Advanced Lessons

The Art and Science of Training LLMs // Bandish Shah and Davis Blalock // MLOps Podcast #219

Hypothesis Testing and Stakeholder Collaboration // Alexandra Diem // MLOps Podcast #212 clip

[Exclusive] Zilliz Roundtable // Why Purpose-built Vector Databases Matter for Your Use Case

Language Processing, Recommendations, System Integration // Aayush Mugdal // MLOps Podcast #211 clip

LLM Applications & Outcome Evaluation in the New Era // Aparna Dhinakaran // MLOps Podcast #210 clip

Information Retrieval & Relevance // Daniel Svonava // MLOps Podcast #214

The AI Engineer Song

The Realistic Approach to MLOps // Jonathan Frankle // MLOps Podcast clip #205

The Myth of AI Breakthroughs // Jonathan Frankle // MLOps Podcast #205

Pioneering AI Models for Regional Languages // Aleksa Gordić // MLOps Podcast #203

Building the Future of AI in Software Development // Varun Mohan // MLOps Podcast #195

Scaling MLOps for Computer Vision // MLOps Mini Summit Meetup #4

Cambrium's Material Biotech Innovations // Pierre Salvy // MLOps Podcast #193 clip

LLMs in Biomaterials Production // Pierre Salvy // MLOps Podcast #193

GenAI: An Unreliable Information Store // Noble Ackerson // LLMs in Production Conference III Talk

Data Quality’s Impact on Large Language Models // Mona Rakibe & Maxim Lukichev // LLMs III Talk

Exploring Trade-Offs in MLOps // Richa Sachdev // MLOps Podcast #184 clip

Exploring the Latency/Throughput & Cost Space for LLM Inference // Timothée Lacroix // CTO Mistral

The Centralization of Power in AI // Kyle Harrison // MLOps Podcast # 181

Unleashing the Potential of Data Scientists and Engineers // Vin Vashishta // MLOps Podcast 176 clip

#mlops #ai #generativeai #llm

#mlops #ai #generativeai #llm

Steering a Large-Scale Data Migration // Michelle Marie Conway // MLOps Podcast Coffee #174 clip

Harnessing MLOps in Finance // Michelle Marie Conway // MLOps Podcast Coffee #174

AI-Powered Code Search // Beyang Liu // MLOps Podcast #173 clip

Building Cody, an Open Source AI Coding Assistant // Beyang Liu // MLOps Podcast #173

Cutting Costs Without Compromising Accuracy // Lingjiao Chen // MLOps Podcast #172 clip 2

FrugalGPT: Better Quality and Lower Cost for LLM Applications // Lingjiao Chen // MLOps Podcast #172

LLMs vs LMs in Prod // Denys Linkov // LLMs in Production Conference Part 2

Considerations and Optimizations for Deploying Open Source LLMs at Your Company // Oscar Rovira //

LIMA: Less is More for Alignment // Chunting Zhou // LLMs in Production Conference Part 2

Ux of a LLM User // Panel 5 // LLMs in Production Conference Part 2

End-to-end Modern Machine Learning in Production // Omar Sanseviero // LLMs in Prod Con Part 2

MLOps at the Age of Generative AI // Barak Turovsky // MLOps Podcast #169

Designing Human in the Loop Experiences for LLMs // Alberto Rizzoli // LLMs in Prod Con Part 2

Unleashing Code Completion with LLMs // Monmayuri Ray // LLMs in Production Conference Part 2

Linguistically-informed LLMs Perform Better // Chris Brousseau // LLMs in Prod Conference

Building Products // Panel 3 // LLMs in Production Conference part 2

Tabular vs Complex Data // Sammy Sidhu // MLOps Podcast #165 short clip

Solving LLM Data Problems // Yujian Tang // LLMs in Prod Conference Part 2

Python Power: How Daft Embeds Models and Revolutionizes Data Processing //Sammy Sidhu// Podcast #165

$360k Question - Understanding the LLM Economics // Nikunj Bajaj // LLMs in Production Conference

Large Model Training and Inference with DeepSpeed // Samyam Rajbhandari // LLMs in Prod Conference

Exploring the Challenges and Potential of LLMs // Yujian Tang // MLOps Podcast #163 short clip

Democratizing AI // Yujian Tang // MLOps Podcast #163

Leveraging Models Without Extensive Technical Know-How // Tuhin Srivastava //MLOps Podcast #161 clip

Boosting Databases and Language Models

Understanding Semantic Vectors: Extracting Embeddings and Calculating Similarity