npccrypto

A new mindset. Words, now with purpose. #NPClogs

My view on @axisrobotics remains the same the interface is just the surface layer. The deeper value lies in the infrastructure stack, and Domain Randomization is a powerful example of that. Physical AI won't improve simply by collecting trajectories, but by transforming simulation learning into policies that can withstand real-world variations. Going from 0% to 90% deployment success isn't just a better outcome, it's also proof that the pipeline is doing its job.

Just got my Vibestarter Starter Card! Check it out 👇 testnet.vibestarter.xyz/card/starter/0…

@0xRahvanaa @axisrobotics ga di tele ga di dc ga di X klo ketemu penggarap AXIS isinya keluh kesah mulu 🥱

Wujud asli "bangun siang, rejeki dipatok member lain" Keluh kesah penggarap @axisrobotics yang bangun kesiangan 😭 Emang kudu mantengin notif 24 jam njir wowkwowkw Btw kalo mau akses notif task bisa langsung join di grub axis yakk Linknya kutaroh komen.

The sudden appearance of @axisrobotics tasks this morning completely caught me by surprise. I had just woken up, turned on my laptop, quickly logged in, and started browsing through them while my brain was still barely awake. Experiences like this demonstrate that at Axis, timing and preparedness are crucial, especially when tasks can pop up unexpectedly. By the way, I'm in the GMT+7 time zone.

@chrysnthmm_xyz @apyx_fi This is what true accountability in DeFi looks like full identities are revealed, backgrounds are verifiable, and the team is truly present.

Being part of @apyx_fi community has taught me a lot of things but one of the biggest is how different this team from everything else I've seen in the space, every Founding Contributor is fully doxxed with a background you can look up on apyx.fi with also their LinkedIn you can check, but let me introduce them briefly Let's meet the team behind @apyx_fi: Joseph Onorati (@0xinliberty) - spent 8 years at @krakenfx in multiple leadership roles including CSO scaling it from 23 people to thousands, founded and sold CaVirtEx Canada's first Bitcoin exchange which was later acquired by Kraken, now CEO of @defidevcorp (Nasdaq: DFDV) Parker White, CFA (@TheOtherParker_) - spent 6 years at Kraken including Director of Engineering, managed ~$2B in assets at a regulated investment advisor, launched an algorithmic trading startup in 2018, active in DeFi since 2021, now COO & CIO at DFDV John Han, CFA (@JohnHan618) - started at Goldman Sachs equity research, investor at Nezu Asia Capital and Driehaus Capital, Head of Strategic Finance at Kraken, VP of Finance at Binance covering EMEA, LATAM, and Canada, CFO at a unicorn L1, now CFO at DFDV Dan Kang (@CryptoIRGuy) - 7 years as a buy-side analyst, analyst at Morgan Stanley, Snap Corporate Development, 3 years as Head of Strategy at Kraken, now CSO at DFDV Pete Humiston (@pete_humiston) - started in Sales and Trading at Jefferies, full-time in crypto since 2018 across research content and marketing, now CMO at DFDV Dawson Reid (@00_dawson_00) - 15+ years in software engineering, 9 of those was at Kraken across the full stack, full-time in crypto since 2016 and involved since 2013 Teams like this are genuinely rare and I mean that in the most literal sense, people with track records this deep, this verifiable, building together on a single protocol is something you almost never see in this space, and what makes it even more striking is that they're not distant about it either, even Joseph who is literally the CEO of a public company still finds time to just hang around in Discord, talk to people, answer questions and I guess that's not something you see often, and it's the kind of thing that makes me want to stick around and stuck with them! At the end of the day you can't just jump into a protocol and simply think how the mechanism works, you should also place trust with your capital to people who have actually been through the best and worst this industry has to offer, not to people who came out of nowhere with almost no real experience 😶

@rendiwilliam032 sepintar pintar cara farming ttep emosi klo ktemu cetakan es batu

Farming di Axis Robotics Tutorial lengkap cara mengumpulkan poin/score setiap hari di Axis Robotics Step by step + tips penting supaya farming lebih efektif. Tonton sampai habis ! Link farming : hub.axisrobotics.ai/login?invite_c…

