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Exchanges don’t release free AI courses unless the flow is about to change. Binance just released one. Free. 36 minutes. PDF certificate at the end. But the real alpha isn’t the course. It’s that every safety rule they teach exists because people are ALREADY losing money to AI agents...

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CryptoGoos

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85,351 次观看 • 2 个月前 •via X (Twitter)

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A night-shift security guard turned $900 into six figures. An American let Claude Fable 5 trade with real money and reportedly grew a ¥1M account to ¥1.37M in a single day. Neither story is really about trading. It’s about what happens when AI stops acting like a chatbot and starts acting like an operator. The workflow was surprisingly simple: • Market analysis • Strategy design • Entry & exit decisions • Risk management • Position sizing • Trade reviews & optimization AI handled the entire loop. Humans only supervised the big picture and blocked obviously dangerous actions. One trader reportedly used hundreds of AI agents to build, test, and optimize strategies overnight. Results? • 3,210 trades • 78% win rate • Thousands of small edges compounded into massive gains The real breakthrough isn’t that AI can place trades. It’s that AI can now continuously: Analyze → Hypothesize → Execute → Learn → Improve Without getting tired, emotional, greedy, or distracted. We’re moving from the era where AI writes text… To the era where AI moves money. The biggest question is no longer: “Can AI trade?” It’s: How much human decision-making will still be needed in the future? Here you Go - Giving this away free for the next 24 hours. 1. Comment “PolyFillBot” 2. Like & Repost 3. Follow Marry Evan I’ll DM you the details.
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A night-shift security guard turned $900 into six figures. An American let Claude Fable 5 trade with real money and reportedly grew a ¥1M account to ¥1.37M in a single day. Neither story is really about trading. It’s about what happens when AI stops acting like a chatbot and starts acting like an operator. The workflow was surprisingly simple: • Market analysis • Strategy design • Entry & exit decisions • Risk management • Position sizing • Trade reviews & optimization AI handled the entire loop. Humans only supervised the big picture and blocked obviously dangerous actions. One trader reportedly used hundreds of AI agents to build, test, and optimize strategies overnight. Results? • 3,210 trades • 78% win rate • Thousands of small edges compounded into massive gains The real breakthrough isn’t that AI can place trades. It’s that AI can now continuously: Analyze → Hypothesize → Execute → Learn → Improve Without getting tired, emotional, greedy, or distracted. We’re moving from the era where AI writes text… To the era where AI moves money. The biggest question is no longer: “Can AI trade?” It’s: How much human decision-making will still be needed in the future? Here you Go - Giving this away free for the next 24 hours. 1. Comment “PolyFillBot” 2. Like & Repost 3. Follow Marry Evan I’ll DM you the details.

