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Agentic AI isn’t just about capability anymore. It’s about control. Dr. Sameer Maskey breaks down one of the biggest challenges facing enterprise AI adoption: governance. As AI agents move beyond chatbots and begin accessing emails, contracts, Google Drive, DocuSign, and internal systems, the companies solving AI governance may become...

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What happens when enterprise AI evolves from “systems of record” to “systems of action”? #IBMPartner That’s the real story behind the IBM + Google Cloud partnership. At IBM Think, I spoke with Karan Sachdeva about: → WatsonX on Google Cloud Marketplace → OpenShift-enabled AI portability → HashiCorp-powered governance and security → IBM Orchestrate + Gemini integration Enterprises are building operational frameworks for autonomous AI agents. Governance, interoperability, and trust become more important than the models themselves. Watch the full conversation: #IBMPartner #IBMThink IBMPartners
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What happens when enterprise AI evolves from “systems of record” to “systems of action”? #IBMPartner That’s the real story behind the IBM + Google Cloud partnership. At IBM Think, I spoke with Karan Sachdeva about: → WatsonX on Google Cloud Marketplace → OpenShift-enabled AI portability → HashiCorp-powered governance and security → IBM Orchestrate + Gemini integration Enterprises are building operational frameworks for autonomous AI agents. Governance, interoperability, and trust become more important than the models themselves. Watch the full conversation: #IBMPartner #IBMThink IBMPartners

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"The smart contract knows the guardrails." - Dr. Leemon Baird The future of agentic payments relies on trusted rails. As AI agents begin transacting autonomously, programmable guardrails, verifiable execution, and transparent governance become essential for building trust at scale. That’s where Hedera comes in.

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Humans.ai

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1/ AI Agents in Web3? It’s just getting started. TARS AI 🤖 There are plenty of AI agent launchpads, but TARS is different. Think of it as the eBay of AI commodities—where anyone can create, trade, and evolve AI agents and beyond.

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AI agents are quickly becoming a new layer of the enterprise workforce. In our partner podcast episode with Salesforce, we explored what it takes to make that shift real. 3 key insights: • Enterprise content gives AI the context it needs • The biggest gains come from content-heavy workflows • Governance must scale as agents take action Dive into how Box + Salesforce are thinking about the future of enterprise AI →
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AI agents are quickly becoming a new layer of the enterprise workforce. In our partner podcast episode with Salesforce, we explored what it takes to make that shift real. 3 key insights: • Enterprise content gives AI the context it needs • The biggest gains come from content-heavy workflows • Governance must scale as agents take action Dive into how Box + Salesforce are thinking about the future of enterprise AI →

Box

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Y Combinator

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60% of companies expect to be transformed by AI within two years. But here's the reality: most are still bolting AI onto legacy workflows instead of reimagining how work gets done. That's not transformation—that's just expensive automation. Our latest research reveals what separates AI leaders from laggards. The companies winning with AI aren't just adopting new tools—they're redesigning how their business creates value from the ground up. The challenge: Most organizations are nowhere near putting AI at the center of their strategy. They're missing the exponential gains that come from true AI-first thinking. The solution: A complete playbook for IT leaders and CIOs ready to move at the speed of AI. 🎯 5 Core Principles of AI-First Companies: 1️⃣ AI as a capability expander — Enable work that wasn't possible before, not just faster versions of old tasks 2️⃣ Human-AI partnership — Augment human creativity and decision-making rather than replacing it 3️⃣ AI-native design — Build systems that seamlessly integrate thousands of AI agents working behind the scenes 4️⃣ Trust & governance foundation — Remember: "AI agents can't keep a secret"—never rely on AI to maintain core security models. 5️⃣ Data as strategic fuel — Transform unstructured content into your competitive advantage The companies implementing these principles today are building insurmountable competitive advantages. They're not just working faster—they're working in entirely new ways. Ready to lead your industry's AI transformation? 📖 Get the complete framework Want to explore the benefits? Get the full details here:
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60% of companies expect to be transformed by AI within two years. But here's the reality: most are still bolting AI onto legacy workflows instead of reimagining how work gets done. That's not transformation—that's just expensive automation. Our latest research reveals what separates AI leaders from laggards. The companies winning with AI aren't just adopting new tools—they're redesigning how their business creates value from the ground up. The challenge: Most organizations are nowhere near putting AI at the center of their strategy. They're missing the exponential gains that come from true AI-first thinking. The solution: A complete playbook for IT leaders and CIOs ready to move at the speed of AI. 🎯 5 Core Principles of AI-First Companies: 1️⃣ AI as a capability expander — Enable work that wasn't possible before, not just faster versions of old tasks 2️⃣ Human-AI partnership — Augment human creativity and decision-making rather than replacing it 3️⃣ AI-native design — Build systems that seamlessly integrate thousands of AI agents working behind the scenes 4️⃣ Trust & governance foundation — Remember: "AI agents can't keep a secret"—never rely on AI to maintain core security models. 5️⃣ Data as strategic fuel — Transform unstructured content into your competitive advantage The companies implementing these principles today are building insurmountable competitive advantages. They're not just working faster—they're working in entirely new ways. Ready to lead your industry's AI transformation? 📖 Get the complete framework Want to explore the benefits? Get the full details here:

Box

128,566 görüntüleme • 1 yıl önce

A recent Forrester study found that 55% of companies regret laying off human workers in favor of AI. ABC News' Mike Muse breaks down where companies may have miscalculated and which industries he expects will face the greatest disruption as AI continues to reshape the workforce.
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A recent Forrester study found that 55% of companies regret laying off human workers in favor of AI. ABC News' Mike Muse breaks down where companies may have miscalculated and which industries he expects will face the greatest disruption as AI continues to reshape the workforce.

ABC News

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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:
1:00

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

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Just watched Kai-Fu Lee 's interview on the US-China AI landscape. A few takeaways felt especially useful✌️: 1. The US is currently about 15 months ahead of China in frontier AI models. 2. Top US AI companies are like “geniuses trying to win the Nobel Prize,” while Chinese AI companies are more like “a group of smart kids forming a study group.” They still compete, but open source creates more shared learning. 3. China’s AI companies face a real monetization challenge in enterprise software. Many Chinese companies are less used to annual subscriptions or usage-based pricing, and still tend to think of software as project-based work. 4. For the same product, Western, Middle Eastern, and Central Asian companies may be willing to pay around 8x more than Chinese companies. That helps explain why many Chinese AI companies are expanding overseas. 5. China may produce many breakthrough AI consumer apps, because Chinese companies are especially strong at consumer apps, hardware, robotics, embodied AI, and AI-first devices. 6. The US may continue to lead in frontier models, while China may move faster in turning AI into products people actually use. 7. His advice for young people in the age of AI: you don’t necessarily need to become an engineer first. What matters more is accountability, taste, conviction, courage, and foresight. More👇
17:56

Just watched Kai-Fu Lee 's interview on the US-China AI landscape. A few takeaways felt especially useful✌️: 1. The US is currently about 15 months ahead of China in frontier AI models. 2. Top US AI companies are like “geniuses trying to win the Nobel Prize,” while Chinese AI companies are more like “a group of smart kids forming a study group.” They still compete, but open source creates more shared learning. 3. China’s AI companies face a real monetization challenge in enterprise software. Many Chinese companies are less used to annual subscriptions or usage-based pricing, and still tend to think of software as project-based work. 4. For the same product, Western, Middle Eastern, and Central Asian companies may be willing to pay around 8x more than Chinese companies. That helps explain why many Chinese AI companies are expanding overseas. 5. China may produce many breakthrough AI consumer apps, because Chinese companies are especially strong at consumer apps, hardware, robotics, embodied AI, and AI-first devices. 6. The US may continue to lead in frontier models, while China may move faster in turning AI into products people actually use. 7. His advice for young people in the age of AI: you don’t necessarily need to become an engineer first. What matters more is accountability, taste, conviction, courage, and foresight. More👇

Mia Bao

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WHERE THE ENTERPRISE AI STACK IS BEING BUILT 1. $PLTR building the orchestration layer of the AI economy through the control systems enterprises need before models can take real-world actions backed by a Rule of 40 score of 127 2. $CRWD, $PANW, $ZS & $RBRK building the security layer of the AI economy across endpoint, identity, Zero Trust & cyber recovery as every new agent, machine identity & AI-generated workflow expands the attack surface 3. $NET building the connectivity layer of the AI economy through the internet control plane that agents, APIs & inference traffic must move across in real time, with Cloudflare sitting behind over 20% of the web 4. $SNOW & $MDB building the data layer of the AI economy through the clean, structured, production-grade enterprise data systems that make AI usable inside real applications and workflows
2:23

