#vehicle owners

[fatehbaz]

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[passengerpigeons]

becoming largely chill about most things. but i give myself permission to be mad about car infrastructure, car dependence, and cars flagrantly ignoring pedestrian right-of-way and generally endangering beings of flesh. because this is one of the few truly moral axis of this world

[r0semultiverse]

I refuse to hop in a Zoox car in my entire life if I can avoid it. I refuse to hop into any self-driving robo taxi (or robotaxi) that uses AI to keep it’s passengers “safe.” If this is actually a service they are legally allowed to provide publicly, there’s about to be a whole bunch of new laws made in hopefully very little time! Now you know me, obviously fuck the law, many laws are unjust, but sometimes we need some regulations to keep up with the shit that rich Silicon Valley tech bros “put out” while claiming it’s allegedly their own work. These rich bastards are dangerous! Now I’ll pass along the questions that my partner & I jokingly pondered. If something happens that the AI & detection systems doesn’t know how to handle, will us as the passengers be held legally responsible say if a child gets punted into the air by the self driving car & we can’t do anything to stop it? What if we’re asleep assuming the car is safe & it runs over a legally endangered animal? What if we’re on our phones & these self-driving robot cars cleave someone in half? What if it crashes into someone’s private property? Are we held responsible in any of these cases or is the big rich guy’s company? If it’s anything like Tesla, you should get your kids or pets out of the road when you see a Zoox car coming, it could allegedly cause some mortalities. Two more things. What’s stopping someone from hijacking, hacking, or planting a virus on these self-driving taxi services? What if one of them gets hijacked to take someone to a human trafficker meetup spot? Will the company be held responsible at all? The gifs below pretty much summarizes my feelings.

[fjordfolk]

they have now added 'heavy rain and thunder' to where i am going to be sleeping in my car with two dogs this weekend. awesome

[prvtocol]

@bellytochin : The ikran is sniffing about the supply crates the short blond one just brought in her flying metal machine. Daia can smell the food inside and wants it. There’s a na’vi woman nearby, smells wrong, but she’s respectful and purposely looks away from her.  However she has hands. She can get Daia something to eat. With a flap of many wings, Daia lands atop the crates, trilling at the woman in a way that anyone could understand. Even the wrong smelling ones. Get me something and I’ll leave you alone! | random wonderful asks ( always accepting ) ᠂ ⚘ ˚

The supply coordinator is prepped with datapad in one hand to survey the entirety of the crated supplies dropped off by Becca’s transport that morning — a mix of RDA rations and hopefully, the artillery needed to bolster the outer bases. With the amount of Na’vi warriors stationed here, the number of ikran scattered throughout the grounds has also increased. Most stay in a designated area, thankfully. If not, an attempt is made to ignore their presence, work around them, give them no heed or offense. It’s worked so far to keep her head.

     The same will be done with this one; her distance is managed on the outskirts of the drop until the winged beast imposes further on her space. Its proximity, flapping its wings and with confrontational cries leaving its throat, only speak danger to Brianne. She makes the only wise decision one of her nature can — she slowly backs away, careful step by careful step, chin dipped, and datapad pulled into her chest. Counting supplies can wait, and just maybe, she thinks as she turns back towards the airtight steel entrance doors of the module, she can find the ikran’s rider to get it to shoo. 

[identittie-crisis]

spent an hour on a bus when it was supposed to be 30 mins 😍😍

you’d think that with the amount of rain we get here, people would be used to driving in the rain

BUT NO

BECAUSE APPARENTLY EVERYONE LOST THE ABILITY TO DRIVE THE SECOND IT STARTED RAINING

[theautoexperts]

How to check the previous owner of any vehicle?

[lastoneout]

I still think the single funniest thing about the cybertruck is that it has all those security cameras built in that are set to activate if anyone gets too close to the vehicle...and those cameras need electricity to run, and the cybertruck is a piece of shit that has way less battery life than you'd think, so you can legit just fuck over the owner by just standing near it and doing nothing else.

Like goddamn Elongated Muskrat found a way to let us siphon gas out of a car without even touching it. Fucking incredible.

[techdriveplay]

What Is the Best Electric Car Charger for Home Use?