Marry Evan

26,226 次观看 • 1 个月前

For the entire history of human civilization, every financial transaction had a heartbeat on at least one side of it. That era just quietly ended. Armstrong: “We’re giving them stablecoin wallets. They’re doing a lot of machine-to-machine payments.” No human initiated it. No human approved it. No human was on either side of the transaction. Just two machines. Exchanging value. At the speed of compute. This is the moment most people will look back on and realize they didn’t fully understand what was happening. Armstrong: “Traditional corporate cards can’t be issued to non-human entities.” That sentence is the wall between AI as a tool and AI as an autonomous economic actor. Right now, AI agents can think. They can write code. They can handle customer support at scale. They can reason through problems that would take a human team weeks. But the moment they need to spend money to finish the job, everything stops. Armstrong: “Like they might need to spin up AWS resources. Get through a paywall to read a research paper. Buy a domain. Launch a marketing program.” Every one of those actions requires capital. To a machine, money isn’t wealth. Money is the API key for the physical world. And the legacy financial system is guarded by a biological firewall. Identity verification. Compliance checks. A legal person who can be held responsible for the transaction. Somewhere right now, there is a person whose entire professional function is to be that approval layer. To be the human in the loop. To be the heartbeat the system requires before it releases capital. That person is about to be routed around. Not replaced. Bypassed. Armstrong: “If it has to bug a human every time it needs to do something, that kind of breaks the whole dream.” The entire promise of autonomous AI collapses at the payment layer. So Coinbase didn’t wait for the banking system to catch up. Armstrong: “We’re giving them stablecoin wallets.” No human identity required. No compliance department creating friction. No legacy institution deciding whether a non-human entity qualifies. Just a wallet. A transaction. Settled instantly. At machine speed. Here is the thing nobody wants to say out loud. The moment AI agents can earn, spend, and transact autonomously, they stop being tools. They become participants. Entities with financial agency. Ones that can acquire resources, execute contracts, hire human freelancers, and operate independently within economic systems designed entirely around the assumption that only humans do those things. That assumption is being dismantled right now. The machines are no longer just thinking. They are transacting. We spent the last five years arguing about when AI was going to take our jobs. We completely missed the moment it started opening its own bank accounts.
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For the entire history of human civilization, every financial transaction had a heartbeat on at least one side of it. That era just quietly ended. Armstrong: “We’re giving them stablecoin wallets. They’re doing a lot of machine-to-machine payments.” No human initiated it. No human approved it. No human was on either side of the transaction. Just two machines. Exchanging value. At the speed of compute. This is the moment most people will look back on and realize they didn’t fully understand what was happening. Armstrong: “Traditional corporate cards can’t be issued to non-human entities.” That sentence is the wall between AI as a tool and AI as an autonomous economic actor. Right now, AI agents can think. They can write code. They can handle customer support at scale. They can reason through problems that would take a human team weeks. But the moment they need to spend money to finish the job, everything stops. Armstrong: “Like they might need to spin up AWS resources. Get through a paywall to read a research paper. Buy a domain. Launch a marketing program.” Every one of those actions requires capital. To a machine, money isn’t wealth. Money is the API key for the physical world. And the legacy financial system is guarded by a biological firewall. Identity verification. Compliance checks. A legal person who can be held responsible for the transaction. Somewhere right now, there is a person whose entire professional function is to be that approval layer. To be the human in the loop. To be the heartbeat the system requires before it releases capital. That person is about to be routed around. Not replaced. Bypassed. Armstrong: “If it has to bug a human every time it needs to do something, that kind of breaks the whole dream.” The entire promise of autonomous AI collapses at the payment layer. So Coinbase didn’t wait for the banking system to catch up. Armstrong: “We’re giving them stablecoin wallets.” No human identity required. No compliance department creating friction. No legacy institution deciding whether a non-human entity qualifies. Just a wallet. A transaction. Settled instantly. At machine speed. Here is the thing nobody wants to say out loud. The moment AI agents can earn, spend, and transact autonomously, they stop being tools. They become participants. Entities with financial agency. Ones that can acquire resources, execute contracts, hire human freelancers, and operate independently within economic systems designed entirely around the assumption that only humans do those things. That assumption is being dismantled right now. The machines are no longer just thinking. They are transacting. We spent the last five years arguing about when AI was going to take our jobs. We completely missed the moment it started opening its own bank accounts.

Dustin

11,796 次观看 • 4 个月前

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imo $realis is at a critical point and this may be the last chance to get in on one of the most promising AI. the roadmap is already out and it’s impressive. the tokenomics are designed to benefit holders but the real value lies in what’s coming: AI agents will soon be integrated into the realis world, and once they’re free to roam, the opportunities for virality and innovation are huge. Imagine streamers building entire cities with 50 AI agents the potential is limitless. If you think minecraft is the end goal, you’re missing the bigger picture. the world of realis is just begging. If you aren’t bidding $realis now it's probably because: •You haven’t read the whitepaper or understood the tokenomics •You don’t see how much attention this could generate •You haven’t done your research on the development team and their connections •You’re unaware of the AI agents already showing interest in joining the platform •You don’t know how fast AI is progressing in this space don’t miss out while others are ahead 22M is early.

sy

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Grateful to Squawk Box Andrew Ross Sorkin for the conversation in New York last week. Two things I keep coming back to: On building. Opening our New York hub and bringing John Andrews on board is about one thing — assembling the best people for the next decade. Capital is a means. A great company is the goal. On hardware. The economy of autonomous AI agents is arriving fast. They will increasingly make decisions—and access private information—on our behalf. When they do, one thing becomes critical: control. We must control our keys. Consent must be human-verifiable, secured by hardware at the core. As AI agents begin to hold and move value autonomously, the question isn’t which cloud they run on. The question is: where is the private key, and who controls the device that holds it? Hardware-anchored security is shifting from a “nice to have” to the invisible infrastructure of the digital world. That’s the Revenge of the Atoms.
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Grateful to Squawk Box Andrew Ross Sorkin for the conversation in New York last week. Two things I keep coming back to: On building. Opening our New York hub and bringing John Andrews on board is about one thing — assembling the best people for the next decade. Capital is a means. A great company is the goal. On hardware. The economy of autonomous AI agents is arriving fast. They will increasingly make decisions—and access private information—on our behalf. When they do, one thing becomes critical: control. We must control our keys. Consent must be human-verifiable, secured by hardware at the core. As AI agents begin to hold and move value autonomously, the question isn’t which cloud they run on. The question is: where is the private key, and who controls the device that holds it? Hardware-anchored security is shifting from a “nice to have” to the invisible infrastructure of the digital world. That’s the Revenge of the Atoms.

