BRN Discussion Ongoing
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Food4 thought
Regular
But is there any mention of Brainchip being used as yet ????
Or could there be someone else with this technology mmm I wonder
TasTroy77
Founding Member
I am just showing the manual that Gazza found brainchip would not be mentioned directlyBut is there any mention of Brainchip being used as yet ????
Or could there be someone else with this technology mmm I wonder
Learning
Learning to the Top 🕵♂️
Hot off the press from the new Mercedes EQS manual has gesture recognition to control various functions it's a new feature
Hot off the press from the new Mercedes EQS manual has gesture recognition to control various functions it's a new feature
View attachment 19611
And tracks head and eye movements
Attachments
Izzzzzzzzzzy
Regular
This screen shot right above this comment of mine sounds way too much like Akida, I don’t know maybe someone else can verify
Vanguard just invest in ASX300 mate. They don't pick and chooseAbsolutelyEasytiger,
Follow the smart money.
It's great to be a shareholder 🏖.
buena suerte :-)
BOB Bank of Brainchip
So they don't invest in the ASX 200 then??
Whatever is in the top 200 is also in 300
Sirod69
bavarian girl ;-)
Charlie Zhou
Principal hardware Architect at Microsoft writes:It is great honor to have ARM CEO Rene to make keynote speech in CASPA 31st Dinner Banquet,more than 450 people join this event,thanks Chloe Ma, Tony Xia,Mingyu Qu and other CASPA teammate collaboration. as 2021-2022 CASPA president I am very proud of my team to make it happen.
Sirod69
bavarian girl ;-)
I no longer let such sites impress me, we have enough of them here in Germany, e.g. Aktiencheck (https://www.aktiencheck.de/news/Art...e_hat_man_kurzer_Zeit_nicht_erwartet-14903226) , it's always about buying, holding and selling. They calculate the whole thing mainly according to the current course lines. As such, opinions are constantly changing.
I deliberately never put them in here because they don't really mean anything
Sirod69
bavarian girl ;-)
Our very own Rob Telson, Vice President of Ecosystem and Partnerships, will present “Essential AI: Efficient, Effective, Everywhere.” at #IoTWorld & The #AISummit Austin at the Austin Convention Center, November 2 at 12:30 p.m. CDT -Register here: tinyurl.com/4cnrh72w
D
Deleted member 118
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Wouldn’t wanna be a shorter on Monday especially if we get our 4C showing a nice increase in $$$$ and on top of that the Nasdaq is looking good for a nice 2% gain overnight..
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D
Deleted member 118
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D
Deleted member 118
Guest
Nice article including brainchip
idstch.com
Next generation neuromorphic chips bringing deep learning from cloud to IoT Edge Devices and mobiles - International Defense Security & Technology
Within AI is a large subfield called machine learning, the field of study that gives computers the a
idstch.com
thelittleshort
Top Bloke
Nice article including brainchip
Next generation neuromorphic chips bringing deep learning from cloud to IoT Edge Devices and mobiles - International Defense Security & Technology
Within AI is a large subfield called machine learning, the field of study that gives computers the a
View attachment 19623
The BrainChip section copied and pasted
BrainChip’s Akida™ is a revolutionary advanced neural networking processor that brings Artificial Intelligence to the Edge
Akida leverages advanced neuromorphic computing as the engine to solve critical problems such as privacy, security, latency, low power requirements, with key features such as one-shot learning and computing on the device with no dependency on the cloud. These capabilities satisfy next-generation demands by achieving efficient, effective and easy AI functionality.“Sensors at the edge require real-time computation and managing both ultra-low power and latency requirements with traditional maching learning is extremely difficult when it comes to empowering smart intelligent edge sensors,” said Telson. “The Akida processor provides OEMs and car makers with a cost-effective and robust ability to perform real-time, in-vehicle preventative care by running noise and vibration analysis. I’m looking forward to sharing how BrainChip’s Akida makes intelligent AI to the edge easy at both my panel discussion and the roundtable with Denso and Toyota.”
Akida is high-performance, small, ultra-low power and enables a wide array of edge capabilities. The Akida (NSoC) and intellectual property, can be used in applications including Smart Home, Smart Health, Smart City and Smart Transportation. These applications include but are not limited to home automation and remote controls, industrial IoT, robotics, security cameras, sensors, unmanned aircraft, autonomous vehicles, medical instruments, object detection, sound detection, odor and taste detection, gesture control and cybersecurity.