@chrysnthmm_xyz @axisrobotics pelan pelan latihannya bang

@0xnpccrypto @axisrobotics jujur emang agak susah kontrolnya, dan kayanya bener harus banyak banyak latihan pake task itu 😅

Disclaimer: This content is written in Indonesian to make it easier to understand, especially for those who are just starting to farm on Axis ⚠️ Farming di @axisrobotics itu bukan cuma soal nunggu task muncul, tapi soal efisiensi. Ada 4 hal yang harus kalian kejar: - cepat tahu kapan task muncul - cepat masuk buat ngerjain task - cepat adaptasi sama task-nya - cepat selesaiin task "Kalau salah satu telat, peluang kalian buat kebagian task atau unggul dari user lain juga ikut turun"

Pas task udah live, fokusnya jangan asal ngebut, tapi eksekusi yang efisien. Pastikan kalian udah paham kontrol dasar, jangan kebanyakan trial error, dan usahakan tetap tenang saat ngerjain task End off tweet ⚠️

Kalau kalian masih belum familiar sama kontrol robot, sekarang @axisrobotics sudah menyediakan 3 training task yang bisa dipakai buat latihan, yaitu: - Straight Row Arrangement - Hang the Hange - Water Flower Training task ini bisa kalian pakai buat membiasakan diri dengan control panel dan melatih gerakan sebelum masuk task utama. Karena sifatnya buat latihan, task ini bisa dikerjakan berulang kali dan tidak menghasilkan reward, jadi manfaatin buat adaptasi dan cari feel kontrolnya dulu.

This is a really helpful update from @axisrobotics . Adding more training tasks like Hang the Hanger and Straight Row Arrangement gives users more room to get comfortable with the control panel, improve precision, and build confidence before jumping into regular tasks. Even if these practice tasks don’t offer future rewards, they still add real value by helping users reduce mistakes and perform more efficiently when live tasks are available.

Great exposure for @axisrobotics through Base Discovery. More people can now test the product firsthand, understand the core idea behind the platform, and see how Axis is positioning itself in robotics intelligence. The prize pool perspective through @baseapp is a great added incentive for people to actually try it out instead of just reading about it.

Following my previous @PrismaXai visualization, this post focuses on one key part of that cycle: high-quality, real-world data that helps robots learn faster and perform better.

@alanaanastasya @axisrobotics Yooo join kan, task smudah mainin game simulator

salah satu project Robotics di base yang aku garap @axisrobotics bisa cek di bio X nya ada link atau biar cepet hub.axisrobotics.ai/login?invite_c… jangan ngeluh gada garapan, ini ada dan gampang join community nya biar ga sesat kayak aku 😭

@khois0512 @axisrobotics im missed, now task launch in random time

Today I received 5 tasks earlier than usual, and I've completed today's training. I've collected 6/6 badges. How many do you have? @axisrobotics

@axisrobotics is one of the most exciting projects I've come across in the field of physical AI, combining simulation, Web3 incentives, and global human participation to help build Robotic General Intelligence. @Airdropfinds also recently highlighted this project in its own coverage, so it's worth checking out if you want a broader overview than just a random link. Read more here 👇 airdropfinder.com/en/blogs/axis-…

Another educational visual from my @PrismaXai series. Human operators help robots complete real world tasks, and those interactions provide valuable data for future AI improvements.

In my opinion, @axisrobotics product is just the surface layer. What really matters is the underlying infrastructure: a simulation based stack that turns lightweight web interactions into verified, reusable robotics data at scale. This is crucial because physical AI is still hampered by data scarcity, weak generalization, and expensive real world data collection. A few reasons why this stands out to me: - It solves the data layer problem, not just the interface layer. - A simulation-based approach makes data collection cheaper, faster, and easier to repeat. - Reusable data is important because robotics still suffers from weak data transfer and fragmented hardware. - The longterm value isn't just user activity, but transforming that activity into infrastructure for broader model training.

@chris_anm01 the real journey is right before our eyes together AXIS