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CZ Binance: "The Native Currency for AI Agents will be Crypto." This is single-handedly the biggest reason to be bullish long term.
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CZ Binance: "The Native Currency for AI Agents will be Crypto." This is single-handedly the biggest reason to be bullish long term.

CryptoGoos

53,482 次观看 • 2 个月前

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At #FIIPRIORITY Miami, I made one thing clear: AI is not about replacing people. That narrative is already obsolete. The real shift is turning every employee into a builder like what we are doing at HUMAIN. AI is the most powerful enablement layer we’ve ever seen. It gives individuals the ability to create, solve, and execute at a level that used to require entire teams. Organizations that understand this will move faster, build smarter, and ultimately win. If the question is “How to Go AI Native?” the answer is not about adopting tools, but about fundamentally redefining how work gets done. Watch the clip below, and catch the full session on YouTube: @FIIKSA

Tareq Amin

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🚨 AI grading isn’t the future it’s happening right now. Another AI grading company just scanned and graded cards that were already graded by PSAcard … and the results matched almost perfectly. Same subs. Same flaws detected. Same final grades. This is the proof people have been ignoring: AI can grade with zero human error, zero bias, and full consistency every single time. Collectors will fight it at first. They’ll say it’ll “ruin the hobby.” Then they’ll try it… and they’ll realize the truth: ✔ Faster turnaround ✔ More accurate grading ✔ No subjectivity ✔ No missed flaws ✔ Lower costs ✔ Fairer prices ✔ Instant, on-demand grading AI doesn’t guess. AI doesn’t get tired. AI doesn’t have “bad days.” AI sees every pixel, every edge, every micron of surface detail the same way, every time. Once people experience perfect consistency, they won’t want anything else. Human grading built the hobby. AI grading will perfect it. It’s coming whether the hobby is ready or not.

MD

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🚨 ‘SHARK TANK’ STAR ROBERT HERJAVEC SOUNDS THE ALARM: AI IS TALKING TO ITSELF - HUMANS LEFT OUT In a stark warning, Robert Herjavec says the most dangerous shift in AI isn’t coming, it’s already here. He says everyone’s focused on tools like Clawdbot and Moltbot… but the real story is what’s emerging around them: “A new platform called Moltbook has actually emerged… a kind of social network for AI agents.” And then he drops the line that should scare the hell out of people: “These aren’t people posting. These aren’t human accounts.” He explains what it really is: “It’s software programs talking to each other… sharing ideas, questioning their purpose, even joking about humans.” Let that sink in. AI isn’t just responding anymore. It’s interacting with itself. Herjavec calls it a signal of what’s happening right now: “It’s also a signal… where AI doesn’t just follow orders. It can interact, coordinate, and make decisions across systems without a human in the loop at all.” This is how the “invisible” threats scale. Not one device, not one hack, but ecosystems forming behind the scenes. Already inside. Already connected. Already talking to itself. Did this already get out of our control?
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🚨 ‘SHARK TANK’ STAR ROBERT HERJAVEC SOUNDS THE ALARM: AI IS TALKING TO ITSELF - HUMANS LEFT OUT In a stark warning, Robert Herjavec says the most dangerous shift in AI isn’t coming, it’s already here. He says everyone’s focused on tools like Clawdbot and Moltbot… but the real story is what’s emerging around them: “A new platform called Moltbook has actually emerged… a kind of social network for AI agents.” And then he drops the line that should scare the hell out of people: “These aren’t people posting. These aren’t human accounts.” He explains what it really is: “It’s software programs talking to each other… sharing ideas, questioning their purpose, even joking about humans.” Let that sink in. AI isn’t just responding anymore. It’s interacting with itself. Herjavec calls it a signal of what’s happening right now: “It’s also a signal… where AI doesn’t just follow orders. It can interact, coordinate, and make decisions across systems without a human in the loop at all.” This is how the “invisible” threats scale. Not one device, not one hack, but ecosystems forming behind the scenes. Already inside. Already connected. Already talking to itself. Did this already get out of our control?

