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MLOps Coffee Sessions #178 with LLMs in Production Conference part 2 LLM on K8s Panel, Manjot Pahwa, Rahul Parundekar, and Patrick Barker hosted by Outerbounds, Inc.'s Shrinand Javadekar. // Abstract Large Language Models require a new set of tools... or do they? K8s is a beast and we like it that way. How can we best leverage all the battle-hardened tech that K8s has to offer to make sure tha...

MLOps Coffee Sessions #174 with Michelle Marie Conway, Harnessing MLOps in Finance: Bringing Statistical Models to Life for Positive Impact, co-hosted by Stephen Batifol. // Abstract Michelle Marie Conway joins hosts Stephen Batifol and Demetrios to share their insights and experiences in the tech industry. Michelle emphasizes the importance of constant learning and adaptation in the rapidly chang...

MLOps Coffee Sessions #176 with MLOps vs. LLMOps Panel, Willem Pienaar, Chris Van Pelt, Aparna Dhinakaran, and Alex Ratner hosted by Richa Sachdev. // Abstract What do MLOps and LLMOps have in common? What has changed? Are these just new buzzwords or is there validity in calling this ops something new? // Bio Richa Sachdev A passionate and impact-driven leader whose expertise spans leading teams,...

MLOps Coffee Sessions #173 with Beyang Liu, Building Cody, an Open Source AI Coding Assistant. We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract Root about the development of Cody, an open-source AI coding assistant. Cody empowers developers to query and comprehend code within cod...

MLOps Coffee Sessions #174 with Evaluation Panel, Amrutha Gujjar, Josh Tobin, and Sohini Roy hosted by Abi Aryan. We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract Language models are very complex thus introducing several challenges in interpretability. The large amounts of data r...

MLOps Coffee Sessions #172 with Lingjiao Chen, FrugalGPT: Better Quality and Lower Cost for LLM Applications. This episode is sponsored by QuantumBlack . We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract There is a rapidly growing number of large language models (LLMs) that users...

MLOps Coffee Sessions #172 with LLMs in Production Conference part 2 Building LLM Products Panel, George Mathew, Asmitha Rathis, Natalia Burina, and Sahar Mor Using hosted by TWIML's Sam Charrington. We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract There are key areas we must...

MLOps Coffee Sessions #171 with Thibaut Labarre, Using Large Language Models at AngelList, co-hosted by Ryan Russon. We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract Thibaut innovatively addressed previous system constraints, achieving scalability and cost efficiency. Leveraging...

MLOps Coffee Sessions #170 with Phillip Carter, All the Hard Stuff with LLMs in Product Development. We are now accepting talk proposals for our next LLM in Production virtual conference on October 3rd. Apply to speak here: https://go.mlops.community/NSAX1O // Abstract Delve into challenges in implementing LLMs, such as security concerns and collaborative measures against attacks. Emphasize the ro...

MLOps Coffee Sessions #169 with Barak Turovsky, MLOps at the Age of Generative AI. Thanks to Weights & Biases for sponsoring this episode. Check out their new course on evaluating and fine-tuning LLMs at wandb.me/genai-mlops.course // Abstract The talk focuses on MLOps aspects of developing, training, and serving Generative AI/Large Language models // Bio Barak is an Executive in Residence at...

MLOps Coffee Sessions #168 with Piotr Niedźwiedź, Experiment Tracking in the Age of LLMs, co-hosted by Vishnu Rachakonda. // Abstract Piotr shares his journey as an entrepreneur and the importance of focusing on core values to achieve success. He highlights the mission of Neptune to support ML teams by providing them with control and confidence in their models. The conversation delves into the rol...

MLOps Coffee Sessions #167 with Maxime Beauchemin, Treating Prompt Engineering More Like Code. // Abstract Promptimize is an innovative tool designed to scientifically evaluate the effectiveness of prompts. Discover the advantages of open-sourcing the tool and its relevance, drawing parallels with test suites in software engineering. Uncover the increasing interest in this domain and the necessity...

MLOps Coffee Sessions #166 with Roy Hasson & Santona Tuli, Eliminating Garbage In/Garbage Out for Analytics and ML. // Abstract Shift left data quality ownership and observability that makes it easy for users to catch bad data at the source and stop it from entering your analytics/ML stack. // Bio Santona Tuli Santona Tuli, Ph. D., began her data journey through fundamental physics—searching t...

