Research in AI, human-robot interaction, autonomous vehicles, and machine learning at MIT.

Lex Fridman

I stand with the people of Iran ❤️

I have a lot of Iranian friends, including my childhood best friend. Amazing people.

It's one of the great cultures and peoples in the history of the world.

Stay strong ❤️

Here's my conversation all about AI in 2026, including technical breakthroughs, scaling laws, closed & open LLMs, programming & dev tooling (Claude Code, Cursor, etc), China vs US competition, training pipeline details (pre-, mid-, post-training), rapid evolution of LLMs, work culture, diffusion, robotics, tool use, compute (GPUs, TPUs, clusters), continual learning, long context, AGI timelines (including how stuff might go wrong), advice for beginners, education, a LOT of discussion about the future, and other topics.

It's a great honor and pleasure for me to be able to do this kind of episode with two of my favorite people in the AI community: Sebastian Raschka and Nathan Lambert. They are both widely-respected machine learning researchers & engineers who also happen to be great communicators, educators, writers, and X posters.

This was a whirlwind conversation: everything from the super-technical to the super-fun.

https://lnkd.in/gViznQAt

Open video: State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI | Lex Fridman Podcast #490 on youtube.com

State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI | Lex Fridman Podcast #490

"We are all in the gutter, but some of us are looking at the stars." - Oscar Wilde

Abdelaziz Testas, Ph.D., is a seasoned data scientist with over a decade of experience in data analysis and machine learning. He earned his Ph.D. in Business Economics from Leeds University in England and holds a Master’s degree in the same field from Glasgow University in Scotland. Additionally, he has acquired several certifications in computer science and data science.

For more than 10 years, Abdelaziz served as a Data Scientist, Senior Data Scientist, and Lead Data Scientist at Nielsen, where he played a pivotal role in enhancing the company’s audience measurement capabilities. He was instrumental in planning, initiating, and executing end-to-end data science projects, and in developing methodologies that advanced Nielsen’s digital ad and content rating products. His expertise in media measurement and data science drove the creation of cutting-edge solutions.

Recently, Abdelaziz transitioned to the public sector, joining the State of California's Department of Health Care Access and Information (HCAI). In his new role, he leverages his coding and data science leadership skills to make a meaningful impact, supporting HCAI’s mission to ensure quality, equitable, and affordable health care for all Californians.

Abdelaziz is the author of two books:

Distributed Machine Learning with PySpark: Migrating Effortlessly from Pandas and Scikit-Learn (Apress, Nov 2023)

Building Scalable Deep Learning Pipelines on AWS: Develop, Train, and Deploy Deep Learning Models (Apress, Dec 2024)

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