Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

The real bottleneck in AI’s next leap isn’t compute, it’s the human data it can actually learn from. Our co-founder Manish | HumynLabs; KGeN addresses our community on why KGeN has the moat to solve it. Sneak peek below 👀

KGeN_IO's profile picture

KGeN Foundation 🟩

216,274 subscribers

68,990 görüntüleme • 24 gün önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

What does it take to build AI that understands the real world? At VeriFi Korea: Humans x Robots, our cofounder, Manish | HumynLabs; KGeN breaks down what we’re building, how the Brazil community is earning rewards by contributing AI data, and how the Korean community can get involved. Your contributions can help train the next generation of AI.
0:50

What does it take to build AI that understands the real world? At VeriFi Korea: Humans x Robots, our cofounder, Manish | HumynLabs; KGeN breaks down what we’re building, how the Brazil community is earning rewards by contributing AI data, and how the Korean community can get involved. Your contributions can help train the next generation of AI.

KGeN Foundation 🟩

57,740 görüntüleme • 12 gün önce

Everyone is racing to build smarter robots. But here’s the question: Can a robot truly understand the physical world by only seeing it? Humans don’t learn with vision alone. We learn through sound, sight, motion, and touch… all working together to make sense of our environment. That’s what makes Humyn Labs so interesting. They’re building the Multi-Sensory Platform for Physical AI, creating one fused training signal instead of isolated datasets. And through KGeN Community’s verified global network, that data comes from real people performing real tasks in real environments. In this video, I explain why I think this approach could be one of the missing pieces for Physical AI’s next leap… and why I used the Infinity Gauntlet as the perfect analogy. 👇🎥 Watch, share your thoughts, and let me know if the comparison makes sense. Humyn Labs KGeN Community KGeN Foundation 🟩 #HumynLabs #KGeN #PhysicalAI #AI
1:17

Everyone is racing to build smarter robots. But here’s the question: Can a robot truly understand the physical world by only seeing it? Humans don’t learn with vision alone. We learn through sound, sight, motion, and touch… all working together to make sense of our environment. That’s what makes Humyn Labs so interesting. They’re building the Multi-Sensory Platform for Physical AI, creating one fused training signal instead of isolated datasets. And through KGeN Community’s verified global network, that data comes from real people performing real tasks in real environments. In this video, I explain why I think this approach could be one of the missing pieces for Physical AI’s next leap… and why I used the Infinity Gauntlet as the perfect analogy. 👇🎥 Watch, share your thoughts, and let me know if the comparison makes sense. Humyn Labs KGeN Community KGeN Foundation 🟩 #HumynLabs #KGeN #PhysicalAI #AI

Bahdfella™ ❤️‍🔥

28,381 görüntüleme • 1 ay önce

I'm not staking $KGEN because someone told me to. I'm staking because I actually understand what they're building. So I made a video explaining it the way I wish someone explained it to me 🎬👇 🟩 00:00–0:17 Intro 🟩 00:18–0:34 Who I am + why listen? 🟩 00:35–0:56 What is KGeN? 🟩 00:55–1:27 Why I believe in $KGEN? 🟩 01:28–2:18 Why the $KGEN token can get stronger ? (KGeN 2.0) 🟩 02:19–2:44 Why I think about the next cycle? 🟩 02:45–3:58 How to stake $KGEN ? (step-by-step tutorial) 🟩 03:59–4:28 My own vault + my target... 🟩 04:29–4:48) Close KGeN Community || #KGeN
4:48

I'm not staking $KGEN because someone told me to. I'm staking because I actually understand what they're building. So I made a video explaining it the way I wish someone explained it to me 🎬👇 🟩 00:00–0:17 Intro 🟩 00:18–0:34 Who I am + why listen? 🟩 00:35–0:56 What is KGeN? 🟩 00:55–1:27 Why I believe in $KGEN? 🟩 01:28–2:18 Why the $KGEN token can get stronger ? (KGeN 2.0) 🟩 02:19–2:44 Why I think about the next cycle? 🟩 02:45–3:58 How to stake $KGEN ? (step-by-step tutorial) 🟩 03:59–4:28 My own vault + my target... 🟩 04:29–4:48) Close KGeN Community || #KGeN

Meow

12,148 görüntüleme • 2 ay önce

AI is only as good as its data. Everyone talks about building smarter AI models, but fewer people ask where the training data comes from. That’s what makes Humyn Labs interesting. They’re focused on collecting high-quality, real-world human data across different environments, behaviors, and sensory inputs. Because if AI is going to understand the physical world, it first needs to learn from the people who already live and work in it. I shared my thoughts in this short video. Let me know what stood out to you. 👇🎥 Humyn Labs KGeN Community #KGeN
1:20

