A BARGIN BASEMENT .........STEAL at this pricing!
Why? Thinking about ole' Andreas I posted about and the info I gained shows -
the MARKET SATURATION BRAINCHIP IS ACHIEVING GLOBALLY
with its INFORMATION and MARKETING Strategy!!
Yak52
BRN Discussion Ongoing
- Thread starter TechGirl
- Start date
A BARGIN BASEMENT .........STEAL at this pricing!
Why? Thinking about ole' Andreas I posted about and the info I gained shows -
the MARKET SATURATION BRAINCHIP IS ACHIEVING GLOBALLY
with its INFORMATION and MARKETING Strategy!!
Yak52
DingoBorat
Slim
It's too low?..
With the current volume, the "days to cover" for shorters, would be up from @Slymeat's 8.8 days, to around 30 days..
He said over 10 days and they would be feeling uncomfortable?...
BaconLover
Founding Member
Andreas is a shareholder.
Some of TSE members have chatted with him on various platforms including Twitter/LinkedIn etc.
I wouldn't read too much into his comments, it's not a testimony from an insider perspective.
Like most of us, he also comments on BRN and Akida which is great, to increase awareness amongst the masses on a variety of social media platforms.
DYOR.
Some of TSE members have chatted with him on various platforms including Twitter/LinkedIn etc.
I wouldn't read too much into his comments, it's not a testimony from an insider perspective.
Like most of us, he also comments on BRN and Akida which is great, to increase awareness amongst the masses on a variety of social media platforms.
DYOR.
Tony Coles
Regular
lol 
F
Filobeddo
Guest
Makeme 2020
Regular
How drone autonomy unlocks a new era of AI opportunities
Reese Mozer, American Robotics@reesemozerJuly 23, 2022 1:10 PM
Image Credit: Anton Petrus/Getty
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[Editor’s note: American Robotics is a commercial developer of automated drone systems.]
Drones have been talked about extensively for two decades now. In many respects, that attention has been warranted. Military drones have changed the way we fight wars. Consumer drones have changed the way we film the world. For the commercial market, however, drones have largely been a false start. In 2013, the Association for Unmanned Vehicle Systems International (AUVSI) predicted an $82 billion market by 2025. In 2016, PwC predicted $127 billion within the “near future.” But we aren’t anywhere close to those projections yet. Why is that?
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Presentation: Why operationalizing data mesh is critical for operating in the cloud
Let’s start with the primary purpose of drones in a commercial setting: data collection and analysis. The drone itself is a means to an end – a flying camera from which to get a unique aerial perspective of assets for inspection and analysis, be it a pipeline, gravel storage yard, or vineyard. As a result, drones in this context fall under the umbrella of “remote sensing.”
In the world of remote sensing, drones are not the only player. There are high-orbit satellites, low-orbit satellites, airplanes, helicopters and hot air balloons. What do drones have that the other remote sensing methods do not? The first thing is: image resolution.
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What does “high resolution” really mean?
One product’s high resolution is another product’s low resolution.Image resolution, or more aptly Ground Sample Distance (GSD) in this case, is a product of two primary factors: (1) how powerful your imaging sensor is, and (2) how close you are to the object you are imaging. Because drones are typically flying very low to the ground (50-400 feet AGL), the opportunity to collect higher image resolutions than aircraft or satellites operating at higher altitudes is significant. Eventually you run into issues with physics, optics and economics, and the only way to get a better picture is to get closer to the object. To quantify this:
- “High resolution” for a drone operating at 50ft AGL with a 60MP camera is around 1 mm/pixel.
- “High resolution” for a manned aircraft service, like the now-defunct Terravion, was 10 cm/pixel.
- “High resolution” for a low-orbit satellite service, like Planet Labs, is 50 cm/pixel.
