Smoothsailing
Regular
Omsemi and brainchip still working in the background tho,View attachment 63149
PS: Unfortunately I can't ask for a refund because the "not going to hell" was an optional extra that I wasn't prepared to pay for.
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
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".
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".
Last edited:
Better late than never
Toyota, Nissan and Honda to team on AI and chips for next-gen cars
Japanese automakers to collaborate in 7 areas under government strategyasia.nikkei.com
RobjHunt
Regular
Great minds think alikeJust voted!
All 8: For
Last one: 110% Against.
Just my 2 cent.
Have a great weekend everyone
Learning
Pantene Peeps
Smoothsailing
Regular
"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
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
Nvidia took several attempts to bring a successful chip to market. It’s first 2 chips were flops. Success is not a straight line!
The 84-Year-Old Man Who Saved Nvidia
The 84-Year-Old Man Who Saved Nvidia
MadMayHam | 合氣道
Regular
Manny how would you come across this information?
Frangipani
Regular
Sean said on the last podcast that they had put strategies into place including speaking to funds.
Quite right - it's more of a hockey stick ...
DingoBorat
Slim
China moving further in front with humanoid robotics, by the looks of things..
Frangipani
Regular
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:Magnus Östberg on LinkedIn: #neuromorphic #ml #ai #intel #leadincarsoftware | 38 comments
Neuromorphic computing? We’ve got that. 😎 Because it’s still nascent technology, I am frequently asked to describe #neuromorphic computing. It is a paradigm… | 38 comments on LinkedIn
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
CHIPS
Regular
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.
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 Smith3 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
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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.
Last edited:
Very interesting and informative. Innatera taking a seemingly more direct approach to get their products to marketView attachment 63189
View attachment 63190
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.sifted.eu
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.
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.
MadMayHam | 合氣道
Regular
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.
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.
View attachment 63165
Magnus Östberg on LinkedIn: #neuromorphic #ml #ai #intel #leadincarsoftware | 38 comments
Neuromorphic computing? We’ve got that. 😎 Because it’s still nascent technology, I am frequently asked to describe #neuromorphic computing. It is a paradigm… | 38 comments on LinkedInwww.linkedin.com
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
MadMayHam | 合氣道
Regular
And yet here we are, with each capital raise the company valuation tanks further.
View attachment 63189
View attachment 63190
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.
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.View attachment 63189
View attachment 63190
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.
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.
I don't think they do on-chip learning. They have an SDK for training.
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