]

Akida is needed everywhere, even the economist is making the case this month.. (without actually knowing it!)

 

[Bravo]

lol yeah sorry mate, this is what happens when you find these things when you're half asleep..........

On a more definitive note..........(and this could have been posted before and could be old news, so apologies in advance if that's the case)

VORAGO and TENSOR

NASA SBIR 2020-I Solicitation | H6.22-4509 - CNN RNN Processor | Proposal Summary

Estimated Technology Readiness Level (TRL) :
Begin: 1
End: 4
Technical Abstract (Limit 2000 characters, approximately 200 words)
The ultimate goal of this project is to create a radiation-hardened Neural Network suitable for Ede use. Neural Networks operating at the Edge will need to perform Continuous Learning and Few-shot/One-shot Learning with very low energy requirements, as will NN operation. Spiking Neural Networks (SNNs) provide the architectural framework to enable Edge operation and Continuous Learning. SNNs are event-driven and represent events as a spike or a train of spikes. Because of the sparsity of their data representation, the amount of processing Neural Networks need to do for the same stimulus can be significantly less than conventional Convolutional Neural Networks (CNNs), much like a human brain. To function in Space and in other extreme Edge environments, Neural Networks, including SNNs, must be made rad-hard.
Brainchip’s Akida Event Domain Neural Processor (www.brainchipinc.com) offers native support for SNNs. Brainchip has been able to drive power consumption down to about 3 pJ per synaptic operation in their 28nm Si implementation. The Akida Development Environment (ADE) uses industry-standard development tools Tensorflow and Keras to allow easy simulation of its IP.
Phase I is the first step towards creating radiation-hardened Edge AI capability. We plan to use the Akida Neural Processor architecture and, in Phase I, will:

1. Understand the operation of Brainchip’s IP
2. Understand 28nm instantiation of that IP (Akida)
3. Evaluate radiation vulnerability of different parts of the IP through the Akida Development Environment
4. Define architecture of target IC
5. Define how HARDSIL® will be used to harden each chosen IP block
6. Choose a target CMOS node (likely 28nm) and create a plan to design and fabricate the IC in that node, including defining the HARDSIL® process modules for this baseline process
7. Define the radiation testing plan to establish the radiation robustness of the IC

Successfully accomplishing these objectives:

• Establishes the feasibility of creating a useful, radiation-hardened product IC with embedded NPU and already-existing supporting software ecosystem to allow rapid adoption and productive use within NASA and the Space community.
• Creates the basis for an executable Phase II proposal and path towards fabrication of the processor.

Potential NASA Applications (Limit 1500 characters, approximately 150 words)
NASA applications will include miniaturized instruments and subsystems that must operate in harsh environments, interplanetary CubeSats and SmallSats, instruments bound for outer planets and heliophysics missions to harsh radiation environments. Neural-network and machine learning capabilities are required for robotic vision, navigation, communication, observation and system health management in future autonomous robotic systems.
Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)
The greatest potential for the next computing revolution lies in scaling AI to the billions of smaller, power-constrained Edge devices, while making them Rad-Hard. Innovative signal processing and ML techniques will open up new opportunities for SoC architects to deliver new levels of efficient AI performance in microcontrollers targeted at both the space and terrestrial markets.
Duration: 6

NASA SBIR 2020-I Solicitation | H6.22-6631 - Scalable Neural Net and Neuromorphic Module for In-Space Autonomous Orientation and Maneuvering | Proposal Summary

Estimated Technology Readiness Level (TRL) :
Begin: 5
End: 7
Technical Abstract (Limit 2000 characters, approximately 200 words)
Tensor, along with several commercial partners, is developing new technology suitable for small satellites (SmallSat/CubeSat) and small launch vehicles. As part of this development, we are designing autonomy and artificial cognition capabilities for small scale satellites and vehicles that will be scalable to any space vehicle. Taking advantage of our previous experience in the areas of neural modelling and advanced automation algorithms we are proposing a deep neural net and in-space autonomy and cognition systems neuromorphic processing module for this solicitation. Using the COTS The BrainChip, Inc. Akida with fully configurable neural processing cores and scalable neural nets, we can design autonomy and artificial cognition capabilities for our prototype CubeSat that will be scalable to any space vehicle. The overarching goal is to make spacecraft autonomy affordable and ubiquitous.
For Phase I of this SBIR, we intend to develop a neuromorphic-based modular architecture suitable for SmallSat autonomous operation and create metrics to validate the SWaP performance of our hardware design in Phase II. As with any hardware, the driving cost factor is often the software that makes it useful. In AI systems, the cost of the deep learning needed to provide robust, adaptable performance is often prohibitive. In addition to a modular hardware design, Tensor will also design a cost effective, user-friendly suite of tools to support simplified training and implementation of spacecraft autonomy during Phase I for development and application during Phase II. It is our goal in Phase II of this SBIR to demonstrate an affordable package of prototype autonomous control hardware and software that is scalable and readily adaptable to a variety of spacecraft morphologies and mission classes.
Potential NASA Applications (Limit 1500 characters, approximately 150 words)
The possibilities and applications are practically limitless across a spectrum of mission types. Short list of the possibilities: Predictive and adaptive communications, radio, and system architecture, Opportunistic data collection, Continuous power allocation, Predictive failure/error detection, maintenance, mediation, and mitigation, Mission decision prioritization, Spacecraft constellation active collaboration optimizing, Continuous allocation optimization of system resources, Optimized integration of navigation, situation awareness, etc.
Potential Non-NASA Applications (Limit 1500 characters, approximately 150 words)
Our commercialization plan includes continuing development for the neuromorphic autonomous module for insertion into several commercial small launcher programs now and in the future. We will also apply the technology developed to other military applications with groups such as MDA, DARPA and USAF. The system will be available as a “plug and play module” for all future spacecraft.
Duration: 5

