MadMayHam | 合氣道
Regular
Finally... proof that ChatGPT has surpassed human (well, at least some) intelligence.
BRN Discussion Ongoing
- Thread starter TechGirl
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Fact Finder
Top 20
Anyone remember the competition Mercedes ran and Neuromorphic won and still we have not heard a word.
Markus Schäfer• Follower:inMitglied des Vorstands der Mercedes-Benz Group AG, Chief Technology Officer, Entwicklung & Einkauf
1 Std. • vor 1 Stunde
At Mercedes-Benz, technology is a key driver of desire. We are focused on making life easier by turning automated driving into reality, substantially improving in-car entertainment and giving our customers back precious time.
Here at #CES, we are introducing Automatic Lane Change to our Level 2 advanced driver-assistance systems in North America. DRIVE PILOT, our Level 3 system for conditionally automated driving, is already available in Germany and now we have applied for certification in the states of California and Nevada.
The Nevada Department of Motor Vehicles (DMV) has approved our application and they are now preparing the certificate of compliance that will be issued within the next two weeks. With that, Mercedes-Benz will be the first OEM to have a Level 3 system to offer in the US – and we are optimistic that California will follow soon.*
Our new Burmester audio system boasts 1,750 watts powering up to 31 speakers and eight exciters that transfer vibrations, creating an unmatched acoustic environment where you hear and feel every sound.
We’re also creating perfect harmony between the sound experience and premium content in collaboration with Apple Music, Universal Music Group and Dolby Laboratories. “Approved in a Mercedes-Benz” recordings make our vehicles the best place to listen to premium high-fidelity music. We recently added ZYNC to ensure the best quality streaming content is available directly in your Mercedes-Benz vehicle!
Finally, we announced yesterday our development of the Mercedes-Benz High Power Charging Network, to accelerate the adoption of electric mobility and drive the world toward a more sustainable future.
Follow us Mercedes-Benz AG and join us at CES (www.ces.tech) to see how we are transforming technology and desire.
The reason Neuromorphic won was clearly because of TSEx.
I suggested at the time that this distorted what the Mercedes Benz focus groups had predicted and as a result Mercedes may solve the problem by delaying the Neuromorphic presentation till when they originally anticipated delivering it.
This seems to be playing out so if I was right and they expected it to come in third then I am thinking February, 2023 for it to be released.
My opinion only DYOR
FF
AKIDA BALLISTA
MadMayHam | 合氣道
Regular
FF I have access but no mention of Brainchip of Akida, it's more of an algorthmic model called Random Neural Network. I don't want to run afoul of copyright laws so am not going to link the document here.
"
Our approach is based on Locality Sensitive Hashing (LSH) [58], an algorithmic technique which uses hash functions to map input data points to buckets. These functions are designed to map similar inputs to the same bucket. LSH is typically used for data clustering [59] and nearest neighbor search [60] but can also be used for anomaly detection [61]. Since anomalous data points differ substantially from normal inputs, they will be mapped to different buckets. An anomaly score is then obtained by counting how many normal training samples are allocated to the same bucket as the test sample. Different families of hash functions such as p-stable hashing [62] and randomized trees [63] have been proposed before while other, more advanced methods use properties of the training data to select suitable hash functions [64].
A major benefit of LSH-based approaches for anomaly detection is that they have a limited computational and memory footprint."
"
Our approach is based on Locality Sensitive Hashing (LSH) [58], an algorithmic technique which uses hash functions to map input data points to buckets. These functions are designed to map similar inputs to the same bucket. LSH is typically used for data clustering [59] and nearest neighbor search [60] but can also be used for anomaly detection [61]. Since anomalous data points differ substantially from normal inputs, they will be mapped to different buckets. An anomaly score is then obtained by counting how many normal training samples are allocated to the same bucket as the test sample. Different families of hash functions such as p-stable hashing [62] and randomized trees [63] have been proposed before while other, more advanced methods use properties of the training data to select suitable hash functions [64].
A major benefit of LSH-based approaches for anomaly detection is that they have a limited computational and memory footprint."
Fact Finder
Top 20
Thank you that’s great. Can you complete the sentence regarding NASA just so I/we know what this part relates too.
