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2024.05.29 07:12 Cal_Aesthetics_Club Proof that the claims of the StopIndianImmigration sub not being about race are BS
submitted by Cal_Aesthetics_Club to SouthAsianMasculinity [link] [comments]
2024.05.29 07:11 AutoModerator Where for way to streaming IF movie 2024 at home?
IF Movie 2024 can be streamed online through various platforms, including popular ones like Netflix, Amazon Prime Video, Hulu, and Disney+. Check your local streaming services for availability. Enjoy the movie from the comfort of your home!
✴Watch Full Movie Online free✴
Still Now Here Option’s to Downloading or watching IF streaming the Full Movie online for free on 124movies, Reddit, Amazon Prime, Peacock, HBO Max or Netflix!. Do you like movies? If so, then you’ll love the New Movie: IF. This movie is one of the best in its genre. IF will be available to watch online on Netflix's very soon!
submitted by AutoModerator to LateNightwithDevlDiT [link] [comments]
✴Watch Full Movie Online free✴
Still Now Here Option’s to Downloading or watching IF streaming the Full Movie online for free on 124movies, Reddit, Amazon Prime, Peacock, HBO Max or Netflix!. Do you like movies? If so, then you’ll love the New Movie: IF. This movie is one of the best in its genre. IF will be available to watch online on Netflix's very soon!
2024.05.29 07:11 perfectfire Where did all the hobbyist NPU/TPU inference hardware accelerators go?
TL;DR: AI Inference hardware accelerators were all the rage a few years ago. They still are, but they seem to have abandoned the hobbyist, low-power, low-size, low-mid cost, seperate board user, such that abandoned projects such as the Google edge TPU from 2019 (5 yrs ago) are still your best bet $/perf wise. The $20 - $150 range is empty or has some products that aren't worth it at all. What happened? Are there any modern hobbyist $20 - $150 accelerators you can buy right now anywhere?
Sidenote: I know TOPS isn't the end-all be-all of perf comparison, but it's all I got.[1]
Skip for history of my interest: I've long been interested in machine learning, especially artificial neural networks since I took a class on ML in college in around 2004. I've done some hobbyist projects on the CPU and even released a C#/.Net wrapper for FANN (Fast Artificial Neural Network, a fast open-source neural network run on CPUs because everything was on CPUs then): https://github.com/joelself/FannCSharp. When deep learning took off I got excited. I got into competitive password cracking and although my ML based techniques were about a dozen orders of magnitudes slower at making guesses, they were almost immediately able to find a few passwords in old leaks that had been gone over and over for years by the best crackers with the most absurd hardware and extremely specially tuned password guess generators. That made me pretty proud that I was able to do something in a few months that years of dozens of groups with $100,000s of thousands of dollars of hardware and who know how many watt-hours couldn't do. I even thought about writing a a paper on it, but I was kinda in over my head and my life got a lot worse so I had to put all of my side projects on hold unfortunately. Recently though I did a vanity search for my FANN C# wrapper and found people talking about it and some references in some papers and student projects which made me feel proud.
Skip for history of my interest: Now I really want to get into the cross section of hardware-accelerated inference (no training this time, I'm not a trillion dollar company with billion dollars of supercomputers running on specialized training hardware that took 100's of millions of dollars to develop), microcontrollers for robots, drones, other smallish tasks that can't carry around their own 100 lb diesel generator and 2 1U rackmount servers full of inference hardware that I can't even get ahold of because you can only buy that stuff if you are an Intel or GE or some other company that might make products in the 10's of thousands at least. And this is where I hit a wall.
I just started looking around and one of the first things I found was Google's TPU by Coral.ai. 4 TOPs in a package, 2 chips on a small m2 card. Only about 40 bucks for developers to try out, $60 for an easier to use, but 1 chip only USB product. But this was about 5 years ago, and they just slowly disappeared and haven't made a peep in like 3 years. They timed the market perfectly. AI stuff was right on the verge of BLOWING THE F*CK UP. They could be THE edge/robotics/iot/anything-other-than-servecloud-phone-tablet-PC-laptop company. But they just seemed to give up. They're obviously not giving up on improving edge inference hardware. They release their phones twice a year (regular version, then A version) and they always update the tensor processing unit in those and are really starting to push that as a must have feature. They could use the same hardware improvements to make somewhat bigger chips to sell for other markets. You never know, someone might take their 3rd gen 16 TOPS TPU chip and makes a product(s) that takes the world by storm. Maybe multiple people/companies will do that.
Okay, so Google, seems to have dropped the hat. Hardware inference companies are a dime a dozen these days just go with another. But that's the problem. It seems all the focus is on Cloud scale, super-computer (some overlap between those 2), embedded on finished phones/tables/laptop/PCs, powerful server accelerators, and a very few extremely tiny MCUs with accordingly tiny MPUs. I seems everybody has abandoned the lower-mid range-robotics-drone-hobbyist space with haste.
ARM introduced the Ethos U-55 and U65 with the 65 having about double the TOPS of the 55 at a max of 1 TOPS in 2020. As far as I can tell the first products to use the U-55 were in 2022 and there haven't been a lot and I don't think they ran at top speed. Noone has opted to implement even an unmodified U-65 for anything. I recently bought a Grove AI Vision Kit with a U-55 NPU and it's specced at a lowly 50 GOPS (ARM's top-end says it could hit 10 times that and until *just now* I thought it was 500 GOPS and thus offered good $/TOPS ...oops).
There's a lot of companies making hype, a lot seeming to have selling dev or reference boards, but instead producing a few thousands and distributing them via the usual (Mouser, DigiKey, Element14, SparkFun, etc), they want you to fill out extensive forms to ensure you're a big player that will definitely eventually buy at least 100,000 units a day otherwise you're a waste of time for them to consider you (even though going over every applicant individually is WAY more time consuming than just producing a couple thou and have DigiKey take care of selling 1 to 2 at a time).
Thus I've come to the point that while Google edge TPU is abandoned (even though Google is going full steam ahead on AI inference for their cellphones and tablets) and Coral.ai is seemingly doing nothing. Their TPUs still provide the best $/TOPS in the range I want. Take a look at [VOXL2](https://www.modalai.com/collections/blue-uas-framework-components/products/voxl-2?variant=39914779836467). Basically exactly what I want and would expect we should have had something like a Google Edge TPU v3 by now (but a bit smaller and a little less power consumption, yes, I know moore's law doesn't really apply anymore, but in rapidly growing and learning fields like accelerated inference, double the speed every 2 years is not unreasonable and it has been 5 years since the Google TPU @ 4 TOPS per chip). But the damn thing is over $1,2000.
So, my point finally is that even though Google and Coral.ai seem to have abandoned their TPU. At about $40 for 2 chips at 4 TOPS apiece for 8 TOPS total, they still seem to be the best middle ground. The next best might be the BeagleBone reference studio for about 8 TOPS at $187. Same TOPS (though on one chip) for more than 4.5 times the cost. The Jetson Orin Nano by NVIDIA is $259 for 20 TOPS at $51/4TOPS that a single Google edge TPU will put out at $20 (including the board and stuff). It seems everyone is abandoning the hobbyist edge inference space at lightning speed. There are a lot of companies with promising size (physical) and performance products, but they won't talk to you until you fill out a form that implies that they only want to talk to someone that has already decided to buy 100,000s of your units whereas in the past, companies would have dev/reference boards out trying to find someone that would develop that killer app and make them a lot of money.
