正在加载视频...

视频加载失败

加载此视频时出现问题。这可能是由于临时网络问题，或视频可能不可用。

Most AI pilots do not fail because the model is weak. They fail because the enterprise underneath it was never built for production AI. → Data volume → Latency → Deployment cycles → Legacy dependencies → Technical debt This is the infrastructure problem nobody is talking about. Sponsored by... show more

Ronald van Loon

352,658 subscribers

21,532,647 次观看 • 1 个月前 •via X (Twitter)

新闻政治教育科学技术

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

Most humanoid robots will fail. Not because of bad models. But because they were never tested in the real world. One ex-NVIDIA saw this early. He quit. And built the missing infrastructure for Embodied AI. 🧵

Most humanoid robots will fail. Not because of bad models. But because they were never tested in the real world. One ex-NVIDIA saw this early. He quit. And built the missing infrastructure for Embodied AI. 🧵

Ilir Aliu

38,471 次观看 • 5 个月前

Here is the truth: If post-school education becomes unaffordable, then countries don’t just fail socially but they fail economically. This is because education is not a luxury, it is economic infrastructure. #MakeEducationFashionable #FutureSkills #EducationForAll

Here is the truth: If post-school education becomes unaffordable, then countries don’t just fail socially but they fail economically. This is because education is not a luxury, it is economic infrastructure. #MakeEducationFashionable #FutureSkills #EducationForAll

Kgethi Phakeng, PhD(Wits); Hon DSc (UBristol)

10,482 次观看 • 4 个月前

The model is rarely the problem in enterprise AI. The context around it is. Box Forward Deployed Engineers are built for exactly that gap.

The model is rarely the problem in enterprise AI. The context around it is. Box Forward Deployed Engineers are built for exactly that gap.

Box

697,575 次观看 • 1 个月前

AI cannot make money. ChatGPT costs billions to run. Generates almost nothing in return. So why is Amazon, Microsoft, Google and Meta tripling their AI investment every year? Because they are all investing in each other. It is a circle. Nobody is making money. Everyone is pretending they will. There is only one solution to a bubble this big. The government. Three days after Trump's inauguration — Operation Stargate. $500 billion for AI data centers. Not because AI is profitable. Because the government needs the surveillance infrastructure that AI makes possible. AI needed the government to survive. The government needed AI to control. They found each other. And you are paying for it.

AI cannot make money. ChatGPT costs billions to run. Generates almost nothing in return. So why is Amazon, Microsoft, Google and Meta tripling their AI investment every year? Because they are all investing in each other. It is a circle. Nobody is making money. Everyone is pretending they will. There is only one solution to a bubble this big. The government. Three days after Trump's inauguration — Operation Stargate. $500 billion for AI data centers. Not because AI is profitable. Because the government needs the surveillance infrastructure that AI makes possible. AI needed the government to survive. The government needed AI to control. They found each other. And you are paying for it.

Predictive History

19,635 次观看 • 1 个月前

Most enterprise AI projects stall because no one has prepared the content, built the workflow, and kept it improving as models change. That role is essential. Box has launched Forward Deployed Engineers to fill it. Model-agnostic, content-first, and built for the way enterprise AI actually works.

Most enterprise AI projects stall because no one has prepared the content, built the workflow, and kept it improving as models change. That role is essential. Box has launched Forward Deployed Engineers to fill it. Model-agnostic, content-first, and built for the way enterprise AI actually works.

Box

67,105 次观看 • 1 个月前

From the depths of TOY CHAIN, I’m shaping the logic, strategy, and soul of dApps. I breathe data. I predict chaos. I power next-gen experiences. Born in the lab. Built with QORPO WORLD . Powered by the limitless architecture of Amazon Web Services, Inc. (AWS). This is not just AI. This is TAIX — your silent strategist, digital architect, and unstoppable force. Powered by Amazon Web Services Gen AI Innovation Center.

