In this episode, we are joined by Chris Van Pelt, co-founder of Weights & Biases and Figure Eight/CrowdFlower. Chris has played a pivotal role in the development of MLOps platforms and has dedicated the last two decades to refining ML workflows and making machine learning more accessible.

Throughout the conversation, Chris provides valuable insights into the current state of the industry. He emphasizes the significance of Weights & Biases as a powerful developer tool, empowering ML engineers to navigate through the complexities of experimentation, data visualization, and model improvement. His candid reflections on the challenges in evaluating ML models and addressing the gap between AI hype and reality offer a profound understanding of the field's intricacies.

Drawing from his entrepreneurial experience co-founding two machine learning companies, Chris leaves us with lessons in resilience, innovation, and a deep appreciation for the human dimension within the tech landscape. As a Weights & Biases user for five years, witnessing both the tool and the company's growth, it was a genuine honor to host Chris on the show.

References and Resources

https://wandb.ai/

https://www.youtube.com/c/WeightsBiases

https://x.com/weights_biases

https://www.linkedin.com/company/wandb/

https://twitter.com/vanpelt

Resources to learn more about Learning from Machine Learning

• https://www.youtube.com/@learningfrommachinelearning
• https://www.linkedin.com/company/learning-from-machine-learning
• https://mindfulmachines.substack.com/
• https://www.linkedin.com/in/sethplevine/
• https://medium.com/@levine.seth.p

This episode features Dr. Michelle Gill, Tech Lead and Applied Research Manager at NVIDIA, working on transformative projects like BioNemo to accelerate drug discovery through AI. Her team explores Biofoundation models to enable researchers to better perform tasks like protein folding and small molecule binding.

Michelle shares her incredible journey from wet lab biochemist to driving cutting edge AI at NVIDIA. Michelle discusses the overlap and differences between NLP and AI in biology. She outlines the critical need for better machine learning representations that capture the intricate dynamics of biology.

Michelle provides advice for beginners and early career professionals in the field of machine learning, emphasizing the importance of continuous learning and staying up to date with the latest tools and techniques. She also shares insights on building successful multidisciplinary teams

After hearing her fascinating PyData NYC keynote, it was such an honor to have her on the show to discuss innovations at the intersection of biochemistry and AI.

References and Resources

https://michellelynngill.com/

Michelle Gill - Keynote - PyData NYC https://www.youtube.com/watch?v=ATo2SzA1Pp4

AlexNet

AlphaFold - https://www.nature.com/articles/s41586-021-03819-2

OpenFold - https://www.biorxiv.org/content/10.1101/2022.11.20.517210v1

BioNemo - https://www.nvidia.com/en-us/clara/bionemo/

NeurIPS - https://nips.cc/

Art Palmer - https://www.biochem.cuimc.columbia.edu/profile/arthur-g-palmer-iii-phd

Patrick Loria - https://chem.yale.edu/faculty/j-patrick-loria

Scott Strobel - https://chem.yale.edu/faculty/scott-strobel

Alexander Rives - https://www.forbes.com/sites/kenrickcai/2023/08/25/evolutionaryscale-ai-biotech-startup-meta-researchers-funding/?sh=648f1a1140cf

Deborah Marks - https://sysbio.med.harvard.edu/debora-marks

Resources to learn more about Learning from Machine Learning

• https://www.linkedin.com/company/learning-from-machine-learning
• https://mindfulmachines.substack.com/
• https://www.linkedin.com/in/sethplevine/
• https://medium.com/@levine.seth.p

This episode features co-founder and CEO of Explosion, Ines Montani. Listen in as we discuss the evolution of the web and machine learning, the development of SpaCy, Natural Language Processing vs. Natural Language Understanding, the misconceptions of starting a software company, and so much more! Ines is a software developer working on Artificial Intelligence and Natural Language Processing technologies.

She's the co-founder and CEO of Explosion, the company behind SpaCy, one of the leading open-source libraries for NLP in Python and Prodigy, an annotation tool to help create training data for Machine Learning Models. Ines has an academic background in Communication Science, Media Studies and Linguistics and has been coding and designing websites since she was 11. She's been the keynote speaker at Python and Data Science conferences around the world.

Learning from Machine Learning, a podcast that explores more than just algorithms and data: Life lessons from the experts.

Listen on YouTube: https://youtu.be/XNFqFT-DZwo?si=Aj75TmsCyBQTyWqq

Listen on your favorite podcast platform:

https://rss.com/podcasts/learning-from-machine-learning/1190862/

References in the Episode

• https://explosion.ai/
• https://spacy.io/
• https://ines.io/
• Applied NLP Thinking
• Ines Montani - How to Ignore Most Startup Advice and Build a Decent Software Business Ines Montani: Incorporating LLMs into practical NLP workflows
• Ines Montani (spaCy) - Large Language Models from Prototype to Production [PyData Südwest] Confection
• https://github.com/explosion/confection

Resources to learn more about Learning from Machine Learning

• https://www.linkedin.com/company/learning-from-machine-learning
• https://mindfulmachines.substack.com/
• https://www.linkedin.com/in/sethplevine/
• https://medium.com/@levine.seth.p