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。

I am about to COMPLETELY disrupt the cybersecurity industry...💀💀💀 Presenting the Continuous Reasoning AI Pentester! Multiple AI agents running every security tool under the sun against your environment, at record speeds. Full pentests achieved in less than AN HOUR. Zero human input. One hundred percent success.

Tib3rius

73,230 subscribers

249,127 次观看 • 5 个月前 •via X (Twitter)

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

What if the question isn’t whether to use AI, but how fast you can learn to work with it? In this special episode recorded live at Webex One, I talk with Jeetu Patel (Jeetu Patel), President and Chief Product Officer at Cisco, about the mindset shift every company, and every professional, must make to thrive in the AI era. From rethinking work culture to designing products for both humans and AI agents, Jeetu shares a thoughtful, optimistic vision for the future, one rooted in curiosity, responsibility, and human creativity. “AI won’t take your job. But someone who uses AI better than you might.” An honest, energizing look at how to lead and learn in an AI-first world. 1:08 Embracing AI In The Workforce 5:17 AI Is More Than A Productivity Tool 8:35 Generational Differences In AI Use 10:49 The Future of Integrating AI Agents 13:44 AI As A "Given" 17:08 Speed of Accumulating Knowledge 19:00 Ethical AI Use 21:16 What The Industry Gets Wrong About AI

What if the question isn’t whether to use AI, but how fast you can learn to work with it? In this special episode recorded live at Webex One, I talk with Jeetu Patel (Jeetu Patel), President and Chief Product Officer at Cisco, about the mindset shift every company, and every professional, must make to thrive in the AI era. From rethinking work culture to designing products for both humans and AI agents, Jeetu shares a thoughtful, optimistic vision for the future, one rooted in curiosity, responsibility, and human creativity. “AI won’t take your job. But someone who uses AI better than you might.” An honest, energizing look at how to lead and learn in an AI-first world. 1:08 Embracing AI In The Workforce 5:17 AI Is More Than A Productivity Tool 8:35 Generational Differences In AI Use 10:49 The Future of Integrating AI Agents 13:44 AI As A "Given" 17:08 Speed of Accumulating Knowledge 19:00 Ethical AI Use 21:16 What The Industry Gets Wrong About AI

Carolina Milanesi

37,076 次观看 • 10 个月前

Hot topic in vogue is what happens to systems of record in an era of 1000x more agents than humans. Aaron Levie has been the CEO of Box for 20 years and believes that systems of record become more important, not less, with agents: “Systems of record were built for a TAM of human employees. And that was sort of where the value maxed out at. And now maybe we'll have a hundred times more agents than people or a thousand times more agents than people. So I think on a relative basis, the agent layer will seize growth from zero to a trillion. But the system of record layer now has a thousand times more users on it that need to access data and need to execute a workflow and need to move things through various events. And importantly, you need as an enterprise to care about data integrity and security and the controls in your workflow and traffic copying the agents. So basically, this is where I am very diametrically opposed to the view that the system of record gets is squeezed into a database interaction layer because you actually need all of the core system of record properties for the agents to operate on.”

Hot topic in vogue is what happens to systems of record in an era of 1000x more agents than humans. Aaron Levie has been the CEO of Box for 20 years and believes that systems of record become more important, not less, with agents: “Systems of record were built for a TAM of human employees. And that was sort of where the value maxed out at. And now maybe we'll have a hundred times more agents than people or a thousand times more agents than people. So I think on a relative basis, the agent layer will seize growth from zero to a trillion. But the system of record layer now has a thousand times more users on it that need to access data and need to execute a workflow and need to move things through various events. And importantly, you need as an enterprise to care about data integrity and security and the controls in your workflow and traffic copying the agents. So basically, this is where I am very diametrically opposed to the view that the system of record gets is squeezed into a database interaction layer because you actually need all of the core system of record properties for the agents to operate on.”

Corinne Marie Riley

119,410 次观看 • 7 个月前

Using AI for promote Product in Ads with your original character ? It's possible ! My partner Ad Machine contacted me to tell me about their tool that lets you input your product into an AI model that generates multiple ads at once! (And soon with Seedance 2 on the tool ! which made it possible to create this extract) It also works with reference characters and storytelling visuals.

