Well the first thing I would say is it does not apply to AKIDA technology.can somebody say or find something about this ... from a brainchip follower at twitter
Automation: Who Is This Human Being? by Nikolaus Kimla - SalesPOP!
The topic of automation and humans is important to consider and think about because humans are the ones behind creating AI. So who is this human?salespop.net
Quick surf while heading to the office and haven't had chance to register but one for the more technically adept?
Not sure what's in there....well, data sheet by looks.
T2M Akida-Scalable Neural Network AI Silicon IP | ChipEstimate.com IP Catalog
AKIDA - Neuromorphic Computingwww.chipestimate.com
View attachment 4697
View attachment 4698
IMO this kind of media announcement ofDESIGNLINES
AI & BIG DATA DESIGNLINE
SiFive and BrainChip Partner to Demo IP Compatibility
By Sally Ward-Foxton 04.20.2022 0
Share Post
SiFive and BrainChip have partnered to show their IP is compatible in SoC designs for embedded artificial intelligence (AI). The companies have demonstrated BrainChip’s neuromorphic processing unit (NPU) IP working alongside SiFive’s RISC–V host processor IP.
Brainchip’s NPU processor IP, the basis for its Akida chip, is a neuromorphic processor designed to accelerate spiking neural networks. This IP can be used to analyze inputs from most sensor types, including cameras, to provide ultra–low power analysis in real–time applications. A recent BrainChip demo showed its Akida chip in a vehicle, detecting the driver, recognizing the driver’s face, and identifying their voice simultaneously. Keyword spotting required 600 µW, facial recognition needed 22 mW, and the visual wake–word inference used to detect the driver was 6–8 mW.
ADVERTISING
BrainChip’s NPU is available as IP or in the company’s Akida chip (Source: BrainChip) (Click image to enlarge)
SiFive is a provider of RISC–V processor IP, including its Intelligence series of multi–core capable RISC–V processors with vector extensions which are optimized for AI workloads in edge devices.
ADVERTISEMENT
SCROLL DOWN TO CONTINUE READING
“BrainChip can run [AI] algorithms on their own, but when they move into a larger system, they will need a host processor,” Chris Jones, vice president, product at SiFive, told EE Times. “You could pick a host processor that does nothing but scheduling, or you could pick a host processor that actually contributes to the AI processing, and that’s where the SiFive Intelligence product comes in.”
In an SoC design for edge AI, the AI workload would typically be split between host processor, vector processor, and AI accelerator — some parts of edge workloads are better suited to general purpose compute rather than a dedicated AI accelerator, Jones said.
“It’s advantageous for BrainChip to align with industry leaders to make sure their customers have a seamless integration experience, so BrainChip can deliver the requisite software that runs on the host processor and makes it easier for the end user to integrate their products and ours,” he said.
Jones described work done so far as the “tip of the iceberg,” adding that the two companies have so far demonstrated compatibility of BrainChip’s IP with SiFive’s RISC–V architecture. The companies will work together on an ongoing basis to further integrate software and hardware IP.
“We have ambitious plans going forward,” Jones said. “SiFive has made great strides in the last year or so, bringing vector processing to market now that [vector processing] has found its niche in AI and image signal processing.”
Part of SiFive’s plan is to build an ecosystem of AI accelerator IP providers whose products are compatible with its host processor IP.
“Our relationship with BrainChip is in no way exclusive,” Jones said. “BrainChip is the first partner we’ve gone public with, but we’re talking to many other players in this space.”
While BrainChip is the company’s first hardware IP partner, SiFive has design wins for its host processor IP, including data center AI accelerator company Tenstorrent.
“Certainly, we’re open to exploring partnerships with people who have novel technology,” he said. “Companies that are bringing IP or chips to market can’t ignore RISC–V as a platform just because of the market share we’re taking.”
Well the first thing I would say is it does not apply to AKIDA technology.
So far the issue with deep training models has been that they are not intelligent so if the programmers do not like shapely short women with green eyes, olive complexions and dark hair this bias might reflect in how they program and this will be an ingrained feature and the deeply trained machine will have no insight and select on the basis of this flawed programming.
It may not even be biased it might be just forgetfulness such as happened with the women pushing a bike across a road having not been a trained image.
Currently when a manager who likes this type of person becomes aware that there are no women matching this description on the shop floor he or she has to suck it up or close everything down and send it back for retraining.
AKIDA on the other hand allows on device personalisation so having noticed this anomaly the manager grabs a few photos and with one shot learning adds this missing profile.