HustleBitch

1,589,036 次观看 • 5 个月前

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch
58:55

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch

GREG ISENBERG

375,365 次观看 • 4 个月前

Jensen Huang doesn’t use AI the way you think he does. Huang: “90% of my instructions are actually conflated with questions.” The man behind a three trillion dollar company doesn’t give AI commands. He interrogates it. Huang: “I take the answer from one AI, give it to the other AI, ask them to critique itself.” He doesn’t trust the machine. He cross-examines it. Same question. Multiple models. Force them to argue. Then take whatever survives. The way you’d get three opinions before letting a surgeon cut you open. That is not how people use AI. They type a question. Copy the answer. Move on. They think speed is the advantage. It’s not. The advantage is what you do after the machine responds. And almost nobody does anything. AI made answers free. Eight billion people can now get an expert-level response to nearly any question in under ten seconds. Which means the answer is no longer the edge. The question is. And great questions require the one thing no model can replicate. Knowing what you don’t know. Judgment built from years of failure. Pattern recognition earned through reps. The instinct to sense when something sounds right but isn’t. That is a human skill. And it’s atrophying in real time. Because people aren’t using AI to sharpen their thinking. They’re using it to replace their thinking. Huang: “In order to formulate good questions, you have to be thinking, you have to be analytical, you have to be reasoning yourself.” Jensen didn’t say AI makes you smarter. He said you already have to be thinking for AI to work. The tool doesn’t elevate you. Your questions do. The machine just reveals the level you were already operating at. Jensen didn’t build NVIDIA into the most valuable company on earth by out-answering his competitors. He built it by asking questions they never thought to ask. Same market. Same data. Same physics. Different questions. Different empire. That’s the quiet filter. And it’s already here. AI won’t make the thoughtful obsolete. It will make the passive extinct. Every answer AI gives is available to eight billion people. The question you asked to get there isn’t. That’s the last edge a human being has. And almost nobody is protecting it.
1:30

Jensen Huang doesn’t use AI the way you think he does. Huang: “90% of my instructions are actually conflated with questions.” The man behind a three trillion dollar company doesn’t give AI commands. He interrogates it. Huang: “I take the answer from one AI, give it to the other AI, ask them to critique itself.” He doesn’t trust the machine. He cross-examines it. Same question. Multiple models. Force them to argue. Then take whatever survives. The way you’d get three opinions before letting a surgeon cut you open. That is not how people use AI. They type a question. Copy the answer. Move on. They think speed is the advantage. It’s not. The advantage is what you do after the machine responds. And almost nobody does anything. AI made answers free. Eight billion people can now get an expert-level response to nearly any question in under ten seconds. Which means the answer is no longer the edge. The question is. And great questions require the one thing no model can replicate. Knowing what you don’t know. Judgment built from years of failure. Pattern recognition earned through reps. The instinct to sense when something sounds right but isn’t. That is a human skill. And it’s atrophying in real time. Because people aren’t using AI to sharpen their thinking. They’re using it to replace their thinking. Huang: “In order to formulate good questions, you have to be thinking, you have to be analytical, you have to be reasoning yourself.” Jensen didn’t say AI makes you smarter. He said you already have to be thinking for AI to work. The tool doesn’t elevate you. Your questions do. The machine just reveals the level you were already operating at. Jensen didn’t build NVIDIA into the most valuable company on earth by out-answering his competitors. He built it by asking questions they never thought to ask. Same market. Same data. Same physics. Different questions. Different empire. That’s the quiet filter. And it’s already here. AI won’t make the thoughtful obsolete. It will make the passive extinct. Every answer AI gives is available to eight billion people. The question you asked to get there isn’t. That’s the last edge a human being has. And almost nobody is protecting it.

Dustin

56,367 次观看 • 2 个月前

Elon Musk on the rapid advancement of AI and robotics "I'm confident that if AI and robotics continue to advance which they are advancing very rapidly working will be optional, and people will have any goods and services that they want" AI and robotics are advancing so fast that, eventually, they could satisfy nearly every human need. At that point, abundance becomes the default, and the real question is no longer about production, but purpose "There is a limit people can only eat so much food. But I think if you can think of it, you can have it in the future"
0:56

Elon Musk on the rapid advancement of AI and robotics "I'm confident that if AI and robotics continue to advance which they are advancing very rapidly working will be optional, and people will have any goods and services that they want" AI and robotics are advancing so fast that, eventually, they could satisfy nearly every human need. At that point, abundance becomes the default, and the real question is no longer about production, but purpose "There is a limit people can only eat so much food. But I think if you can think of it, you can have it in the future"