Regards
FF
AKIDA BALLISTA
Jumpchooks
Regular
And,, with UV Lights installed , you get a Tan down under as well !!New product at CES by Koehler. They should install a VOC sensor linked to Akida to detect disease & improve diet. Then Alexa would say something like "that's foul, go see the doctor" or "you have to eat more greens & drink less booze". Possibly standard feature in all dunnies in 10 years.
View attachment 26336
A toilet with Alexa inside
One minute we’re being told not to take Alexa into the bedroom, now we’re being encouraged to take Alexa into the toilet.
American manufacturer Kohler will show off a $16,900 toilet which has Alexa inside. So you can get the weather report while sitting on the throne.
The Numi 2.0 also comes with LED lights that illuminate the bowl, jets that can power wash all of your bits and bobs and a mist to help disguise smells.
And that perennial problem of people leaving the toilet seat up is a problem no more. The Numi can automatically lower the seat after every use so the interior of the bowl is banished from public view.
The Numi has been around as a concept for a while but the manufacturer says it is now ready to be installed.
Volatile organic compounds (VOCs) emitted from stool are the components of the smell of stool representing the end products of microbial activity and metabolism that can be used to diagnose disease. Despite the abundance of hydrogen, carbon dioxide, and methane that have already been identified in human flatus, the small portion of trace gases making up the VOCs emitted from stool include organic acids, alcohols, esters, heterocyclic compounds, aldehydes, ketones, and alkanes, among others. These are the gases that vary among individuals in sickness and in health, in dietary changes, and in gut microbial activity. Electronic nose devices are analytical and pattern recognition platforms that can utilize mass spectrometry or electrochemical sensors to detect these VOCs in gas samples. When paired with machine-learning and pattern recognition algorithms, this can identify patterns of VOCs, and thus patterns of smell, that can be used to identify disease states. In this review, we provide a clinical background of VOC identification, electronic nose development, and review gastroenterology applications toward diagnosing disease by the volatile headspace analysis of stool.
Diagnosing gastrointestinal illnesses using fecal headspace volatile organic compounds
Volatile organic compounds (VOCs) emitted from stool are the components of the smell of stool representing the end products of microbial activity and metabolism that can be used to diagnose disease. Despite the abundance of hydrogen, carbon dioxide, and ...www.ncbi.nlm.nih.gov
MadMayHam | 合氣道
Regular
Looks like the only use of NASA is their dataset for failed bearings to see if the AI model can predict the failures.
We experimented with the NASA Intelligent Maintenance Systems (IMS) bearing dataset [93]. It was collected on a test rig which consists of an electric motor that drives a shaft mounted with 4 double row Rexnord ZA-2115 bearings. For each bearing, accelerometer data was collected at a rate of 20 kHz. The entire lifetime of the bearing is recorded and the task is to detect when the bearing starts to degrade and ultimately fails. The dataset consists of three experiments with four failed bearings in total.
We applied our model in an online fashion to this dataset. Every sample is passed through the model which returns an anomaly score and updates its internal memory. We first transformed the data from the time domain to the frequency domain by applying a Fast Fourier Transform (FFT) to every window of 1 s (20.000 samples). The resulting 10.000 components are then passed through our random sparse anomaly detection model with two layers of 1000 neurons each and a sparsity rate of 90%. The model uses a learning rate of 0.05. To decide when to flag an input window as anomalous, we need to compare the returned anomaly score with a predefined threshold. For this, we calculated the mean (μ) and standard deviation (σ) of the predicted anomaly score of the first 10% of the dataset and set the threshold to (μ+5σ). The intuition behind this is that in the first part of the experiment, the bearing is still in a healthy state. We discard the first 100 predictions in this threshold calculation since the model returns a very high anomaly score for these samples as it is still learning to model the data. Table 8 shows the earliest detected anomalous samples for the four failed bearings, for different state-of-the-art methods. Our approach with sparse random neural networks performs similar or even sometimes slightly better than the existing approaches. A benefit of our approach however is that it does not require a separate training stage as it is trained in an online fashion.