Why is this? Am I looking in the wrong place? Should I hoard Google edge TPUs? I bought their USB version to tinker with and the Grove AI Vision Kit (now that I realize is only 50 GOPS, so might be worthless). What are my options. For example. A single quadcopter a 100 - 300m above the ground looking "things", not image classic image classification where it can identify thousands of different objects. It just needs to identify one type of thing. Doesn't even have to be very fast. In fact, don't these NNs run on single images? I could just buy multiple chips and run in parallel to get the framerate I want if it isn't fast enough (it won't improve latency, but 100 - 500 ms latency probably isn't a problem until you get real close at which time you can switch to a different, much cheaper solution that works even better at close range and wide FOV).
Maybe I can use a phone and get low level access to the NPU/TPU and use that or use their powerful graphics cards on the phone or small laptop like a caveman from 2017. Still pretty expensive and I would be paying a ton of money for hardware I don't want. Maybe I could buy broken phones "for parts" on ebay, but I'm not that hardware savvy. I need a dev board to get me going.
The next best idea is to just push video from my drone/robot/project to a central station with a super powerful 1-4U server inference accelerator (not sure how I would get one), or Jetson Orin, computer with RTX4090 and do inference there and just tolerate the latency. That won't be feasible for some applications I would like to do though.
submitted by perfectfire to MLQuestions [link] [comments]
Sidenote: I know TOPS isn't the end-all be-all of perf comparison, but it's all I got.[1]
Skip for history of my interest: I've long been interested in machine learning, especially artificial neural networks since I took a class on ML in college in around 2004. I've done some hobbyist projects on the CPU and even released a C#/.Net wrapper for FANN (Fast Artificial Neural Network, a fast open-source neural network run on CPUs because everything was on CPUs then): https://github.com/joelself/FannCSharp. When deep learning took off I got excited. I got into competitive password cracking and although my ML based techniques were about a dozen orders of magnitudes slower at making guesses, they were almost immediately able to find a few passwords in old leaks that had been gone over and over for years by the best crackers with the most absurd hardware and extremely specially tuned password guess generators. That made me pretty proud that I was able to do something in a few months that years of dozens of groups with $100,000s of thousands of dollars of hardware and who know how many watt-hours couldn't do. I even thought about writing a a paper on it, but I was kinda in over my head and my life got a lot worse so I had to put all of my side projects on hold unfortunately. Recently though I did a vanity search for my FANN C# wrapper and found people talking about it and some references in some papers and student projects which made me feel proud.
Skip for history of my interest: Now I really want to get into the cross section of hardware-accelerated inference (no training this time, I'm not a trillion dollar company with billion dollars of supercomputers running on specialized training hardware that took 100's of millions of dollars to develop), microcontrollers for robots, drones, other smallish tasks that can't carry around their own 100 lb diesel generator and 2 1U rackmount servers full of inference hardware that I can't even get ahold of because you can only buy that stuff if you are an Intel or GE or some other company that might make products in the 10's of thousands at least. And this is where I hit a wall.
I just started looking around and one of the first things I found was Google's TPU by Coral.ai. 4 TOPs in a package, 2 chips on a small m2 card. Only about 40 bucks for developers to try out, $60 for an easier to use, but 1 chip only USB product. But this was about 5 years ago, and they just slowly disappeared and haven't made a peep in like 3 years. They timed the market perfectly. AI stuff was right on the verge of BLOWING THE F*CK UP. They could be THE edge/robotics/iot/anything-other-than-servecloud-phone-tablet-PC-laptop company. But they just seemed to give up. They're obviously not giving up on improving edge inference hardware. They release their phones twice a year (regular version, then A version) and they always update the tensor processing unit in those and are really starting to push that as a must have feature. They could use the same hardware improvements to make somewhat bigger chips to sell for other markets. You never know, someone might take their 3rd gen 16 TOPS TPU chip and makes a product(s) that takes the world by storm. Maybe multiple people/companies will do that.
Okay, so Google, seems to have dropped the hat. Hardware inference companies are a dime a dozen these days just go with another. But that's the problem. It seems all the focus is on Cloud scale, super-computer (some overlap between those 2), embedded on finished phones/tables/laptop/PCs, powerful server accelerators, and a very few extremely tiny MCUs with accordingly tiny MPUs. I seems everybody has abandoned the lower-mid range-robotics-drone-hobbyist space with haste.
ARM introduced the Ethos U-55 and U65 with the 65 having about double the TOPS of the 55 at a max of 1 TOPS in 2020. As far as I can tell the first products to use the U-55 were in 2022 and there haven't been a lot and I don't think they ran at top speed. Noone has opted to implement even an unmodified U-65 for anything. I recently bought a Grove AI Vision Kit with a U-55 NPU and it's specced at a lowly 50 GOPS (ARM's top-end says it could hit 10 times that and until *just now* I thought it was 500 GOPS and thus offered good $/TOPS ...oops).
There's a lot of companies making hype, a lot seeming to have selling dev or reference boards, but instead producing a few thousands and distributing them via the usual (Mouser, DigiKey, Element14, SparkFun, etc), they want you to fill out extensive forms to ensure you're a big player that will definitely eventually buy at least 100,000 units a day otherwise you're a waste of time for them to consider you (even though going over every applicant individually is WAY more time consuming than just producing a couple thou and have DigiKey take care of selling 1 to 2 at a time).
Thus I've come to the point that while Google edge TPU is abandoned (even though Google is going full steam ahead on AI inference for their cellphones and tablets) and Coral.ai is seemingly doing nothing. Their TPUs still provide the best $/TOPS in the range I want. Take a look at [VOXL2](https://www.modalai.com/collections/blue-uas-framework-components/products/voxl-2?variant=39914779836467). Basically exactly what I want and would expect we should have had something like a Google Edge TPU v3 by now (but a bit smaller and a little less power consumption, yes, I know moore's law doesn't really apply anymore, but in rapidly growing and learning fields like accelerated inference, double the speed every 2 years is not unreasonable and it has been 5 years since the Google TPU @ 4 TOPS per chip). But the damn thing is over $1,2000.
So, my point finally is that even though Google and Coral.ai seem to have abandoned their TPU. At about $40 for 2 chips at 4 TOPS apiece for 8 TOPS total, they still seem to be the best middle ground. The next best might be the BeagleBone reference studio for about 8 TOPS at $187. Same TOPS (though on one chip) for more than 4.5 times the cost. The Jetson Orin Nano by NVIDIA is $259 for 20 TOPS at $51/4TOPS that a single Google edge TPU will put out at $20 (including the board and stuff). It seems everyone is abandoning the hobbyist edge inference space at lightning speed. There are a lot of companies with promising size (physical) and performance products, but they won't talk to you until you fill out a form that implies that they only want to talk to someone that has already decided to buy 100,000s of your units whereas in the past, companies would have dev/reference boards out trying to find someone that would develop that killer app and make them a lot of money.
Why is this? Am I looking in the wrong place? Should I hoard Google edge TPUs? I bought their USB version to tinker with and the Grove AI Vision Kit (now that I realize is only 50 GOPS, so might be worthless). What are my options. For example. A single quadcopter a 100 - 300m above the ground looking "things", not image classic image classification where it can identify thousands of different objects. It just needs to identify one type of thing. Doesn't even have to be very fast. In fact, don't these NNs run on single images? I could just buy multiple chips and run in parallel to get the framerate I want if it isn't fast enough (it won't improve latency, but 100 - 500 ms latency probably isn't a problem until you get real close at which time you can switch to a different, much cheaper solution that works even better at close range and wide FOV).
Maybe I can use a phone and get low level access to the NPU/TPU and use that or use their powerful graphics cards on the phone or small laptop like a caveman from 2017. Still pretty expensive and I would be paying a ton of money for hardware I don't want. Maybe I could buy broken phones "for parts" on ebay, but I'm not that hardware savvy. I need a dev board to get me going.