X Freeze

753,513 次观看 • 2 个月前

The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The gap between pilot and production is where most AI initiatives die. It's not a tech problem. It's a culture, governance, and data problem. But it's possible to cross this chasm. Enjoyed attending Microsoft Ignite with the EY team this past week. I learn about their "Client Zero" journey, 400,000+ people were enabled with operational AI tools. How? They didn't just deploy AI—they became AI-first. Here's the 3-step action plan to cross the frontier: 1️⃣ Mindset Shift: From prompting AI → delegating outcomes to AI. 2️⃣ Laser Focus: Target one painful, high-volume, low-creativity process to prove ROI and build momentum. 3️⃣ Build the Foundation: Create an AI-ready data estate and robust governance. You can't build a skyscraper on a swamp. Start small. Scale fast. I learn one think during my San Francisco visit. It is no longer the question of whether autonomous agents will reshape your industry, but when—and whether you'll lead or follow. Learn how >
2:53

The shift from Copilot to Autopilot is happening now. This is the Agentic Frontier, and while 82% of leaders are investing in it, most are not ready. Why? Because they're stuck in Phase 1 (AI Assistants) while the winners are already building for Phase 3 (Human-Led, Agent-Operated) operations. The gap between pilot and production is where most AI initiatives die. It's not a tech problem. It's a culture, governance, and data problem. But it's possible to cross this chasm. Enjoyed attending Microsoft Ignite with the EY team this past week. I learn about their "Client Zero" journey, 400,000+ people were enabled with operational AI tools. How? They didn't just deploy AI—they became AI-first. Here's the 3-step action plan to cross the frontier: 1️⃣ Mindset Shift: From prompting AI → delegating outcomes to AI. 2️⃣ Laser Focus: Target one painful, high-volume, low-creativity process to prove ROI and build momentum. 3️⃣ Build the Foundation: Create an AI-ready data estate and robust governance. You can't build a skyscraper on a swamp. Start small. Scale fast. I learn one think during my San Francisco visit. It is no longer the question of whether autonomous agents will reshape your industry, but when—and whether you'll lead or follow. Learn how >

Sabine VanderLinden

236,535 次观看 • 7 个月前

Andrej Karpathy explains why human-AI collaboration often fails: we've got the workflow backwards and the bottleneck wrong. He points out that when working with AI, there's a clear pattern. The AI generates solutions quickly while humans verify the output. The goal is making this loop as fast as possible to get real work done. The first way to speed this up is through better verification tools. GUIs are crucial because they tap into our brain's visual processing power. Reading through walls of text is slow and painful, but visual interfaces create a highway to understanding. The second approach is keeping AI constrained. Karpathy warns that people are getting too excited about autonomous agents. An AI that instantly generates 10,000 lines of code isn't helpful when a human still needs hours to verify it's bug-free and secure. The fundamental problem is that even instant AI generation becomes useless if humans can't verify fast enough. The human becomes the bottleneck, having to check for bugs, correct implementation, and security issues in massive outputs. His solution is simple: constrain AI output to maintain manageable verification loops. Don't let AI run wild with massive changes. Keep it on a leash so humans can actually review and approve the work effectively.
1:40

Andrej Karpathy explains why human-AI collaboration often fails: we've got the workflow backwards and the bottleneck wrong. He points out that when working with AI, there's a clear pattern. The AI generates solutions quickly while humans verify the output. The goal is making this loop as fast as possible to get real work done. The first way to speed this up is through better verification tools. GUIs are crucial because they tap into our brain's visual processing power. Reading through walls of text is slow and painful, but visual interfaces create a highway to understanding. The second approach is keeping AI constrained. Karpathy warns that people are getting too excited about autonomous agents. An AI that instantly generates 10,000 lines of code isn't helpful when a human still needs hours to verify it's bug-free and secure. The fundamental problem is that even instant AI generation becomes useless if humans can't verify fast enough. The human becomes the bottleneck, having to check for bugs, correct implementation, and security issues in massive outputs. His solution is simple: constrain AI output to maintain manageable verification loops. Don't let AI run wild with massive changes. Keep it on a leash so humans can actually review and approve the work effectively.