6. Evaluation on time series data
In the previous sections, we focused on image data. Visual anomaly detection is an important task with many real-world applications in quality control and product safety. In addition, the visual nature of the data made it easier to intuitively understand the behavior of our model. There are however also many use cases where the input data is in the form of a time series. In this section, we show how our method can also be applied to this domain.We experimented with the NASA Intelligent Maintenance Systems (IMS) bearing dataset [93]. It was collected on a test rig which consists of an electric motor that drives a shaft mounted with 4 double row Rexnord ZA-2115 bearings. For each bearing, accelerometer data was collected at a rate of 20 kHz. The entire lifetime of the bearing is recorded and the task is to detect when the bearing starts to degrade and ultimately fails. The dataset consists of three experiments with four failed bearings in total.
We applied our model in an online fashion to this dataset. Every sample is passed through the model which returns an anomaly score and updates its internal memory. We first transformed the data from the time domain to the frequency domain by applying a Fast Fourier Transform (FFT) to every window of 1 s (20.000 samples). The resulting 10.000 components are then passed through our random sparse anomaly detection model with two layers of 1000 neurons each and a sparsity rate of 90%. The model uses a learning rate of 0.05. To decide when to flag an input window as anomalous, we need to compare the returned anomaly score with a predefined threshold. For this, we calculated the mean (μ) and standard deviation (σ) of the predicted anomaly score of the first 10% of the dataset and set the threshold to (μ+5σ). The intuition behind this is that in the first part of the experiment, the bearing is still in a healthy state. We discard the first 100 predictions in this threshold calculation since the model returns a very high anomaly score for these samples as it is still learning to model the data. Table 8 shows the earliest detected anomalous samples for the four failed bearings, for different state-of-the-art methods. Our approach with sparse random neural networks performs similar or even sometimes slightly better than the existing approaches. A benefit of our approach however is that it does not require a separate training stage as it is trained in an online fashion.
Was worth having a crack at it thoyeah... nah.... not really going to work. You can do weird things with infinity and zero, but not everything.
TGIF
Steve10
Regular
It can write code for trading bots in pine script which can be loaded into tradingview. I had it write code for a BRN trading bot . 75% profitable & 3.632 profit factor for BRN.
Fact Finder
Top 20
Just brilliant. Many thanks.
Brainchip-Peter van der Made published performance figures for AKIDA processing a bearing fault data set. Pretty sure it ended up on website under automotive vibration monitoring and my vague memory was a state of the art 99% but will need to check.
My opinion only DYOR
FF
AKIDA BALLISTA
Jumpchooks
Regular
From what I can tell this project closed to submissions a year ago this week. Do they ever announce who was successful?
sam.gov
Army SBIR 21.4 Topic Index
A214-051 Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles
A214-051
TITLE: Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles
OBJECTIVE:
Most military scenarios consist of highly cluttered and dynamic scenes. Asynchronous on chip smart event cameras can eliminate cluttered scenarios with a much-reduced latency, power, and would be able to hand off images of interest to imbedded autonomous target algorithms. Development of a smart digital readout circuit, with embedded processing, containing this capability would significantly enhance infrared cameras for use in autonomous detection. The objective of this topic is to take this new technology and apply it to the 3GEN FLIR program and all other systems that use or will use 3GEN FLIR Cameras.
DESCRIPTION:
Currently, 3GEN FLIR consists of imaging in two infrared bands with four fields of view. This capability for the Army increases the effectiveness of the sensors to operate in all atmospheric conditions with much longer range than previous versions. In addition, new ground systems will employ autonomous vehicles that will have to contain some use of artificial intelligence to navigate and target. This will regain overmatch by reducing target acquisition time and engagement timelines compared to today’s manual search and acquiring “next target” process. It will also reduce the cognitive burden for vehicle crew by automating search and acquisition – targets are verified by man-in-the-loop prior to engagement. The project, if successful, will make a game changing improvement by indicating temporal events at the focal plane level and reduce latency of target acquisition times. This project will design a neuromorphic chip to be combined with the digital 3GEN FLIR readout circuit at the 12 micron pixel level. This two chip stacked readout will perform the basic sensor functions as well as the neuromorphic processing. Power dissipation of the neuromorphic chip will be at a minimum since it is cryogenically cooled to 75K and added heat load needs to be minimized.
PHASE I:
Phase I will be a short study phase to come up with a neuromorphic design chip.