AI is only as good as its data. Everyone talks about building smarter AI models, but fewer people ask where the training data comes from. That’s what makes Humyn Labs interesting. They’re focused on collecting high-quality, real-world human data across different environments, behaviors, and sensory inputs. Because if AI is going to understand the physical world, it first needs to learn from the people who already live and work in it. I shared my thoughts in this short video. Let me know what stood out to you. 👇🎥 Humyn Labs KGeN Community #KGeN

Bahdfella™ ❤️‍🔥

18,156 görüntüleme • 1 ay önce

For all the rKGEN holders, Holders will be able to swap their rKGEN to $KGEN (on Aptos chain) from 15:01 PM UTC Here’s how to swap rKGEN → $KGEN 👇 1️⃣ Connect/log in to your KGeN Wallet 2️⃣ Select the eligible rKGEN you want to swap 3️⃣ Confirm the swap — your rKGEN instantly converts to $KGEN on Aptos (the swap will be done on the KGeN wallet) Have rKGEN on your Petra wallet? Connect your Petra wallet to the KGeN wallet and follow the above steps PS: To support long-term community benefits, a 50% swap limit is set on the conversion of rKGEN to $KGEN at launch. This measure is designed to promote sustained project health and stability. rKGEN was your ticket. $KGEN is your entry. Claim it. 🔓
0:21

For all the rKGEN holders, Holders will be able to swap their rKGEN to $KGEN (on Aptos chain) from 15:01 PM UTC Here’s how to swap rKGEN → $KGEN 👇 1️⃣ Connect/log in to your KGeN Wallet 2️⃣ Select the eligible rKGEN you want to swap 3️⃣ Confirm the swap — your rKGEN instantly converts to $KGEN on Aptos (the swap will be done on the KGeN wallet) Have rKGEN on your Petra wallet? Connect your Petra wallet to the KGeN wallet and follow the above steps PS: To support long-term community benefits, a 50% swap limit is set on the conversion of rKGEN to $KGEN at launch. This measure is designed to promote sustained project health and stability. rKGEN was your ticket. $KGEN is your entry. Claim it. 🔓

KGeN 🟩

36,745 görüntüleme • 11 ay önce

Why did the Co-Founder of Tether invest in Planck? 🤔 Brock Pierce — Co-Founder of Tether (USDT), Blockchain Capital & EOS — has joined our journey🚀 🎥 Hear it from him: why he believes in $PLANCK and the future of decentralized AI compute! ✨The vision is real. The time is now. #PlanckNetwork #DePIN #AI #Web3
0:50

Why did the Co-Founder of Tether invest in Planck? 🤔 Brock Pierce — Co-Founder of Tether (USDT), Blockchain Capital & EOS — has joined our journey🚀 🎥 Hear it from him: why he believes in $PLANCK and the future of decentralized AI compute! ✨The vision is real. The time is now. #PlanckNetwork #DePIN #AI #Web3

Planck

413,589 görüntüleme • 1 yıl önce

With idOS, you choose who has access to your data. Learn more about how Access Grants work from our Co-Founder web the third!
1:24

With idOS, you choose who has access to your data. Learn more about how Access Grants work from our Co-Founder web the third!

idOS

173,292 görüntüleme • 11 ay önce

Robots are the bottleneck in scaling robotics, and learning from human video promises to solve it. But how can chaotic human data ever measure up to sanitized, lab-made teleoperation data? Introducing Do as I Do: establishing a much needed correspondence between human videos and dexterous robot data. Some fun insights below: 🧵
0:55

Robots are the bottleneck in scaling robotics, and learning from human video promises to solve it. But how can chaotic human data ever measure up to sanitized, lab-made teleoperation data? Introducing Do as I Do: establishing a much needed correspondence between human videos and dexterous robot data. Some fun insights below: 🧵

Mahi Shafiullah 🏠🤖

95,568 görüntüleme • 2 ay önce

What we’re seeing: frontier robotics teams are rebuilding data pipelines from scratch because generic licensed datasets aren’t moving their models forward. The next wave won’t be about more data. It’ll be about precise, domain-specific data that actually improves performance. The bottleneck isn’t compute. It’s the right data. 🎥 Our CCO Arthur at Wrapped’s Multichain Day (ETHDenver 🏔🦬🦄)
0:43

