DataFramed

#346 Get Quantum Ready with Yonatan Cohen, CTO at Quantum Machines


Listen Later

Quantum computing is advancing fast, but it comes with a core industry challenge: noise. The big promise—better simulations, faster optimization, and maybe new kinds of AI—depends on quantum error correction and scaling from physical qubits to reliable logical qubits. For working professionals, that translates into system design questions, not just theory. How do you budget for the overhead of error correction? What does a hybrid quantum‑classical workflow look like when classical processors must process error data in real time? If a quantum approach shows “advantage” today, how do you know a better classical heuristic won’t catch up next month? Where should you focus first: hardware readiness or use cases?

Dr. Yonatan Cohen is a physicist, entrepreneur, and co-founder of Quantum Machines, where he serves as Chief Technology Officer. He earned his Ph.D. at the Weizmann Institute of Science in Israel, focusing on quantum electronics, superconducting–semiconducting devices, and microfabrication. He is also a co-founder and former managing director of the Weizmann Institute’s entrepreneurship program and has published extensively in peer-reviewed journals, with recognized contributions to quantum computing. As CTO, Dr. Cohen has played a key role in developing the Quantum Orchestration Platform, a first-of-its-kind control and operating system for quantum computers that accelerates the path to practical, useful quantum systems.

In the episode, Richie and Yonatan explore near-term quantum simulation, encryption risks, the open question of quantum AI, noisy qubits and error correction, physical vs logical scaling, the need for algorithms and use cases, how to try quantum coding via Amazon Braket, and much more.

Links Mentioned in the Show:

  1. Quantum Machines
  2. Amazon Braket
  3. IBM Qiskit
  4. NVIDIA Cuda Quantum
  5. Google Cirq
  6. Connect with Yonatan
  7. AI-Native Course: Intro to AI for Work
  8. Related Episode: Developing Better Predictive Models with Graph Transformers with Jure Leskovec, Pioneer of Graph Transformers, Professor at Stanford
  9. Explore AI-Native Learning on DataCamp

New to DataCamp?

  1. Learn on the go using the DataCamp mobile app

Empower your business with world-class data and AI skills with DataCamp for business

...more
View all episodesView all episodes
Download on the App Store

DataFramedBy DataCamp

  • 4.9
  • 4.9
  • 4.9
  • 4.9
  • 4.9

4.9

265 ratings


More shows like DataFramed

View all
Data Skeptic by Kyle Polich

Data Skeptic

478 Listeners

Software Engineering Daily by Software Engineering Daily

Software Engineering Daily

627 Listeners

Talk Python To Me by Michael Kennedy

Talk Python To Me

583 Listeners

Super Data Science: ML & AI Podcast with Jon Krohn by Jon Krohn

Super Data Science: ML & AI Podcast with Jon Krohn

302 Listeners

Python Bytes by Michael Kennedy and Brian Okken

Python Bytes

213 Listeners

NVIDIA AI Podcast by NVIDIA

NVIDIA AI Podcast

346 Listeners

Practical AI by Practical AI LLC

Practical AI

215 Listeners

The Real Python Podcast by Real Python

The Real Python Podcast

140 Listeners

Last Week in AI by Skynet Today

Last Week in AI

314 Listeners

Machine Learning Street Talk (MLST) by Machine Learning Street Talk (MLST)

Machine Learning Street Talk (MLST)

99 Listeners

Me, Myself, and AI by MIT Sloan Management Review

Me, Myself, and AI

110 Listeners

Latent Space: The AI Engineer Podcast by Latent.Space

Latent Space: The AI Engineer Podcast

100 Listeners

The AI Daily Brief: Artificial Intelligence News and Analysis by Nathaniel Whittemore

The AI Daily Brief: Artificial Intelligence News and Analysis

675 Listeners

AI + a16z by a16z

AI + a16z

32 Listeners

Training Data by Sequoia Capital

Training Data

40 Listeners