Zedjack33
Regular
Why doesn’t someone tell them their horses have been stolen.
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
Boab
I wish I could paint like Vincent
Nut JobsFair enough @Fox151. I mean who are we to judge how you pass your time? Have you considered purchasing some titanium undies to protect the family jewels?
View attachment 17487
Bravo
If ARM was an arm, BRN would be its biceps💪!
The guy on the end is cheating. You're not fooling anyone buddy!Fair enough @Fox151. I mean who are we to judge how you pass your time? Have you considered purchasing some titanium undies to protect the family jewels?
View attachment 17487
Frank Zappa
Regular
We are all responsible for our own well being .Just my own opinion and definitely not advice but paying for a 12 month subscription may not be the best way to go .
.Fact Finder
Top 20
Maybe he is the only one who is doing it properly?
Slymeat
Move on, nothing to see.
I like @Lex555's abbreviated image better as I also hold CXO which is at the top of the decliners list.You pipped me at the post or is that to the post
It is lovely seeing Brainchip getting some free publicity. At last. All that hard work by the 1000 eyes has paid off in convincng the ASX to report the ASX200 gainers correctly. It only took about 6 months!
Slymeat
Move on, nothing to see.
And now that Disney have moved to DVDs, and online, there might be hope for Beta yet! Shouldn't be any competition.I am actually going to go to the newsagents and buy the Australian Financial Review as I read that 2—3 times a week years ago and enjoyed doing it . Why I stopped I do not remember. I see old farts reading them in coffee️ shops . Maybe there is a renaissance happening like vinyl and now cassettes.
Slymeat
Move on, nothing to see.
That's the way I originally read it. Maybe I just haven't been diagnosed yet!
thelittleshort
Top Bloke
Markus Schäfer on LinkedIn: MBUX HYPERSCREEN | 18 comments
Visually impressive, radically easy to operate and extremely eager to learn: that’s the #MBUX Hyperscreen – just one of the many technical highlights that make… | 18 comments on LinkedIn
Food4 thought
Regular
On motley fool
Brainchip Holdings Ltd(ASX: BRN)
The Brainchip share price is up 5.5% to 87.5 cents. Investors have been buying this loss-making semi-conductor company despite there being no news out of it. They may believe that recent weakness in the Brainchip share price has created a buying opportunity. That’s despite its market capitalisation still hovering around $1.5 billionWhat a bunch of wancas
Fullmoonfever
Top 20
That wording, phrasing etc sounds exactly like something (ball) sackman would post elsewhere....hmmmm.
S
Straw
Guest
Massive egos, zero integrity.... dodgy as hell.
rgupta
Regular
Just checking if the MBUX hyprrscreen have brn ip.View attachment 17494
Markus Schäfer on LinkedIn: MBUX HYPERSCREEN | 18 comments
Visually impressive, radically easy to operate and extremely eager to learn: that’s the #MBUX Hyperscreen – just one of the many technical highlights that make… | 18 comments on LinkedInwww.linkedin.com
I assume Merc is going with us for EQXx which means that screen will be more intelligent than this one. As Merc quoted it is 10 times better than any other alternative available.
Xhosa12345
Regular
Boab
I wish I could paint like Vincent
Another potentially huge possibility.
www.drive.com.au
US road safety body wants mandatory drink-driving interlocks fast-tracked
Nearly one-third of all US road deaths are caused by alcohol-related crashes, prompting road safety experts to call for mandatory drink-driving detection systems in new vehicles.
Boab
I wish I could paint like Vincent
And even if they thought they were drinking Shiraz Akida would say no no, it was actually a Cab Merlot from South AustraliaAnother potentially huge possibility.
US road safety body wants mandatory drink-driving interlocks fast-tracked
Nearly one-third of all US road deaths are caused by alcohol-related crashes, prompting road safety experts to call for mandatory drink-driving detection systems in new vehicles.
equanimous
Norse clairvoyant shapeshifter goddess
Came across this and thought it was relevant to share in this current financial situation
I heard they down graded the British pound to an Ounce
I heard they down graded the British pound to an Ounce
buena suerte :-)
BOB Bank of Brainchip
On that note it reminded me of this ..........
Cheers to a Green day... enjoying a Red
In this video, BrainChip demonstrates for the first time a live application of the Akida1000 accurately tasting different types of wine.
Cheers to a Green day... enjoying a Red
BrainChip Wine Tasting
In this video, BrainChip demonstrates for the first time a live application of the Akida1000 accurately tasting different types of wine.
Learning
Learning to the Top 🕵♂️
From the untrained eye, this looked like they are searching of Akida back in April 2020. I wonder if Brainchip has submitted their White Paper?
The potential $99 million five-year project seeks to achieve improvements in SWaP for artificial intelligence and machine learning embedded computing.
John Keller
ROME, N.Y. – U.S. Air Force researchers are asking for industry help in making big improvements in small, lightweight embedded computing for artificial intelligence (AI) and machine learning (AI/ML) capabilities in an embedded computing environment.
Officials of the Air Force Research Laboratory's Information Directorate in Rome, N.Y., issued a broad agency announcement on Thursday (FA875019S7007) for the Robust and Efficient Computing Architectures, Algorithms, and Applications For Embedded Deep Learning.
The potential $99 million five-year project seeks to achieve orders of magnitude improvement in size, weight and power (SWaP) for deploying artificial intelligence and machine learning capabilities in an embedded computing environment.
Researchers are asking industry for embedded computing technologies with improved autonomy, intelligence, and assurance for command, control, communications, computers, intelligence, surveillance and reconnaissance (C4ISR) applications in SWaP-constrained Air Force applications. Of particular interest are advanced efficient computing architectures, algorithms, and applications.