Using AI for promote Product in Ads with your original character ? It's possible ! My partner Ad Machine contacted me to tell me about their tool that lets you input your product into an AI model that generates multiple ads at once! (And soon with Seedance 2 on the tool ! which made it possible to create this extract) It also works with reference characters and storytelling visuals.

Anima

48,038 次观看 • 5 个月前

Jensen Huang says the PC is about to be reinvented, just like the phone became the smartphone In the future, every house has an AI supercomputer, like a home theater — running all your agents and assistants, working for you all the time "more like R2-D2 or C-3PO than a PC"

Jensen Huang says the PC is about to be reinvented, just like the phone became the smartphone In the future, every house has an AI supercomputer, like a home theater — running all your agents and assistants, working for you all the time "more like R2-D2 or C-3PO than a PC"

Haider.

16,718 次观看 • 2 个月前

Google just confirmed the first case of hackers using AI to build a zero-day exploit from scratch. An actual zero-day vulnerability that no human had EVER found before, discovered by an AI model, turned into a working weapon, and aimed at a mass exploitation campaign targeting thousands of systems simultaneously. Google's Threat Intelligence Group caught it yesterday and killed the operation before it scaled. But the details of how it worked are genuinely scary: The AI found a flaw in a popular two-factor authentication system that traditional security tools had missed entirely. The vulnerability was a logic error buried deep in the authentication flow where a developer had hard-coded a trust exception years ago. No human security researcher or automated scanner had caught it. The flaw was invisible to EVERY tool the cybersecurity industry has built over the past two decades. But the AI spotted it immediately. Then it wrote a full Python exploit script to weaponize it. Google's analysts could tell the code was AI-generated because it had textbook formatting, educational comments explaining every function, and even a hallucinated severity score that doesn't exist in any real database. The AI literally graded its own attack with a fake rating. So the code had MISTAKES in it. The criminals' implementation was clumsy enough that it probably interfered with the actual deployment. This was the sloppy first attempt by people who are still learning how to use these tools. And it still found a vulnerability that the entire cybersecurity industry missed. Google's chief threat analyst John Hultquist said: "There's a misconception that the AI vulnerability race is imminent. The reality is that it's already begun. For every zero-day we can trace back to AI, there are probably many more out there." But here's where it gets truly insane... This wasn't even a sophisticated operation. North Korea's APT45 hacking unit is sending thousands of repetitive prompts to AI models, recursively analyzing known vulnerabilities and building an entire exploit arsenal that would be physically impossible for human hackers to assemble at the same speed. They're essentially industrializing cyberattacks. A Chinese state-linked group jailbroke Google's own Gemini by simply asking it to "pretend to be a network security expert" and then used that persona to research how to hack TP-Link routers and corporate file transfer systems. Another Chinese group deployed autonomous AI agents that probed a Japanese tech firm with minimal human oversight, deciding on their own which tools to use and pivoting between targets based on internal reasoning. And then there's PROMPTSPY, an Android backdoor that calls Google's Gemini API to read your phone screen in real time, navigate your interface autonomously, capture your biometric data, replay your lock screen PIN, and block you from uninstalling it by placing an invisible overlay over the uninstall button. It literally OPERATES your phone using commercial AI tools anyone can access. Everyone spent the last 3 years arguing about whether AI would take people's jobs. Meanwhile AI is making every password, every firewall, and every two-factor authentication system on Earth fundamentally less secure. The entire $190 billion cybersecurity industry was built on one assumption: that finding vulnerabilities is hard and requires deep expertise. But AI just removed that assumption from the equation. And the scariest part is that Google said the criminals made errors this time. The implementation was rough and the campaign probably didn't fully work. These were amateurs, now imagine what professionals are able to do. There's a reason Sam Altman predicted an inevitable massive cyberattack THIS year. What do you think?

