Christopher Aziz

Podonos just raised $2.4 million in pre-seed funding, and the signal is loud and clear: the voice AI industry finally has someone measuring the sound, not just making the noise. Based in Los Gatos, Podonos is building the infrastructure layer that decides whether voice AI feels real, human, and ready for primetime. The industry is racing toward a projected $47.5 billion by 2034, but growth without standards is chaos. Podonos is making sure the hype actually holds up when you press play. At the center is ✦Soohyun Bae, PhD in Computer Engineering from Georgia Institute of Technology and Y Combinator W22 alumnus. His track record stretches from engineering roles at Google Maps to leading AR mapping at Niantic, plus co-founding Bobidi and TickTock AI. He has seen what happens when technology scales without proper #guardrails. With Podonos, he's betting the future of AI isn't just about how smart the models get, but how believable and trustworthy they sound. Podonos evaluates models across naturalness, similarity, emotion, recognition accuracy, pronunciation, tone, and resilience. Add in #personaconsistency, and suddenly you're not just testing machines, you're testing their ability to pass as human. The twist? They deliver results in under twelve hours, when the legacy approach drags on for two months. In AI time, that's the difference between relevance and irrelevance. Investors caught the beat. Serac Ventures, led by Kevin Moore, took the lead, backed by NAVER D2SF, the venture arm of South Korea's NAVER, and KAIST Venture Investment Holdings. Together, they've now backed Podonos twice, with this $2.4 million round stacking on top of a $750,000 raise in March 2025. Total funding sits at $3.15 million, and every dollar is pointed toward scaling #engineering, refining #analysistools, and launching into the U.S., Europe, and Southeast Asia. This isn't theory. Podonos already serves Resemble AI, Play AI, and Sanas AI, hitting six-digit ARR by November 2024 with just four employees. Their secret weapon is reach: 150,000 evaluators spread across nine languages and thirteen locales, forming a human-in-the-loop platform that blends speed, rigor, and global coverage. That reach lets Podonos deliver evaluations at a scale and pace that no competitor has matched. The strategy is ambitious: expand into high-demand sectors like #healthcare, #finance, #gaming, and #advertising, then move beyond voice into #multimodal model evaluation, spanning video AI and large language models. The mission isn't just to check if AI works, it's to decide if AI works for people. #Startups #StartupFunding #EarlyStage #VentureCapital #PreSeed #AI #AIInfrastructure #Voice #VoiceAI #VoiceTech #Infrastructure #Technology #Innovation #TechEcosystem #StartupEcosystem #Hiring #TechHiring If software engineering peace of mind is what you crave, Vention is your zen.

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Do you know what is being built by the "king of inference," NVIDIA? I spent part of my holiday feeding my inner tech nerd and catching up on NVIDIA GTC 2026. It did not disappoint. GTC ran March 16–19 in San Jose, California. A couple of things stood out for me from Jensen Huang's keynote which lasted for almost three hours. The scale of what NVIDIA is building is hard to ignore. They now expect at least $1 trillion in AI infrastructure revenue between 2025 and 2027, double what they had projected before. The Blackwell Ultra chips, the Vera Rubin architecture coming next, NVIDIA Dynamo for running AI at scale. This is not a company iterating slowly. Things are moving fast. OpenClaw was another highlight. In simple terms it is a platform that allows AI agents to actually do things on your behalf. For businesses this means automating workflows, handling customer interactions, managing operations and freeing up time for the work that actually needs a human. We are moving from asking AI questions to AI actually handling tasks for you. The physical AI section was my favourite part. Mercedes, Toyota, BYD, GM, Hyundai all building autonomous vehicles on NVIDIA platforms. Uber rolling out robotaxis across 28 cities. Robotics partnerships with ABB, FANUC, KUKA, Figure and others putting AI into factories and real world environments. And then Jensen brought Disney's Olaf robot on stage. Actually walking. On stage. I did not see that coming and I loved every second of it. On sovereign AI, Japan, France, Saudi Arabia, India, the UK were all named as countries partnering with NVIDIA to build their own national AI infrastructure. Africa is actually in the mix through Cassava Technologies. They are building NVIDIA-powered AI Factories starting in South Africa, with Kenya, Egypt, Morocco and Nigeria next in line. Beyond the infrastructure, they are working with African governments on national AI initiatives, training local startups, building AI models in African languages and developing use cases around agriculture, healthcare and mobile payments. Honestly, I was glad to see this and it is one I am keen to monitor. I am excited about where all of this is heading, genuinely. But I am also aware that the pace of innovation brings with it real questions around safety, governance and who gets to participate. Should we be excited about these developments or more worried? I would love to hear your thoughts. #NvidiaGTC2026 #AI #PhysicalAI #SovereignAI #CassavaTechnologies #AfricaTech #Innovation #FutureOfAI