Related: AI, machine learning driving embedded bus-and-board development
The Air Force needs unconventional computing architectures for pattern recognition, event reasoning, decision making, adaptive learning, and autonomous tasking on energy-efficient Air Force manned and unmanned aircraft.
A major focus area is neuromorphic computing -- or brain-inspired computing that involves processors more advanced than more-traditional the Von Neumann architectures. This kind of design could lead to unconventional circuits based on emerging nanotechnology like memristors and nano-photonics, researchers say.
There is a need for in-hardware and efficient adaptive learning architectures and algorithms, as well as novel artificial intelligence and machine learning algorithms optimized for neuromorphic computing hardware architectures.
Air Force researchers want to demonstrate modular computing for future real-time embedded plug-and-play capabilities. Technologies could include artificial intelligence and machine learning models for big data analytics for sensor processing; data fusion algorithms for situational awareness and sense making; and autonomous decision making.
Related: Microelectronics packaging for SWaP-constrained military embedded computing introduced by Mercury
Modular designs should support interchangeable sensors, with automatic software reconfiguration based on available resources. Companies participating should choose computing and interfaces to accommodate expected growth in data bandwidth in future systems. SWaP optimization is a priority.
Other considerations are ways to validate and improve scalability and security for artificial intelligence and machine learning technologies; deep-learning models and algorithms; and power-aware and energy-optimized deep learning models and algorithms for embedded computing.
Companies interested should email white papers no later than 27 May 2022 to the Air Force's Albert Frantz at albert.frantz@us.af.mil. Other deadlines for white paper submissions are 30 April and 31 July 2019; 29 May 2020; and 28 May 2021.
Related: DARPA asks industry for SWaP-optimized machine learning real-time ASICs able to learn from data
Those submitting promising white papers will be asked to submit full proposals. Email technical questions or concerns to Albert Frantz at albert.frantz@us.af.mil, and contracting questions to Amber Buckley at amber.buckley@us.af.mil.
More information is online at https://beta.sam.gov/opp/710000c429424dbf87606d0bc569d29e/view.
www.militaryaerospace.com
Learning.
Air Force researchers ask industry for SWaP-constrained embedded computing for artificial intelligence (AI)
April 27, 2020The potential $99 million five-year project seeks to achieve improvements in SWaP for artificial intelligence and machine learning embedded computing.
John Keller
- https://www.militaryaerospace.com/print/content/14174721
- https://thestockexchange.com.au/javascript:void(0)
- https://thestockexchange.com.au/javascript:void(0)
- https://thestockexchange.com.au/javascript:void(0)
- https://thestockexchange.com.au/javascript:void(0)
ROME, N.Y. – U.S. Air Force researchers are asking for industry help in making big improvements in small, lightweight embedded computing for artificial intelligence (AI) and machine learning (AI/ML) capabilities in an embedded computing environment.
Officials of the Air Force Research Laboratory's Information Directorate in Rome, N.Y., issued a broad agency announcement on Thursday (FA875019S7007) for the Robust and Efficient Computing Architectures, Algorithms, and Applications For Embedded Deep Learning.
The potential $99 million five-year project seeks to achieve orders of magnitude improvement in size, weight and power (SWaP) for deploying artificial intelligence and machine learning capabilities in an embedded computing environment.
Researchers are asking industry for embedded computing technologies with improved autonomy, intelligence, and assurance for command, control, communications, computers, intelligence, surveillance and reconnaissance (C4ISR) applications in SWaP-constrained Air Force applications. Of particular interest are advanced efficient computing architectures, algorithms, and applications.
Related: AI, machine learning driving embedded bus-and-board development
The Air Force needs unconventional computing architectures for pattern recognition, event reasoning, decision making, adaptive learning, and autonomous tasking on energy-efficient Air Force manned and unmanned aircraft.
A major focus area is neuromorphic computing -- or brain-inspired computing that involves processors more advanced than more-traditional the Von Neumann architectures. This kind of design could lead to unconventional circuits based on emerging nanotechnology like memristors and nano-photonics, researchers say.
There is a need for in-hardware and efficient adaptive learning architectures and algorithms, as well as novel artificial intelligence and machine learning algorithms optimized for neuromorphic computing hardware architectures.
Air Force researchers want to demonstrate modular computing for future real-time embedded plug-and-play capabilities. Technologies could include artificial intelligence and machine learning models for big data analytics for sensor processing; data fusion algorithms for situational awareness and sense making; and autonomous decision making.
Related: Microelectronics packaging for SWaP-constrained military embedded computing introduced by Mercury
Modular designs should support interchangeable sensors, with automatic software reconfiguration based on available resources. Companies participating should choose computing and interfaces to accommodate expected growth in data bandwidth in future systems. SWaP optimization is a priority.
Other considerations are ways to validate and improve scalability and security for artificial intelligence and machine learning technologies; deep-learning models and algorithms; and power-aware and energy-optimized deep learning models and algorithms for embedded computing.
Companies interested should email white papers no later than 27 May 2022 to the Air Force's Albert Frantz at albert.frantz@us.af.mil. Other deadlines for white paper submissions are 30 April and 31 July 2019; 29 May 2020; and 28 May 2021.
Related: DARPA asks industry for SWaP-optimized machine learning real-time ASICs able to learn from data
Those submitting promising white papers will be asked to submit full proposals. Email technical questions or concerns to Albert Frantz at albert.frantz@us.af.mil, and contracting questions to Amber Buckley at amber.buckley@us.af.mil.
More information is online at https://beta.sam.gov/opp/710000c429424dbf87606d0bc569d29e/view.
Air Force researchers ask industry for SWaP-constrained embedded computing for artificial intelligence (AI)
The potential $99 million five-year project seeks to achieve improvements in SWaP for artificial intelligence and machine learning embedded computing.
Learning.
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