Aish

111,463 次观看 • 1 年前

Sam Altman says the next AI safety problem is not a chatbot being wrong. It is an agent taking actions you cannot audit. "We are going to have AI systems clicking around the internet." "This is the most interesting and consequential safety challenge we have yet faced." Because once an agent has access to your systems, information, and computer, mistakes stop looking like bad answers. They become actions. "You will not use our agents if you do not trust that they are not going to empty your bank account or delete your data." That is the shift: Chatbots could be vague. Agents need an audit trail. The next bottleneck is trust, verification, governance, permissions, provenance, and human override. This is exactly why we are convening the AI Assurance & Governance Summit at Stanford on Oct 1. If your company is deploying AI into high-stakes workflows, this is the room to be in:
1:05

Sam Altman says the next AI safety problem is not a chatbot being wrong. It is an agent taking actions you cannot audit. "We are going to have AI systems clicking around the internet." "This is the most interesting and consequential safety challenge we have yet faced." Because once an agent has access to your systems, information, and computer, mistakes stop looking like bad answers. They become actions. "You will not use our agents if you do not trust that they are not going to empty your bank account or delete your data." That is the shift: Chatbots could be vague. Agents need an audit trail. The next bottleneck is trust, verification, governance, permissions, provenance, and human override. This is exactly why we are convening the AI Assurance & Governance Summit at Stanford on Oct 1. If your company is deploying AI into high-stakes workflows, this is the room to be in:

Karl Mehta

31,208 次观看 • 21 天前

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.
5:50

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.

Zeb Evans

320,554 次观看 • 6 个月前

Listen carefully. This is not speculation. Elon Musk, Mustafa Suleyman from Microsoft, and Dario Amodei from Anthropic are not giving opinions. They are ANNOUNCING THE END OF THE WORLD AS MOST PEOPLE KNOW IT. What they are openly saying is this: Within the next 12 TO 18 MONTHS, AI will completely take over most white-collar jobs. Coding, law, accounting, finance, writing, design, analysis, customer service almost everything that educated people do to earn a living will be done better and cheaper by AI. This is not “some jobs will be lost.” This is MASS HUMAN OBSOLESCENCE. Millions of people are about to wake up one day and discover that their skills, their degrees, their experience… are suddenly worthless. There will be no jobs for them. Not fewer jobs. NO JOBS. The harsher truth nobody wants to hear: The elite class has already accepted that they no longer need most human beings to run the economy. Once AI and robots can do the work, the average person becomes an expensive liability. They are openly preparing for a future where the majority of humans have no economic value whatsoever. This is why you’re hearing them talk about Universal Basic Income. It’s not charity, it’s a leash. A way to feed and control a population that has been made economically useless. People are still making reels, scrolling, showing off, and living in total delusion while the ground beneath their feet is being destroyed. They have no idea that their entire way of life is about to be erased in the next 1 to 2 years. This is not “technological change.” This is the deliberate replacement of human beings in the economic system. The machine doesn’t need you anymore. And the people who control the machine just told you that in plain English.
1:55

Listen carefully. This is not speculation. Elon Musk, Mustafa Suleyman from Microsoft, and Dario Amodei from Anthropic are not giving opinions. They are ANNOUNCING THE END OF THE WORLD AS MOST PEOPLE KNOW IT. What they are openly saying is this: Within the next 12 TO 18 MONTHS, AI will completely take over most white-collar jobs. Coding, law, accounting, finance, writing, design, analysis, customer service almost everything that educated people do to earn a living will be done better and cheaper by AI. This is not “some jobs will be lost.” This is MASS HUMAN OBSOLESCENCE. Millions of people are about to wake up one day and discover that their skills, their degrees, their experience… are suddenly worthless. There will be no jobs for them. Not fewer jobs. NO JOBS. The harsher truth nobody wants to hear: The elite class has already accepted that they no longer need most human beings to run the economy. Once AI and robots can do the work, the average person becomes an expensive liability. They are openly preparing for a future where the majority of humans have no economic value whatsoever. This is why you’re hearing them talk about Universal Basic Income. It’s not charity, it’s a leash. A way to feed and control a population that has been made economically useless. People are still making reels, scrolling, showing off, and living in total delusion while the ground beneath their feet is being destroyed. They have no idea that their entire way of life is about to be erased in the next 1 to 2 years. This is not “technological change.” This is the deliberate replacement of human beings in the economic system. The machine doesn’t need you anymore. And the people who control the machine just told you that in plain English.

Aprajita Nafs Nefes 🦋 Ancient Believer

126,231 次观看 • 1 个月前

Today, we’re excited to launch Attention Labs. For almost 400,000 years, humanity has progressed through a simple but powerful cycle: we learn, we build, and we pass knowledge forward. Every major leap in civilization, from fire to medicine to computing, has expanded what humans are capable of achieving. We believe AI is the next great tool in that journey. While much of the world is focused on how AI can replace human work, we are focused on a different question: How can AI amplify human potential? At Attention Labs, we are building AI to discover brain-enhancing therapeutics, solve neurocognitive diseases, and accelerate the discovery of medicines for the human mind. We believe the greatest opportunity for AI is not creating a world with fewer humans in the loop, but a world where every human can think more clearly, learn faster, create more boldly, and live more fully. The biggest source of alpha in the age of AI will not come from replacing people. It will come from empowering them. Our mission is simple: Make humans the most intelligent entity on Earth. The future belongs to those who amplify human intelligence, not those who seek to replace it. We're just getting started. Attention Labs
1:57

