Mansoor Basha

Today on School for Startups Radio, we’re joined by Rafsan B. – Founder & CEO of OrionQ. Rafsan shares how AI-driven revenue intelligence is changing the way companies identify opportunity, optimize sales, and scale smarter. A forward-looking conversation for founders and leaders navigating growth in an AI-powered world. Discover the podcast link in the comments to tune in! This is brought to you by: LifeWave Corporate #AIAgentBuilder #RealEnvironmentalists #entrepreneurship #startuppodcast

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Learn to build conversational AI voice agents in "Building AI Voice Agents for Production", created in collaboration with LiveKit and RealAvatar, and taught by Russ d'Sa (Co-founder & CEO of LiveKit), Shayne Parmelee (Developer Advocate, LiveKit), and Nedelina Teneva, PhD (Head of AI at RealAvatar, an AI Fund portfolio company). Voice agents combine speech and reasoning capabilities to enable real-time conversations. They're already being used to support customer service, to improve accessibility in healthcare, for entertainment applications, and for talk therapy. In this course, you’ll learn to build voice agents that listen, reason, and respond naturally. You’ll follow the architecture used to create the "AI Andrew" Avatar, a collaborative project between DeepLearning.AI and RealAvatar that responds to users in what sounds like my voice. You’ll build a voice agent from scratch and deploy it to the cloud, enabling support for many simultaneous users. What you’ll learn: - Understand the fundamentals of voice agents, including key components like speech-to-text (STT), text-to-speech (TTS), and LLMs, and how latency is introduced at each layer. - Explore voice agent architectures and the trade-offs between modular pipelines and speech-to-speech APIs. - Explore how platforms like LiveKit mitigate latency issues with optimized networking infrastructure and low-latency communication protocols. - Learn how to connect client devices to voice agents using WebRTC—and why it outperforms HTTP and WebSocket for low-latency audio streaming. - Incorporate voice activity detection (VAD), end-of-turn detection, and context management to detect turns, handle interruptions, and manage conversational flow. - Understand the trade-offs between latency, quality, and cost in an example in which you build a voice agent and change its voice. - Equip your agent with metrics to measure latency at each stage of the voice pipeline and learn the key levers you can pull to make your agent faster and more responsive. The voice agents built in this course also incorporate voice technology from ElevenLabs, a supporting contributor to the project. By the end of this course, you'll have learned the components of an AI voice agent pipeline, combined them into a system with low-latency communication, and deployed them on cloud infrastructure so it scales to many users. I’m looking forward to seeing what voice agents you build from this course! Please sign up here: https://lnkd.in/gEBXAGH8

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The IBM/Confluent acquisition is a clear signal that real-time streaming is now foundational to enterprise AI. But it also raises a tough question: what happens when openness and independence become absorbed into a single vendor’s stack? If you're concerned about how this impacts you, I recommend this resource from Cloudera that explains the benefits of an independent, managed, containerized alternative: https://shorturl.at/LYcwD

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In an era of growing competition from streaming services, broadcasters are increasingly challenged to do more with less. Layered Division Multiplexing (LDM) has emerged as a key infrastructure solution, enabling public stations to maximize the utility of their limited spectrum while simultaneously delivering high-end artistic content and essential public services. LDM allows a single broadcast channel to be expanded into two distinct "layers": a robust core layer, optimized for local news, emergency alerts, and public safety information, and a high-capacity enhanced layer, capable of delivering 4K video, 8K art, or other rich cultural programming. By leveraging LDM, broadcasters can expand service offerings without the need for costly additional towers or spectrum allocations. For art-focused public services, the objective is to deliver museum-quality visuals, both at home and on public displays. Lifestyle art TVs designed for artistic visual experiences are ideal for this purpose, but their ability to reliably receive and decode these high-bandwidth signals has historically been limited. ATSC 3.0’s LDM standard provides a solution. Unlike compression technologies such as HEVC, which reduce the size of video data, LDM governs how the data is transmitted over the air. It enables broadcasters to send multiple layers of content simultaneously within the same RF channel, optimizing spectrum efficiency—the ability to transmit more data within a fixed 6 MHz channel. This combination of robust core services and high-bandwidth cultural content represents a transformative approach to public broadcasting, enhancing both service reliability and quality of viewer experience. https://lnkd.in/e4ghFqEC