What we’re seeing: frontier robotics teams are rebuilding data pipelines from scratch because generic licensed datasets aren’t moving their models forward. The next wave won’t be about more data. It’ll be about precise, domain-specific data that actually improves performance. The bottleneck isn’t compute. It’s the right data. 🎥 Our CCO Arthur at Wrapped’s Multichain Day (ETHDenver 🏔🦬🦄)

Perle Labs

30,597 görüntüleme • 6 ay önce

EP:19 ft Ishank Gupta the co-founder of KGeN Foundation 🟩! Discussing: The benefits of travelling, how to navigate the stress of web3, solving distribution and much more! Timestamps: 2:00 What was life like before web3? 7:25 What lessons did you learn from travelling so much? 11:30 How has travelling impacted your perspective for business 14:45 Biggest lessons from working with some of the largest brands in the world. 20:00 What do you look like when hiring? 26:45 How do you navigate such a volatile market on a personal level? 32:55 Story of how KGEN started 40:00 How important is it when selecting which investors to work with. 43:30 What are the missing pieces to solving distribution for web3 gaming? 47:00 How do you re-engage users? 50:00 How does KGEN Chiefs work? 53:00 Aligning incentives in the KGEN ecosystem 56:00 What are the goals for KGEN over the next 3-6 months? 1:00:00 What is one perspective you have found most valuable to yourself?
1:02:30

EP:19 ft Ishank Gupta the co-founder of KGeN Foundation 🟩! Discussing: The benefits of travelling, how to navigate the stress of web3, solving distribution and much more! Timestamps: 2:00 What was life like before web3? 7:25 What lessons did you learn from travelling so much? 11:30 How has travelling impacted your perspective for business 14:45 Biggest lessons from working with some of the largest brands in the world. 20:00 What do you look like when hiring? 26:45 How do you navigate such a volatile market on a personal level? 32:55 Story of how KGEN started 40:00 How important is it when selecting which investors to work with. 43:30 What are the missing pieces to solving distribution for web3 gaming? 47:00 How do you re-engage users? 50:00 How does KGEN Chiefs work? 53:00 Aligning incentives in the KGEN ecosystem 56:00 What are the goals for KGEN over the next 3-6 months? 1:00:00 What is one perspective you have found most valuable to yourself?

Caleb

172,504 görüntüleme • 1 yıl önce

The bottleneck in LLM inference isn't compute. It's how fast you can move the weights. Our CTO Mathias Lechner, Mathias Lechner, joins Piotr Mazurek, Piotr Mazurek (in SF 🌉), from our inference team, to discuss what actually limits token throughput and how we're optimizing for it.
4:47

The bottleneck in LLM inference isn't compute. It's how fast you can move the weights. Our CTO Mathias Lechner, Mathias Lechner, joins Piotr Mazurek, Piotr Mazurek (in SF 🌉), from our inference team, to discuss what actually limits token throughput and how we're optimizing for it.

Liquid AI

21,393 görüntüleme • 3 ay önce

AI needs verified human data. Here’s why that actually matters, and why I’m one of the people contributing it. As you watch this video, you might wonder 'okay, but why are YOU doing this?' so let me be honest with you in this thread. 🧵👇 KGeN Foundation 🟩
1:35

AI needs verified human data. Here’s why that actually matters, and why I’m one of the people contributing it. As you watch this video, you might wonder 'okay, but why are YOU doing this?' so let me be honest with you in this thread. 🧵👇 KGeN Foundation 🟩

M. Younis

36,122 görüntüleme • 27 gün önce

Our social data doesn't just reflect culture, it defines it. On the recent space, V talked about why this data is so valuable, and how creators can finally reclaim it from Instagram. 🎧 Listen to the full space below
0:52

Our social data doesn't just reflect culture, it defines it. On the recent space, V talked about why this data is so valuable, and how creators can finally reclaim it from Instagram. 🎧 Listen to the full space below