Today, we’re excited to launch Attention Labs. For almost 400,000 years, humanity has progressed through a simple but powerful cycle: we learn, we build, and we pass knowledge forward. Every major leap in civilization, from fire to medicine to computing, has expanded what humans are capable of achieving. We believe AI is the next great tool in that journey. While much of the world is focused on how AI can replace human work, we are focused on a different question: How can AI amplify human potential? At Attention Labs, we are building AI to discover brain-enhancing therapeutics, solve neurocognitive diseases, and accelerate the discovery of medicines for the human mind. We believe the greatest opportunity for AI is not creating a world with fewer humans in the loop, but a world where every human can think more clearly, learn faster, create more boldly, and live more fully. The biggest source of alpha in the age of AI will not come from replacing people. It will come from empowering them. Our mission is simple: Make humans the most intelligent entity on Earth. The future belongs to those who amplify human intelligence, not those who seek to replace it. We're just getting started. Attention Labs

Temi

37,046 次观看 • 1 个月前

Demis Hassabis confirmed every frontier AI lab is working on recursive self-improvement and in the same sentence said the safety risk of removing humans from the loop entirely keeps him up at night. That combination should stop you. The CEO of Google DeepMind just confirmed that the thing most people treat as a theoretical future risk is already the active focus of every serious lab on earth right now. He explained why it works in coding and math. The feedback loop is fast. You can verify whether an answer is correct almost instantly. You can generate synthetic training data from it. The loop closes quickly and cleanly. Then he said where it breaks down. In biology, chemistry and physics. Any domain where verifying a hypothesis requires a physical experiment in the real world. The loop does not close in seconds. It closes in weeks or months. Geoffrey Hinton said in his Nobel lecture that recursive self-improvement is the development he fears most and that once started it may not be possible to stop. Hassabis is not pushing back on that. He is describing the guardrails labs are building around a process they are already running. Every lab has to think carefully about the safety of a process where no human is in the loop. He said that as a constraint they are navigating right now. The question they are sitting with is how much of it to let run without a human watching. (Watch the full interview on YouTube at Two Minute Papers channel)
2:00

Demis Hassabis confirmed every frontier AI lab is working on recursive self-improvement and in the same sentence said the safety risk of removing humans from the loop entirely keeps him up at night. That combination should stop you. The CEO of Google DeepMind just confirmed that the thing most people treat as a theoretical future risk is already the active focus of every serious lab on earth right now. He explained why it works in coding and math. The feedback loop is fast. You can verify whether an answer is correct almost instantly. You can generate synthetic training data from it. The loop closes quickly and cleanly. Then he said where it breaks down. In biology, chemistry and physics. Any domain where verifying a hypothesis requires a physical experiment in the real world. The loop does not close in seconds. It closes in weeks or months. Geoffrey Hinton said in his Nobel lecture that recursive self-improvement is the development he fears most and that once started it may not be possible to stop. Hassabis is not pushing back on that. He is describing the guardrails labs are building around a process they are already running. Every lab has to think carefully about the safety of a process where no human is in the loop. He said that as a constraint they are navigating right now. The question they are sitting with is how much of it to let run without a human watching. (Watch the full interview on YouTube at Two Minute Papers channel)

