Hongsen He

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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A friend of my colleague from Google, who’s based in the US, has just interviewed for the E4 role at Meta. The total package on the table was up to ($260-270k ~ 2.7 Cr) Sharing his interview experience for everyone preparing for interviews right now: 1. Technical screen – pure DSA - 45 minutes - 2 problems straight from Meta’s “Top 25 in last 3 months” on LeetCode - Code could run, but there were almost no test cases - He first explained the approach out loud, wrote it as comments, then coded and walked through examples He cleared this, then got the final loop. 2. Final loop DSA round - Another 45-minute DSA interview - Difficulty very similar to the screen - This time code could not be executed, so clarity of reasoning mattered more than speed - He still did 2 problems, 10 to 15 minutes each, and spent the rest of the time explaining trade offs 3. AI coding round - Given a small codebase with functions to fix or implement - 4 tasks, he fully solved 3 and explained the approach for the last one - AI could help read the code and give context, but not solve details, so fundamentals still mattered 4. System design - 45 minutes - One of the most common Meta questions from HelloInterview - They used Excalidraw, he followed a strict delivery framework and kept asking for feedback as he went - Clear trade offs, scaling discussion, and follow ups on high traffic cases Before we move forward, I also want to tell you about our latest addition to Layrs. The AI based interview tools for system design and DSA are live and free to try: layrs.me/interviews You can run DSA mocks that pick real interview-style questions, get follow-up questions step by step, and get instant feedback on structure and coding. For system design, you can practice delivery on real prompts, draw designs, and get nudges on coverage gaps before you sit in front of an interviewer. 5. Behavioral and the surprise twist - 45 minute behavioral - He under prepared, thought “tech is what really matters” - Feedback after debrief: very strong technical signals, but too many missing signals on behavioral - Meta asked for a behavioral follow up - He then spent a week building strong STAR plus learning stories, did a focused follow up round, and only then cleared into team matching The point is simple. For roles at this level, you cannot treat DSA, system design, AI coding and behavioral as optional sliders. All four show up, and any one of them can decide the outcome.

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Microsoft Just Made 100B Parameter LLMs Run on Your Laptop. Who Governs Them? BitNet breaks the GPU barrier. 1.58 bit quantization. 100 billion parameters on a single CPU. No cloud. No API costs. Local inference at human reading speed. This is a genuine breakthrough for accessibility. But accessibility without governance is liability. Running locally solves the infrastructure problem. It does not solve the governance problem. A 100B parameter model on your laptop can still hallucinate with confidence. It can still produce biased outputs. It can still make decisions with no audit trail. It can still violate constitutional bounds you never defined. Privacy from cloud providers is not the same as privacy from the model itself. Local execution means your data stays on your device. It does not mean the model operates within governance constraints. The question is not where the model runs. The question is whether the model can prove it operated within bounds. YIN-GATEWAY solves this. YIN-GATEWAY is a cryptographic control plane that sits between any LLM and its users. Cloud model, local model, quantized model, full precision model. The deployment changes. The governance requirement does not. Layer 2 Admissibility Gates reject non-compliant queries before execution. The model never sees requests that violate policy. Layer 3 Constitutional Bounds verify every output before it reaches users. If the output would violate governance constraints, it does not proceed. Layer 14 SENTINEL Verification runs independent binary checkpoint validation. Pass or fail. No partial compliance. Layer 15 Human Override requires cryptographic signatures before high-risk outputs proceed. Not a checkbox. A mathematical proof that a human authorized this specific action. BitNet gives you a 100B parameter model on your CPU. YIN-GATEWAY gives you cryptographic proof that the model operated within constitutional bounds, regardless of where it runs. The hardware revolution is here. The governance layer was already built. https://lnkd.in/eb2EdEwR 32 USPTO applications. 3,057 claims. Any model. One governance layer. Enforced behavior. #BitNet #YINMazariArchitecture #YINGATEWAY #AIGovernance #CryptographicCompliance #Microsoft #LocalAI #LLM #PrivacyPreserving #ResponsibleAI #EdgeAI #CPUInference #OpenSource

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🎉 New paper from #NVIDIAResearch 🧩 Puzzle: Distillation-Based NAS for Inference-Optimized LLMs+ Puzzle is a distillation-based NAS approach, that transforms trained LLMs into far more efficient, inference-aware (heterogeneous) architectures.

