Getupthere
Regular
Only Seven weeks to go for the 2.0
Hopefully moved us to the pad in readiness for something decent via official channelsOnly Seven weeks to go for the 2.0
Good to see someone also noticing the funny business occuring. I think ball will drop soon. I loved picking up100K more shares at 36 cents. Mission accomplishedSo many single figure trades today, laughable!
If you don’t realise that there’s manipulation going on with the share price I’m not sure what will make it more obvious?
I want a big announcement, also tattslotto numbers and to be younger and better looking. Looks like I need BRN to shine
University of Virginia Joins the BrainChip University AI Accelerator Program
University of Virginia Joins the BrainChip University AI Accelerator Programwww.businesswire.com
University of Virginia Joins the BrainChip University AI Accelerator Program
August 01, 2023 02:00 PM Eastern Daylight Time
LAGUNA HILLS, Calif.--(BUSINESS WIRE)--BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY), the world’s first commercial producer of ultra-low power, fully digital, event-based, neuromorphic AI IP, today announced that the University of Virginia has joined the BrainChip University AI Accelerator Program, ensuring that UVA students have the tools and resources needed to establish the development of leading-edge technologies that will continue to usher in an era of intelligent AI solutions.
UVA’s computer engineering program gives students an opportunity to collaborate with top researchers in the country and participate in new research initiatives. The program is jointly administered by the Charles L. Brown Department of Electrical and Computer Engineering and Computer Science in the School of Engineering and Applied Science. The BrainChip University AI Accelerator Program equips UVA to incorporate neuromorphic technology – simulation of the brain’s neural network – into the department’s leading-edge curriculum.
BrainChip’s University AI Accelerator Program provides platforms, and guidance to students at higher education institutions with AI engineering programs training. Students participating in the program will have access to real-world, event-based technologies offering unparalleled performance and efficiency to advance their learning through graduation and beyond.
“As technology evolves, we are constantly adding areas of research to allow our students every opportunity to experience cutting-edge technology firsthand,” said Mircea Stan, director of the Virginia Microelectronics Consortium (VMEC) and professor of computer engineering at UVA. “As one of the leading institutions at the forefront of AI, we are excited to partner with BrainChip to share their approach to neuromorphic computing with the next generation of computer scientists by providing them an opportunity to learn and apply practical applications in the world of intelligent computing.”
BrainChip’s neural processor, Akida™ IP is an event-based technology that is inherently lower power when compared to conventional neural network accelerators. Lower power affords greater scalability and lower operational costs. BrainChip’s Akida supports incremental learning and high-speed inference in a wide variety of use cases. Among the markets that BrainChip’s Essential AI technology will impact are the next generation of smart cars, smart homes of today and tomorrow, and industrial IoT.
“The University of Virginia has developed a computer engineering program that focuses on several areas of research that give students a deep and meaningful learning experience across fields that are revolutionizing computing,” said Rob Telson, VP Ecosystems and Partnerships at BrainChip. “Our University AI Accelerator Program continues to provide top educational and research institutions with real-world opportunities to learn more about neuromorphic computing and its applications. We are pleased to work with the University of Virginia on advancing their mission to provide cutting-edge tools and resources that help them achieve their objectives.”
The University of Virginia joins current participants Arizona State University, Carnegie Mellon University, Rochester Institute of Technology, and the University of Oklahoma in the accelerator program. Other institutions of higher education interested in how they can become members of BrainChip’s University AI Accelerator Program can find more details at https://brainchip.com/brainchip-university-ai-accelerator/.