PHASE II:
Phase II will consist of the design and fabrication of the asynchronous neuromorphic digital readout. Testing will be done to prove out the concept performance. If Phase II Sequential required, it should demonstrate the chip in a 3GEN FLIR focal plane. Packaging and testing will validate the conceptual success of the project.
PHASE III:
Phase III will consist of the commercialization of the selected proposal.
KEYWORDS:
3GEN FLIR, Neuromorphic chip, latency
SAM.gov
Army SBIR 21.4 Topic Index
A214-051 Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles
A214-051
TITLE: Asynchronous Neuromorphic Digital Readout Circuit for Infrared Cameras for Autonomous Target Acquisition and Autonomous Vehicles
OBJECTIVE:
Most military scenarios consist of highly cluttered and dynamic scenes. Asynchronous on chip smart event cameras can eliminate cluttered scenarios with a much-reduced latency, power, and would be able to hand off images of interest to imbedded autonomous target algorithms. Development of a smart digital readout circuit, with embedded processing, containing this capability would significantly enhance infrared cameras for use in autonomous detection. The objective of this topic is to take this new technology and apply it to the 3GEN FLIR program and all other systems that use or will use 3GEN FLIR Cameras.
DESCRIPTION:
Currently, 3GEN FLIR consists of imaging in two infrared bands with four fields of view. This capability for the Army increases the effectiveness of the sensors to operate in all atmospheric conditions with much longer range than previous versions. In addition, new ground systems will employ autonomous vehicles that will have to contain some use of artificial intelligence to navigate and target. This will regain overmatch by reducing target acquisition time and engagement timelines compared to today’s manual search and acquiring “next target” process. It will also reduce the cognitive burden for vehicle crew by automating search and acquisition – targets are verified by man-in-the-loop prior to engagement. The project, if successful, will make a game changing improvement by indicating temporal events at the focal plane level and reduce latency of target acquisition times. This project will design a neuromorphic chip to be combined with the digital 3GEN FLIR readout circuit at the 12 micron pixel level. This two chip stacked readout will perform the basic sensor functions as well as the neuromorphic processing. Power dissipation of the neuromorphic chip will be at a minimum since it is cryogenically cooled to 75K and added heat load needs to be minimized.
PHASE I:
Phase I will be a short study phase to come up with a neuromorphic design chip.
PHASE II:
Phase II will consist of the design and fabrication of the asynchronous neuromorphic digital readout. Testing will be done to prove out the concept performance. If Phase II Sequential required, it should demonstrate the chip in a 3GEN FLIR focal plane. Packaging and testing will validate the conceptual success of the project.
PHASE III:
Phase III will consist of the commercialization of the selected proposal.
KEYWORDS:
3GEN FLIR, Neuromorphic chip, latency
Rise from the ashes
Regular
I was trying to teach it the meaning of WANCA I thought I was successful after a bit of to and fro as it kept responding with the correct definition. Once I closed the chat then reopened it and asked the same question it reverted back to me having to explain it allover again.
Xhosa12345
Regular
Sirod69
bavarian girl ;-)
Mercedes announces major autonomous driving update at CES
Mercedes has slowly become a leader in autonomous driving and vehicle software, along with the likes of Tesla. And while its far more conservative approach to software introduction has meant that fewer of its customers have benefited from its offering than its American counterpart, the company’s full legal acceptance of responsibility has inspired rare confidence in the system. Now, Mercedes has announced key updates coming to its autonomous driving suite in 2023.
Mercedes announces major autonomous driving update at CES
Mercedes announced a slate of new software updates coming to vehicles in 2023, notably including new autonomous driving features in the U.S.
www.teslarati.com
White Horse
Regular
Hi FF,When our children were young and understood a general concept of infinity as the number it was impossible to count too in a million lifetimes I would say ‘I love you to infinity plus one more just in case.’
Infinity is a pretty big number and unlike with my children if they achieved infinite or ubiquitous profit I would say enough. And one more just in case would be unnecessary.
My eight year old grandson floored me last year when we bidding up with higher numbers about something of which I don't recollect, when I said, infinity. He said, you can't say that Pa, infinity is not a number, its a concept. End of contest.
Good evening Chippers,
Great week all in all , finnished on par with last week. Incredible.
As Fact Finder was kind enough to lay out for all , in an earlier post, our company is engaged with 6 to 7 partners this week @ C.E.S , most of which behind closed doors, showcasing our tech & the benefits to clientele, some of which require confidentiality / NDA 's to be signed before a viewing.