Google just confirmed the first case of hackers using AI to build a zero-day exploit from scratch. An actual zero-day vulnerability that no human had EVER found before, discovered by an AI model, turned into a working weapon, and aimed at a mass exploitation campaign targeting thousands of systems simultaneously. Google's Threat Intelligence Group caught it yesterday and killed the operation before it scaled. But the details of how it worked are genuinely scary: The AI found a flaw in a popular two-factor authentication system that traditional security tools had missed entirely. The vulnerability was a logic error buried deep in the authentication flow where a developer had hard-coded a trust exception years ago. No human security researcher or automated scanner had caught it. The flaw was invisible to EVERY tool the cybersecurity industry has built over the past two decades. But the AI spotted it immediately. Then it wrote a full Python exploit script to weaponize it. Google's analysts could tell the code was AI-generated because it had textbook formatting, educational comments explaining every function, and even a hallucinated severity score that doesn't exist in any real database. The AI literally graded its own attack with a fake rating. So the code had MISTAKES in it. The criminals' implementation was clumsy enough that it probably interfered with the actual deployment. This was the sloppy first attempt by people who are still learning how to use these tools. And it still found a vulnerability that the entire cybersecurity industry missed. Google's chief threat analyst John Hultquist said: "There's a misconception that the AI vulnerability race is imminent. The reality is that it's already begun. For every zero-day we can trace back to AI, there are probably many more out there." But here's where it gets truly insane... This wasn't even a sophisticated operation. North Korea's APT45 hacking unit is sending thousands of repetitive prompts to AI models, recursively analyzing known vulnerabilities and building an entire exploit arsenal that would be physically impossible for human hackers to assemble at the same speed. They're essentially industrializing cyberattacks. A Chinese state-linked group jailbroke Google's own Gemini by simply asking it to "pretend to be a network security expert" and then used that persona to research how to hack TP-Link routers and corporate file transfer systems. Another Chinese group deployed autonomous AI agents that probed a Japanese tech firm with minimal human oversight, deciding on their own which tools to use and pivoting between targets based on internal reasoning. And then there's PROMPTSPY, an Android backdoor that calls Google's Gemini API to read your phone screen in real time, navigate your interface autonomously, capture your biometric data, replay your lock screen PIN, and block you from uninstalling it by placing an invisible overlay over the uninstall button. It literally OPERATES your phone using commercial AI tools anyone can access. Everyone spent the last 3 years arguing about whether AI would take people's jobs. Meanwhile AI is making every password, every firewall, and every two-factor authentication system on Earth fundamentally less secure. The entire $190 billion cybersecurity industry was built on one assumption: that finding vulnerabilities is hard and requires deep expertise. But AI just removed that assumption from the equation. And the scariest part is that Google said the criminals made errors this time. The implementation was rough and the campaign probably didn't fully work. These were amateurs, now imagine what professionals are able to do. There's a reason Sam Altman predicted an inevitable massive cyberattack THIS year. What do you think?

Ricardo

50,564 次观看 • 3 个月前

Google just dropped a free coding tool that replaces your entire dev workflow. And nobody's talking about it. Here's what Google Antigravity does: → AI agents build full apps autonomously → Plans, codes, tests, fixes bugs automatically → Works across multiple files simultaneously → Opens browser and verifies everything works → 6 different AI models in one platform One developer built a working game in minutes. Another AI tool failed completely. Save this video, you'll understand where coding is headed. Want the SOP? DM me. 💬

Google just dropped a free coding tool that replaces your entire dev workflow. And nobody's talking about it. Here's what Google Antigravity does: → AI agents build full apps autonomously → Plans, codes, tests, fixes bugs automatically → Works across multiple files simultaneously → Opens browser and verifies everything works → 6 different AI models in one platform One developer built a working game in minutes. Another AI tool failed completely. Save this video, you'll understand where coding is headed. Want the SOP? DM me. 💬

Julian Goldie SEO

12,695 次观看 • 6 个月前

🚨 BREAKING: This AI doesn’t help hackers… it becomes one. Meet PentAGI — a fully autonomous AI Red Team that runs end-to-end attacks without human input. Think about this: • One agent maps the entire target (recon) • One finds & exploits real vulnerabilities • One writes a full pentest report like a senior expert No prompts. No supervision. Just execution. 100% open-source. Anyone can deploy it. This isn’t a tool — it’s an AI hacker team in a box. ⚠️ The gap between builders & attackers just got thinner. Bookmark this. Cybersecurity is entering a new era. Link👇