About BrainChip Holdings Ltd (ASX: BRN, OTCQX: BRCHF, ADR: BCHPY) BrainChip is the worldwide leader in edge AI on-chip processing and learning. The company’s first-to-market, fully digital, event-based AI processor, AkidaTM, uses neuromorphic principles to mimic the human brain, analyzing only essential sensor inputs at the point of acquisition, processing data with unparalleled efficiency, precision, and economy of energy. Akida uniquely enables edge learning local to the chip, independent of the cloud, dramatically reducing latency while improving privacy and data security. Akida Neural processor IP, which can be integrated into SoCs on any process technology, has shown substantial benefits on today’s workloads and networks, and offers a platform for developers to create, tune and run their models using standard AI workflows like Tensorflow/Keras. In enabling effective edge compute to be universally deployable across real world applications such as connected cars, consumer electronics, and industrial IoT, BrainChip is proving that on-chip AI, close to the sensor, is the future, for its customers’ products, as well as the planet. Explore the benefits of Essential AI at www.brainchip.com.
Follow BrainChip on Twitter: https://www.twitter.com/BrainChip_inc
Follow BrainChip on LinkedIn: https://www.linkedin.com/company/7792006
About UVA Engineering
As part of the top-ranked, comprehensive University of Virginia, UVA Engineering is one of the nation’s oldest and most respected engineering schools. Our mission is to make the world a better place by creating and disseminating knowledge and by preparing future engineering leaders. Outstanding students and faculty from around the world choose UVA Engineering because of our growing and internationally recognized education and research programs. UVA is among the top engineering schools in the United States for the four-year graduation rate of undergraduate students and among the top-growing public engineering schools in the country for the rate of Ph.D. enrollment growth. Learn more at https://engineering.virginia.edu/.
Contacts
Media Contact:
Mark Smith
JPR Communications
818-398-1424
Investor Contact:
Tony Dawe
BrainChip
tdawe@brainchip.com
BRAINCHIP HOLDINGS LTD
Hopefully moved us to the pad in readiness for something decent via official channels
View attachment 41747
"UVA Joins BrainChip AI Accelerator Program
Charlottesville, Va. — BrainChip Holdings, a California-based producer of artificial intelligence IP that simulates the brain’s neural network, said the University of Virginia has joined its BrainChip University AI Accelerator Program. The company said the move will allow UVA’s engineering department to incorporate neuromorphic technology — simulation of the brain’s neural network — into its curriculum."
https://www.potomactechwire.com/p/potomac-tech-wire-aug-10
UVA’s engineering department
=> https://engineering.virginia.edu/
e. g. =>
"On-Chip Neuromorphic Hardware Will Optimize Size, Power and Speed of Computing Devices
By Karen Walker
mkw3a@virginia.edu
The Virginia NanO-computing (ViNO) group simulates and designs the hardware underlying the internet of things, from exploring the fundamental physics of emerging materials to quantum transport of electrons, to projecting overall device, circuit and system-level performance for memory, logic and sensing applications. Led by Avik Ghosh, professor of electrical and computer engineering and physics, the team develops state-of-the-art computational models and collaborates with experimentalists to understand the limits of various low-power electronic computing paradigms.
At the lowest atomistic level of modeling, the ViNO group specializes in exploring fundamental physical properties of a wide range of nanomaterials for emerging device technologies. Examples include nanomagnetic alloys that can store non-volatile data at high-bit density, 2-D materials such as graphene and topological insulators that capitalize on unconventional electron flow at very high mobility, compositionally graded thermal interface materials that minimize heat loss, and digitally grown III-V alloys and polycrystalline lead salts for high-sensitivity, single-photon detectors.
At the opposite, higher level of systems modeling, the ViNO group is looking at “on-chip” neuromorphic hardware to optimize the trade-off between a device’s size and power requirements and a software algorithm’s processing speed. The group's simulations show that a noisy low-barrier magnet* may enable the design of a scalable low-power hardware unit that behaves like an analog neuron, which can be used in turn to build large-scale hardware neural networks for real-time learning and prediction.
Neural networks are computing systems that learn to perform tasks through training sequences, without being pre-programmed with task-specific rules. This resulting artificial analog neural net could potentially be attached directly on chip with an image sensor to identify and track moving objects on video in real time, and for deployment in self-driving automobiles, robots and unmanned autonomous vehicles.
Maybe that's why they joined the fabulous BRN Ai AP?