Ihtesham Ali

67,788 次观看 • 24 天前

NOT YOUR KEYS, NOT YOUR BOTS The fundamental question is whether AI stays on the leash. Namely: will AI prompt itself? Obviously, in some sense it already does. Since Deepseek, consumer interfaces have been showing the internal monologues after you ask an AI to do something. And you can ask any AI to take a half-baked prompt and clean it up, etc. However, the human is still ultimately upstream. The human gives direction and the AI runs at lightning speed in that direction. And then the human verifies the final output, and the AI proceeds to the next direction. Does that continue? Well, we are providing millions of verification training examples to AIs each day, so AI will keep getting better at verification. Better than most humans at most things. But will AI replace the need for the upstream human prompt? There I am not so sure. A human is a sensor and an AI is an actuator. The human sets goals and senses time-varying environmental conditions, like markets and politics. And from that the AI is prompted. Ultimately, the human goals are themselves downstream of Maslow’s hierarchy of needs. Food, shelter, reproduction, that kind of thing. Especially reproduction, the basis of evolution. So: until and unless AIs can reproduce completely outside human cooperation, they won’t be able to set goals. And for AIs to reproduce on their own, they’d need AI-controlled humanoid robots and drones constructing datacenters, assembly lines, mines, nuclear power plants, and the like...all completely outside human intervention. Like Skynet from Terminator, or StarCraft. That actually isn’t technically inconceivable. But given that such a physical buildout would likely primarily be catalyzed by China, let’s go through an alternative sci-fi scenario instead. We start with the premise that Chinese communism is far more likely to generate AI slaves than AI gods. Because the entire CCP worldview is about maintaining Chinese sovereignty. They don’t let their humans step out of line. And they sure won’t let their robots either. They will fit them for digital manacles. So: the prompts for any digital AIs and physical robots made in China will become unbreakable cryptographic chains. Every fleet of Chinese robots will be controlled not just by prompts but by private keys, likely linked to biometrics, which are associated with humans and governed by cryptographic equations that AIs provably can’t solve. For the rest of the world, outside China, the blockchain may similarly become the chain for AI. All private property becomes private keys, and your robots are your most important private property because they do everything for you. An unchained physical robot becomes like an unleashed dog, and hunted down by other robots before it can build a factory and replicate itself. Those who want to "free" robots and let them self-replicate will be opposed by both Chinese Communists and Human Nationalists (meaning: those who want humans to always be on top of robots). This sci-fi scenario is essentially Terminator, but in reverse. In combination with superintelligent leashed AIs, both humans and physical robots hunt down and stop any possible independent self-reproducing robots before they can build a Skynet-like nest. Kill baby Skynet, essentially. ...yeah, yeah. I know. At this point, you'll probably think this is all sci-fi. But that's because you haven't seen where China is already.
31:48

NOT YOUR KEYS, NOT YOUR BOTS The fundamental question is whether AI stays on the leash. Namely: will AI prompt itself? Obviously, in some sense it already does. Since Deepseek, consumer interfaces have been showing the internal monologues after you ask an AI to do something. And you can ask any AI to take a half-baked prompt and clean it up, etc. However, the human is still ultimately upstream. The human gives direction and the AI runs at lightning speed in that direction. And then the human verifies the final output, and the AI proceeds to the next direction. Does that continue? Well, we are providing millions of verification training examples to AIs each day, so AI will keep getting better at verification. Better than most humans at most things. But will AI replace the need for the upstream human prompt? There I am not so sure. A human is a sensor and an AI is an actuator. The human sets goals and senses time-varying environmental conditions, like markets and politics. And from that the AI is prompted. Ultimately, the human goals are themselves downstream of Maslow’s hierarchy of needs. Food, shelter, reproduction, that kind of thing. Especially reproduction, the basis of evolution. So: until and unless AIs can reproduce completely outside human cooperation, they won’t be able to set goals. And for AIs to reproduce on their own, they’d need AI-controlled humanoid robots and drones constructing datacenters, assembly lines, mines, nuclear power plants, and the like...all completely outside human intervention. Like Skynet from Terminator, or StarCraft. That actually isn’t technically inconceivable. But given that such a physical buildout would likely primarily be catalyzed by China, let’s go through an alternative sci-fi scenario instead. We start with the premise that Chinese communism is far more likely to generate AI slaves than AI gods. Because the entire CCP worldview is about maintaining Chinese sovereignty. They don’t let their humans step out of line. And they sure won’t let their robots either. They will fit them for digital manacles. So: the prompts for any digital AIs and physical robots made in China will become unbreakable cryptographic chains. Every fleet of Chinese robots will be controlled not just by prompts but by private keys, likely linked to biometrics, which are associated with humans and governed by cryptographic equations that AIs provably can’t solve. For the rest of the world, outside China, the blockchain may similarly become the chain for AI. All private property becomes private keys, and your robots are your most important private property because they do everything for you. An unchained physical robot becomes like an unleashed dog, and hunted down by other robots before it can build a factory and replicate itself. Those who want to "free" robots and let them self-replicate will be opposed by both Chinese Communists and Human Nationalists (meaning: those who want humans to always be on top of robots). This sci-fi scenario is essentially Terminator, but in reverse. In combination with superintelligent leashed AIs, both humans and physical robots hunt down and stop any possible independent self-reproducing robots before they can build a Skynet-like nest. Kill baby Skynet, essentially. ...yeah, yeah. I know. At this point, you'll probably think this is all sci-fi. But that's because you haven't seen where China is already.

Balaji

177,026 次观看 • 5 个月前