Hi MC,

I just noticed this update on the NASA Space Station Status Report 10 May 2022.

(Extract Only)

SpaceBorne Computer-2 (SBC-2): In an attempt to recover functionality of one of the two SBC-2 server units, an inspection and replacement of the system's ethernet cable was performed. Spaceborne Computer-2 High Performance Commercial Off-The-Shelf (COTS) Computer System on the ISS (SBC-2) builds upon the successes of the Spaceborne Computer. The Spaceborne Computer explored how COTS can advance exploration by processing data significantly faster in space with edge computing and artificial intelligence (AI) capabilities. Spaceborne Computer-2 further tests additional techniques for recovering or mitigating errors in the extreme environment of unprotected solar radiation, galactic cosmic radiation (GCR) and other events. Additionally, Hewlett Packard Enterprise (HPE) works with the space community and the International Space Station-National Laboratory (ISS-NL) to test and demonstrate that current Earth-based data processing of ISS experimental data can be performed onboard during the anticipated 24-to-36-month mission of Spaceborne Computer-2.​

NASA Space Station Status Report 10 May, 2022 - A New Spacecraft to Visit Next Week

Human research took precedence aboard the International Space Station on Tuesday as the seven-member Expedition 67 crew explored how living in space affects the human body. Meanwhile, Boeing’s first crew […]

spaceref.com

 

[Bravo]

Mandatory reading IMO. Article written by René Torres the VP / General Manager of IOT Sales and Marketing Group at Intel Corporation.

sponsored content

Enabling the era of intelligent edge​

René Torres

In a few years, we may be largely living “on the edge.” As the amount of data grows exponentially, there is a greater need for edge computing solutions to aid in real-time decision-making. Gartner predicts that by 2025, 75% of enterprise-generated data will be created and processed at the edge, outside of traditional centralized data centers or the cloud.
But with data centers and cloud computing traditionally supporting data flow, where does edge fit in? As a form of distributed computing, edge computing enables processing to happen where data is being generated. The convergence of 5G networks with edge computing means data is not only traveling faster, but can be quickly translated via media, inferencing and analytics into insights and action, enabling new, ultra-low latency applications to come to life. An autonomous vehicle that senses a pedestrian moving into the road may have less than a second to stop or swerve to avoid hitting them, and removing the latency caused by the data traveling to the cloud and back could literally be life-saving. Other benefits of analyzing data at the edge include stronger security protection of data, lower transportation costs, enhanced data quality and increased reliability, particularly in rural or remote places.



A fireside chat with Intel youtu.be

The opportunities and challenges of edge adoption​

The ability to make fully autonomous vehicles a reality is just one example. Together, 5G and the intelligent edge will enable a new era of distributed intelligence that will transform all types of industries, from smart cities to health care. According to IDC, 77% of U.S. organizations regard edge as a strategic business investment. The need for edge solutions has also been accelerated by the pandemic due to trends like distributed workforces, the growth of remote environments and companies’ digital transformations.
At the same time, while realization of the value of the intelligent edge is growing, companies are struggling to find the right resources to move adoption forward. An IDG survey found that top challenges include identifying clear use cases, security, a lack of internal skills and cost. If the age of distributed intelligence is to reach its full potential, solution providers will need to rely on proven hardware and software platforms, supported by trusted partners with industry-specific experience.