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The best way to predict Nvidia's next move isn't their earnings calls. It's their investment portfolio. They backed OpenAI, Anthropic, and Cursor before anyone was paying attention. Now they're writing checks into companies most people haven't heard of yet. Ayar Labs — $155M round (Dec 2024) They're replacing copper wires in data centers with light. Literally. Their optical interconnects move data faster with less power. AMD, Intel, and Nvidia all participated in the same round. When three competitors agree on something, pay attention. Sandbox AQ — $150M round (April 2024) Spun out of Google. Building "large quantitative models" for complex numerical analysis. Now valued at $5.75B. The bet here is that not everything in AI is about language models. Hippocratic AI — $141M Series B (Jan 2024) Healthcare LLMs for non-diagnostic tasks like pre-op procedures and patient monitoring. Valued at $1.64B, now at $3.5B after another raise. Weka — $140M round (May 2024) AI-native data management. Training models is only as good as how fast you can feed them data. Runway — $308M round (April 2024) Generative AI for video and media production. Valued at $3.55B. Nvidia's been in since 2023. Bright Machines — $126M Series C (June 2024) Smart robotics and AI-driven manufacturing software. Physical world automation. Kore AI — $150M round (Dec 2023) Enterprise AI chatbots before ChatGPT made it trendy. Reka AI — $110M round (July 2024) Multimodal AI research lab now valued at $1B+. But the most interesting one is Enfabrica. Nvidia participated in their $125M Series B back in September 2023. The company builds networking chips that can unify 100,000+ GPUs into a single computing system. Then in September 2025, Nvidia spent $900M to acquihire the CEO and license the technology. If you want to understand where Nvidia thinks AI is going, don't just watch their chip announcements. Watch where they're putting money 2+ years before anyone else notices.

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Anysphere, maker of AI coding assistant Cursor, has reportedly raised $900M at a $9B valuation, led by Thrive Capital, with participation from a16z and Accel, according to the Financial Times. Previously, Cursor raised $100M at a $2.6B valuation. The startup has now raised over $173M. Investors like Index Ventures and Benchmark are eager to join, but existing backers are doubling down. Rival AI coding startup Windsurf is also seeking funding at a $3B valuation. #AI #CursorAI #Anysphere #AIStartups #TechFunding #DealonAI

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AI Agents are taking over --not just in the digital world but in the physical world. Waymo, which is the physical manifestation of an AI agent (can sense the environment, determine a course of action, completes action, non-deterministic, learns over time, orchestrates with others in network) is taking over SF, and has apparently already bypassed Lyft rider adoption, and is easting up the Uber market share. So why is Waymo winning the war? I gave Fast Company my take, (link in comments)

