BRN Discussion Ongoing

Bravo

If ARM was an arm, BRN would be its biceps💪!
Aiieeeyyyee!

On this Youtube interview from 3 days ago, Sam Altman is asked a question about the prospect of developing an on-device model for latency. His response is very interesting and it seems IMO like he believes there will be a necessity for it, especially for generated video content with AR goggles in real-time.


(3.50 mins)

Interviewer :"Do you think you need to develop an on-device model to decrease latency to the point for usability."

Sam Atman: "Umm for video, maybe it would be hard to deal with network latency at some point, like, the thing that I've thought would be super amasing would be to put on someday a pair of AR goggles or whatever and just speak the world in real-time and watch things change and that might get harder over network latency. But for this (meaning ChatGPT 4), 200 or 300 milliseconds of latency feels super, like, it feels faster than a a human responding to me in many cases".

Interviewer "Is video in this case images?

Sam Atman: "Oh, sorry I meant video if you wanted generated video, not input video".

Interviewer " Got it. So currently it's working with actual video the way it is.

Sam Altman: "Well, frame by frame".


 
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7für7

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MegaportX

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Lots of good info coming from everywhere, thanks Chippers, and remember Ai is everywhere now. Hoping AGM goes well, no punches please..

MegaportX.
 

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RobjHunt

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Just voted!

All 8: For
Last one: 110% Against.

Just my 2 cent.

Have a great weekend everyone 😀

Learning 🪴
Great minds think alike ;)

Pantene Peeps
 
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manny100

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"We know the market is heading in our direction, and the ability to process data on The Edge is something that more and more AI applications will be expected to perform. In that case, we are uniquely positioned to capitalise on that trend." bleating is just a smokescreen
Not much more potential investors need to know. The SP at these levels is way undervalued for what is to come.
All the 'where is the revenue' is just a smokescreen to divert attention from the inevitable simple concept as outlined above.
Yes, we BRN are unique as we offer the only 'cloudless' commercial solution ATM - this is an indisputable fact
 
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Moonshot

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BRN has canvassed the funds.
They will vote no spill. They likely will vote YES to remuneration as a strike may lead to an SP drop which sees a fall on the value of funds under their control .
Also those controlling voting have big pay jobs and probably have some empathy for their peers at BRN.
IMO there is no chance of a spill.

Manny how would you come across this information?
 
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Frangipani

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302FDD11-6A30-4FED-B03F-4EE8B1DADF0D.jpeg
 
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manny100

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Manny how would you come across this information?
Sean said on the last podcast that they had put strategies into place including speaking to funds.
 
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Diogenese

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China moving further in front with humanoid robotics, by the looks of things..

 
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Frangipani

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Yes, we BRN are unique as we offer the only 'cloudless' commercial solution ATM - this is an indisputable fact

Is it?

Hi manny100,

I presume you meant to say commercial neuromorphic Edge AI solutions rather than commercial Edge AI solutions in general? But even then, your statement is incorrect. SynSense also offers commercial neuromorphic solutions by now, and so does Innatera:

See this article dated February 6, 2024:


“Innatera, a spinout from the University of Delft, has grown to 65 people with recent funding from the European Innovation Council (15.5 million Euro) alongside Matterwave Ventures and MIG Capital. Commercial samples of the T1 and hardware evaluation kits are available now while the T1 will ramp to production quantities in the second half of this year.

After Mercedes Chief Software Officer Magnus Östberg had posted “Neuromorphic computing? We’ve got that. 😎” on LinkedIn earlier this year, I noticed Innatera’s CEO Sumeet Kumar commenting on his post, and subsequently two neuromorphic researchers at Mercedes liking Sumeet Kumar’s post, so those in the industry involved in neuromorphic tech are evidently aware of the choices they have besides implementing Akida. Of course all those neuromorphic solutions available differ from each other in various aspects - Innatera’s T1 spiking neural processor, for example, is not digital and does not have on-chip learning:


7DB1AC11-E2E9-4613-8A54-D09EC5A0505B.jpeg







88763757-BEC5-4477-8FD4-DDE737A6EE1C.jpeg


37272CD3-F0D2-44B7-A0EC-50C4643416FE.jpeg



The BrainChip website and LinkedIn profile reflect this development by no longer talking about offering the only commercially available neuromorphic processor, but by using the term ‘first-to-market’ nowadays:

BrainChip’s first-to-market, digital neuromorphic processor IP, akidaTM, mimics the human brain to analyze only essential sensor inputs at the point of acquisition—processing data with unparalleled performance, precision, and reduced power consumption.”


