History of Diffusion
Claim This Podcastby BCV
Podcast Authority
Beta
Podcast Overview
<p>How did diffusion models go from an obscure research idea to the foundation of modern generative AI? In History of Diffusion, BCV partner <strong>Slater Stich</strong> sits down with the researchers who shaped the field—<strong>Jascha Sohl-Dickstein, Yang Song, and Sander Dieleman</strong>—to trace the origins, breakthroughs, and future of diffusion-based AI.</p><p>From the <strong>2015 paper that started it all</strong> to the <strong>latest advancements in generative models</strong>, this series unpacks the key ideas, challenges, and moments that led to diffusion’s dominance in AI.</p><p>Whether you’re deep in machine learning research or just want to understand the tech behind tools like <strong>MidJourney, DALL·E, and Stable Diffusion</strong>, this is a must-listen.</p>
Language
🇺🇲
Publishing Since
2/15/2025
Unlock The Full Podcast Authority Score Report
See how your podcast performs across key metrics
Podcast Authority
BetaRecommendations available
Unlock the full report to see detailed tips
Recommendations available
Unlock the full report to see detailed tips
Unlock comprehensive insights including:
- • YouTube presence analysis
- • Social media reach metrics
- • RSS compliance scoring
- • Podcast 2.0 features
- • Technical standards
Detailed Analytics
- Complete breakdown of all 19 authority metrics
- Personalized recommendations for each metric
- Industry benchmarks and comparisons
- Technical RSS feed analysis and compliance scoring
Growth Strategies
- Step-by-step action plans for improvement
- Quick wins to boost your score immediately
- Pro tips from successful podcasters
See how your show performs across every key metric
High authority scores make your podcast more attractive to industry leaders and influencers who want to appear on credible shows.
Sponsors look for podcasts with proven authority and engagement. Your score demonstrates your podcast's value to potential partners.
Understanding your strengths and weaknesses helps you make data-driven decisions to expand your listener base effectively.
Reach the team behind History of Diffusion
Verified contact details for this show aren't on file yet — sign up to get notified when they land.
Recent Episodes
May 14, 2025
History of Diffusion - Sander Dieleman
<p>Research Scientist Sander Dieleman joins BCV Partner Slater Stich to unpack the core mechanics of diffusion models and explore why diffusion has become central to generative AI.</p><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://baincapitalventures.com/">https://baincapitalventures.com/</a> X: @BainCapVC @slaterstich</p>
April 9, 2025
Yang Song
<p>Before diffusion models powered tools like DALL·E and MidJourney, they were a niche research idea. In this episode, BCV partner Slater Stich talks with Yang Song about the early bets, surprising math, and big breakthroughs that made diffusion the backbone of generative AI—as well as what’s next. </p><p></p><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://baincapitalventures.com/">https://baincapitalventures.com/</a> </p><p>X: @BainCapVC @slaterstich</p>
February 15, 2025
Jascha Sohl-Dickstein
<p>Diffusion models now dominate generative AI, powering MidJourney, DALL·E, Ideogram, Stable Diffusion, and more—but just a few years ago, they were an obscure research idea. In this episode, BCV partner Slater Stich sits down with Jascha Sohl-Dickstein, the researcher behind the foundational 2015 paper that introduced diffusion as a generative model. </p><p></p><p><a target="_blank" rel="noopener noreferrer nofollow" href="https://baincapitalventures.com/">BCV.com</a></p><p>X: <a target="_blank" rel="noopener noreferrer nofollow" href="https://x.com/BainCapVC">@BainCapVC</a> <a target="_blank" rel="noopener noreferrer nofollow" href="https://x.com/slaterstich">@slaterstich</a></p>
3 total episodes available
Deep-dive analytics for History of Diffusion
Frequently asked questions
Have a different question and can't find the answer you're looking for? Reach out to our support team by sending us an email and we'll get back to you as soon as we can.
- What is History of Diffusion?
<p>How did diffusion models go from an obscure research idea to the foundation of modern generative AI? In History of Diffusion, BCV partner <strong>Slater Stich</strong> sits down with the researchers who shaped the field—<strong>Jascha Sohl-Dickstein, Yang Song, and Sander Dieleman</strong>—to trace the origins, breakthroughs, and future of diffusion-based AI.</p><p>From the <strong>2015 paper that started it all</strong> to the <strong>latest advancements in generative models</strong>, this series unpacks the key ideas, challenges, and moments that led to diffusion’s dominance in AI.</p><p>Whether you’re deep in machine learning research or just want to understand the tech behind tools like <strong>MidJourney, DALL·E, and Stable Diffusion</strong>, this is a must-listen.</p> - How often does this podcast release new episodes?
This podcast updates daily.
- Where can I listen to this podcast?
This podcast is available on 4 platforms including Apple Podcasts, Spotify, and more. You can also use the RSS feed directly.
- Does this podcast accept guests?
Yes, this podcast regularly features guests.
Legal Disclaimer
Pod Engine is not affiliated with, endorsed by, or officially connected with any of the podcasts displayed on this platform. We operate independently as a podcast discovery and analytics service.
All podcast artwork, thumbnails, and content displayed on this page are the property of their respective owners and are protected by applicable copyright laws. This includes, but is not limited to, podcast cover art, episode artwork, show descriptions, episode titles, transcripts, audio snippets, and any other content originating from the podcast creators or their licensors.
We display this content under fair use principles and/or implied license for the purpose of podcast discovery, information, and commentary. We make no claim of ownership over any podcast content, artwork, or related materials shown on this platform. All trademarks, service marks, and trade names are the property of their respective owners.
While we strive to ensure all content usage is properly authorized, if you are a rights holder and believe your content is being used inappropriately or without proper authorization, please contact us immediately at hey@podengine.ai for prompt review and appropriate action, which may include content removal or proper attribution.
By accessing and using this platform, you acknowledge and agree to respect all applicable copyright laws and intellectual property rights of content owners. Any unauthorized reproduction, distribution, or commercial use of the content displayed on this platform is strictly prohibited.