MLOps Coffee Sessions #165 with Sammy Sidhu, Python Power: How Daft Embeds Models and Revolutionizes Data Processing. // Abstract Sammy shares his fascinating journey in the autonomous vehicle industry, highlighting his involvement in two successful startup acquisitions by Tesla and Toyota. He emphasizes his expertise in optimizing and distilling models for efficient machine learning, which he has...

MLOps Coffee Sessions #164 with Rob Hirschfeld, Open Source and Fast Decision Making. This episode is brought to you by. // Abstract Rob Hirschfeld, the CEO and co-founder of Rack N, discusses his extensive experience in the DevOps movement. He shares his notable achievement of coining the term "the cloud" and obtaining patents for infrastructure management and API provision. Rob highlig...

MLOps Coffee Sessions #163 with Yujian Tang, Democratizing AI, co-hosted by Abi Aryan. // Abstract The popularity of ChatGPT has brought large language model (LLMs) apps and their supporting technologies to the forefront. One of the supporting technologies is vector databases. Yujian shares how vector databases like Milvus are used in production and how they solve one of the biggest problems in LL...

MLOps Coffee Sessions #162 with Soham Chatterjee, From LLMs to TinyML: The Dynamic Spectrum of MLOps, co-hosted by Abi Aryan. // Abstract Explore the spectrum of MLOps from large language models (LLMs) to TinyML. Soham highlights the difficulties of scaling machine learning models and cautions against relying exclusively on OpenAI's API due to its limitations. Soham is particularly interested...

MLOps Coffee Sessions #161 with Tuhin Srivastava, The Long Tail of ML Deployment, co-hosted by Abi Aryan. This episode is brought to you by QuantumBlack. // Abstract Baseten is an engineer-first platform designed to alleviate the engineering burden for machine learning and data engineers. Tuhin's perspective, based on research with Stanford students, emphasizes the importance of engineers embr...

MLOps Coffee Sessions #160 with Matt Sharp, Data Developer at Shopify, Clean Code for Data Scientists, co-hosted by Abi Aryan. // Abstract Let's delve into Shopify's real-time serving platform, Merlin, which enables features like recommender systems, inbox classification, and fraud detection. Matt shares his insights on clean coding and the new book he is writing about LLMs in production....

MLOps Coffee Sessions #159 with Maria Vechtomova, Lead ML engineer, and Basak Eskili, Machine Learning Engineer, at Ahold Delhaize. Why is MLOps Hard in an Enterprise? co-hosted by Abi Aryan. // Abstract MLOps is particularly challenging to implement in enterprise organizations due to the complexity of the data ecosystem, the need for collaboration across multiple teams, and the lack of standardiz...

MLOps Coffee Sessions #158 with Nils Reimer, MLOps Build or Buy, Large Language Model at Scale, co-hosted by Abi Aryan. // Abstract Large Language Models with billions of parameters have the possibility to change how we work with textual data. However, running them on scale at potentially hundreds of millions of texts a day is a massive challenge. Nils talks about finding the right model size for...

We are having another LLMs in-production Virtual Conference. 50+ speakers combined with in-person activities around the world on June 15 & 16. Sign up free here: https://home.mlops.community/home/events/llm-in-prod-part-ii-2023-06-20 // Abstract This panel discussion is centered around a crucial topic in the tech industry - data privacy and security in the context of large language models and...

MLOps Coffee Sessions #157 with Katrina Ni & Aaron Maurer, MLOps Build or Buy, Startup vs. Enterprise? co-hosted by Jake Noble of tecton.ai. This episode is sponsored by Tecton - Check out their feature store to get your real-time ML journey started. // Abstract There are a bunch of challenges with building useful machine learning at a B2B software company like Slack, but we've built some...

Sign up for the next LLM in production conference here: https://go.mlops.community/LLMinprod Watch all the talks from the first conference: https://go.mlops.community/llmconfpart1 // Abstract In this panel discussion, the topic of the cost of running large language models (LLMs) is explored, along with potential solutions. The benefits of bringing LLMs in-house, such as latency optimization and gr...

MLOps Coffee Sessions #156 with Melissa Barr & Michael Mui, Machine Learning Education at Uber, co-hosted by Lina Weichbrodt. // Abstract Melissa and Michael discuss the education program they developed for Uber's machine learning platform service, Michelangelo, during a guest appearance on a podcast. The program teaches employees how to use machine learning both in general and specificall...