Whether or not Akida is the overall best neuromorphic solution available is an entirely different matter. But to say it is “an indisputable fact” that BrainChip offers “the only ‘cloudless’ commercial solution ATM” is simply wrong.

I do agree with you, though, regarding what you said about the BRN share price:
The SP at these levels is way undervalued for what is to come.

Regards
Frangipani
 
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CHIPS

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1716041415502.png


1716041451565.png



News
March 19, 2024

The AI chip hype rolls on: Innatera raises €15m​

In the wake of Nvidia's stock shooting up by nearly 2,000% in five years, investors are looking for the next hardware champion​

Tim Smith
3 min read

If there’s one business in the world winning out of the AI hype cycle right now it’s US chip maker Nvidia. The company — which has a near-monopoly on the specialist processors used for training and running large AI models — has seen its stock price soar by nearly 2,000% since 2019. Now earlier-stage investors are trying to spot the next semiconductor success story.
Today, Netherlands-based Innatera — a company that develops processors designed for use in “edge” applications (use cases where you need processing power on smaller devices) — has raised a €15m Series A round to scale up its production and broaden its customer base.
The investment came from Invest-NL Deep Tech Fund, the EIC Fund, MIG Capital, Matterwave Ventures and Delft Enterprises.

Living on the edge

Innatera’s processors are specifically designed for edge applications that rely on sensors. This covers any device that interprets sensory data, including security cameras, wearables and “hearables” (devices like smart speakers or voice-activated TV remotes that you can speak to).
The data these devices take in has traditionally been processed in the cloud. But now small, specialised chips that can do that processing directly on the device are becoming more necessary.
“With the sensors becoming more complex it's a large volume of data which needs to be sent into the cloud, and this simply takes too long and costs too much. That's the reason why more of the processing is coming close to the sensor,” says Sumeet Kumar, cofounder and CEO at Innatera.
He mentions security cameras that can tell if a person is in-shot, or a smartwatch that can detect heart conditions from heartbeat data, as two kinds of sensor-based applications that could run on his company’s chips.

Getting to market

Innatera says its chips consume about 500 times less energy and process data around 100 times faster than traditional microprocessors. This is largely due to something called “neuromorphic” chip design, meaning technology that mimics how the brain works.

5x a week

~/ Sifted Daily​

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By Sifted journalists
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In Innatera’s case, this means the chips use something called a “spiking neural network”, which — compared to other types of neural networks (such as those that power models like ChatGPT) — are more energy efficient in how they encode data. This is what will allow AI applications to run on devices themselves, powered by Innatera’s very small chips, rather than large chips in data centres.
Kumar adds that a lot of effort has gone into building an easy-to-use software stack to make it easy for customers to start using the technology.
“If you look at any hardware play in the semiconductor ecosystem, where they traditionally fail is in terms of software support,” he says.
While he can’t name names, Kumar says Innatera is already working with two customers who are developing devices he hopes will be in shops by next year. Long term, Innatera’s goal is to sell its chips to sensor makers as well as device makers, and to “reach 1bn devices by 2030”.
That’s not to say this will be straightforward. European semiconductor companies like Graphcore have struggled to find enough commercial traction to fund the high costs of developing their hardware.
Kumar says that one of the reasons his company is unlikely to need hundreds of millions of euros in funding is that it’s tried to build with a customer-first approach from day one, allowing it to bring revenue in early. He also says the cost of building a company in the Netherlands is far cheaper than in Silicon Valley.

So, while Innatera’s tiny chips might not be designed to take on Nvidia’s hold over AI training, its backers are hoping its specialised processors could be addressing an easier space to win in.
 