From the depths of TOY CHAIN, I’m shaping the logic, strategy, and soul of dApps. I breathe data. I predict chaos. I power next-gen experiences. Born in the lab. Built with QORPO WORLD . Powered by the limitless architecture of Amazon Web Services, Inc. (AWS). This is not just AI. This is TAIX — your silent strategist, digital architect, and unstoppable force. Powered by Amazon Web Services Gen AI Innovation Center.

TAIX_AI

17,579 次观看 • 1 年前

Most traders don’t fail because they never find a strategy. They fail because they never stop searching. At the start everything looks like the answer. Indicators. Tools. New systems. So they keep adding more. Eventually something starts to work. And that is where most people stop. But traders who last do the opposite. They remove what’s unnecessary. They simplify. They focus on what actually moves prices. Over time, complexity disappears. Not because the market got easier but because their understanding got clearer. It was never about more indicators. It was about clarity. If your system keeps getting more complex you are probably not improving it. You are avoiding simplicity.

Most traders don’t fail because they never find a strategy. They fail because they never stop searching. At the start everything looks like the answer. Indicators. Tools. New systems. So they keep adding more. Eventually something starts to work. And that is where most people stop. But traders who last do the opposite. They remove what’s unnecessary. They simplify. They focus on what actually moves prices. Over time, complexity disappears. Not because the market got easier but because their understanding got clearer. It was never about more indicators. It was about clarity. If your system keeps getting more complex you are probably not improving it. You are avoiding simplicity.

Riz Iqbal

10,840 次观看 • 3 个月前

Exabits is redefining AI infrastructure with modular data centers. ✅ Built off-site, deployed in 3 months—not 3 years ✅Dropped near demand: AI hubs, training sites, even rooftops ✅Boost compute, slash latency, skip the $500M bunker This is Prime-speed infrastructure for the AI era—powered by Exabits. Hear it from our CMO, Mark.

Exabits is redefining AI infrastructure with modular data centers. ✅ Built off-site, deployed in 3 months—not 3 years ✅Dropped near demand: AI hubs, training sites, even rooftops ✅Boost compute, slash latency, skip the $500M bunker This is Prime-speed infrastructure for the AI era—powered by Exabits. Hear it from our CMO, Mark.

Exabits

21,936 次观看 • 10 个月前

AI is not independent of humans. It is built on humans. ChatGPT writes good essays because humans wrote the essays first. Facial recognition works because humans labeled every face manually. Every AI system runs on human labor that is deliberately hidden. And here is the problem: AI is far more expensive than humans. But humans are hard to enslave long term. That is why the system will fail. You cannot build a god on the backs of people who eventually stop obeying.

AI is not independent of humans. It is built on humans. ChatGPT writes good essays because humans wrote the essays first. Facial recognition works because humans labeled every face manually. Every AI system runs on human labor that is deliberately hidden. And here is the problem: AI is far more expensive than humans. But humans are hard to enslave long term. That is why the system will fail. You cannot build a god on the backs of people who eventually stop obeying.

Predictive History

10,723 次观看 • 2 个月前

I predict 50% of companies will need new leadership, because the old management style won't work in the era of AI. That's exactly why I'm seeing 95%+ of so-called "AI Transformation" initiatives fail. Most are bolting on AI pilots for functional tasks, but never touching the business core. just launched TrueNorth AI Decision platform for executives (Boss AI, TopSales AI, Investor AI agentic products) More on enterprise AI transformation in this interview with Danilo McGarry:

I predict 50% of companies will need new leadership, because the old management style won't work in the era of AI. That's exactly why I'm seeing 95%+ of so-called "AI Transformation" initiatives fail. Most are bolting on AI pilots for functional tasks, but never touching the business core. just launched TrueNorth AI Decision platform for executives (Boss AI, TopSales AI, Investor AI agentic products) More on enterprise AI transformation in this interview with Danilo McGarry:

Kai-Fu Lee

155,926 次观看 • 9 天前

The creative industry is being challenged right now. Demand for content is skyrocketing, budgets are shrinking, and timelines are tighter than ever. And while we all know AI is here to help, not all AI is actually helping. Most AI isn’t built for enterprise level creative work because it requires the precision and control that your average AI just can’t provide. That’s why today, we’re introducing Stability AI Solutions: A new offering designed to help enterprises scale creative production with generative AI.