Choosing the right electric car charger for home use is a crucial decision for EV owners. With the growing popularity of electric vehicles (EVs), having a reliable and efficient charging solution at home is essential for convenience, cost savings, and ensuring your vehicle is always ready for the road. In this article, we’ll explore what is the best electric car charger for home use by examining…

[rightnewshindi]

हिमाचल के 8 लाख वाहन मालिकों ने नहीं भुगत रहे चालान, पुलिस ने जारी की चेतावनी; जानें पूरा मामला

हिमाचल के 8 लाख वाहन मालिकों ने नहीं भुगत रहे चालान, पुलिस ने जारी की चेतावनी; जानें पूरा मामला #News #RightNewsIndia #RightNews

Himachal News: हिमाचल प्रदेश में मोटर वाहन अधिनियम के तहत काटे जाने वाले चालान का लाखों वाहन मालिक भुगतान नहीं कर रहे हैं। यही वजह है कि लंबित चालान का आंकड़ा आठ लाख से अधिक हो गया है। यह चालान पुलिस और अदालतों में लंबित हैं। चालान का भुगतान नहीं करने पर पुलिस विभाग ने ऐसे वाहन मालिकों को सख्त हिदायत दी है। इसमें चेताया गया है कि अगर वाहन मालिकों ने जल्द चालान का भुगतान नहीं किया तो उनके खिलाफ…

[kazifatagar]

Tesla owner fuming after $26,000 pay up to get access to his car

A Tesla owner, Mario Zelaya, took to TikTok in 2022 to express frustration after being locked out of his $140,000 Tesla due to a dead battery, facing a staggering $26,000 replacement cost. Unable to justify the expense, Mario decided to sell the car, but encountered another issue—his documents were locked inside. He eventually paid $30 for replacement papers. The viral video drew millions of…

[aesthetic-lillie]

how do u get rid of a bumper sticker...

[townpostin]

Jamshedpur Trailer Owners Union Refutes Company Stand on Rate Hike, Says - Company is Guardian

Union challenges Tata Company’s statement, emphasizes company’s responsibility towards all stakeholders. Tata Company states rate hike decision is between vendor and union; union president demands broader company accountability. JAMSHEDPUR – The Jamshedpur Local Trailer Owners Union has refuted Tata Company’s recent statement regarding the rate hike being an affair between the local vendors and…

[jcmarchi]

How Bias Will Kill Your AI/ML Strategy and What to Do About It

New Post has been published on https://thedigitalinsider.com/how-bias-will-kill-your-ai-ml-strategy-and-what-to-do-about-it/

How Bias Will Kill Your AI/ML Strategy and What to Do About It

‘Bias’ in models of any type describes a situation in which the model responds inaccurately to prompts or input data because it hasn’t been trained with enough high-quality, diverse data to provide an accurate response. One example would be Apple’s facial recognition phone unlock feature, which failed at a significantly higher rate for people with darker skin complexions as opposed to lighter tones. The model hadn’t been trained on enough images of darker-skinned people. This was a relatively low-risk example of bias but is exactly why the EU AI Act has put forth requirements to prove model efficacy (and controls) before going to market. Models with outputs that impact business, financial, health, or personal situations must be trusted, or they won’t be used.

Tackling Bias with Data

Large Volumes of High-Quality Data

Among many important data management practices, a key component to overcoming and minimizing bias in AI/ML models is to acquire large volumes of high-quality, diverse data. This requires collaboration with multiple organizations that have such data. Traditionally, data acquisition and collaborations are challenged by privacy and/or IP protection concerns–sensitive data can’t be sent to the model owner, and the model owner can’t risk leaking their IP to a data owner. A common workaround is to work with mock or synthetic data, which can be useful but also have limitations compared to using real, full-context data. This is where privacy-enhancing technologies (PETs) provide much-needed answers.

Synthetic Data: Close, but not Quite

Synthetic data is artificially generated to mimic real data. This is hard to do but becoming slightly easier with AI tools. Good quality synthetic data should have the same feature distances as real data, or it won’t be useful. Quality synthetic data can be used to effectively boost the diversity of training data by filling in gaps for smaller, marginalized populations, or for populations that the AI provider simply doesn’t have enough data. Synthetic data can also be used to address edge cases that might be difficult to find in adequate volumes in the real world. Additionally, organizations can generate a synthetic data set to satisfy data residency and privacy requirements that block access to the real data. This sounds great; however, synthetic data is just a piece of the puzzle, not the solution.