The intelligent edge, practically applied​

On the factory floor, the convergence of technologies like edge, 5G, AI and automation is setting the stage for sectorwide Industry 4.0 transformation. Specifically, edge computing is enabling manufacturers access to real-time insights about operations, which allows them to automate control and monitoring processes, optimize logistics and anticipate and correct anomalies before they impact production. Modernizing the factory can be a complicated process due to the time and cost associated with replacing legacy systems with new technology and ensuring everything seamlessly integrates. However, edge computing with 5G can also provide greater flexibility to connect the factory in stages over time, since compute is localized. Intel is currently working with partners to build an end-to-end smart factory to demonstrate how with a modular application environment, digitalization can happen at any scale.
In health care, edge computing could have a similarly transformative effect on patient care. In the near-term future, edge devices may help with sharing real-time data about patients’ vital signs as soon as they enter an ambulance. Instead of having to run an assessment and additional tests once the patient arrives at the hospital, doctors and clinicians would be able to utilize the data already gathered to begin care immediately, continuing to assess, analyze and adjust treatment through the operative and the post-operative phases and beyond to ensure care is always personalized and based on the most up-to-date information. This is a single example; already, edge devices are being used in many other areas of health care to aid with advanced remote patient monitoring, image-based diagnostics, medical equipment management and robotic surgery.

What’s next for intelligent edge adoption​

As companies’ edge innovations scale and mature, moving from POC to full-scale deployment, collaboration will play a large role in the success of projects. Solution providers are beginning to realize the value of partnering with technology providers with deep, purpose-built portfolios and industry experience to develop customized edge solutions that drive efficiencies and outcomes. Security will remain a key concern, with connected, intelligent devices making attractive targets for attackers interested in stealing data or disrupting the flow of operations. For that reason, providers should also seek platforms infused with silicon-level telemetry to improve the detection of advanced threats at every level.
Distributed computing will enable limitless potential by ensuring many everyday devices aren’t just connected, but intelligent. In this future, data will no longer be stored in centralized locations, but always moving to where it can provide the most value. The companies that master the manipulation of data this way will be the ones to unlock its true potential, unleashing a new wave of innovation.




René Torres
René Torres is currently the VP / General Manager of IOT Sales and Marketing Group at Intel Corporation. René has been with Intel for 20+ years having started in 1997. René has worked in multiple management roles including sales, marketing, product management, and platform application engineering for Intel Architecture and software solutions with a special focus on markets such as wireless communications infrastructure, networking and mobile client computing. Prior to his current role, René was the Director of Marketing & Platform Enabling for Software Defined Networking and Network Function Virtualization in the Data Center Group (DCG). René was also the chief of staff and technical assistant to Doug Davis, SVP and GM of the Internet of Things Group (IOTG). He has worked abroad under three expat assignments in Brazil, China and Germany. René has a BS in Business Administration from Pepperdine University and MBA in Global Management from the Thunderbird School of Global Management.

 

[Realinfo]

Another week older and deeper in…volved !

For mine, the past week was another big one for ‘The Eyes‘. Their dot joining, analysis, research, news and reporting has again been first class. Some within this esteemed group are working twelve hour plus shifts and posting up to twenty comments each day. Those of us like me, who lack the wherewithal to be part of this, are indeed indebted to them for their unflagging efforts to uncover the classified manoeuverings of our battler.

This being the case, and in an my ongoing attempt to generate healthy debate, I do have a couple of questions to pose on what appears to be weather wise…a wonderful weekend ahead.

Having taken the time to read the proposed new company constitution and remuneration report, and with the AGM fast approaching, I’m wondering what you in TSE land think?

Although there has been much speculation about it for sometime, we recently discovered that our company is indeed engaged in a partnership with ARM. As many have stated, this is a very important and welcome development... but it did not come from any formal announcement, a press release, or even a passing mention in an interview. Rather, it was discovered within the depths of our new website. Me myself personally wonders if you think this was the best way to handle such an important declaration?

It’s been another great week for accumulation by trading…see you at the AGM.

 

[Deleted member 118]

Mandatory reading IMO. Article written by René Torres the VP / General Manager of IOT Sales and Marketing Group at Intel Corporation.

sponsored content

Enabling the era of intelligent edge​

René Torres

In a few years, we may be largely living “on the edge.” As the amount of data grows exponentially, there is a greater need for edge computing solutions to aid in real-time decision-making. Gartner predicts that by 2025, 75% of enterprise-generated data will be created and processed at the edge, outside of traditional centralized data centers or the cloud.
But with data centers and cloud computing traditionally supporting data flow, where does edge fit in? As a form of distributed computing, edge computing enables processing to happen where data is being generated. The convergence of 5G networks with edge computing means data is not only traveling faster, but can be quickly translated via media, inferencing and analytics into insights and action, enabling new, ultra-low latency applications to come to life. An autonomous vehicle that senses a pedestrian moving into the road may have less than a second to stop or swerve to avoid hitting them, and removing the latency caused by the data traveling to the cloud and back could literally be life-saving. Other benefits of analyzing data at the edge include stronger security protection of data, lower transportation costs, enhanced data quality and increased reliability, particularly in rural or remote places.



