Loading video...

Video Failed to Load

Go Home

Stop settling for one-click AI dubbing. If you're serious about creating multilingual content, VMEG AI gives you complete control over every step—from transcription and translation to voice refinement, subtitle editing, and timeline synchronization. 🎬 Built for long-form videos, movies, documentaries, online courses, and enterprise-scale localization. ✨ Why VMEG AI...

12,960 views • 8 days ago •via X (Twitter)

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

🚀 Here’s more on AgentCore, launched today: If AI agents are going to transform how we work and live, developers need the right set of tools to move them from prototype to production at scale. Today, I'm thrilled to announce Amazon Bedrock AgentCore, a comprehensive set of services to deploy and operate highly capable agents securely at scale. The journey from prototype to production for AI agents has been filled with complex infrastructure challenges. Teams spend months building secure runtime environments, implementing memory systems, and creating monitoring solutions. AgentCore eliminates this undifferentiated heavy lifting, with fully-managed, modular services - providing everything you need to operate trustworthy agents. What makes AgentCore powerful: 🟠 Complete Development Flexibility: Build agents your way using any framework and any model, and work with any protocol (including MCP and A2A) - all while maintaining enterprise-grade security and control 🟠 Purpose-Built Infrastructure: First serverless runtime to offer framework-agnostic flexibility, complete session isolation, and industry-leading 8-hour workload support 🟠 Trust and Reliability: Built on AWS's proven security foundation with built-in identity controls and strict security boundaries for operating agents at scale 🟠 Composable Services: Use exactly what you need independently or together, paying only for what you use as your needs evolve AgentCore represents a significant milestone in our mission to make advanced AI accessible and practical for every organization. Whether you're just starting with AI agents or scaling enterprise-wide implementations, AgentCore gives you the foundation to build with confidence. This is just the beginning of our journey to enable an agentic future. Can't wait to see the transformative solutions you'll build with AgentCore! Bring your AI agents to life at scale – learn more about AgentCore today. Amazon Web Services #AmazonBedrock #AgentCore

Swami Sivasubramanian

11,646 views • 1 year ago

It's not every day I get to interview a former principal scientist who worked at Google, and is a Professor Emeritus at Stanford University, about the state of AI. But here we go. Introducing an hour with Yoav Shoham, Yoav Shoham, AI pioneer and cofounder of AI21 Labs . This will make you smarter, not that all my videos aren't that way. :-) ++++++++++++++++++ Here's what we discussed (this part was written by Chat GPT after I gave it the transcript of the video): 🚀 The State of AI Today •The pace of AI development is unprecedented, likened to a “universal firehose” of innovation. •Everyone—from your plumber to enterprise CTOs—is using AI. But not all use cases are equal or enterprise-ready. 🏢 Enterprise vs Consumer AI •Enterprise adoption is still slow compared to consumer. Shoham cites AWS data showing only 6% of AI pilots go into production. •Enterprises demand reliability, cost control, and explainability, which raw LLMs like ChatGPT don’t fully offer out of the box. 🧱 Beyond the LLM Hype •Shoham explains that pure LLMs aren’t enough. Enterprises need “compound AI systems” or “AI agents” that: •Use tools like calculators for arithmetic instead of relying on the model •Integrate with company databases via RAG (retrieval-augmented generation) •Plan, reason, and execute tasks through orchestrated workflows •AI21 Labs built Maestro, their orchestration system, to do exactly this. 🔐 Enterprise Concerns •Enterprises worry about IP leakage, data privacy, and hallucinations. •AI21 addresses this by running models on-prem or in VPCs, ensuring data doesn’t leave customer control. 📉 Why Models Still Fail •LLMs generate “authoritative bullshit” — convincing but wrong answers. •Shoham says “prompt-and-pray” doesn’t work for serious business tasks. •Real-world enterprise deployments need robust evaluation frameworks, not just leaderboards. 📊 Case Study: French Retailer Auchan •Auchan deployed AI21’s system to automatically generate product descriptions—a clear ROI, but required careful iteration to build trust. 🧰 What’s Next in AI21’s R&D •Working on planning systems, action models, and ways to estimate cost/accuracy trade-offs before running tasks. •Focused on enterprise AI orchestration, not flashy multimodal generation. ⚠️ Agent Washing Warning •Shoham warns against the buzzword “agent” being overused. His advice: “Translate ‘AI agent’ to ‘software system that does X.’ If it still makes sense, keep going.” 🤖 The Human-AI Hybrid Future •Shoham sees a world of hybrid teams: humans and AI agents working together. •This transformation will affect everything from org charts to HR policies. •The AI-powered worker is scalable, reliable, and multilingual — changing customer service, operations, and more. 🗣️ Closing Thoughts •Enterprise leaders need to move beyond the fear and hype to start small, test carefully, and scale based on value. •“AI won’t replace humans,” Shoham says, “but humans using AI will replace those who don’t.”

Robert Scoble

44,061 views • 1 year ago

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 views • 11 months ago