One of the obvious limitations of synthetic data is the disconnect from the real world. For example, autonomous vehicles trained solely on synthetic data will struggle with real, unforeseen road conditions. Additionally, synthetic data inherits bias from the real-world data used to generate it–pretty much defeating the purpose of our discussion. In conclusion, synthetic data is a useful option for fine tuning and addressing edge cases, but significant improvements in model efficacy and minimization of bias still rely upon accessing real world data.

A Better Way: Real Data via PETs-enabled Workflows

PETs protect data while in use. When it comes to AI/ML models, they can also protect the IP of the model being run–”two birds, one stone.” Solutions utilizing PETs provide the option to train models on real, sensitive datasets that weren’t previously accessible due to data privacy and security concerns. This unlocking of dataflows to real data is the best option to reduce bias. But how would it actually work?

For now, the leading options start with a confidential computing environment. Then, an integration with a PETs-based software solution that makes it ready to use out of the box while addressing the data governance and security requirements that aren’t included in a standard trusted execution environment (TEE). With this solution, the models and data are all encrypted before being sent to a secured computing environment. The environment can be hosted anywhere, which is important when addressing certain data localization requirements. This means that both the model IP and the security of input data are maintained during computation–not even the provider of the trusted execution environment has access to the models or data inside of it. The encrypted results are then sent back for review and logs are available for review.

This flow unlocks the best quality data no matter where it is or who has it, creating a path to bias minimization and high-efficacy models we can trust. This flow is also what the EU AI Act was describing in their requirements for an AI regulatory sandbox.

Facilitating Ethical and Legal Compliance

Acquiring good quality, real data is tough. Data privacy and localization requirements immediately limit the datasets that organizations can access. For innovation and growth to occur, data must flow to those who can extract the value from it.

Art 54 of the EU AI Act provides requirements for “high-risk” model types in terms of what must be proven before they can be taken to market. In short, teams will need to use real world data inside of an AI Regulatory Sandbox to show sufficient model efficacy and compliance with all the controls detailed in Title III Chapter 2. The controls include monitoring, transparency, explainability, data security, data protection, data minimization, and model protection–think DevSecOps + Data Ops.

The first challenge will be to find a real-world data set to use–as this is inherently sensitive data for such model types. Without technical guarantees, many organizations may hesitate to trust the model provider with their data or won’t be allowed to do so. In addition, the way the act defines an “AI Regulatory Sandbox” is a challenge in and of itself. Some of the requirements include a guarantee that the data is removed from the system after the model has been run as well as the governance controls, enforcement, and reporting to prove it.

Many organizations have tried using out-of-the-box data clean rooms (DCRs) and trusted execution environments (TEEs). But, on their own, these technologies require significant expertise and work to operationalize and meet data and AI regulatory requirements. DCRs are simpler to use, but not yet useful for more robust AI/ML needs. TEEs are secured servers and still need an integrated collaboration platform to be useful, quickly. This, however, identifies an opportunity for privacy enhancing technology platforms to integrate with TEEs to remove that work, trivializing the setup and use of an AI regulatory sandbox, and therefore, acquisition and use of sensitive data.

By enabling the use of more diverse and comprehensive datasets in a privacy-preserving manner, these technologies help ensure that AI and ML practices comply with ethical standards and legal requirements related to data privacy (e.g., GDPR and EU AI Act in Europe). In summary, while requirements are often met with audible grunts and sighs, these requirements are simply guiding us to building better models that we can trust and rely upon for important data-driven decision making while protecting the privacy of the data subjects used for model development and customization.

[noohyah]

Mercedes-Benz GLE-Class Fuel Tank Recall: What You Need to Know!

If you own a Mercedes-Benz GLE-Class, you might want to pay attention to this important safety recall.  The fuel tank on some of these vehicles may not have been welded properly during manufacturing, which could result in a fuel leak and increase the risk of a fire.  This recall affects more than 105,000 vehicles in the US and is part of a larger recall of 2.3 million vehicles from various…

[taxi-davis]

General Motors EV1 electric car commercial