A self-contained, low-power hardware neural chip might also be trained to recognize an individual’s medical signals, similar to how an electrocardiogram monitors heartbeats, or to identify atypical events and quickly classify the type of anomaly for real-time personalized medicine. Judicious on-chip processing of sensor data can greatly reduce size, weight and power of such networks, enabling the chip to operate “off line”—in the absence of a reliable wifi signal, and to protect against cyber-hacking.
The ViNO research leverages funding from NASA, the Defense Advanced Research Projects Agency, the Semiconductor Research Corporation’s Joint University Microelectronics Program, and a multi-university National Science Foundation Industry-University Cooperative Research Center on Multifunctional Integrated Systems Technology, for which Ghosh is a site-leader."
Or did NASA give the hint that UVA should join Brainchip's programme?
https://engineering.virginia.edu/ne...s-nano-materials-emerging-device-technologies
* @Diogenese and/or others
What do you think could be meant with 'noisy low-barrier magnet'? Do they mean NC with NVM (non-volatile memory) or something else entirely?
___________
Here in Germany, the universities of Bonn and Bochum should take their feet in their hands and join as well.
Or thereabouts. It's an "expected" date, not set in stone.Only Seven weeks to go for the 2.0
I didnt think of that, Using your smart watch as a remote via hand gesture controls for everything.View attachment 41739
Tata Consultancy Services - Research on LinkedIn: #smartwatch #wearables #researchpaper #tcsresearch #inventingforimpact… | 11 comments
Your #smartwatch is about to get smarter! Existing #wearables have motion sensing capabilities that are limited to mostly activity tracking. At the… | 11 comments on LinkedInwww.linkedin.com
I didnt think of that, Using your smart watch as a remote via hand gesture controls for everything.
Deaf people could also translate in real time to people who can not read sign language via Siri translation.
SNN really needs to be incorporated into smart watches for battery life, performance and efficiency.
View attachment 41613Edge AI in Medical Applications - Digica | AI powered software
A practical use for object detection based on Convolutional Neural Networks is in devices which can support people with impaired vision. An embeddedwww.digica.com
There seems to be a clear inference (sic) in this article that Prophesee are achieving their goals as a result of their collaboration with Brainchip. If that is, in fact, the case then there is the often talked about dot joining us to Qualcomm, albeit indirectly. How many mobile phones are sold worldwide with Snapdragon on board? The mind boggles at what this would mean for Brainchip if Prophesee is incorporating our IP into this deal..........Hard to imagine they wouldn't be after what they have previously said about us closing the circle (my term) for them and their stated goal of a commercial relationship with us. Definitely one to watch closely!!!!!Brainchip mentioned in this article about the same deal with Prophesee.
View attachment 41722
Hi Cosors,"UVA Joins BrainChip AI Accelerator Program
Charlottesville, Va. — BrainChip Holdings, a California-based producer of artificial intelligence IP that simulates the brain’s neural network, said the University of Virginia has joined its BrainChip University AI Accelerator Program. The company said the move will allow UVA’s engineering department to incorporate neuromorphic technology — simulation of the brain’s neural network — into its curriculum."
https://www.potomactechwire.com/p/potomac-tech-wire-aug-10
UVA’s engineering department
=> https://engineering.virginia.edu/
e. g. =>
"On-Chip Neuromorphic Hardware Will Optimize Size, Power and Speed of Computing Devices
By Karen Walker
mkw3a@virginia.edu
The Virginia NanO-computing (ViNO) group simulates and designs the hardware underlying the internet of things, from exploring the fundamental physics of emerging materials to quantum transport of electrons, to projecting overall device, circuit and system-level performance for memory, logic and sensing applications. Led by Avik Ghosh, professor of electrical and computer engineering and physics, the team develops state-of-the-art computational models and collaborates with experimentalists to understand the limits of various low-power electronic computing paradigms.