The power of high resolution
Why does this matter? It turns out there is a very direct and powerful correlation between image resolution and potential value. As the computing phrase goes: “garbage in, garbage out.” The quality and breadth of machine vision-based analytics opportunities are exponentially higher at the resolutions a drone can provide vs. other methods.A satellite might be able to tell you how many well pads are in Texas, but a drone can tell you exactly where and how the equipment on those pads is leaking. A manned aircraft might be able to tell you what part of your cornfield is stressed, but a drone can tell you what pest or disease is causing it. In other words, if you want to resolve a crack, bug, weed, leak or similarly small anomaly, you need the proper image resolution to do so.
Bringing artificial intelligence into the equation
Once that proper image resolution is obtained, now we can begin training neural networks (NNs) and other machine learning (ML) algorithms to learn about these anomalies, detect them, alert for them and potentially even predict them.Now our software can learn how to differentiate between an oil spill and a shadow, precisely calculate the volume of a stockpile, or measure a slight skew in a rail track that could cause a derailment.
American Robotics estimates that over 10 million industrial asset sites worldwide have use for automated drone-in-a-box (DIB) systems, collecting and analyzing 20GB+ per day per drone. In the United States alone, there are over 900,000 oil and gas well pads, 500,000 miles of pipeline, 60,000 electrical substations, and 140,000 miles of rail track, all of which require constant monitoring to ensure safety and productivity.
As a result, the scale of this opportunity is actually hard to quantify. What does it mean to fully digitize the world’s physical assets every day, across all critical industries? What does it mean if we can start applying modern AI to petabytes of ultra-high-resolution data that has never existed before? What efficiencies are unlocked if you can detect every leak, crack and area of damage in near-real time? Whatever the answer, I’d wager the $82B and $127B numbers estimated by AUVSI and PwC are actually low.
So: if the opportunity is so large and clear, why haven’t these market predictions come true yet? Enter the second important capability unlocked by autonomy: imaging frequency.
What does “high frequency” really mean?
The useful imaging frequency rate is 10x or more than what people originally thought.The biggest performance difference between autonomous drone systems and piloted ones is the frequency of data capture, processing and analysis. For 90% of commercial drone use cases, a drone must fly repetitively and continuously over the same plot of land, day after day, year after year, to have value. This is the case for agricultural fields, oil pipelines, solar panel farms, nuclear power plants, perimeter security, mines, railyards and stockpile yards. When examining the full operation loop from setup to processed, analyzed data, it is clear that operating a drone manually is much more than a full-time job. And at an average of $150/hour per drone operator, it is clear a full-time operational burden across all assets is simply not feasible for most customers, use cases and markets.
This is the central reason why all the predictions about the commercial drone industry have, thus far, been delayed. Imaging an asset with a drone once or twice a year has little to no value in most use cases. For one reason or another, this frequency requirement was overlooked, and until recently [subscription required], autonomous operations that would enable high-frequency drone inspections were prohibited by most federal governments around the world.
With a fully-automated drone-in-a-box system, on-the-ground humans (both pilots and observers) have been removed from the equation, and the economics have completely changed as a result. DIB technology allows for constant operation, multiple times per day, at less than a tenth of the cost of a manually operated drone service.
With this increased frequency comes not only cost savings but, more importantly, the ability to track problems when and where they occur and properly train AI models to do so autonomously. Since you don’t know when and where a methane leak or rail tie crack will occur, the only option is to scan every asset as frequently as possible. And if you are gathering that much data, you better build some software to help filter out the key information to end users.
Tying this to real-world applications today
Autonomous drone technology represents a revolutionary ability to digitize and analyze the physical world, improving the efficiency and sustainability of our world’s critical infrastructure.And thankfully, we have finally moved out of the theoretical and into the operational. After 20 long years of riding drones up and down the Gartner Hype Cycle, the “plateau of productivity” is cresting.
In January 2021, American Robotics became the first company approved by the FAA to operate a drone system beyond visual line-of-sight (BVLOS) with no humans on the ground, a seminal milestone unlocking the first truly autonomous operations. In May 2022, this approval was expanded to include 10 total sites across eight U.S. states, signaling a clear path to national scale.