🚨 BREAKING: This AI doesn’t help hackers… it becomes one. Meet PentAGI — a fully autonomous AI Red Team that runs end-to-end attacks without human input. Think about this: • One agent maps the entire target (recon) • One finds & exploits real vulnerabilities • One writes a full pentest report like a senior expert No prompts. No supervision. Just execution. 100% open-source. Anyone can deploy it. This isn’t a tool — it’s an AI hacker team in a box. ⚠️ The gap between builders & attackers just got thinner. Bookmark this. Cybersecurity is entering a new era. Link👇

divyansh tiwari

16,341 次观看 • 4 个月前

> "In no scenario is it bad for the US to have frontier-class open-source models." > "Every time there’s a step-function improvement in AI, a human bottleneck emerges alongside it." > "Your desire to be liked sometimes takes away from your desire to do the right thing and seek the truth." > "Every job will get refactored. The people who aren’t AI fluent will have a very hard time finding jobs." Jeetu Patel (Jeetu Patel), President & Chief Product Officer at Cisco sat down for an expansive talk about life and the future. 00:00 AI, jobs, and human potential 00:41 AI cybersecurity and Cisco’s security models 06:33 Why Cisco released the models openly 08:08 Running AI models locally 10:12 Why people are negative about AI 12:14 Will humans always be needed? 14:56 Can curiosity and ambition be taught? 17:12 Passion vs. expertise 19:39 The importance of unlearning 23:52 How to find the truth 26:06 How to get people excited about AI 33:35 How open source affects the AI industry 35:07 Can open-source AI make money? 46:44 Are Chinese open-source models good for the US? 49:55 Should the US restrict Chinese AI models? 53:05 Does open source make humanity safer? 54:11 Advice for people worried about AI

> "In no scenario is it bad for the US to have frontier-class open-source models." > "Every time there’s a step-function improvement in AI, a human bottleneck emerges alongside it." > "Your desire to be liked sometimes takes away from your desire to do the right thing and seek the truth." > "Every job will get refactored. The people who aren’t AI fluent will have a very hard time finding jobs." Jeetu Patel (Jeetu Patel), President & Chief Product Officer at Cisco sat down for an expansive talk about life and the future. 00:00 AI, jobs, and human potential 00:41 AI cybersecurity and Cisco’s security models 06:33 Why Cisco released the models openly 08:08 Running AI models locally 10:12 Why people are negative about AI 12:14 Will humans always be needed? 14:56 Can curiosity and ambition be taught? 17:12 Passion vs. expertise 19:39 The importance of unlearning 23:52 How to find the truth 26:06 How to get people excited about AI 33:35 How open source affects the AI industry 35:07 Can open-source AI make money? 46:44 Are Chinese open-source models good for the US? 49:55 Should the US restrict Chinese AI models? 53:05 Does open source make humanity safer? 54:11 Advice for people worried about AI

Matthew Berman

68,268 次观看 • 11 天前

The accidental success of ai16z has catapulted AI agents and their transformational promise into the spotlight. .Shaw (spirit/acc), founder of Eliza Labs, talks about: 🔗 How the Eliza framework brings AI agents to every blockchain 📈 How ai16z is rethinking DAOs and decentralized investing 🌍 The societal shifts AI could bring—and who will control its value Timestamps: 00:00 Intro 03:01 Shaw’s inspiration for launching ai16z 08:45 How AI agents are evolving beyond simple tasks 10:28 The Eliza framework and its open-source impact 13:22 Can AI agents excel at trading? 21:19 Why Eliza works seamlessly across multiple blockchains 24:08 The story behind launching Marc Andreessen as an AI character 35:18 Plans for ai16z’s layer 1 and its future launchpad 40:23 Transforming AI agents into more than just “reply bots” 43:26 Shaw’s vision for AI’s role in shaping human society 49:26 Crypto News Recap Thank you to our sponsors! Kelp Polkadot

The accidental success of ai16z has catapulted AI agents and their transformational promise into the spotlight. .Shaw (spirit/acc), founder of Eliza Labs, talks about: 🔗 How the Eliza framework brings AI agents to every blockchain 📈 How ai16z is rethinking DAOs and decentralized investing 🌍 The societal shifts AI could bring—and who will control its value Timestamps: 00:00 Intro 03:01 Shaw’s inspiration for launching ai16z 08:45 How AI agents are evolving beyond simple tasks 10:28 The Eliza framework and its open-source impact 13:22 Can AI agents excel at trading? 21:19 Why Eliza works seamlessly across multiple blockchains 24:08 The story behind launching Marc Andreessen as an AI character 35:18 Plans for ai16z’s layer 1 and its future launchpad 40:23 Transforming AI agents into more than just “reply bots” 43:26 Shaw’s vision for AI’s role in shaping human society 49:26 Crypto News Recap Thank you to our sponsors! Kelp Polkadot