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In an AI-enabled world, how our systems connect is becoming as crucial as what they connect. This insightful post from Glama.ai outlines why MCP (Model Context Protocol) matters—and why the old API paradigms may no longer suffice for agentic models. Instead of brittle REST endpoints and scattered schemas, MCP offers a unified, discovery-based, bidirectional protocol built for AI-first interoperability. It’s like moving from static documentation to GPS navigation for autonomous systems. Curious how this affects AI integration at scale? https://lnkd.in/gK9wB2gm #AIFoundation #AIInteroperability #MCP

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𝗪𝗵𝗲𝗻 𝗮𝗻 𝗔𝗜 “𝗮𝗴𝗲𝗻𝘁” 𝘀𝘁𝗮𝗿𝘁𝘀 𝗰𝗵𝗼𝗼𝘀𝗶𝗻𝗴 𝗼𝗻 𝗼𝘂𝗿 𝗯𝗲𝗵𝗮𝗹𝗳, 𝘄𝗵𝗼 𝗲𝘅𝗮𝗰𝘁𝗹𝘆 𝗶𝘀 𝗶𝘁 𝗮𝗰𝘁𝗶𝗻𝗴 𝗳𝗼𝗿? I’ve been genuinely intrigued by Ekow Nelson's recent Substack "𝗪𝗵𝗲𝗻 𝗧𝗼𝗼𝗹𝘀 𝗕𝗲𝗴𝗶𝗻 𝘁𝗼 𝗖𝗵𝗼𝗼𝘀𝗲" https://lnkd.in/d38BFaqT .. It’s a breath of fresh air amidst all the AI slop and raises some fascinating philosophical questions on the topic of human agency in the age of AI agents. 𝗔 𝗳𝗲𝘄 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 𝗲𝘀𝘀𝗮𝘆 𝘁𝗼 𝘁𝗲𝗮𝘀𝗲 𝘆𝗼𝘂:  • 𝗪𝗼𝗿𝗱𝘀 𝗺𝗮𝘁𝘁𝗲𝗿. “Agent” may not be the best term in use. Its cultural lexicology spans caustic chemical agents, pushy real estate agents, and, for some of us, The Matrix .. agents of conformity, control, and institutional power suppressing awakening.  • In the shift from “𝗧𝗼𝗼𝗹𝘀 𝘁𝗼 𝗔𝗰𝘁𝗼𝗿𝘀,” what remains meaningfully human and what silently becomes machine-owned?  • If agency becomes “thin” who truly owns intent, judgment, and consequence in practice?  • How do we prevent an “accountability vacuum” when action and responsibility no longer go together?  • In the “Passenger Paradox,” what does real control look like beyond merely stating a destination?  • And where should society draw the line on machine autonomy in life-and-death domains? I strongly encourage you to read the Substack. Sartre’s “𝘄𝗲 𝗮𝗿𝗲 𝗰𝗼𝗻𝗱𝗲𝗺𝗻𝗲𝗱 𝘁𝗼 𝗯𝗲 𝗳𝗿𝗲𝗲” kept echoing for me: the outsourcing of agency may feel like convenience, but the consequences won’t be shared. Freedom means we chose it and we own what follows! #AIAgents #AgenticAI #HumanAgency #Philosophy Francisco Goya - The Sleep of Reason Produces Monsters

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The latest episode of "Where AI Works" just aired. I was honored to discuss AI, technology, and business in an interview by Serguei Netessine, Sr. Vice Dean of Innovation at The Wharton School. We covered topics including strategies for new AI business models, shifts to AI platforms, and the cultural divide between AI adopters and skeptics. You can find the full podcast here: https://lnkd.in/gCjQnRhU #AI #Strategy #Businessmodels #innovation #Wharton  

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As the #telecom industry shifts toward open and #AI-driven RAN architectures, operators, vendors, and policymakers must navigate key challenges in software integration, location constraints, functional interoperability, and deployment complexities. This panel will speak with leaders from Vodafone, AMD and Rakuten Symphony on what is required to achieve a truly open, intelligent, and efficient #RAN ecosystem. Access Session: https://lnkd.in/eRzxGMm8, powered by NMG Media Dr.-Ing. Muslim Elkotob, Gilles Garcia, Mohammed Talaat

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“In under a year, nearly one million users chose Ai+, and that trust is what we’re building on.” #NovaPods and #NovaWatch are not standalone launches. They are part of a connected AIoT ecosystem designed to simplify everyday experiences through seamless integration and purposeful innovation. The focus is to build products that work intelligently together while delivering technology that solves, not complicates. With Ai+ Smartphone Pulse 2 launching on March 2, we are strengthening our smartphone portfolio while expanding this ecosystem with clarity and intent. Read the full article here: https://lnkd.in/g5zcTvuQ #ConnectedEcosystem #AIOT #Pulse2