The next best idea is to just push video from my drone/robot/project to a central station with a super powerful 1-4U server inference accelerator (not sure how I would get one), or Jetson Orin, computer with RTX4090 and do inference there and just tolerate the latency. That won't be feasible for some applications I would like to do though.
- I found a github repo that collects perf comparison projects and I checked their data, and it's extremely sparse. One set is dominated by NVIDIA 4090, L(s), L4(s), and QUALCOMM T100 (or something, it's a cloud only processor, so you can't buy it). Then a few rows at the bottom have Raspi 4 and like 5 other mini applications units and MCU chips. And the results were hard to interpret especially since not all entrants have run all benchmarks and they can run it in probably dozens of different ways and then the results may not matter because their accuracy might have been bad. TOPS right now is like Whetstone/Drystone or MIPS, FLOPS, etc back in the day. It's a very rough estimate, but it can get you in the ballpark, so you can narrow down hundreds of options to 15 or so and then do more research from there. If someone comes up with something better then for sure let's all use that. Or if we could get some standardized benchmarks (I found some last night, there were several, and the results were very sparse (not every entry ran all of the benchmarks in all the different ways it could), one dataset was mostly a couple hundred rows NVIDIA 4090, L4, L40, QUALCOMM AI 100 (a cloud processor, you can't buy and run it) and then the last several rows where like a few Raspi 4s and some other MPU boards with drastically lower scores. Every once in a while some announces a project to fix this, but it hasn't helped at all.
2024.05.29 07:11 Disastrous_Head_4282 Favorite Honda dealers/specific mechanics
I have my first Honda, a 2011 Accord. Has some minimal things that need done. I like North City Honda so far but would want some other recommendations. What do you think of this place? https://www.haaschicago.com
I liked Morton Grove Honda but they’re under construction. Honda downtown was nice enough to tell me I had an open recall but it is a pain to get in and out of. Thanks in advance
submitted by Disastrous_Head_4282 to AskChicago [link] [comments]
I liked Morton Grove Honda but they’re under construction. Honda downtown was nice enough to tell me I had an open recall but it is a pain to get in and out of. Thanks in advance
2024.05.29 07:10 Gracks69 my post got removed for no reason by reddit spam filters
submitted by Gracks69 to help [link] [comments]2024.05.29 07:10 TerribleSell2997 Portable Air Compressor Market Increasing Demand, Growth Analysis and Future Outlook by 2031
The ~global portable air compressor market~ is anticipated to grow at a significant CAGR of 7.2% during the forecast period (2023-2029). Portable Air Compressor Market research report refers to gathering and analyzing significant market data serve as best medium for various industry players to launch novel product or service. It is vital for key firms to have constant observation of latest market trends which keep on changing. Constants shifts in the trends and key advancements are observed in the market through this Portable Air Compressor Market report and inform key firms about them. By knowing this, business owners can take effective actions before actually developing any product or service. It also aims at offering thorough knowledge regarding competitors to assist them in taking strategic decision making.
Get Free Sample link @ https://www.omrglobal.com/request-sample/portable-air-compressor-market
The global portable air compressor market is segmented based on the power source, technology, lubrication, and application. Based on the power source, the market is classified as electric and gas. Based on the technology, the market is segmented into rotary which comprises of screw & scroll and reciprocating. Based on the application, the market is segmented into oil & gas, mining & energy, healthcare, manufacturing, semiconductor & electronics, building & construction, food & beverage, and others. Among the application segment, the semiconductor & electronics is projected to hold prominent share of the market and grow at a significant CAGR over the forecast period. Due to the rise in utilization and demand for oil free air compressors among the industry.
full report of Portable Air Compressor Market available @ https://www.omrglobal.com/industry-reports/portable-air-compressor-market
· Market Coverage
· Market number available for – 2024-2031
· Base year- 2024
· Forecast period- 2024-2031
· Segment Covered- By Source, By Product Type, By Applications
· Competitive Landscape- Archer Daniels Midland Co., Ingredion Inc., Kerry Group Plc, Cargill
· Inc., and others
Global Portable Air Compressor Market Report Segment
By Power Source
• Electric
• Gas
By Technology
• Rotary (Screw, Scroll)
• Reciprocating
By Lubrication
• Oil Free
• Oil Filled
By Application
• Oil & Gas
• Mining & Energy
• Healthcare
• Manufacturing
• Semiconductors & Electronics
• Building & Construction
• Food & Beverage
• Others (Home Appliances)
Global Portable Air Compressor Market Report Segment by Region
North America
• United States
• Canada
Europe
• UK
• Germany
• Italy
• Spain
• France
• Rest of Europe
Asia-Pacific
• China
• India
• Japan
• South Korea
• Rest of Asia-Pacific
Rest of the World
• Latin America
• Middle East & Africa
The Report Covers
• Annualized market revenues ($ million) for each market segment.
• Country-wise analysis of major geographical regions.
• Key companies operating in the global portable air compressor market. Based on the availability of data, information related to new product launches, and relevant news is also available in the report.
• Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
• Analysis of market-entry and market expansion strategies.
• Competitive strategies by identifying ‘who-stands-where’ in the market.
For More Customized Data, Request for Report Customization @ https://www.omrglobal.com/report-customization/portable-air-compressor-market
About Orion Market Research Orion Market Research (OMR) is a market research and consulting company known for its crisp and concise reports. The company is equipped with an experienced team of analysts and consultants. OMR offers quality syndicated research reports, customized research reports, consulting and other research-based services. The company also offer Digital Marketing services through its subsidiary OMR Digital and Software development and Consulting Services through another subsidiary Encanto Technologies.
Media Contact:
Company Name: Orion Market Research
Contact Person: Mr. Anurag Tiwari
Email: [info@omrglobal.com](mailto:info@omrglobal.com)
Contact no: +91 780-304-0404
submitted by TerribleSell2997 to Nim2908 [link] [comments]
Get Free Sample link @ https://www.omrglobal.com/request-sample/portable-air-compressor-market
The global portable air compressor market is segmented based on the power source, technology, lubrication, and application. Based on the power source, the market is classified as electric and gas. Based on the technology, the market is segmented into rotary which comprises of screw & scroll and reciprocating. Based on the application, the market is segmented into oil & gas, mining & energy, healthcare, manufacturing, semiconductor & electronics, building & construction, food & beverage, and others. Among the application segment, the semiconductor & electronics is projected to hold prominent share of the market and grow at a significant CAGR over the forecast period. Due to the rise in utilization and demand for oil free air compressors among the industry.
full report of Portable Air Compressor Market available @ https://www.omrglobal.com/industry-reports/portable-air-compressor-market
· Market Coverage
· Market number available for – 2024-2031
· Base year- 2024
· Forecast period- 2024-2031
· Segment Covered- By Source, By Product Type, By Applications
· Competitive Landscape- Archer Daniels Midland Co., Ingredion Inc., Kerry Group Plc, Cargill
· Inc., and others
Global Portable Air Compressor Market Report Segment
By Power Source
• Electric
• Gas
By Technology
• Rotary (Screw, Scroll)
• Reciprocating
By Lubrication
• Oil Free
• Oil Filled
By Application
• Oil & Gas
• Mining & Energy
• Healthcare
• Manufacturing
• Semiconductors & Electronics
• Building & Construction
• Food & Beverage
• Others (Home Appliances)
Global Portable Air Compressor Market Report Segment by Region
North America
• United States
• Canada
Europe
• UK
• Germany
• Italy
• Spain
• France
• Rest of Europe
Asia-Pacific
• China
• India
• Japan
• South Korea
• Rest of Asia-Pacific
Rest of the World
• Latin America
• Middle East & Africa
The Report Covers
• Annualized market revenues ($ million) for each market segment.