TOP SHELF & extremely exciting.
Future , solid partners & connections, with serious engagement, one on one.
Sterling effort to all contributors this week .
Big end of town is deffinately trying to psychologically play with us on the share price side of things.
Personally, I am 97% certain Brainchip share price will be many fold from where it is pressently, in the not to distant.
On a lighter note....
Have a great weekend all.
This Lass goes off,
Korolova, Live so track Boa @ Sao Paulo, Brazil / Melodic Techno & Progressive House Mix.
1:25:24 duration.
* Once again if a savvy person could locate and post link would be greatfull, thankyou in advance.
Regards,
Esq.
Great week all in all , finnished on par with last week. Incredible.
As Fact Finder was kind enough to lay out for all , in an earlier post, our company is engaged with 6 to 7 partners this week @ C.E.S , most of which behind closed doors, showcasing our tech & the benefits to clientele, some of which require confidentiality / NDA 's to be signed before a viewing.
TOP SHELF & extremely exciting.
Future , solid partners & connections, with serious engagement, one on one.
Sterling effort to all contributors this week .
Big end of town is deffinately trying to psychologically play with us on the share price side of things.
Personally, I am 97% certain Brainchip share price will be many fold from where it is pressently, in the not to distant.
On a lighter note....
Have a great weekend all.
This Lass goes off,
Korolova, Live so track Boa @ Sao Paulo, Brazil / Melodic Techno & Progressive House Mix.
1:25:24 duration.
* Once again if a savvy person could locate and post link would be greatfull, thankyou in advance.
Regards,
Esq.
Tothemoon24
Top 20
Great positive post Esq,
I did a 10km beach walk today listening to your last banger great vibe .
I’ll await the kind work of a savvy soul for your next delight
Good evening,
2nd day of CES due to start in less than 5 hours, I have noticed a few posts where some have mentioned that companies that
are partnered with us haven't actually raved about the Akida input, and why would they?
NDAs haven't magically dissolved, and as in the case of Edge Impulse, giving us a great plug, well that's truly fantastic, but we
have absolutely no control over what they do and speak.
Is Brainchip going to start pumping up IFS, I don't think so, each company, though partnered up through their ecosystems, are
when all is said and done, looking after themselves, just as our Board is doing.
As has been stated numerous times, we may never even know that our IP is embedded in some company's future products, as far
as they are concerned, it's their product and their name being pumped, we quietly go about our business, assisting with engineering
services when approached or sitting back and enjoying the 90% + profit margin and royalty streams.
It's the doors that have been closed up until now, that I find really interesting, in 12/24 months how many new names will suddenly
appear that were borne out of CES 2023, having Brainchip's team making the most of a great business opportunity...now that's exciting
to ponder over.
5 days in, just pace yourselves, all of 2023 and all of 2024....then we probably have fair reason to question how we are travelling, I
realise that my timeline isn't yours and that's fair enough, you make that choice, which I respect.
Love Brainchip. Tech.
2nd day of CES due to start in less than 5 hours, I have noticed a few posts where some have mentioned that companies that
are partnered with us haven't actually raved about the Akida input, and why would they?
NDAs haven't magically dissolved, and as in the case of Edge Impulse, giving us a great plug, well that's truly fantastic, but we
have absolutely no control over what they do and speak.
Is Brainchip going to start pumping up IFS, I don't think so, each company, though partnered up through their ecosystems, are
when all is said and done, looking after themselves, just as our Board is doing.
As has been stated numerous times, we may never even know that our IP is embedded in some company's future products, as far
as they are concerned, it's their product and their name being pumped, we quietly go about our business, assisting with engineering
services when approached or sitting back and enjoying the 90% + profit margin and royalty streams.
It's the doors that have been closed up until now, that I find really interesting, in 12/24 months how many new names will suddenly
appear that were borne out of CES 2023, having Brainchip's team making the most of a great business opportunity...now that's exciting
to ponder over.
5 days in, just pace yourselves, all of 2023 and all of 2024....then we probably have fair reason to question how we are travelling, I
realise that my timeline isn't yours and that's fair enough, you make that choice, which I respect.
Love Brainchip. Tech.
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