Laura Shin

216,192 次观看 • 1 年前

The "Old Way" of running a company is dead. 💀 Brian Armstrong just revealed how he’s using AI agents to run Coinbase 🛡️, and it’s a glimpse into the future of leadership. 1. Real-Time Monitoring 👁️ No more waiting for "quarterly reviews." Brian uses AI agents to synthesize Slack and emails in real-time. He can feel the "vibration" of the entire company and spot bottlenecks before they become crises. 2. The RAPID-D Framework 🤖 At Coinbase, AI has a seat at the decision table. Their "RAPID-D" system uses agents to debate strategy, challenge assumptions, and probe for weaknesses in every major proposal. The AI isn't just a tool; it’s a participant. 3. CEO Coaching 📈 Ever wonder if you’re focusing on the wrong thing? Brian uses AI to audit his own schedule. The AI compares his daily actions against the company's top goals and tells him exactly where he’s wasting time. 4. Adapt or Exit 🚪 The mandate was simple: "Learn AI coding in 7 days or you’re out." Armstrong fired engineers who refused to onboard. Result? 1/3 of Coinbase code is now AI-generated, headed for 50%. The Bottom Line: We are moving from "companies that use AI" to "Agentic Organizations." The information lag is being set to zero. ⚡ #Coinbase #AI #TechLeadership #BrianArmstrong #FutureOfWork

The "Old Way" of running a company is dead. 💀 Brian Armstrong just revealed how he’s using AI agents to run Coinbase 🛡️, and it’s a glimpse into the future of leadership. 1. Real-Time Monitoring 👁️ No more waiting for "quarterly reviews." Brian uses AI agents to synthesize Slack and emails in real-time. He can feel the "vibration" of the entire company and spot bottlenecks before they become crises. 2. The RAPID-D Framework 🤖 At Coinbase, AI has a seat at the decision table. Their "RAPID-D" system uses agents to debate strategy, challenge assumptions, and probe for weaknesses in every major proposal. The AI isn't just a tool; it’s a participant. 3. CEO Coaching 📈 Ever wonder if you’re focusing on the wrong thing? Brian uses AI to audit his own schedule. The AI compares his daily actions against the company's top goals and tells him exactly where he’s wasting time. 4. Adapt or Exit 🚪 The mandate was simple: "Learn AI coding in 7 days or you’re out." Armstrong fired engineers who refused to onboard. Result? 1/3 of Coinbase code is now AI-generated, headed for 50%. The Bottom Line: We are moving from "companies that use AI" to "Agentic Organizations." The information lag is being set to zero. ⚡ #Coinbase #AI #TechLeadership #BrianArmstrong #FutureOfWork

Jungle Inc | Markets & Future Systems

279,137 次观看 • 6 个月前

Free 3-hour course from an ex-Google engineer. AI agents, graph engineering, harness, agent loops. Covers more than most $500 paid courses. This is the exact playbook to learn how to actually build and monetize AI agents. Don't miss your shot, save it now. • 0:00 - Design an AI agent system from scratch • 7:38 - When your agent should hand off to a human • 19:27 - RAG and vector databases explained simply • 52:38 - Deploy your AI agent to Google Cloud • 1:25:57 - Turn AI agents into a paid business via WhatsApp • 1:33:00 - Turn conversations into real leads automatically • 2:24:01 - Loop engineering vs graphs, the real difference • 2:33:08 - Build your own multi-tool agent graph Save this video, because it's the only one that can actually take you to your $2,000+ profit.