The forgetfulness issue is resolved this way as well - but AKIDA does not identify objects as a whole but looks for enough points of similarity to say this is a person regardless of whether they are pushing a bike or standing on their head naked in the middle of the road.
In both scenarios on chip learning allows human frailty to be accounted for and resolved.
AKIDA allows for the fact that humans are not perfect and make mistakes which may need to be corrected on the fly.
My opinion only DYOR
FF
AKIDA BALLISTA
_ASX Announcement BrainChip Inc and Magik Eye Inc. Partner to Combine Best of AI with 3D Sensing for Total 3D Vision Solution Companies to jointly pursue market opportunities using BrainChip AI processor and MagikEye 3D image sensor technology _IMO this kind of media announcement of
SiFive and BrainChip Partner to Demo IP Compatibility
is definitely worthy of an ASX announcement from our head office to show the broader market who aren't searching the globe from BRN AKIDA media releases that we are actually making progress.
Its called a market update.
The same goes for the Merc media release and anything else newsworthy.
If its big enough news be in the world media, the Company needs to officially update the ASX market, in the interest of shareholder investors. IMO
If they have 100 companies interested in signing it could get a bit monotonous with announcements after a while! . I don’t think these latest engagements are but it could start to look like fluff announcements!_ASX Announcement BrainChip Inc and Magik Eye Inc. Partner to Combine Best of AI with 3D Sensing for Total 3D Vision Solution Companies to jointly pursue market opportunities using BrainChip AI processor and MagikEye 3D image sensor technology _
I agree, back on 20/08/2020 we did announce these types of partnerships then our SP was around 25c then and three weeks later (09/09/2020) around 75c !! so ASX announcements DO make a difference just not sure why this doesn't happen anymore??
Hallo why woman bah, sorry i have no imageNun, das erste, was ich sagen würde, ist, dass es nicht auf die AKIDA-Technologie zutrifft.
Bisher bestand das Problem bei Deep-Training-Modellen darin, dass sie nicht intelligent sind. Wenn die Programmierer also keine wohlgeformten kleinen Frauen mit grünen Augen, olivfarbenem Teint und dunklem Haar mögen, könnte sich diese Voreingenommenheit in ihrer Programmierung widerspiegeln, und dies wird ein tief verwurzeltes Merkmal sein Die tief trainierte Maschine wird keine Einsicht haben und auf der Grundlage dieser fehlerhaften Programmierung auswählen.
Es kann nicht einmal voreingenommen sein, es könnte nur Vergesslichkeit sein, wie es bei den Frauen passiert ist, die ein Fahrrad über eine Straße schieben, ohne ein trainiertes Bild zu sein.
Wenn derzeit ein Manager, der diese Art von Person mag, merkt, dass es keine Frauen gibt, die dieser Beschreibung in der Werkstatt entsprechen, muss er oder sie es aufsaugen oder alles schließen und zur Umschulung zurückschicken.
AKIDA hingegen ermöglicht die Personalisierung des Geräts, sodass der Manager, nachdem er diese Anomalie bemerkt hat, ein paar Fotos aufnimmt und mit One-Shot-Learning dieses fehlende Profil hinzufügt.
Auch das Problem der Vergesslichkeit wird auf diese Weise gelöst - aber AKIDA identifiziert Objekte nicht als Ganzes, sondern sucht nach genügend Ähnlichkeitspunkten, um zu sagen, dass es sich um eine Person handelt, unabhängig davon, ob sie ein Fahrrad schiebt oder mittendrin nackt auf dem Kopf steht die Straße.
In beiden Szenarien ermöglicht On-Chip-Lernen die Berücksichtigung und Lösung menschlicher Gebrechlichkeit.
AKIDA berücksichtigt die Tatsache, dass Menschen nicht perfekt sind und Fehler machen, die möglicherweise spontan korrigiert werden müssen.
Meine Meinung nur DYOR
FF
AKIDA-BALLISTA
Nice to see the BRN Beer Baby Back
OMG we hit $1, maybe someone should organise a party?
Made my day ........
Sean said that he was asking partners if willing to show themselves, which would benefit existing shareholders.If they have 100 companies interested in signing it could get a bit monotonous with announcements after a while! . I don’t think these latest engagements are but it could start to look like fluff announcements!
I’m hopeful Brainchip aren’t as concerned with minor ASX announcements as they will outline their progress at the AGM and the financials will do the talking in the 4c.
I am glad their focus is on selling the product and not the SP!
Fuck Evil Putin!
Peace
Are you swearing at someone?ist unser gutes altes deutschland wird immer gehen die aktien gehen rauf oder runter mal sehen wir sind irgendwie zusammen
View attachment 4710