At the lowest atomistic level of modeling, the ViNO group specializes in exploring fundamental physical properties of a wide range of nanomaterials for emerging device technologies. Examples include nanomagnetic alloys that can store non-volatile data at high-bit density, 2-D materials such as graphene and topological insulators that capitalize on unconventional electron flow at very high mobility, compositionally graded thermal interface materials that minimize heat loss, and digitally grown III-V alloys and polycrystalline lead salts for high-sensitivity, single-photon detectors.
At the opposite, higher level of systems modeling, the ViNO group is looking at “on-chip” neuromorphic hardware to optimize the trade-off between a device’s size and power requirements and a software algorithm’s processing speed. The group's simulations show that a noisy low-barrier magnet* may enable the design of a scalable low-power hardware unit that behaves like an analog neuron, which can be used in turn to build large-scale hardware neural networks for real-time learning and prediction.
Neural networks are computing systems that learn to perform tasks through training sequences, without being pre-programmed with task-specific rules. This resulting artificial analog neural net could potentially be attached directly on chip with an image sensor to identify and track moving objects on video in real time, and for deployment in self-driving automobiles, robots and unmanned autonomous vehicles.
Maybe that's why they joined the fabulous BRN Ai AP?
A self-contained, low-power hardware neural chip might also be trained to recognize an individual’s medical signals, similar to how an electrocardiogram monitors heartbeats, or to identify atypical events and quickly classify the type of anomaly for real-time personalized medicine. Judicious on-chip processing of sensor data can greatly reduce size, weight and power of such networks, enabling the chip to operate “off line”—in the absence of a reliable wifi signal, and to protect against cyber-hacking.
The ViNO research leverages funding from NASA, the Defense Advanced Research Projects Agency, the Semiconductor Research Corporation’s Joint University Microelectronics Program, and a multi-university National Science Foundation Industry-University Cooperative Research Center on Multifunctional Integrated Systems Technology, for which Ghosh is a site-leader."
Or did NASA give the hint that UVA should join Brainchip's programme?
https://engineering.virginia.edu/ne...s-nano-materials-emerging-device-technologies
* @Diogenese and/or others
What do you think could be meant with 'noisy low-barrier magnet'? Do they mean NC with NVM (non-volatile memory) or something else entirely?
___________
Here in Germany, the universities of Bonn and Bochum should take their feet in their hands and join as well.
The trouble is that Qualcomm and Sony manufacture their own chips. So one of them would need to license Akida, and this would require an ASX announcement.There seems to be a clear inference (sic) in this article that Prophesee are achieving their goals as a result of their collaboration with Brainchip. If that is, in fact, the case then there is the often talked about dot joining us to Qualcomm, albeit indirectly. How many mobile phones are sold worldwide with Snapdragon on board? The mind boggles at what this would mean for Brainchip if Prophesee is incorporating our IP into this deal..........Hard to imaging they wouldn't be after what they have previously said about us closing the circle (my term) for them and their stated goal of a commercial relationship with us. Definitely one to watch closely!!!!!
Maybe in a hypothetical senario, to give Sony and Qualcomm the ledging edge 'they' in the interim go through a 3rd party until everything on their end is sorted out this avoids showing their cards and going public.The trouble is that Qualcomm and Sony manufacture their own chips. So one of them would need to license Akida, and this would require an ASX announcement.
Yeah, had a look through the course of sales, and it's incredible the number of 2 figure trades there have been today. Not sure the %, but has to be pretty high.I know my Westpac trading account is normally a bit behind the times but a very slow trading day in progress and most of the exchanges are in the 2 and 3 figure range.
I have found myself becoming immune to these types of days with a shrug of the shoulders and a ho hum.
Happy days around the corner.
Haha, of course, just after I've posted this, someone has decided to put a 500,000 volume trade on. Just like that, we've gone up 1,200,000 in just 15 min.Yeah, had a look through the course of sales, and it's incredible the number of 2 figure trades there have been today. Not sure the %, but has to be pretty high.
We're now half way through the day and the volume sits at 510,100. The lowest volume for a day this year was 2,686,383 back on 4th May. The way things are going, today could beat that low easily.