Free 3-hour course from an ex-Google engineer. AI agents, graph engineering, harness, agent loops. Covers more than most $500 paid courses. This is the exact playbook to learn how to actually build and monetize AI agents. Don't miss your shot, save it now. • 0:00 - Design an AI agent system from scratch • 7:38 - When your agent should hand off to a human • 19:27 - RAG and vector databases explained simply • 52:38 - Deploy your AI agent to Google Cloud • 1:25:57 - Turn AI agents into a paid business via WhatsApp • 1:33:00 - Turn conversations into real leads automatically • 2:24:01 - Loop engineering vs graphs, the real difference • 2:33:08 - Build your own multi-tool agent graph Save this video, because it's the only one that can actually take you to your $2,000+ profit.

unicode

139,175 次观看 • 7 天前

Most CA firms still download GSTR-2B manually. One client at a time. Every month. I built an AI batch tool. Select FY → Add GSTINs → Enter CAPTCHA once. Everything downloads automatically. Want to automate your CA practice with AI? Join my free masterclass on 22 Feb, 11 AM. Comment your Email ID & I’ll send the link.

Most CA firms still download GSTR-2B manually. One client at a time. Every month. I built an AI batch tool. Select FY → Add GSTINs → Enter CAPTCHA once. Everything downloads automatically. Want to automate your CA practice with AI? Join my free masterclass on 22 Feb, 11 AM. Comment your Email ID & I’ll send the link.

Deepak Gupta

32,913 次观看 • 5 个月前

CBS News National Security Contributor Sam Vinograd says “every individual encountered at our borders is vetted,” but she believes the U.S. has “under-resourced” collecting foreign terrorism intelligence in other parts of the world, with gaps particularly in Central Asia. “So today, I am less concerned about an individual on our watch list somehow sneaking through our southern border than I am about a bad actor who is unknown to us.”

CBS News National Security Contributor Sam Vinograd says “every individual encountered at our borders is vetted,” but she believes the U.S. has “under-resourced” collecting foreign terrorism intelligence in other parts of the world, with gaps particularly in Central Asia. “So today, I am less concerned about an individual on our watch list somehow sneaking through our southern border than I am about a bad actor who is unknown to us.”

Face The Nation

55,697 次观看 • 2 年前

Ex-Google engineer just released a free 3-hour course on building and monetizing AI agents. How to go from one agent to a full system that finds leads and makes money: 00:00 - Design an AI agent system 07:38 - Add human handoffs 19:27 - Understand RAG and vector databases 52:38 - Deploy agents to Google Cloud 1:25:57 - Turn agents into a paid WhatsApp business 1:33:00 - Convert conversations into leads 2:24:01 - Learn loops vs graphs 2:33:08 - Build a multi-tool agent graph Most people are still building AI demos. This course shows the full stack: Agents → RAG → Deployment → Leads → Revenue Building agents is the old workflow. Monetizing agent systems is the new one. This 3-hour watch covers more than most $500 paid courses. Save it before everyone starts selling the same thing.

Ex-Google engineer just released a free 3-hour course on building and monetizing AI agents. How to go from one agent to a full system that finds leads and makes money: 00:00 - Design an AI agent system 07:38 - Add human handoffs 19:27 - Understand RAG and vector databases 52:38 - Deploy agents to Google Cloud 1:25:57 - Turn agents into a paid WhatsApp business 1:33:00 - Convert conversations into leads 2:24:01 - Learn loops vs graphs 2:33:08 - Build a multi-tool agent graph Most people are still building AI demos. This course shows the full stack: Agents → RAG → Deployment → Leads → Revenue Building agents is the old workflow. Monetizing agent systems is the new one. This 3-hour watch covers more than most $500 paid courses. Save it before everyone starts selling the same thing.

Lunar

327,586 次观看 • 5 天前

Jensen Huang doesn’t use AI to think less. He uses it to think past his own limits. Huang: “90% of my instructions are actually conflated with questions.” The man running a five 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.” Same question. Multiple models. Pit them against each other. Keep only what survives. Not because the machine can’t be trusted. Because challenging it is where the sharpest thinking happens. Huang: “The process of critiquing, criticizing the answers, applying your critical thinking, enhances cognitive skills.” AI doesn’t replace your thinking. It demands more of it than you’ve ever given. Every question takes reasoning. Every answer takes scrutiny. The machine isn’t thinking for you. It’s pulling thinking out of you that didn’t exist before you sat down. Huang: “In order to formulate good questions, you have to be thinking, you have to be analytical, you have to be reasoning yourself.” AI is not the shortcut everyone thinks it is. It is the most powerful cognitive amplifier ever built. It sharpens the engaged. It leaves the passive exactly where they started. Same tool. Same access. The only variable is what you bring to it. The world is debating whether AI will replace human thinking. Wrong conversation. The real question is what happens when a tool built to think for you becomes the thing that forces you to think beyond yourself. That’s not a threat to humanity. That’s the entire point.