vana

28,618 görüntüleme • 10 ay önce

The best conversations at GTC didn't happen in the sessions. They happened after. That's why we threw the party. We hosted Open Hands on March 17 in San Jose, a casino night that brought together 100+ researchers, founders and operators. Teams from Adobe, NVIDIA, Intel, TELUS Digital, Aptos, tuesday and 60+ others. Researchers from UC Berkeley, Carnegie Mellon University and institutions across the US and Asia. All in one room, across tables, over drinks. Three things we're taking back from San Jose: > The data bottleneck for physical AI is real and underestimated. Getting a robot to pick up an object, navigate a room, respond to a human. Each of those tasks needs millions of hours of egocentric video across real environments with real variability. Something we've been building towards and GTC validated it. > The Global South, India in particular, is emerging as a critical source of the linguistic and environmental diversity that production-grade models need. Low-resource languages, diverse acoustic conditions, real-world dialects. The data infrastructure for this doesn't exist at scale yet. We're building it. > Human intelligence remains the key variable that separates models that benchmark well from models that hold up in deployment. Judgment, nuance, and context aren't features you can generate. They have to be sourced, verified and embedded from the start. Grateful to albert chun (Founder, AI Circle) for co-hosting a night that proved the point. The best signal at NVIDIA GTC wasn't on a slide. It was in this room. Ishank Gupta Manish | HumynLabs; KGeN Arunabh Rohatgi Anoushka
1:43

The best conversations at GTC didn't happen in the sessions. They happened after. That's why we threw the party. We hosted Open Hands on March 17 in San Jose, a casino night that brought together 100+ researchers, founders and operators. Teams from Adobe, NVIDIA, Intel, TELUS Digital, Aptos, tuesday and 60+ others. Researchers from UC Berkeley, Carnegie Mellon University and institutions across the US and Asia. All in one room, across tables, over drinks. Three things we're taking back from San Jose: > The data bottleneck for physical AI is real and underestimated. Getting a robot to pick up an object, navigate a room, respond to a human. Each of those tasks needs millions of hours of egocentric video across real environments with real variability. Something we've been building towards and GTC validated it. > The Global South, India in particular, is emerging as a critical source of the linguistic and environmental diversity that production-grade models need. Low-resource languages, diverse acoustic conditions, real-world dialects. The data infrastructure for this doesn't exist at scale yet. We're building it. > Human intelligence remains the key variable that separates models that benchmark well from models that hold up in deployment. Judgment, nuance, and context aren't features you can generate. They have to be sourced, verified and embedded from the start. Grateful to albert chun (Founder, AI Circle) for co-hosting a night that proved the point. The best signal at NVIDIA GTC wasn't on a slide. It was in this room. Ishank Gupta Manish | HumynLabs; KGeN Arunabh Rohatgi Anoushka

Humyn Labs

10,727 görüntüleme • 5 ay önce

Every app shipped on Canopy adds to the open-source knowledge base powering AI agents. The smarter our agents get, the more builders show up, and the faster the next wave of apps gets built. That flywheel is our real moat. Our founder Adam Liposky breaks down why.
1:01

Every app shipped on Canopy adds to the open-source knowledge base powering AI agents. The smarter our agents get, the more builders show up, and the faster the next wave of apps gets built. That flywheel is our real moat. Our founder Adam Liposky breaks down why.

Canopy

19,376 görüntüleme • 12 gün önce

In case you missed it on our livestream, here’s a sneak peek of what’s coming during The Division 10th Anniversary event 👀
3:36

In case you missed it on our livestream, here’s a sneak peek of what’s coming during The Division 10th Anniversary event 👀

Tom Clancy's The Division

151,920 görüntüleme • 7 ay önce

Hear from our founder, Reeve Collins (co-founder of ), on why STBL is different. Stablecoin 2.0 isn’t just another upgrade, it’s the start of a new era for digital money! P.S. $STBL launching soon on Binance Alpha :)
2:38

Hear from our founder, Reeve Collins (co-founder of ), on why STBL is different. Stablecoin 2.0 isn’t just another upgrade, it’s the start of a new era for digital money! P.S. $STBL launching soon on Binance Alpha :)

STBL

300,578 görüntüleme • 1 yıl önce

It's easy for robots to nail a demo. It's much harder to get them to work reliably in the real world. The bottleneck is data. At Axis Robotics we're building a compounding data engine that combines simulation, ego-centric data and DAgger correction data at scale. Watch our CEO ChrisF(✱,✱) break down the data bottleneck, why messy data can still train good models, and what it takes to get robots out of the lab with blocmates. ⬇️
29:39

It's easy for robots to nail a demo. It's much harder to get them to work reliably in the real world. The bottleneck is data. At Axis Robotics we're building a compounding data engine that combines simulation, ego-centric data and DAgger correction data at scale. Watch our CEO ChrisF(✱,✱) break down the data bottleneck, why messy data can still train good models, and what it takes to get robots out of the lab with blocmates. ⬇️

Axis Robotics

22,634 görüntüleme • 1 ay önce