The CEO Behind the Fastest-Growing AI Inference Company | Tuhin Srivastava

The CEO Behind the Fastest-Growing AI Inference Company | Tuhin Srivastava

In this episode of Gradient Dissent, Lukas Biewald talks with Tuhin Srivastava, CEO and founder of Baseten, one of the fastest-growing companies in the AI inference ecosystem. Tuhin shares the real story behind Baseten’s rise and how the market finally aligned with the infrastructure they’d spent years building.

They get into the core challenges of modern inference, including why dedicated deployments matter, how runtime and infrastructure bottlenecks stack up, and what makes serving large models fundamentally different from smaller ones.

Tuhin also explains how vLLM, TensorRT-LLM, and SGLang differ in practice, what it takes to tune workloads for new chips like the B200, and why reliability becomes harder as systems scale.

The conversation dives into company-building, from killing product lines to avoiding premature scaling while navigating a market that shifts every few weeks.

Connect with us here:

Tuhin Srivastva: https://www.linkedin.com/in/tuhin-srivastava/

Lukas Biewald: https://www.linkedin.com/in/lbiewald/

Weights & Biases: https://www.linkedin.com/company/wandb/

Jaksot(130)

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

Nicolas Koumchatzky — Machine Learning in Production for Self-Driving Cars

👨🏻‍💻Nicolas Koumchatzky is the Director of AI infrastructure at NVIDIA, where he's responsible for MagLev, the production-grade machine learning platform by NVIDIA. His team supports diverse ML use cases: autonomous vehicles, medical imaging, super resolution, predictive analytics, cyber security, robotics. He started as a Quant in Paris, then joined Madbits, a startup specialized on using deep learning for content understanding. When Madbits was acquired by Twitter in 2014, he joined as a deep learning expert and led a few projects in Cortex, include a real-time live video classification product for Periscope. In 2016, he focused on building an scalable AI platform for the company. Early 2017, he became the lead for the Cortex team. He joined NVIDIA in 2018. 🐦Follow Nicolas on twitter: https://twitter.com/nkoumchatzky 🛠Maglev: https://blogs.nvidia.com/blog/2018/09/13/how-maglev-speeds-autonomous-vehicles-to-superhuman-levels-of-safety/ ✍️Scalable Active Learning for Autonomous Driving: https://medium.com/nvidia-ai/scalable-active-learning-for-autonomous-driving-a-practical-implementation-and-a-b-test-4d315ed04b5f ✍️Active Learning – Finding the right self-driving training data doesn’t have to take a swarm of human labelers: https://blogs.nvidia.com/blog/2020/01/16/what-is-active-learning/ 👫Continue the conversation on our slack community - http://bit.ly/wandb-forum 🤖Gradient Dissent by Weights and Biases We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it. 👩🏼‍🚀Weights and Biases: We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions. * Visualize your Scikit model performance with W&B - https://app.wandb.ai/lavanyashukla/visualize-sklearn/reports/Visualizing-Sklearn-With-Weights-and-Biases--Vmlldzo0ODIzNg * Blog: https://www.wandb.com/articles * Gallery: See what you can create with W&B - https://app.wandb.ai/gallery 🎙Host: Lukas Biewald - https://twitter.com/l2k 👩🏼‍💻Producer: Lavanya Shukla - https://twitter.com/lavanyaai 📹Editor: Cayla Sharp - http://caylasharp.com/

21 Maalis 202044min

Brandon Rohrer — Machine Learning in Production for Robots

Brandon Rohrer — Machine Learning in Production for Robots

👨🏻‍💻Brandon Rohrer is a Mechanical Engineer turned Data Scientist. He’s currently a Principal Data Scientist at iRobot and has an incredibly popular Machine Learning course at e2eML where he’s made some wildly popular videos on convolutional neural networks and deep learning. His fascination with robots began after watching Luke Skywalker’s prosthetic hand in the Empire Strikes Back. He turned this fascination into a PhD from MIT and subsequently found his way to building some incredible data science products at Facebook, Microsoft and now at iRobot. ✍️Brandon’s brilliant machine learning course: http://e2eml.school/ 🐦Follow Brandon on twitter: https://twitter.com/_brohrer_ 👫Continue the conversation on our slack community - http://bit.ly/wandb-forum 🤖Gradient Dissent by Weights and Biases - http://wandb.com We started Weights and Biases to build tools for Machine Learning practitioners because we care a lot about the impact that Machine Learning can have in the world and we love working in the trenches with the people building these models. One of the most fun things about these building tools has been the conversations with these ML practitioners and learning about the interesting things they’re working on. This process has been so fun that we wanted to open it up to the world in the form of our new podcast. We hope you have as much fun listening to it as we had making it. Today our guest is Brandon Rohrer. 👩🏼‍🚀Weights and Biases: We’re always free for academics and open source projects. Email carey@wandb.com with any questions or feature suggestions. • Visualize your Scikit model performance with W&B - https://app.wandb.ai/lavanyashukla/visualize-sklearn/reports/Visualizing-Sklearn-With-Weights-and-Biases--Vmlldzo0ODIzNg • Blog: https://www.wandb.com/articles • Gallery: See what you can create with W&B - https://app.wandb.ai/gallery

11 Maalis 202034min

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