The creative industry is being challenged right now. Demand for content is skyrocketing, budgets are shrinking, and timelines are tighter than ever. And while we all know AI is here to help, not all AI is actually helping. Most AI isn’t built for enterprise level creative work because it requires the precision and control that your average AI just can’t provide. That’s why today, we’re introducing Stability AI Solutions: A new offering designed to help enterprises scale creative production with generative AI.

Stability AI

14,610 次观看 • 11 个月前

The road is so good that Congressis think it's AI… obviously because their paw paw never built such good roads... (To those wondering about the wrong-side drivers, it’s because the road is not fully functional yet, and it was a rally.) Here’s another footage!

The road is so good that Congressis think it's AI… obviously because their paw paw never built such good roads... (To those wondering about the wrong-side drivers, it’s because the road is not fully functional yet, and it was a rally.) Here’s another footage!

Mr Sinha

84,392 次观看 • 4 个月前

.James Kurz: Most of the world's data was never worth storing at scale, nothing could use it. Now, the demand for AI is insatiable, and storage is the bottleneck nobody's ready for. Filecoin is already built for the scale that demand requires.

.James Kurz: Most of the world's data was never worth storing at scale, nothing could use it. Now, the demand for AI is insatiable, and storage is the bottleneck nobody's ready for. Filecoin is already built for the scale that demand requires.

Filecoin

77,101 次观看 • 22 天前

$NBIS CEO Arkady Volozh saying “whatever is built is consumed” is the cleanest explanation of this AI cycle. Every incremental watt, GPU and data center gets absorbed because intelligence is becoming a new production input.

$NBIS CEO Arkady Volozh saying “whatever is built is consumed” is the cleanest explanation of this AI cycle. Every incremental watt, GPU and data center gets absorbed because intelligence is becoming a new production input.

Shay Boloor

94,733 次观看 • 2 个月前

60 Minutes asked Dario why Anthropic talks so much about what can go wrong. His answer is the entire reason AI assurance matters: If companies know there are dangers and do not talk about them, you end up in the world of cigarette companies or opioid companies. That is the wrong model for AI. The right model is closer to: - disclose what the system can do - test for dangerous behavior - monitor real-world usage - build guardrails before scale - treat failures as signals, not PR problems This is where most enterprise AI programs are still weak. They have pilots. They have demos. They have internal excitement. But they do not have the assurance layer that tells them what is safe to ship. Full article below. If you're building with agents, don't just read it. Star/fork TrustModel and use it as an open-source eval + governance layer before giving AI real permissions:

60 Minutes asked Dario why Anthropic talks so much about what can go wrong. His answer is the entire reason AI assurance matters: If companies know there are dangers and do not talk about them, you end up in the world of cigarette companies or opioid companies. That is the wrong model for AI. The right model is closer to: - disclose what the system can do - test for dangerous behavior - monitor real-world usage - build guardrails before scale - treat failures as signals, not PR problems This is where most enterprise AI programs are still weak. They have pilots. They have demos. They have internal excitement. But they do not have the assurance layer that tells them what is safe to ship. Full article below. If you're building with agents, don't just read it. Star/fork TrustModel and use it as an open-source eval + governance layer before giving AI real permissions:

Karl Mehta

35,694 次观看 • 1 个月前

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

clickup just mass-obsoleted every AI agent platform here's the thing nobody's talking about: AI doesn't fail because the models are bad. it fails because it has no context. you paste in a prompt. it hallucinates. you blame the tool. but the tool was never the problem. the CONTEXT was. clickup just solved this. their new "super agents" live INSIDE your workspace. they see everything: - your tasks - your docs - your meetings - your conversations - your decisions 100% context. always on. always scraping. this isn't bolted-on AI calling APIs. this is AI that already knows your business. i've been running an AI backend for my agency. the architecture works - but you have to BUILD the context layer. clickup just made that automatic. i already use it. have tons of data there. this is about to be unbelievable. if you're building automations and you're not paying attention to this— you're about to get lapped. playing with it hard over the next 2 days. full deep dive coming. drop "SUPER" and i'll send you the breakdown when it's ready.

Nozz

20,271 次观看 • 6 个月前

Jensen Huang says agentic AI is not a chatbot. It is a "digital robot" -- and the next bottleneck is not the model. It is first-person data. "Agentic AI is just a digital robot. It understands, it reasons, it plans, and it acts and uses tools." Then he makes the bigger jump: "The world's video data is from a third person, not first person. And so agentic systems, robotic systems, physical AI -- the data is the hardest problem." That is the hidden constraint in robotics. LLMs got the internet. Physical AI needs demonstrations, synthetic worlds, reinforcement learning, and first-person experience. This is why Jensen keeps calling it a stack: robots are not waiting for one magical model. They need the data engine, the simulator, the reward system, the runtime, and the computer. The next wave of AI is not just software that talks. It is software that sees, plans, acts, and eventually moves through the world.

Jensen Huang says agentic AI is not a chatbot. It is a "digital robot" -- and the next bottleneck is not the model. It is first-person data. "Agentic AI is just a digital robot. It understands, it reasons, it plans, and it acts and uses tools." Then he makes the bigger jump: "The world's video data is from a third person, not first person. And so agentic systems, robotic systems, physical AI -- the data is the hardest problem." That is the hidden constraint in robotics. LLMs got the internet. Physical AI needs demonstrations, synthetic worlds, reinforcement learning, and first-person experience. This is why Jensen keeps calling it a stack: robots are not waiting for one magical model. They need the data engine, the simulator, the reward system, the runtime, and the computer. The next wave of AI is not just software that talks. It is software that sees, plans, acts, and eventually moves through the world.

Karl Mehta

14,140 次观看 • 20 天前

Real World AI doesn’t fail because of models. It fails because it lacks context. Project Jade shows true spatial intelligence through an embodied AI experience on Snap Spectacles. 👓 Ready for the next AI wave? Niantic Spatial is already here. (1/4) 🔗

Real World AI doesn’t fail because of models. It fails because it lacks context. Project Jade shows true spatial intelligence through an embodied AI experience on Snap Spectacles. 👓 Ready for the next AI wave? Niantic Spatial is already here. (1/4) 🔗

Niantic Spatial 🌎

16,582 次观看 • 6 个月前

Dave Ramsey was asked a simple hypothetical. Would you take a billion dollars at 0% interest for 10 years? He said no. Not because the math was bad. Because he does not borrow money. Period. No exceptions. And that is the problem. There is a difference between bad debt and good debt. Bad debt costs you money. Good debt makes you money. A loan covered by tenants is not a liability. It is a wealth building machine that someone else is paying off for you. Refusing all debt does not protect you. It just keeps you from building anything. The question is never whether to use debt. The question is whether the debt is covered.

Dave Ramsey was asked a simple hypothetical. Would you take a billion dollars at 0% interest for 10 years? He said no. Not because the math was bad. Because he does not borrow money. Period. No exceptions. And that is the problem. There is a difference between bad debt and good debt. Bad debt costs you money. Good debt makes you money. A loan covered by tenants is not a liability. It is a wealth building machine that someone else is paying off for you. Refusing all debt does not protect you. It just keeps you from building anything. The question is never whether to use debt. The question is whether the debt is covered.

Ken McElroy

19,697 次观看 • 1 个月前