• Country-wise analysis of major geographical regions.
• Key companies operating in the global portable air compressor market. Based on the availability of data, information related to new product launches, and relevant news is also available in the report.
• Analysis of business strategies by identifying the key market segments positioned for strong growth in the future.
• Analysis of market-entry and market expansion strategies.
• Competitive strategies by identifying ‘who-stands-where’ in the market.
For More Customized Data, Request for Report Customization @ https://www.omrglobal.com/report-customization/portable-air-compressor-market
About Orion Market Research Orion Market Research (OMR) is a market research and consulting company known for its crisp and concise reports. The company is equipped with an experienced team of analysts and consultants. OMR offers quality syndicated research reports, customized research reports, consulting and other research-based services. The company also offer Digital Marketing services through its subsidiary OMR Digital and Software development and Consulting Services through another subsidiary Encanto Technologies.
Media Contact:
Company Name: Orion Market Research
Contact Person: Mr. Anurag Tiwari
Email: [info@omrglobal.com](mailto:info@omrglobal.com)
Contact no: +91 780-304-0404
2024.05.29 07:10 miekejillian The Horror of the Dimensional Merge Theory -- The Product of a Deranged Mind
The "~Dimensional Merge~" theory is a most obscure, insane, and widely unacceptable theory that I first heard from a certain insane man, now woman, called ~Chris Chan~.
Perhaps some of you already have some familiarity with this person, and perhaps some of you do not. Chris Chan is an American transgender woman with ~low-functioning autism~ who also appears to be suffering from a declining, or should I say, rising, ~mental illness~. They're in prison currently for a crime so shameful I'd best not mention it in this article.
With their declining sanity, Chan have seemed to have eventually lost the ability to not only tell truth from lie, but also reality from fiction. ~As a result, they are easily manipulated~, as they were in the past by ~online trolls,~ and they see themselves as married to the characters they created in their mind and comics.
submitted by miekejillian to askphilosophy [link] [comments]
Perhaps some of you already have some familiarity with this person, and perhaps some of you do not. Chris Chan is an American transgender woman with ~low-functioning autism~ who also appears to be suffering from a declining, or should I say, rising, ~mental illness~. They're in prison currently for a crime so shameful I'd best not mention it in this article.
With their declining sanity, Chan have seemed to have eventually lost the ability to not only tell truth from lie, but also reality from fiction. ~As a result, they are easily manipulated~, as they were in the past by ~online trolls,~ and they see themselves as married to the characters they created in their mind and comics.
2024.05.29 07:10 Infinite-Ad-7985 Peacock Door Handles: A Unique Addition to Your Home's Interior Design
 | In the realm of home decor, the smallest details often make the most significant impact. One such detail that can transform the aesthetic of your living space is the choice of door handles. Among the various options available, peacock door handles peacock door handles stand out as a truly unique and elegant addition to your home's interior design. Let's explore why these stunning handles are a perfect choice for those looking to add a touch of sophistication and charm to their home. submitted by Infinite-Ad-7985 to u/Infinite-Ad-7985 [link] [comments] Click to read more : https://dluxdekor.blogspot.com/2024/05/peacock-door-handles-unique-addition-to.html For more information, contact Email: info@dluxdekor.com Mob: +91-6396731011 Peacock Door Handles: A Unique Addition to Your Home's Interior Design |
2024.05.29 07:09 perfectfire Where did all of the hobbyist NPU/TPU accelerators go in the last 5 years?
TL;DR: AI Inference hardware accelerators were all the rage a few years ago. They still are, but they seem to have abandoned the hobbyist, low-power, low-size, low-mid cost, seperate board user, such that abandoned projects such as the Google edge TPU from 2019 (5 yrs ago) are still your best bet $/perf wise. The $20 - $150 range is empty or has some products that aren't worth it at all. What happened? Are there any modern hobbyist $20 - $150 accelerators you can buy right now anywhere?
Sidenote: I know TOPS isn't the end-all be-all of perf comparison, but it's all I got.[1]
Skip for history of my interest: I've long been interested in machine learning, especially artificial neural networks since I took a class on ML in college in around 2004. I've done some hobbyist projects on the CPU and even released a C#/.Net wrapper for FANN (Fast Artificial Neural Network, a fast open-source neural network run on CPUs because everything was on CPUs then): https://github.com/joelself/FannCSharp. When deep learning took off I got excited. I got into competitive password cracking and although my ML based techniques were about a dozen orders of magnitudes slower at making guesses, they were almost immediately able to find a few passwords in old leaks that had been gone over and over for years by the best crackers with the most absurd hardware and extremely specially tuned password guess generators. That made me pretty proud that I was able to do something in a few months that years of dozens of groups with $100,000s of thousands of dollars of hardware and who know how many watt-hours couldn't do. I even thought about writing a a paper on it, but I was kinda in over my head and my life got a lot worse so I had to put all of my side projects on hold unfortunately. Recently though I did a vanity search for my FANN C# wrapper and found people talking about it and some references in some papers and student projects which made me feel proud.
Skip for history of my interest: Now I really want to get into the cross section of hardware-accelerated inference (no training this time, I'm not a trillion dollar company with billion dollars of supercomputers running on specialized training hardware that took 100's of millions of dollars to develop), microcontrollers for robots, drones, other smallish tasks that can't carry around their own 100 lb diesel generator and 2 1U rackmount servers full of inference hardware that I can't even get ahold of because you can only buy that stuff if you are an Intel or GE or some other company that might make products in the 10's of thousands at least. And this is where I hit a wall.
I just started looking around and one of the first things I found was Google's TPU by Coral.ai. 4 TOPs in a package, 2 chips on a small m2 card. Only about 40 bucks for developers to try out, $60 for an easier to use, but 1 chip only USB product. But this was about 5 years ago, and they just slowly disappeared and haven't made a peep in like 3 years. They timed the market perfectly. AI stuff was right on the verge of BLOWING THE F*CK UP. They could be THE edge/robotics/iot/anything-other-than-servecloud-phone-tablet-PC-laptop company. But they just seemed to give up. They're obviously not giving up on improving edge inference hardware. They release their phones twice a year (regular version, then A version) and they always update the tensor processing unit in those and are really starting to push that as a must have feature. They could use the same hardware improvements to make somewhat bigger chips to sell for other markets. You never know, someone might take their 3rd gen 16 TOPS TPU chip and makes a product(s) that takes the world by storm. Maybe multiple people/companies will do that.
Okay, so Google, seems to have dropped the hat. Hardware inference companies are a dime a dozen these days just go with another. But that's the problem. It seems all the focus is on Cloud scale, super-computer (some overlap between those 2), embedded on finished phones/tables/laptop/PCs, powerful server accelerators, and a very few extremely tiny MCUs with accordingly tiny MPUs. I seems everybody has abandoned the lower-mid range-robotics-drone-hobbyist space with haste.
ARM introduced the Ethos U-55 and U65 with the 65 having about double the TOPS of the 55 at a max of 1 TOPS in 2020. As far as I can tell the first products to use the U-55 were in 2022 and there haven't been a lot and I don't think they ran at top speed. Noone has opted to implement even an unmodified U-65 for anything. I recently bought a Grove AI Vision Kit with a U-55 NPU and it's specced at a lowly 50 GOPS (ARM's top-end says it could hit 10 times that and until *just now* I thought it was 500 GOPS and thus offered good $/TOPS ...oops).