Jensen Huang doesn’t use AI to think less. He uses it to think past his own limits. Huang: “90% of my instructions are actually conflated with questions.” The man running a five 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.” Same question. Multiple models. Pit them against each other. Keep only what survives. Not because the machine can’t be trusted. Because challenging it is where the sharpest thinking happens. Huang: “The process of critiquing, criticizing the answers, applying your critical thinking, enhances cognitive skills.” AI doesn’t replace your thinking. It demands more of it than you’ve ever given. Every question takes reasoning. Every answer takes scrutiny. The machine isn’t thinking for you. It’s pulling thinking out of you that didn’t exist before you sat down. Huang: “In order to formulate good questions, you have to be thinking, you have to be analytical, you have to be reasoning yourself.” AI is not the shortcut everyone thinks it is. It is the most powerful cognitive amplifier ever built. It sharpens the engaged. It leaves the passive exactly where they started. Same tool. Same access. The only variable is what you bring to it. The world is debating whether AI will replace human thinking. Wrong conversation. The real question is what happens when a tool built to think for you becomes the thing that forces you to think beyond yourself. That’s not a threat to humanity. That’s the entire point.

Dustin

19,819 次观看 • 27 天前

OPENAI 🚨: Early look at an upcoming Agent Studio for building and hosting configurable, always-on 24/7 agents on ChatGPT. The "Hermes" feature is tightly coupled with the existing Workflows builder on the OpenAI Platform, and you will also be able to open your Agents in the "Builder" tool. I hope users can assign these animated icons to their agents, too. AI Organizations are closer than you think 👀

OPENAI 🚨: Early look at an upcoming Agent Studio for building and hosting configurable, always-on 24/7 agents on ChatGPT. The "Hermes" feature is tightly coupled with the existing Workflows builder on the OpenAI Platform, and you will also be able to open your Agents in the "Builder" tool. I hope users can assign these animated icons to their agents, too. AI Organizations are closer than you think 👀

TestingCatalog News 🗞

171,238 次观看 • 3 个月前

My co-founder was spending 20+ hours per week handling sales calls So I built an AI clone of to replace him - + to create an interactive replica that asks questions related to the deal - o3 agent reads the transcript and finds identifies key qualification points - Leads get uploaded to our CRM and every interaction gets saved in AgentOps 🖇️ The tool took me less than a day to build at the hackathon. Automate the boring stuff with agents. DM/comment for access

My co-founder was spending 20+ hours per week handling sales calls So I built an AI clone of to replace him - + to create an interactive replica that asks questions related to the deal - o3 agent reads the transcript and finds identifies key qualification points - Leads get uploaded to our CRM and every interaction gets saved in AgentOps 🖇️ The tool took me less than a day to build at the hackathon. Automate the boring stuff with agents. DM/comment for access

Alex Reibman 🖇️

141,387 次观看 • 1 年前

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

MOST AI AGENTS RESET TO ZERO EVERY TIME YOU OPEN A NEW SESSION. Hermes Agent was built to do the opposite. Every task compounds. Every workflow becomes reusable. Every session teaches the next one. That is the core thesis behind Hermes, and it completely changes how AI agents work. Unlike most AI agents built by software tool companies, Hermes was created by the researchers training the Hermes model family itself. Meaning: The same system used internally to generate training data is now open source and available to everyone. One install gives you access to: Claude. GPT. Grok. Local models via Ollama. Telegram, Discord, Slack, iMessage integrations. Custom skills. Persistent memory. CLI control. But the real unlock is the compounding loop: You give Hermes a task. It records every tool call, decision, and result. Then it converts successful workflows into reusable skills automatically. A Hermes setup running for 3 months becomes fundamentally smarter than a fresh install. That’s the big idea. One of the coolest parts: You literally watch the agent evolve in real time from a blank install into a personalized AI operator. Instead of watching Netflix today, spend 28 mins with this. Follow Dami-Defi for more AI systems, agent workflows, and infrastructure alpha.

Dami-Defi

11,668 次观看 • 2 个月前