The company has been developing hardened SoC based on FPGA-based spiking neural network (SNN) accelerator, known as Akida (Greek for spike). Instead of just supporting a spiking neural network computing model, now they’ve integrated the capability to run convolutional neural networks (CNNs) as well.
According to Roger Levinson, BrainChip’s chief operating officer, the CNN support was incorporated to make the solution a better fit for their initial target market of AI at the edge. Specifically, since convolutional neural networks have proven to be especially adept at picking up features in images, audio, and other types of sensor data using these matrix math correlations, they provide a critical capability for the kinds of AI applications commonly encountered in edge environments. Specific application areas being targeted include embedded vision, embedded audio, automated driving (LiDAR, RADAR), cybersecurity, and industrial IoT.
The trick was to integrate the CNN support in such a way as to take advantage of the natural energy efficiency of the underlying spiking behavior of the neuromorphic design. This was accomplished by using spiking converters to create discrete events (spikes) from quantized data. In keeping with the low power and more modest computation demands of edge devices, it uses 1-bit, 2-bit, or 4-bit (INT1, INT2, or INT4) precision for each CNN layer, instead of the typical 8-bit (INT8) precision. That saves both energy and memory space, usually at the cost of only a few percentage points of accuracy,
At a higher level, the Akida chip is comprised of 80 Neuromorphic Processing Units (NPU), providing 1.2 million virtual neurons and 10 billion virtual synapses. Each NPU comes with 100 KB of SRAM memory and is networked with its fellow NPUs into an on-chip mesh. Each NPU also contains eight Neural Processing Engines (NPEs) that are in charge of the convolutional support, namely matrix math, pooling, and activation. Since all of this is built around a sparse spiking-based model, the energy efficiency of these CNN operations is potentially much better than that of a GPU, CPU, or even a purpose-built AI accelerator. Levinson said the first silicon will be implemented on 28 nanometer technology and will consume between a few hundred microwatts up to a few hundred milliwatts, depending on the demands of the application. The rest of the SoC consists of I/O and data interfaces, memory interfaces, and an Arm M-class CPU, which is only used for initial setup. There’s also an interface to create a multi-chip array of Akida devices.
Akida is not, however, suitable for training models requiring high precision. It is mainly built mainly for inference work, which is the primary use case for edge devices. That said, it will also able to do some types of incremental learning on pre-trained CNNs, a capability that separates it from competing neuromorphic designs. So, for example, an Akida-powered smart doorbell outfitted with a camera, would be able to augment a facial recognition model to learn the faces of your family and friends, while the same device next door would be able to learn a different set of faces. That capability can be generalized across all sorts of applications where personalized unsupervised learning could be useful, like keyword spotting, gesture detection, and cybersecurity.
Although the first chip will be available as an 80-NPU SoC on 28 nanometer transistors, the platform can be delivered in various sizes and can be etched on any available process node. In fact, BrainChip will sell its technology either as SoCs or as an IP license, the latter for third-party chipmakers to integrate the neuromorphic technology into their own designs. Akida also comes with a full development environment for programmers, including the TensorFlow and Keras tools for standard CNNs, as well as a Python environment to build native SNNs.
At this point, Levinson said they are more focused on AI edge applications in industrial sensors, like smart city IoT, and similarly specialized applications that aren’t amenable to off-the-shelf solutions. While they believe the technology would be eminently suitable for smartphone AI applications, it’s a much longer-term effort to gain entrance into that particular supply chain. At the other end of the market, Levinson believes Akida also has a place in edge servers, which are increasingly being deployed in manufacturing and telco environments.
Slymeat
Move on, nothing to see.
In this article we have the following that annoys me:
Verre said. “We are very active in this area to prepare for the future — we are working with Intel, SynSense, and other partners in this area
So why no mention of Brainchip? Verge has been vocal about his relationship with BrainChip before!
Here was a PERFECT opportunity to promote Brainchip, so why not? It even makes it seem that they are moving away from Akida. Isn’t SynSense a competitor?
And why mention Intel? Their LOHI chip is not yet commercial. Maybe Intel are paying the bills?
Learning
Learning to the Top 🕵♂️
Hi DK,
Not sure I understand your statement.
Vanguard choose asx 300 and above is to reduce volatile of their ETF.
Vanguard choose which company to go into different Vanguard ETF. Some company are in more than one ETF.
So my understanding is Vanguard do choose.
Learning.
D
Deleted member 118
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Probably written prior to any announcement between us and them and coveted by NDAs I guess
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