There's a lot of companies making hype, a lot seeming to have selling dev or reference boards, but instead producing a few thousands and distributing them via the usual (Mouser, DigiKey, Element14, SparkFun, etc), they want you to fill out extensive forms to ensure you're a big player that will definitely eventually buy at least 100,000 units a day otherwise you're a waste of time for them to consider you (even though going over every applicant individually is WAY more time consuming than just producing a couple thou and have DigiKey take care of selling 1 to 2 at a time).
Thus I've come to the point that while Google edge TPU is abandoned (even though Google is going full steam ahead on AI inference for their cellphones and tablets) and Coral.ai is seemingly doing nothing. Their TPUs still provide the best $/TOPS in the range I want. Take a look at [VOXL2](https://www.modalai.com/collections/blue-uas-framework-components/products/voxl-2?variant=39914779836467). Basically exactly what I want and would expect we should have had something like a Google Edge TPU v3 by now (but a bit smaller and a little less power consumption, yes, I know moore's law doesn't really apply anymore, but in rapidly growing and learning fields like accelerated inference, double the speed every 2 years is not unreasonable and it has been 5 years since the Google TPU @ 4 TOPS per chip). But the damn thing is over $1,2000.
So, my point finally is that even though Google and Coral.ai seem to have abandoned their TPU. At about $40 for 2 chips at 4 TOPS apiece for 8 TOPS total, they still seem to be the best middle ground. The next best might be the BeagleBone reference studio for about 8 TOPS at $187. Same TOPS (though on one chip) for more than 4.5 times the cost. The Jetson Orin Nano by NVIDIA is $259 for 20 TOPS at $51/4TOPS that a single Google edge TPU will put out at $20 (including the board and stuff). It seems everyone is abandoning the hobbyist edge inference space at lightning speed. There are a lot of companies with promising size (physical) and performance products, but they won't talk to you until you fill out a form that implies that they only want to talk to someone that has already decided to buy 100,000s of your units whereas in the past, companies would have dev/reference boards out trying to find someone that would develop that killer app and make them a lot of money.
Why is this? Am I looking in the wrong place? Should I hoard Google edge TPUs? I bought their USB version to tinker with and the Grove AI Vision Kit (now that I realize is only 50 GOPS, so might be worthless). What are my options. For example. A single quadcopter a 100 - 300m above the ground looking "things", not image classic image classification where it can identify thousands of different objects. It just needs to identify one type of thing. Doesn't even have to be very fast. In fact, don't these NNs run on single images? I could just buy multiple chips and run in parallel to get the framerate I want if it isn't fast enough (it won't improve latency, but 100 - 500 ms latency probably isn't a problem until you get real close at which time you can switch to a different, much cheaper solution that works even better at close range and wide FOV).
Maybe I can use a phone and get low level access to the NPU/TPU and use that or use their powerful graphics cards on the phone or small laptop like a caveman from 2017. Still pretty expensive and I would be paying a ton of money for hardware I don't want. Maybe I could buy broken phones "for parts" on ebay, but I'm not that hardware savvy. I need a dev board to get me going.
The next best idea is to just push video from my drone/robot/project to a central station with a super powerful 1-4U server inference accelerator (not sure how I would get one), or Jetson Orin, computer with RTX4090 and do inference there and just tolerate the latency. That won't be feasible for some applications I would like to do though.
submitted by perfectfire to learnmachinelearning [link] [comments]
Sidenote: I know TOPS isn't the end-all be-all of perf comparison, but it's all I got.[1]
Skip for history of my interest: I've long been interested in machine learning, especially artificial neural networks since I took a class on ML in college in around 2004. I've done some hobbyist projects on the CPU and even released a C#/.Net wrapper for FANN (Fast Artificial Neural Network, a fast open-source neural network run on CPUs because everything was on CPUs then): https://github.com/joelself/FannCSharp. When deep learning took off I got excited. I got into competitive password cracking and although my ML based techniques were about a dozen orders of magnitudes slower at making guesses, they were almost immediately able to find a few passwords in old leaks that had been gone over and over for years by the best crackers with the most absurd hardware and extremely specially tuned password guess generators. That made me pretty proud that I was able to do something in a few months that years of dozens of groups with $100,000s of thousands of dollars of hardware and who know how many watt-hours couldn't do. I even thought about writing a a paper on it, but I was kinda in over my head and my life got a lot worse so I had to put all of my side projects on hold unfortunately. Recently though I did a vanity search for my FANN C# wrapper and found people talking about it and some references in some papers and student projects which made me feel proud.
Skip for history of my interest: Now I really want to get into the cross section of hardware-accelerated inference (no training this time, I'm not a trillion dollar company with billion dollars of supercomputers running on specialized training hardware that took 100's of millions of dollars to develop), microcontrollers for robots, drones, other smallish tasks that can't carry around their own 100 lb diesel generator and 2 1U rackmount servers full of inference hardware that I can't even get ahold of because you can only buy that stuff if you are an Intel or GE or some other company that might make products in the 10's of thousands at least. And this is where I hit a wall.
I just started looking around and one of the first things I found was Google's TPU by Coral.ai. 4 TOPs in a package, 2 chips on a small m2 card. Only about 40 bucks for developers to try out, $60 for an easier to use, but 1 chip only USB product. But this was about 5 years ago, and they just slowly disappeared and haven't made a peep in like 3 years. They timed the market perfectly. AI stuff was right on the verge of BLOWING THE F*CK UP. They could be THE edge/robotics/iot/anything-other-than-servecloud-phone-tablet-PC-laptop company. But they just seemed to give up. They're obviously not giving up on improving edge inference hardware. They release their phones twice a year (regular version, then A version) and they always update the tensor processing unit in those and are really starting to push that as a must have feature. They could use the same hardware improvements to make somewhat bigger chips to sell for other markets. You never know, someone might take their 3rd gen 16 TOPS TPU chip and makes a product(s) that takes the world by storm. Maybe multiple people/companies will do that.
Okay, so Google, seems to have dropped the hat. Hardware inference companies are a dime a dozen these days just go with another. But that's the problem. It seems all the focus is on Cloud scale, super-computer (some overlap between those 2), embedded on finished phones/tables/laptop/PCs, powerful server accelerators, and a very few extremely tiny MCUs with accordingly tiny MPUs. I seems everybody has abandoned the lower-mid range-robotics-drone-hobbyist space with haste.
ARM introduced the Ethos U-55 and U65 with the 65 having about double the TOPS of the 55 at a max of 1 TOPS in 2020. As far as I can tell the first products to use the U-55 were in 2022 and there haven't been a lot and I don't think they ran at top speed. Noone has opted to implement even an unmodified U-65 for anything. I recently bought a Grove AI Vision Kit with a U-55 NPU and it's specced at a lowly 50 GOPS (ARM's top-end says it could hit 10 times that and until *just now* I thought it was 500 GOPS and thus offered good $/TOPS ...oops).
There's a lot of companies making hype, a lot seeming to have selling dev or reference boards, but instead producing a few thousands and distributing them via the usual (Mouser, DigiKey, Element14, SparkFun, etc), they want you to fill out extensive forms to ensure you're a big player that will definitely eventually buy at least 100,000 units a day otherwise you're a waste of time for them to consider you (even though going over every applicant individually is WAY more time consuming than just producing a couple thou and have DigiKey take care of selling 1 to 2 at a time).