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ATSC 3.0 broadcasters can soon use Kubernetes to add cloud native capabilities to their infrastructure. The impact of Kubernetes is especially important for ATSC 3.0 transport chain (such as DigiCaster) which converts TV station's studio output feeds into IP transmission signals. Cloud-native broadcast infrastructure is different from virtual architecture and uses Kubernetes to manage software containers. Kubernetes is an open-source orchestration platform designed to automate deployment, scaling, and operation of containerized applications, aka Containers. Containers are lightweight, standalone units that package up code and everything it needs to run it: the application, libraries, environment variables, and dependencies. The use of Kubernetes and Containers creates infrastructure that can thrive in distributed environments. In contrast virtual systems that rely on Virtual Machines (VMs) for isolation and resource management, leading to more overhead and slower operations. Today, June 6, 2025 Kubernetes is only 11 years old yet it's impact on IT worldwide is profound. By 2024 over 60% of enterprises have adopted Kubernetes, with estimates of over 90% by 2027. Source: https://lnkd.in/egyMukhq More information will be coming soon about DigiCAP's cloud native DigiCaster, the ATSC 3.0 transport chain. #kubernetes #containers #atsc3 #virtualmachines #broadcasters #digicap

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Dr. Ryuji Wakikawa, Vice President and Head of the Research Institute of Advanced Technology at SoftBank Group Corp., articulates a profound vision for AI-RAN, positioning it as a revolutionary paradigm shift for the telecommunications industry. He views this integration of Artificial Intelligence into Radio Access Networks (RAN) as essential for transforming traditional network infrastructure from conventional cost centers into intelligent, revenue-generating platforms, which is crucial for the immediate future of mobile communications. The convergence between AI and telecom presents an unprecedented opportunity for renewed US leadership globally. AI-for-RAN is improving spectral efficiency. AI-and-RAN monetizes the converged compute and communication resources and keeps data sovereign. Most importantly, AI-on-RAN brings intelligence closer to the edge, enabling Autonomy 2.0. Intelligent Infrastructure Economic Zones will drive our GDP past 4% and serve as the nervous system for American power projection! NVIDIA AI-RAN is the convergence of AI and the physical world. INTELLIGENT INFRASTRUCTURE supports NextG for DoD and Civil, FAA NextGen, Intelligent Transportation, Golden Dome, resilient grids, precise positioning, and autonomous systems. The U.S. Department of Homeland Security, the United States Department of War, and the U.S. Department of Transportation have championed INTELLIGENT INFRASTRUCTURE for decades to help scale the industry and secure our national sovereignty. https://lnkd.in/gEMbWPT9 The proposed Intelligent Infrastructure Commerce & Defense Act of 2026 (IICDA 2026) represents a critical legislative initiative designed not merely to upgrade public works, but to secure the economic sovereignty and national security of the United States in the era of Industry 4.0.  https://lnkd.in/gUWYVQwf Autonomy Institute

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Advancing E-Commerce with Agentic AI + Adobe Experience Cloud Sharing a quick glimpse of a concept I recently presented in Dentsu Global Services Developers' Meetup 2025—an Agentic AI–driven E-Commerce architecture that integrates seamlessly with Adobe Experience Cloud / AEM and similar CMS platforms. The model uses LLM-powered agents for: • Dynamic bundle generation • Real-time catalog + checkout orchestration • Continuous learning from customer signals By extending Adobe’s personalization, decisioning, and content capabilities with tool-using autonomous agents, brands can unlock: ⚡ Faster experience delivery ⚡ Deep behavioral personalization ⚡ Adaptive, self-optimizing shopping journeys Agentic AI is rapidly becoming the next layer of the Adobe-centric CX stack—and a key enabler for sustainable and scalable retail innovation. If you’re exploring the next wave of Sustainable Green transformations, happy to connect!

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🌟 AI at the Core. TechCo Reimagined. The winners of the next decade will not be those with the largest networks —but those with intelligence embedded at every transaction. The competitive moat in telecom will not be spectrum or scale alone — it will be intelligence. AI must move: - From dashboards → to decision engines - From analytics → to autonomous orchestration - From personalization → to hyper-contextual monetization The real transformation is structural: - AI embedded into BSS/CRM - AI-native charging and loyalty engines - Autonomous care - Dynamic pricing in real time TechCo isn’t a branding exercise. It’s an architectural shift. Circles #telcototechco https://lnkd.in/gbszQN5d

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