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charles2

Regular
View attachment 63189

View attachment 63190


News
March 19, 2024

The AI chip hype rolls on: Innatera raises €15m​

In the wake of Nvidia's stock shooting up by nearly 2,000% in five years, investors are looking for the next hardware champion​

Tim Smith
3 min read

If there’s one business in the world winning out of the AI hype cycle right now it’s US chip maker Nvidia. The company — which has a near-monopoly on the specialist processors used for training and running large AI models — has seen its stock price soar by nearly 2,000% since 2019. Now earlier-stage investors are trying to spot the next semiconductor success story.
Today, Netherlands-based Innatera — a company that develops processors designed for use in “edge” applications (use cases where you need processing power on smaller devices) — has raised a €15m Series A round to scale up its production and broaden its customer base.
The investment came from Invest-NL Deep Tech Fund, the EIC Fund, MIG Capital, Matterwave Ventures and Delft Enterprises.

Living on the edge

Innatera’s processors are specifically designed for edge applications that rely on sensors. This covers any device that interprets sensory data, including security cameras, wearables and “hearables” (devices like smart speakers or voice-activated TV remotes that you can speak to).
The data these devices take in has traditionally been processed in the cloud. But now small, specialised chips that can do that processing directly on the device are becoming more necessary.
“With the sensors becoming more complex it's a large volume of data which needs to be sent into the cloud, and this simply takes too long and costs too much. That's the reason why more of the processing is coming close to the sensor,” says Sumeet Kumar, cofounder and CEO at Innatera.
He mentions security cameras that can tell if a person is in-shot, or a smartwatch that can detect heart conditions from heartbeat data, as two kinds of sensor-based applications that could run on his company’s chips.

Getting to market

Innatera says its chips consume about 500 times less energy and process data around 100 times faster than traditional microprocessors. This is largely due to something called “neuromorphic” chip design, meaning technology that mimics how the brain works.

5x a week

~/ Sifted Daily​

Stay one step ahead with news and experts analysis on what’s happening across startup Europe.
By Sifted journalists
Sign up
In Innatera’s case, this means the chips use something called a “spiking neural network”, which — compared to other types of neural networks (such as those that power models like ChatGPT) — are more energy efficient in how they encode data. This is what will allow AI applications to run on devices themselves, powered by Innatera’s very small chips, rather than large chips in data centres.
Kumar adds that a lot of effort has gone into building an easy-to-use software stack to make it easy for customers to start using the technology.
“If you look at any hardware play in the semiconductor ecosystem, where they traditionally fail is in terms of software support,” he says.
While he can’t name names, Kumar says Innatera is already working with two customers who are developing devices he hopes will be in shops by next year. Long term, Innatera’s goal is to sell its chips to sensor makers as well as device makers, and to “reach 1bn devices by 2030”.
That’s not to say this will be straightforward. European semiconductor companies like Graphcore have struggled to find enough commercial traction to fund the high costs of developing their hardware.
Kumar says that one of the reasons his company is unlikely to need hundreds of millions of euros in funding is that it’s tried to build with a customer-first approach from day one, allowing it to bring revenue in early. He also says the cost of building a company in the Netherlands is far cheaper than in Silicon Valley.

So, while Innatera’s tiny chips might not be designed to take on Nvidia’s hold over AI training, its backers are hoping its specialised processors could be addressing an easier space to win in.
Very interesting and informative. Innatera taking a seemingly more direct approach to get their products to market

In the future when very big money starts to flow from products in the market the patent disputes and pressures to license technology are sure to follow. Unfortunately I may be far too old to see how that plays out.

Damn.
 
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Beebo

Regular
Very interesting and informative. Innatera taking a seemingly more direct approach to get their products to market

In the future when very big money starts to flow from products in the market the patent disputes and pressures to license technology are sure to follow. Unfortunately I may be far too old to see how that plays out.

Damn.
Stand by. The chasm is almost crossed and the hockey stick is upon us.
 
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The way I see it, Sumeet's comment 👇 and invitation to have a conversation is the kind of hunger and drive missing from our co. Even when Rob was at the sales helm too. With technology like this you can't sit and wait for contracts to fall into your lap. You need to nip at every opportunity.


Is it?

Hi manny100,

I presume you meant to say commercial neuromorphic Edge AI solutions rather than commercial Edge AI solutions in general? But even then, your statement is incorrect. SynSense also offers commercial neuromorphic solutions by now, and so does Innatera:

See this article dated February 6, 2024:


“Innatera, a spinout from the University of Delft, has grown to 65 people with recent funding from the European Innovation Council (15.5 million Euro) alongside Matterwave Ventures and MIG Capital. Commercial samples of the T1 and hardware evaluation kits are available now while the T1 will ramp to production quantities in the second half of this year.