More importantly, AI software now has a practical mechanism to flourish and grow. Companies like Stockpile Reports are using automated drone technology for daily stockpile volumetrics and inventory monitoring. The Ardenna Rail-Inspector Software now has a path to scale across our nation’s rail infrastructure.
AI software companies like Dynam.AI have a new market for their technology and services. And customers like Chevron and ConocoPhillips are looking toward a near-future where methane emissions and oil leaks are significantly curtailed using daily inspections from autonomous drone systems.
My recommendation: Look not to the smartphone, but to the oil fields, rail yards, stockpile yards, and farms for the next data and AI revolution. It may not have the same pomp and circumstance as the “metaverse,” but the industrial metaverse might just be more impactful.
Reese Mozer is cofounder and CEO of American Robotics.
Newk R
Regular
My thought on $1.17 is it doesn't bare thinking about.
BaconLover
Founding Member
Hopefully he signs it before he forgets it.
Where's that deLorean when you need it.
F
Filobeddo
Guest
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Deleted member 118
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Slymeat
Move on, nothing to see.
And that’s where Akida will shine. Teslas send a lot of info to The Cloud, and not knowing what gets done with that info from there, is an extremely valid point of this litigation. Once in The Cloud, your data is open for abuse and Completely out of your control. Hence I don’t see this law suit as frivolous.Not sure what happened with this case, but it really highlights the significance of Privacy concerns, in terms of what information is being collected and stored in electric vehicles, which is something that @cosors has also mentioned. In this case the Plaintiff alleges that Tesla’s driver monitoring practices violates his Illinois citizens’ statutorily protected privacy rights. It would be interesting to find what happens with this as I imagine it could set a legal precedent for future facial recognition technology.
It says " The class action complaint seeks to collect statutory damages of $5,000 for every time Tesla willfully or recklessly violated Illinois’ Biometric Information Privacy Act. It also seeks to collect statutory damages of $1,000 for each negligent violation of the state’s BIPA. Tesla’s legal team, for its part, is yet to issue a response to the complaint."
If only @Fact Finder were still here. I would love to hear his thoughts on this and, well, pretty much everything else just generally speaking.
Tesla’s camera-based driver monitoring system triggers legal complaint in Illinois
Tesla has implemented a number of safety improvements for its Autopilot and Full Self-Driving suites over the years, and this includes updates to its driver monitoring systems (DMS). Last year, Tesla activated its camera-based driver monitoring system in Model 3 and Model Y vehicles, allowing...www.teslarati.com
Facial recognition performed on the sensor, and with no info sent off-board, nay even without any ability to send it off board as it will only be the meta data that the sensor sends to the in-car processor, will set Akida-based systems further above the rest.
Akida, and true edge computing, will not have privacy violation concerns. And that extends to all the external cameras, radar and LiDAR. Those sensors will detect stuff, without needing to store it, and will generate meta data for upstream, but still in-car, processing. This should be the root of a huge marketing play by BrainChip and it’s partners.
I actually hope this law suit finds merit and makes the world stand up and take notice.
Akida can help achieve a completely unconnected autonomous vehicle. That should help people feel their privacy is kept safe.
Actually, having autonomous vehicles that do not require external connections solves another valid consideration — that of your vehicle being hacked and control of it taken over externally. Any necessary updates can be performed whilst stationary and better still, via a physical connection. Maybe whilst charging or servicing for instance.
GPS updates, such as live traffic, would need to be considered. But definitely no updates of any car functions whilst mobile!
Bravo
If ARM was an arm, BRN would be its biceps💪!
Who'd have thought we'd receive such great news on the CHIPS Act from POTATO?! He-he-he!
Great work @Potato!
PS: I thought for sure that @Diogenese would have beaten me to that one! Especially since it was such low-hanging fruit (or vegie in this case).
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Slymeat
Move on, nothing to see.
"I'm Andreas"
Frank Zappa
Regular
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Deleted member 118
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Who'd have thought we'd receive such great news on the CHIPS Act from a POTATO?! Great work @Potato? He-he-he!
buena suerte :-)
BOB Bank of Brainchip
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