Thus I've come to the point that while Google edge TPU is abandoned (even though Google is going full steam ahead on AI inference for their cellphones and tablets) and Coral.ai is seemingly doing nothing. Their TPUs still provide the best $/TOPS in the range I want. Take a look at [VOXL2](https://www.modalai.com/collections/blue-uas-framework-components/products/voxl-2?variant=39914779836467). Basically exactly what I want and would expect we should have had something like a Google Edge TPU v3 by now (but a bit smaller and a little less power consumption, yes, I know moore's law doesn't really apply anymore, but in rapidly growing and learning fields like accelerated inference, double the speed every 2 years is not unreasonable and it has been 5 years since the Google TPU @ 4 TOPS per chip). But the damn thing is over $1,2000.
So, my point finally is that even though Google and Coral.ai seem to have abandoned their TPU. At about $40 for 2 chips at 4 TOPS apiece for 8 TOPS total, they still seem to be the best middle ground. The next best might be the BeagleBone reference studio for about 8 TOPS at $187. Same TOPS (though on one chip) for more than 4.5 times the cost. The Jetson Orin Nano by NVIDIA is $259 for 20 TOPS at $51/4TOPS that a single Google edge TPU will put out at $20 (including the board and stuff). It seems everyone is abandoning the hobbyist edge inference space at lightning speed. There are a lot of companies with promising size (physical) and performance products, but they won't talk to you until you fill out a form that implies that they only want to talk to someone that has already decided to buy 100,000s of your units whereas in the past, companies would have dev/reference boards out trying to find someone that would develop that killer app and make them a lot of money.
Why is this? Am I looking in the wrong place? Should I hoard Google edge TPUs? I bought their USB version to tinker with and the Grove AI Vision Kit (now that I realize is only 50 GOPS, so might be worthless). What are my options. For example. A single quadcopter a 100 - 300m above the ground looking "things", not image classic image classification where it can identify thousands of different objects. It just needs to identify one type of thing. Doesn't even have to be very fast. In fact, don't these NNs run on single images? I could just buy multiple chips and run in parallel to get the framerate I want if it isn't fast enough (it won't improve latency, but 100 - 500 ms latency probably isn't a problem until you get real close at which time you can switch to a different, much cheaper solution that works even better at close range and wide FOV).
Maybe I can use a phone and get low level access to the NPU/TPU and use that or use their powerful graphics cards on the phone or small laptop like a caveman from 2017. Still pretty expensive and I would be paying a ton of money for hardware I don't want. Maybe I could buy broken phones "for parts" on ebay, but I'm not that hardware savvy. I need a dev board to get me going.
The next best idea is to just push video from my drone/robot/project to a central station with a super powerful 1-4U server inference accelerator (not sure how I would get one), or Jetson Orin, computer with RTX4090 and do inference there and just tolerate the latency. That won't be feasible for some applications I would like to do though.
- I found a github repo that collects perf comparison projects and I checked their data, and it's extremely sparse. One set is dominated by NVIDIA 4090, L(s), L4(s), and QUALCOMM T100 (or something, it's a cloud only processor, so you can't buy it). Then a few rows at the bottom have Raspi 4 and like 5 other mini applications units and MCU chips. And the results were hard to interpret especially since not all entrants have run all benchmarks and they can run it in probably dozens of different ways and then the results may not matter because their accuracy might have been bad. TOPS right now is like Whetstone/Drystone or MIPS, FLOPS, etc back in the day. It's a very rough estimate, but it can get you in the ballpark, so you can narrow down hundreds of options to 15 or so and then do more research from there. If someone comes up with something better then for sure let's all use that. Or if we could get some standardized benchmarks (I found some last night, there were several, and the results were very sparse (not every entry ran all of the benchmarks in all the different ways it could), one dataset was mostly a couple hundred rows NVIDIA 4090, L4, L40, QUALCOMM AI 100 (a cloud processor, you can't buy and run it) and then the last several rows where like a few Raspi 4s and some other MPU boards with drastically lower scores. Every once in a while some announces a project to fix this, but it hasn't helped at all.
2024.05.29 07:09 AllProGroupLLC ROAD TO COAST INC - Broker Alert!
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submitted by AllProGroupLLC to FreightBrokerWatch [link] [comments]
ROAD TO COAST INC 1645 Palm Beach Lakes Blvd Ste 1200 West Palm Beach, FL (813) 953-6693 MC# 1519370 DOT# 4025364
2024.05.29 07:09 ChaosUndAnarchie AKTUELLE LAGE DES SUBREDDITS...BOTS, KI-INHALTE UND DIE SKY-BESCHWERDEABTEILUNG
ERSTER WICHTIGER PUNKT:
Ich weis nicht, ob es euch als solches aufgefallen ist, aber hier posten seit dieser Saison Bots ins Subreddit und es gibt massenhaft AI-generierte Inhalte...
Als aktuelles Beispiel möchte ich hier mal u/OptionDry6730 nennen, "der" die 2 Leclerc-bezogenen Videos mit Tiktok-Zeichen hochgeladen hat...vor 2 Tagen erst Reddit beigetretet, 2 Tiktok-Videos bzgl Leclerc und 3 generische Kommentare unter Erotik-Bilder auf , die auch sofort wieder gelöscht wurden...BOT! Und nur einer von vielen, die aus dem Nichts auftauchen, zumeist Tiktok-Inhalte hier posten und dann wieder gelöscht werden.
Noch wilder wird es dann bei , ein Kanal eines F1-Merch(eher unnützer Kitsch)-Onlinehandels, der seit 2 Jahren ausschließlich KI-generierte Inhalte in SÄMTLICHE F1-bezogenen Subreddits spamt, und seit diesem Jahr auch ins deutsche. Checkt ruhig mal den Kanal ab...seit über einem Jahr KEIN EINZIGER echter Kommentar, lediglich einige Inhaltsbeschreibungen der Videos, aber keine Reaktion/Antworten auf einen menschlichen Kommentar. Dafür alle Videos gleich 3-4 mal vertreten, weil sie in 4 verschiedene F1-Subreddits gespamt wurden und ALLES ausschließlich KI-generiert.
DAHER LEUTE, VOTET SOLCHE INHALTE NICHT HOCH, NULLT SIE SO SCHNELL ES NUR GEHT!!! WO EIN BOT ERFOLGREICH IST, KOMMEN AUTOMATISCH IMMER MEHR DAZU!
ZWEITER WICHTIGER PUNKT:
Es ist zwar nix neues, aber während hier Beiträge die sich tatsächlich auf den Sport und die Hintergründe der F1 beziehen eher mäßig Anklang, bzw wenig Feedback finden und auch wenige Kommentare geschrieben werden, geht jeder noch so primitive Rant/Hass-Post gegen Sky, deren Kommentatoren, usw stets DURCH DIE DECKE...
Diese Beiträge haben NICHTS, ABER AUCH GARNICHTS mit der F1 selbst zu tun und sie widerholen sich immer und immer wieder...es kommt niemals irgend etwas Neues hinzu!
Ich kann zwar den Frust durchaus nachvollziehen, da ich selbst auch nach "Schulz/Surer" auf Premiere über RTL in die Illegalität absteigen musste, um noch halbwegs vernünftig F1 schauen zu können und daher nachvollziehen kann, dass sich jemand beschweren und seine Wut anderen mitteilen will...
Aber es hat halt NULL mit der F1 selbst zu tun und ist hier im Subreddit VÖLLIG fehl am Platz. Kein einziger Mitarbeiter von Sky wird es lesen, es bringt GARNICHTS, außer dass JEDES scheiß Wochenende der gleiche stumpfe Anti-"Ralf Schumacher"-Post geschrieben wird und alle Beifall klatschen.