A fireside chat with Intel youtu.be

The opportunities and challenges of edge adoption​

The ability to make fully autonomous vehicles a reality is just one example. Together, 5G and the intelligent edge will enable a new era of distributed intelligence that will transform all types of industries, from smart cities to health care. According to IDC, 77% of U.S. organizations regard edge as a strategic business investment. The need for edge solutions has also been accelerated by the pandemic due to trends like distributed workforces, the growth of remote environments and companies’ digital transformations.
At the same time, while realization of the value of the intelligent edge is growing, companies are struggling to find the right resources to move adoption forward. An IDG survey found that top challenges include identifying clear use cases, security, a lack of internal skills and cost. If the age of distributed intelligence is to reach its full potential, solution providers will need to rely on proven hardware and software platforms, supported by trusted partners with industry-specific experience.

The intelligent edge, practically applied​

On the factory floor, the convergence of technologies like edge, 5G, AI and automation is setting the stage for sectorwide Industry 4.0 transformation. Specifically, edge computing is enabling manufacturers access to real-time insights about operations, which allows them to automate control and monitoring processes, optimize logistics and anticipate and correct anomalies before they impact production. Modernizing the factory can be a complicated process due to the time and cost associated with replacing legacy systems with new technology and ensuring everything seamlessly integrates. However, edge computing with 5G can also provide greater flexibility to connect the factory in stages over time, since compute is localized. Intel is currently working with partners to build an end-to-end smart factory to demonstrate how with a modular application environment, digitalization can happen at any scale.
In health care, edge computing could have a similarly transformative effect on patient care. In the near-term future, edge devices may help with sharing real-time data about patients’ vital signs as soon as they enter an ambulance. Instead of having to run an assessment and additional tests once the patient arrives at the hospital, doctors and clinicians would be able to utilize the data already gathered to begin care immediately, continuing to assess, analyze and adjust treatment through the operative and the post-operative phases and beyond to ensure care is always personalized and based on the most up-to-date information. This is a single example; already, edge devices are being used in many other areas of health care to aid with advanced remote patient monitoring, image-based diagnostics, medical equipment management and robotic surgery.

What’s next for intelligent edge adoption​

As companies’ edge innovations scale and mature, moving from POC to full-scale deployment, collaboration will play a large role in the success of projects. Solution providers are beginning to realize the value of partnering with technology providers with deep, purpose-built portfolios and industry experience to develop customized edge solutions that drive efficiencies and outcomes. Security will remain a key concern, with connected, intelligent devices making attractive targets for attackers interested in stealing data or disrupting the flow of operations. For that reason, providers should also seek platforms infused with silicon-level telemetry to improve the detection of advanced threats at every level.
Distributed computing will enable limitless potential by ensuring many everyday devices aren’t just connected, but intelligent. In this future, data will no longer be stored in centralized locations, but always moving to where it can provide the most value. The companies that master the manipulation of data this way will be the ones to unlock its true potential, unleashing a new wave of innovation.



René Torres
René Torres is currently the VP / General Manager of IOT Sales and Marketing Group at Intel Corporation. René has been with Intel for 20+ years having started in 1997. René has worked in multiple management roles including sales, marketing, product management, and platform application engineering for Intel Architecture and software solutions with a special focus on markets such as wireless communications infrastructure, networking and mobile client computing. Prior to his current role, René was the Director of Marketing & Platform Enabling for Software Defined Networking and Network Function Virtualization in the Data Center Group (DCG). René was also the chief of staff and technical assistant to Doug Davis, SVP and GM of the Internet of Things Group (IOTG). He has worked abroad under three expat assignments in Brazil, China and Germany. René has a BS in Business Administration from Pepperdine University and MBA in Global Management from the Thunderbird School of Global Management.

What’s next for intelligent edge adoption​

As companies’ edge innovations scale and mature, moving from POC to full-scale deployment, collaboration will play a large role in the success of projects.

 

[thelittleshort]

Another new employee at Brainchip - Corporate Marketing Manager ....


View attachment 6537

Did BrainChip just win an Emmy Award with GoPro and Socionext?



Logic as follows:

Samantha Hamilton is ex GoPRO and it seems that she is tight with the old crew (photo below)

Following her LinkedIn likes GoPro just won an Emmy for their advanced image stabilisation (photo below)

Socionext are in partnership with GoPro and share the Emmy due to their contribution - camera sensors (photo below)

Socionext are also obviously involved with BrainChip

 

[Pmel]

Nviso may have been working with us for few years . The new video they posted the other day looks like bit similar