After Mercedes Chief Software Officer Magnus Östberg had posted “Neuromorphic computing? We’ve got that. 😎” on LinkedIn earlier this year, I noticed Innatera’s CEO Sumeet Kumar commenting on his post, and subsequently two neuromorphic researchers at Mercedes liking Sumeet Kumar’s post, so those in the industry involved in neuromorphic tech are evidently aware of the choices they have besides implementing Akida. Of course all those neuromorphic solutions available differ from each other in various aspects - Innatera’s T1 spiking neural processor, for example, is not digital and does not have on-chip learning:


View attachment 63165






View attachment 63163

View attachment 63164


The BrainChip website and LinkedIn profile reflect this development by no longer talking about offering the only commercially available neuromorphic processor, but by using the term ‘first-to-market’ nowadays:

BrainChip’s first-to-market, digital neuromorphic processor IP, akidaTM, mimics the human brain to analyze only essential sensor inputs at the point of acquisition—processing data with unparalleled performance, precision, and reduced power consumption.”


Whether or not Akida is the overall best neuromorphic solution available is an entirely different matter. But to say it is “an indisputable fact” that BrainChip offers “the only ‘cloudless’ commercial solution ATM” is simply wrong.

I do agree with you, though, regarding what you said about the BRN share price:


Regards
Frangipani
 
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And yet here we are, with each capital raise the company valuation tanks further. :eek:


View attachment 63189

View attachment 63190


News
March 19, 2024

The AI chip hype rolls on: Innatera raises €15m​

In the wake of Nvidia's stock shooting up by nearly 2,000% in five years, investors are looking for the next hardware champion​

Tim Smith
3 min read

If there’s one business in the world winning out of the AI hype cycle right now it’s US chip maker Nvidia. The company — which has a near-monopoly on the specialist processors used for training and running large AI models — has seen its stock price soar by nearly 2,000% since 2019. Now earlier-stage investors are trying to spot the next semiconductor success story.
Today, Netherlands-based Innatera — a company that develops processors designed for use in “edge” applications (use cases where you need processing power on smaller devices) — has raised a €15m Series A round to scale up its production and broaden its customer base.
The investment came from Invest-NL Deep Tech Fund, the EIC Fund, MIG Capital, Matterwave Ventures and Delft Enterprises.

Living on the edge

Innatera’s processors are specifically designed for edge applications that rely on sensors. This covers any device that interprets sensory data, including security cameras, wearables and “hearables” (devices like smart speakers or voice-activated TV remotes that you can speak to).
The data these devices take in has traditionally been processed in the cloud. But now small, specialised chips that can do that processing directly on the device are becoming more necessary.
“With the sensors becoming more complex it's a large volume of data which needs to be sent into the cloud, and this simply takes too long and costs too much. That's the reason why more of the processing is coming close to the sensor,” says Sumeet Kumar, cofounder and CEO at Innatera.
He mentions security cameras that can tell if a person is in-shot, or a smartwatch that can detect heart conditions from heartbeat data, as two kinds of sensor-based applications that could run on his company’s chips.

Getting to market

Innatera says its chips consume about 500 times less energy and process data around 100 times faster than traditional microprocessors. This is largely due to something called “neuromorphic” chip design, meaning technology that mimics how the brain works.

5x a week

~/ Sifted Daily​

Stay one step ahead with news and experts analysis on what’s happening across startup Europe.
By Sifted journalists
Sign up
In Innatera’s case, this means the chips use something called a “spiking neural network”, which — compared to other types of neural networks (such as those that power models like ChatGPT) — are more energy efficient in how they encode data. This is what will allow AI applications to run on devices themselves, powered by Innatera’s very small chips, rather than large chips in data centres.
Kumar adds that a lot of effort has gone into building an easy-to-use software stack to make it easy for customers to start using the technology.
“If you look at any hardware play in the semiconductor ecosystem, where they traditionally fail is in terms of software support,” he says.
While he can’t name names, Kumar says Innatera is already working with two customers who are developing devices he hopes will be in shops by next year. Long term, Innatera’s goal is to sell its chips to sensor makers as well as device makers, and to “reach 1bn devices by 2030”.
That’s not to say this will be straightforward. European semiconductor companies like Graphcore have struggled to find enough commercial traction to fund the high costs of developing their hardware.
Kumar says that one of the reasons his company is unlikely to need hundreds of millions of euros in funding is that it’s tried to build with a customer-first approach from day one, allowing it to bring revenue in early. He also says the cost of building a company in the Netherlands is far cheaper than in Silicon Valley.