Würdet ihr die gleichen Upvotes doch lieber mal an die nur 5-6 Leute hier verteilen, die für dieses Subreddit hier recherchieren, formulieren, Videos schneiden und auch TATSÄCHLICHE F1-INHALTE posten, oder SELBST gute Inhalte produzieren, wäre so viel mehr für diese Community getan!!!
Die Frage die sich hier abschließend stellt ist folgende:
Was ist ein F1-Subreddit, in dem nur 5 Leute halbwegs relevante Inhalte hochladen und dann Bots und KI-Inhalte bereits 50% aller Inhalte bestimmen, welche dann auch noch blindlinks hochgevotet werden, auf dass es NOCH MEHR werden.
Und alles was sonst hier geschieht, ist das wöchentliche Treffen, des anonymen Anti-"Ralf Schumacher"-Clubs und der allgemeine Kummerkasten für Sky-Zuschauer, die NICHTS ANDERES TUN, als zu meckern, obwohl ihnen VPNs nach Österreich und in die Schweiz, zu F1-TV und auch ohne VPN TV-Streaming in die Schweiz und nach Österreich UND englische Steams zur freien Verfügung stehen!
HÖRT BITTE AUF BOTS UND KI HOCHZUVOTEN! GEBT EURE STIMME DEN ECHTEN INHALTEN, ODER POSTET SELBST ETWAS SINNVOLLES!
HÖRT AUF IN DIESEM SUBREDDIT AUSSCHLIEßLICH ÜBER SKY-KOMMENTATOREN ZU RANTEN, ES BRINGT ABSULUT GARNICHTS UND IST HIER FEHL AM PLATZ! EUCH STEHT DIE WELT OFFEN, WENN IHR F1 DORT NICHT SCHAUEN WOLLT!
submitted by ChaosUndAnarchie to Formel1 [link] [comments]
Ich weis nicht, ob es euch als solches aufgefallen ist, aber hier posten seit dieser Saison Bots ins Subreddit und es gibt massenhaft AI-generierte Inhalte...
Als aktuelles Beispiel möchte ich hier mal u/OptionDry6730 nennen, "der" die 2 Leclerc-bezogenen Videos mit Tiktok-Zeichen hochgeladen hat...vor 2 Tagen erst Reddit beigetretet, 2 Tiktok-Videos bzgl Leclerc und 3 generische Kommentare unter Erotik-Bilder auf , die auch sofort wieder gelöscht wurden...BOT! Und nur einer von vielen, die aus dem Nichts auftauchen, zumeist Tiktok-Inhalte hier posten und dann wieder gelöscht werden.
Noch wilder wird es dann bei , ein Kanal eines F1-Merch(eher unnützer Kitsch)-Onlinehandels, der seit 2 Jahren ausschließlich KI-generierte Inhalte in SÄMTLICHE F1-bezogenen Subreddits spamt, und seit diesem Jahr auch ins deutsche. Checkt ruhig mal den Kanal ab...seit über einem Jahr KEIN EINZIGER echter Kommentar, lediglich einige Inhaltsbeschreibungen der Videos, aber keine Reaktion/Antworten auf einen menschlichen Kommentar. Dafür alle Videos gleich 3-4 mal vertreten, weil sie in 4 verschiedene F1-Subreddits gespamt wurden und ALLES ausschließlich KI-generiert.
DAHER LEUTE, VOTET SOLCHE INHALTE NICHT HOCH, NULLT SIE SO SCHNELL ES NUR GEHT!!! WO EIN BOT ERFOLGREICH IST, KOMMEN AUTOMATISCH IMMER MEHR DAZU!
ZWEITER WICHTIGER PUNKT:
Es ist zwar nix neues, aber während hier Beiträge die sich tatsächlich auf den Sport und die Hintergründe der F1 beziehen eher mäßig Anklang, bzw wenig Feedback finden und auch wenige Kommentare geschrieben werden, geht jeder noch so primitive Rant/Hass-Post gegen Sky, deren Kommentatoren, usw stets DURCH DIE DECKE...
Diese Beiträge haben NICHTS, ABER AUCH GARNICHTS mit der F1 selbst zu tun und sie widerholen sich immer und immer wieder...es kommt niemals irgend etwas Neues hinzu!
Ich kann zwar den Frust durchaus nachvollziehen, da ich selbst auch nach "Schulz/Surer" auf Premiere über RTL in die Illegalität absteigen musste, um noch halbwegs vernünftig F1 schauen zu können und daher nachvollziehen kann, dass sich jemand beschweren und seine Wut anderen mitteilen will...
Aber es hat halt NULL mit der F1 selbst zu tun und ist hier im Subreddit VÖLLIG fehl am Platz. Kein einziger Mitarbeiter von Sky wird es lesen, es bringt GARNICHTS, außer dass JEDES scheiß Wochenende der gleiche stumpfe Anti-"Ralf Schumacher"-Post geschrieben wird und alle Beifall klatschen.
Würdet ihr die gleichen Upvotes doch lieber mal an die nur 5-6 Leute hier verteilen, die für dieses Subreddit hier recherchieren, formulieren, Videos schneiden und auch TATSÄCHLICHE F1-INHALTE posten, oder SELBST gute Inhalte produzieren, wäre so viel mehr für diese Community getan!!!
Die Frage die sich hier abschließend stellt ist folgende:
Was ist ein F1-Subreddit, in dem nur 5 Leute halbwegs relevante Inhalte hochladen und dann Bots und KI-Inhalte bereits 50% aller Inhalte bestimmen, welche dann auch noch blindlinks hochgevotet werden, auf dass es NOCH MEHR werden.
Und alles was sonst hier geschieht, ist das wöchentliche Treffen, des anonymen Anti-"Ralf Schumacher"-Clubs und der allgemeine Kummerkasten für Sky-Zuschauer, die NICHTS ANDERES TUN, als zu meckern, obwohl ihnen VPNs nach Österreich und in die Schweiz, zu F1-TV und auch ohne VPN TV-Streaming in die Schweiz und nach Österreich UND englische Steams zur freien Verfügung stehen!
HÖRT BITTE AUF BOTS UND KI HOCHZUVOTEN! GEBT EURE STIMME DEN ECHTEN INHALTEN, ODER POSTET SELBST ETWAS SINNVOLLES!
HÖRT AUF IN DIESEM SUBREDDIT AUSSCHLIEßLICH ÜBER SKY-KOMMENTATOREN ZU RANTEN, ES BRINGT ABSULUT GARNICHTS UND IST HIER FEHL AM PLATZ! EUCH STEHT DIE WELT OFFEN, WENN IHR F1 DORT NICHT SCHAUEN WOLLT!
2024.05.29 07:09 everbloomindia24 Elegant Sharara Sets for Every Occasion Shop Now
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submitted by everbloomindia24 to u/everbloomindia24 [link] [comments]
2024.05.29 07:09 Yumiriki Kolejne Referendum?1
Cześć,
15 października głosowaliśmy bądź też nie na referendum, które było po prostu ustawką, żeby pompować kasę w kampanię nieoficjalną drogą. Na ten moment, Solidarność zebrała ponad 200,000 z 500,000 podpisów potrzebnych do tego żeby zrobić nam kolejne referendum, tym razem przeciw zielonemu ładowi. Nie wiem kiedy te referendum miałoby się odbyć ale zakładam, że za rok włącznie z wyborami prezydenckimi. Będzie to kolejny moment do wlania milionów, żeby wygrał ktoś z PiS. Dlatego wpadłem na pewien pomysł.