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𝗠𝗶𝗰𝗵𝗶 𝗞𝗮𝗸𝘂 14 𝗬𝗲𝗮𝗿𝘀 𝗮𝗴𝗼 𝘁𝗮𝗹𝗸𝗲𝗱 𝗮𝗯𝗼𝘂𝘁 𝗔𝗺𝗲𝗿𝗶𝗰𝗮'𝘀 𝗦𝗲𝗰𝗿𝗲𝘁 𝗪𝗲𝗮𝗽𝗼𝗻 For decades, the H-1B visa has been the beating heart of America’s innovation engine powering Silicon Valley, biotech labs, AI think tanks, and Wall Street firms. It has brought the brightest minds from India, China, and beyond, filling critical skill gaps and fueling breakthroughs that reshape the world. But here’s the paradox: 📌 Only 85,000 visas are issued each year. 📌 Applications? Several hundred thousand. ➡ The result: a lottery system where dreams of global talent rise and fall like dice on a casino table. For professionals, H-1B is both a golden ticket and a gamble: ✨ Career acceleration & global exposure ✨ A pathway to U.S. residency ⚠️ But also: brutal uncertainty, strict deadlines, and employer dependence that can make or break lives overnight. For companies, it’s a lifeline keeping America competitive in AI, cybersecurity, biotech, and the next industrial revolutions. Without it, the U.S. risks brain drain, ceding ground to rising tech hubs abroad. Yet, the H-1B remains a political battleground: 🔥 Critics argue it suppresses wages and sidelines American workers. 🔥 Supporters insist it’s the only way to maintain U.S. dominance in innovation. 🔥 Policymakers are caught in a tug-of-war between protecting local jobs and fueling global leadership. At its core, the H-1B isn’t just a visa it’s a mirror reflecting America’s struggle: 🌍 𝗢𝗽𝗲𝗻𝗻𝗲𝘀𝘀 𝘃𝘀. 𝗣𝗿𝗼𝘁𝗲𝗰𝘁𝗶𝗼𝗻𝗶𝘀𝗺 ⚖️ 𝗙𝗮𝗶𝗿𝗻𝗲𝘀𝘀 𝘃𝘀. 𝗖𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗶𝘃𝗲𝗻𝗲𝘀𝘀 🚀 𝗡𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗷𝗼𝗯𝘀 𝘃𝘀. 𝗚𝗹𝗼𝗯𝗮𝗹 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 So the real question is: Should the H-1B system expand, reform, or remain the same? Because the answer won’t just decide the fate of immigrants it may decide America’s place in the future of global power. 💯💯 LinkedIn | Krishna Joshi #H1B #Immigration #Innovation #Tech #GlobalTalent #Policy #SiliconValley #India #China #USA #LinkedInCommunity

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The hot stuff in startups and ai labs right now for those not in sf is computer use rl environments for X where X is ecomm, finance etc. Computer use means ai that controls the browser, rl environments means training usually post because only 6 companies can afford to do pre, and for X means trying to copy what a human does like checking out on amazon or making a dominos order If you guys heard of mercor they are at $900mn/yr annual run rate, they took scale ai’s contracts from ai labs after scale ai got meta acquisition. There are now about 20 startups in sf that are now taking mercors contracts from ai labs under the next new thing: “computer use rl env for x” Crazy thing is some of these 20 companies that are building computer use rl environments for x are started by new grads and hiring like crazy. So sometimes they dont care even if you know anything related (rl env, ml infra, etc) they just want the most directionally cracked people and betting on raw intelligence and agency and are willing to pay same at quant base (if you are really good). “So do you need a masters for any of this?” HELL NO. trust. Happy to make an email intro to anyone interested just msg me on LinkedIn Thoughts on this?

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🎉 Thrilled to snag a Top 5 finish at the inaugural Cognee AI-Memory Hackathon yesterday at Pebblebed in SF! 🚀 In the finance world, outdated "beliefs" like an expired vendor discount or a customer's reduced credit limit can lead to wrong decisions and costly errors for the company. Enter Memory Drift Detector Instead of just querying a knowledge graph, it audits the AI's own "belief system" over time, flagging contradictions like outdated discounts before they hit your bottom line. Using Cognee's retriever + Distil Labs SLM, it extracts beliefs from a 14k-node, 56k-edge graph on finance data (vendors, invoices, payments, SKUs) and stores them as vectors in Qdrant. It matches new invoice claims semantically, scores contradictions, flags them on a dashboard, and auto-corrects with one click. Example: A vendor discount belief dropped from 73% to 5% confidence after four conflicting invoices Shout out to cognee, pebblebed, Qdrant , distil labs, DigitalOcean Shout out to Vasilije Markovic , Elizabeth (Lizzie) Siegle, Thierry Damiba, Daniel Scott #AI #Hackathon #Cognee #digitalocean #qdrant #SanFrancisco #MachineLearning

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