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Time to stop spreading incorrect inferences of Trump's new order regarding H1B visas. It is important to cut through the confusion with facts, not speculation. ✅ The $100,000 annual fee applies to H1B entries (new and current holders), not current holders already in the US ✅ Current H1B holders can remain, but face restrictions if they travel and re-enter Displaced Talent ≠ Automatically harnessed Talent. Singing a celebratory note on how this is "good for India" is premature. Brain drain reversal requires intense, long term work to transform Infrastructure, Policy, Monetary and Innovation ecosystem. Things are changing in India, but there's still a lot of work required. 💡 Talent is Borderless and Fluid. There are many other countries, actively courting tech talent. If the US becomes prohibitively expensive or unwelcoming, talent will migrate elsewhere. ❤️ Spare a thought to families caught mid-travel, professionals with established lives, students planning their futures. Such sudden events create genuine hardship and life-changing disruption. It's good to debate policy merits but we need to maintain empathy for those affected. #H1BVisa #Immigration #TalentMigration #Policy #TechWorkers #GlobalTalent

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🗣 Google's ex-CEO Eric Schmidt talks about how his whole early life was basically coding, and how AI just wiped it out. He says in his 20s all he wanted to do was write programs, all the way through college and grad school, and that this is what built his career. But now, every single thing he learned back then can be done by AI. "Each and every one of you has a supercomputer and superprogrammer in your pocket."

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✈️ US H-1B Visa Update: The $100,000 Sponsorship Fee 💰 There’s a major update to the H-1B program that could impact many professionals and employers. Starting September 21, 2025, companies that want to sponsor new H-1B workers from abroad will need to pay a $100,000 fee per petition. 📅 This change will be in place for 12 months (until September 20, 2026) unless extended. ✅ It applies only to new petitions filed after the effective date. ❌ It does not apply to current H-1B holders already in the U.S., to renewals or extensions, or to petitions filed before September 21. What does this mean in practice? 🤔 Employers may become more selective in offering sponsorships, especially smaller companies that may find the cost challenging. Candidates outside the U.S. who are waiting for H-1B approval or consular processing could be directly affected. This rule may increase the focus on highly skilled and highly paid positions, as organizations weigh the value of sponsorship. For professionals, the key steps are: 👉 Confirm with your employer whether your petition is being filed before the deadline. 👉 Clarify who will cover the cost if it applies. 👉 Stay updated through official USCIS and DHS announcements. 👉 Always keep backup options in mind. 🌍 Visa journeys are never simple. They test resilience, patience, and adaptability. But staying informed gives you the power to plan better and make smarter decisions. If you or someone you know is impacted by this change, share your thoughts below. Let’s support each other through these updates. 💬 #H1B #Immigration #VisaUpdates #CareerPlanning #Resilience

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When preparation meets process gaps 🤔 I spent a week preparing for an interview: system design, algorithms, and deep dives into my past projects. Then the first question was about sponsorship. I shared transparently: I am authorized to work in the US for up to 3 years on OPT, and I would need H1B sponsorship in the future. I had also disclosed this during the application. The interview ended immediately. Disappointing, yes. But it reinforced something important Clear alignment upfront saves time and keeps hiring focused on engineering ability and impact. Here is what I bring to engineering teams Scale and reliability 🚀 Scaled distributed systems to 50K plus daily requests at 99.9% uptime ⚡ Improved processing speed by 92% with multi threaded Java pipelines 💰 Delivered 1.2M in annual savings through performance optimization Cloud and modern engineering 🔧 Built production systems using Java, Kotlin, Python, Node.js, Spring Boot, AWS, Kubernetes, Docker, Redis, PostgreSQL 🛠 Strengthened delivery with CI CD, testing, observability, and security hardening, including eliminating 500-plus critical vulnerabilities AI and applied learning 🤖 Built an AI Q and A chatbot using Llama 3.1 on edge serverless infrastructure 🎓 MS Computer Science, AI specialization, 4.0 GPA Leadership 👨‍🏫 Mentoring 200 plus students in Database Systems and OOP, running labs and code reviews Recent builds • Distributed URL shortener with under 50ms p95 latency at 1K requests per second • Crash-safe key-value database in C with 20K plus ops per second • AI powered Q and A chatbot with persistent conversation history I am open to Software Engineer roles and can work on OPT for up to 3 years. For the right long-term fit, I will require sponsorship in the future. For recruiting teams: if sponsorship is not available, confirming it before interviews helps both sides invest time meaningfully. #OpenToWork #SoftwareEngineering #DistributedSystems #CloudNative #AWS #Kubernetes #ArtificialIntelligence #OPT

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