Zrobić drugie referendum, ale nie dla celów propagandowych drugiej strony, tylko żeby wykorzystać tą okazję i dać ludziom szansę się wypowiedzieć na temat prawdziwych zmian na poziomie konstytucji i ustaw, a okazji pokazać, że referendum to nie tylko zabawka dla PiSu. Do głowy przyszło mi parę pomysłów:
Przestudiowałem cały 2015 rok i uważam, że to nie może się powtórzyć. Wysokie progi zmiotły Lewice, KORWiNa i Razem z planszy wyborczej i PiS mając 38% zdobył 50+% miejsc w sejmie i było co było przez kolejne 8 lat. Obejrzałem jakiś czas temu ten film https://www.youtube.com/watch?v=oIAQcvewgTg i byłem pod wielkim wrażeniem, że udało im się zebrać podpisy na referendum i że referendum przeszło i gerrymandering w stanie Michigan się skończyło. Nie wiem jak zebrać 500,000 podpisów ale wiem, że to na pewno nie będzie łatwe. Na pewno byłoby to niezła satysfakcja zagłosować w prawdziwym referendum a nie w jakieś tubie propagandowej o miernej treści.
Zapraszam do dyskusji.
A tak bym zagłosował ja: 1. Tak; 2. Nie; 3. Tak; 4. Tak; 5. Nie; 6. Nie; 7. Tak; 8. Tak; 9. Tak; 10. Tak; 11. Nie; 12. Tak; 13. Nie; 14. Tak; 15. Nie.
submitted by Yumiriki to Polska [link] [comments]
15 października głosowaliśmy bądź też nie na referendum, które było po prostu ustawką, żeby pompować kasę w kampanię nieoficjalną drogą. Na ten moment, Solidarność zebrała ponad 200,000 z 500,000 podpisów potrzebnych do tego żeby zrobić nam kolejne referendum, tym razem przeciw zielonemu ładowi. Nie wiem kiedy te referendum miałoby się odbyć ale zakładam, że za rok włącznie z wyborami prezydenckimi. Będzie to kolejny moment do wlania milionów, żeby wygrał ktoś z PiS. Dlatego wpadłem na pewien pomysł.
Zrobić drugie referendum, ale nie dla celów propagandowych drugiej strony, tylko żeby wykorzystać tą okazję i dać ludziom szansę się wypowiedzieć na temat prawdziwych zmian na poziomie konstytucji i ustaw, a okazji pokazać, że referendum to nie tylko zabawka dla PiSu. Do głowy przyszło mi parę pomysłów:
- Zmniejszyć sejm o 100 posłów
- Zmniejszyć sejm o 20 senatorów
- Zwiększyć siłę polityczną senatu (nie wiem w jaki sposób ale to, że jedyne co mogła opozycja w senacie w latach 2019-2023 to miesiąc przeczekania to jest słabe)
- Zmienić ordynację na proporcjonalną w senacie
- Obniżyć granicę startowania do sejmu i senatu do 18.
- Obniżyć wiek do głosowania do 16
- Ustawić limit wieku do sejmu, senatu i każdej funkcji państwowej do ustawowego wieku emerytalnego w dniu wyborów.
- Wprowadzić dzień do głosowania jak w stanach (np. Druga sobota w październiku bądź 15 października) czyli koniec z maratonami wyborczymi. (poza wyborami do PE)
- Wprowadzić głosowanie rankingowe na prezydenta RP i prezydentów, wójtów itd. (Koniec drugiej tory)
- Zakazać JOWów.
- Wprowadzić obowiązkowe głosowanie jak w Belgii
- Obniżyć progi wyborcze o 1 albo 2%, żeby nie było powtórki z 2015.
- Prowadzić wybory samorządowe co 3 lata ale żeby każdy region np. na poziomie województwa mógł sam decydować mniej więcej kiedy są wybory, co by pomogło mniejszym partiom, które mają mniej kasy. To by sprawiło, że wybory samorządowe, w teorii by się rozjechały i odbyły się niezależnie od siebie.
- Prokuratura jako nowy konstytucyjny i niezależny organ.
- Zwiększyć skład TK o 3-6 sędziów.
Przestudiowałem cały 2015 rok i uważam, że to nie może się powtórzyć. Wysokie progi zmiotły Lewice, KORWiNa i Razem z planszy wyborczej i PiS mając 38% zdobył 50+% miejsc w sejmie i było co było przez kolejne 8 lat. Obejrzałem jakiś czas temu ten film https://www.youtube.com/watch?v=oIAQcvewgTg i byłem pod wielkim wrażeniem, że udało im się zebrać podpisy na referendum i że referendum przeszło i gerrymandering w stanie Michigan się skończyło. Nie wiem jak zebrać 500,000 podpisów ale wiem, że to na pewno nie będzie łatwe. Na pewno byłoby to niezła satysfakcja zagłosować w prawdziwym referendum a nie w jakieś tubie propagandowej o miernej treści.
Zapraszam do dyskusji.
A tak bym zagłosował ja: 1. Tak; 2. Nie; 3. Tak; 4. Tak; 5. Nie; 6. Nie; 7. Tak; 8. Tak; 9. Tak; 10. Tak; 11. Nie; 12. Tak; 13. Nie; 14. Tak; 15. Nie.
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submitted by EmotionOk4357 to PackageDelivered [link] [comments]
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2024.05.29 07:08 dbnhd New Youtube Layout is broken?
 | The new youtube layout was finally rolled out to me, unfortunately but its completely broken. submitted by dbnhd to youtube [link] [comments] https://preview.redd.it/oiv4l7c2ta3d1.png?width=2506&format=png&auto=webp&s=12496540e0b7209cdeb64cfc1ca7c1ba8e5d48b2 https://preview.redd.it/hd0maez2ta3d1.png?width=2518&format=png&auto=webp&s=5ed27bb324ae689d94af92963d772d0d497787cb I don't know why this is happening? I tried checking if it was just because of Opera GX but I had the same issue on Edge. Anyone know a solution? I also tried changing from Theatre mode and normal that also didn't help. |
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2024.05.29 07:07 nainidaiphuoc DIY Pulse Oximeter - advice needed
I'm an 2nd year ECE student and I'm trying to start a project to build a pulse oximeter from scratch for educational purposes, with a timeframe of about 2 months. My goal is to create a solution similar to the MAX30100 sensor module, but using bare basic components, and I want to use an Arduino to process and read the data since I'm familiar with it.
During my research, I have found many other people making similar projects, varying in complexity of the circuit and the components used. Some don't have any signal processing or noise filtering, some use a transistor, some use op-amps. Some use phototransistors, some use photodiodes. I have heard suggestions of using perfboards over breadboards... All of this information has been very overwhelming for me, on top of learning the math behind calculating the actual SpO2 value.
I learned in school about those electronic components and how they work, but have never been asked to design anything with them. Right now I don't really know where I should start. I'm looking for advice on whether the project is feasible for me with the goals that I described above and my current skill level. I'd also like advice on what to start focusing on (either for learning more or for actually starting the project).
submitted by nainidaiphuoc to AskElectronics [link] [comments]
During my research, I have found many other people making similar projects, varying in complexity of the circuit and the components used. Some don't have any signal processing or noise filtering, some use a transistor, some use op-amps. Some use phototransistors, some use photodiodes. I have heard suggestions of using perfboards over breadboards... All of this information has been very overwhelming for me, on top of learning the math behind calculating the actual SpO2 value.
I learned in school about those electronic components and how they work, but have never been asked to design anything with them. Right now I don't really know where I should start. I'm looking for advice on whether the project is feasible for me with the goals that I described above and my current skill level. I'd also like advice on what to start focusing on (either for learning more or for actually starting the project).