So, while Innatera’s tiny chips might not be designed to take on Nvidia’s hold over AI training, its backers are hoping its specialised processors could be addressing an easier space to win in.
 
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Diogenese

Top 20
View attachment 63189

View attachment 63190


News
March 19, 2024

The AI chip hype rolls on: Innatera raises €15m​

In the wake of Nvidia's stock shooting up by nearly 2,000% in five years, investors are looking for the next hardware champion​

Tim Smith
3 min read

If there’s one business in the world winning out of the AI hype cycle right now it’s US chip maker Nvidia. The company — which has a near-monopoly on the specialist processors used for training and running large AI models — has seen its stock price soar by nearly 2,000% since 2019. Now earlier-stage investors are trying to spot the next semiconductor success story.
Today, Netherlands-based Innatera — a company that develops processors designed for use in “edge” applications (use cases where you need processing power on smaller devices) — has raised a €15m Series A round to scale up its production and broaden its customer base.
The investment came from Invest-NL Deep Tech Fund, the EIC Fund, MIG Capital, Matterwave Ventures and Delft Enterprises.

Living on the edge

Innatera’s processors are specifically designed for edge applications that rely on sensors. This covers any device that interprets sensory data, including security cameras, wearables and “hearables” (devices like smart speakers or voice-activated TV remotes that you can speak to).
The data these devices take in has traditionally been processed in the cloud. But now small, specialised chips that can do that processing directly on the device are becoming more necessary.
“With the sensors becoming more complex it's a large volume of data which needs to be sent into the cloud, and this simply takes too long and costs too much. That's the reason why more of the processing is coming close to the sensor,” says Sumeet Kumar, cofounder and CEO at Innatera.
He mentions security cameras that can tell if a person is in-shot, or a smartwatch that can detect heart conditions from heartbeat data, as two kinds of sensor-based applications that could run on his company’s chips.

Getting to market

Innatera says its chips consume about 500 times less energy and process data around 100 times faster than traditional microprocessors. This is largely due to something called “neuromorphic” chip design, meaning technology that mimics how the brain works.

5x a week

~/ Sifted Daily​

Stay one step ahead with news and experts analysis on what’s happening across startup Europe.
By Sifted journalists
Sign up
In Innatera’s case, this means the chips use something called a “spiking neural network”, which — compared to other types of neural networks (such as those that power models like ChatGPT) — are more energy efficient in how they encode data. This is what will allow AI applications to run on devices themselves, powered by Innatera’s very small chips, rather than large chips in data centres.
Kumar adds that a lot of effort has gone into building an easy-to-use software stack to make it easy for customers to start using the technology.
“If you look at any hardware play in the semiconductor ecosystem, where they traditionally fail is in terms of software support,” he says.
While he can’t name names, Kumar says Innatera is already working with two customers who are developing devices he hopes will be in shops by next year. Long term, Innatera’s goal is to sell its chips to sensor makers as well as device makers, and to “reach 1bn devices by 2030”.
That’s not to say this will be straightforward. European semiconductor companies like Graphcore have struggled to find enough commercial traction to fund the high costs of developing their hardware.
Kumar says that one of the reasons his company is unlikely to need hundreds of millions of euros in funding is that it’s tried to build with a customer-first approach from day one, allowing it to bring revenue in early. He also says the cost of building a company in the Netherlands is far cheaper than in Silicon Valley.

So, while Innatera’s tiny chips might not be designed to take on Nvidia’s hold over AI training, its backers are hoping its specialised processors could be addressing an easier space to win in.
Innatera are analog. That makes them fast and low power, but accuracy may be a problem if they go beyond the low hanging fruit.

I don't think they do on-chip learning. They have an SDK for training.
 
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IloveLamp

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