Jacob Moder @Jacobmoder

Tech guru😌😎🔥 Joined December 2024

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Maren @DefiLi_mo

10 months ago

Motivation gets you going 😤 Discipline keeps you going 💯

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.. @_cityvibes_

10 months ago

Can't wait to see him play again 🤩

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.. @_cityvibes_

10 months ago

The goals you asode🫵

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.. @_cityvibes_

10 months ago

Haaland is carrying his nation to the world cup meanwhile my man here is taking photos for vogue😂😭 There's levels to this

🥤𝐁𝐚𝐧𝐤𝐬 @_Afcbanks

10 months ago

My Striker ❤️

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Manchester City @ManCity

10 months ago

Magic @rayan_cherki 😮‍💨✨

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MEXC @MEXC

10 months ago

🌶The CHZ Frenzy is ON! @Chiliz - Zero Fee $CHZ Trades - Up to 400% APR for Staking - Spin to Win Big - New User Pool: 1.6M CHZ & $250K Time to get in the game!

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Maren @DefiLi_mo

11 months ago

This finally makes my crypto feel like spendable money. 😂

Nakins¦ content writer @tgnakins

11 months ago

Shop Anything With Your Crypto: Introducing SP3ND The Future of Shopping Is Here Spend USDC, Not Fiat Crypto has made it easier than ever to earn, save, and invest money online but let’s be honest: spending crypto in the real world is still frustrating. Most online stores still

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Kiojame @Kiojame_

11 months ago

Below is a video of an Autonomous Vehicle (AV) at an intersection, getting bullied by other drivers. The AV is at an intersection and has the right of way. But then, an oncoming car decides to push its luck, inching forward aggressively. The AV in the video hesitates, yields, and almost gets bullied out of its turn. If this were a well-trained AV, it might have handled it differently. Instead of backing down, it could have maintained its position, asserting its right of way while still ensuring safety. After all, the goal is to be predictable and safe, not a pushover. It might have slowed down just enough to signal its intent but not so much that it loses its place in traffic. Training an AV for such scenarios is no small feat. It is about exposing it to a ton of real-world, edge-case situations. That’s where the .@NATIXNetwork and its VX360 are game changers. With $NATIX, an AV could be trained with countless hours of footage from chaotic city streets, where cars cut you off, pedestrians dart out, and cyclists weave through traffic. This kind of data helps the AV learn not just the rules of the road but also the nuances of human behavior. Even with all that training, there’s a fine line between being assertive and being aggressive, and an AV needs to be programmed to handle these situations without escalating them. And let’s not forget, the training doesn’t stop at reacting to other vehicles. It also involves learning from past interactions. If an AV encounters a similar situation multiple times, it should adapt its strategy. Maybe after a few run-ins with bullish drivers, it learns to be a bit more assertive at specific intersections. This adaptive learning is key, and $NATIX can push the boundaries of what an AV can handle. A properly trained AV would have navigated this scenario with a bit more confidence, and with NATIX, that’s very possible.