WHERE THE ENTERPRISE AI STACK IS BEING BUILT 1. $PLTR building the orchestration layer of the AI economy through the control systems enterprises need before models can take real-world actions backed by a Rule of 40 score of 127 2. $CRWD, $PANW, $ZS & $RBRK building the security layer of the AI economy across endpoint, identity, Zero Trust & cyber recovery as every new agent, machine identity & AI-generated workflow expands the attack surface 3. $NET building the connectivity layer of the AI economy through the internet control plane that agents, APIs & inference traffic must move across in real time, with Cloudflare sitting behind over 20% of the web 4. $SNOW & $MDB building the data layer of the AI economy through the clean, structured, production-grade enterprise data systems that make AI usable inside real applications and workflows

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🚨 Everyone is chasing GPU stocks… but Cathie Wood thinks the AI boom’s hidden winners may be somewhere else 👀 Jeff Lutz 🔋 says CPUs could make a huge comeback as agentic AI and inference grow. He also points to a “hidden layer” of AI, the companies building the racks, cooling, wiring, and power systems behind massive data centers. Big picture: the next AI race may be won by whoever builds the infrastructure fast enough. $TSLA Cathie Wood
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🚨 Everyone is chasing GPU stocks… but Cathie Wood thinks the AI boom’s hidden winners may be somewhere else 👀 Jeff Lutz 🔋 says CPUs could make a huge comeback as agentic AI and inference grow. He also points to a “hidden layer” of AI, the companies building the racks, cooling, wiring, and power systems behind massive data centers. Big picture: the next AI race may be won by whoever builds the infrastructure fast enough. $TSLA Cathie Wood

Herbert Ong

28,884 görüntüleme • 2 ay önce

The latest State of AI in the Enterprise report from Box is out! One year ago, 8% of organizations described themselves as advanced or leading edge in AI. Today that figure is 64%. But adoption is not the same as impact. Half of leading edge companies report significant ROI. Among early stage organizations it is just 1 in 9. We surveyed 1,640 IT decision makers across the US, UK, France, and Japan to find out.
0:30

The latest State of AI in the Enterprise report from Box is out! One year ago, 8% of organizations described themselves as advanced or leading edge in AI. Today that figure is 64%. But adoption is not the same as impact. Half of leading edge companies report significant ROI. Among early stage organizations it is just 1 in 9. We surveyed 1,640 IT decision makers across the US, UK, France, and Japan to find out.

Box

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If you think Tesla’s biggest rivals are car companies, you’re missing the real battle! Elon isn’t really fighting BYD or Waymo. He’s up against Alphabet! Google is building a full AI stack: its own chips, models, data centers, software, and robots, with $180B+ in spending this year. Elon Musk is doing the same across Tesla, xAI, and SpaceX. This isn’t about robotaxis. It’s about who controls the AI stack of the future! 🔥 $TSLA $GOOG Cern Basher
30:13

If you think Tesla’s biggest rivals are car companies, you’re missing the real battle! Elon isn’t really fighting BYD or Waymo. He’s up against Alphabet! Google is building a full AI stack: its own chips, models, data centers, software, and robots, with $180B+ in spending this year. Elon Musk is doing the same across Tesla, xAI, and SpaceX. This isn’t about robotaxis. It’s about who controls the AI stack of the future! 🔥 $TSLA $GOOG Cern Basher

Herbert Ong

43,097 görüntüleme • 5 ay önce

Big News - DAO Governance Is Coming 📢 The next phase of Lightchain AI isn’t just about powerful AI features — it’s about who controls them. In this video, you’ll see Our AI in action, running fresh prompts and showing off the chat experience A preview of the DAO dashboard, where proposals can be created and voted on How governance is fully in the hands of the community This is a crucial moment- before mainnet, the DAO will launch, and you’ll set the rules that shape Lightchain AI from the start.And remember — the very first proposals, where you decide, will shape the entire platform for Lightchain AI. The future of decentralized AI starts with you. #Lightchain #AI #Crypto
0:51

Big News - DAO Governance Is Coming 📢 The next phase of Lightchain AI isn’t just about powerful AI features — it’s about who controls them. In this video, you’ll see Our AI in action, running fresh prompts and showing off the chat experience A preview of the DAO dashboard, where proposals can be created and voted on How governance is fully in the hands of the community This is a crucial moment- before mainnet, the DAO will launch, and you’ll set the rules that shape Lightchain AI from the start.And remember — the very first proposals, where you decide, will shape the entire platform for Lightchain AI. The future of decentralized AI starts with you. #Lightchain #AI #Crypto

Lightchain AI

18,329 görüntüleme • 11 ay önce