The AI Dream Team: Strategies for ML Recruitment and Growth // Jelmer Borst and Daniela Solis // #267
mercredi 9 octobre 2024 • Durée 58:42
The AI Dream Team: Strategies for ML Recruitment and Growth // MLOps Podcast #267 with Jelmer Borst, Analytics & Machine Learning Domain Lead, and Daniela Solis, Machine Learning Product Owner, of Picnic.
// Abstract
Like many companies, Picnic started out with a small, central data science team. As this grows larger, focusing on more complex models, it questions the skillsets & organisational setup. Use an ML platform, or build ourselves? A central team vs. embedded? Hire data scientists vs. ML engineers vs. MLOps engineers. How to foster a team culture of end-to-end ownership to balance short-term & long-term impact
// Bio
Jelmer Borst
Jelmer leads the analytics & machine learning teams at Picnic, an app-only online groceries company based in the Netherlands. Whilst his background is in aerospace engineering, he was looking for something faster-paced and found that at Picnic. He loves the intersection of solving business challenges using technology & data. In his free time loves to cook food and tinker with the latest AI developments.
Daniela Solis Morales
As a Machine Learning Lead at Picnic, I am responsible for ensuring the success of end-to-end Machine Learning systems. My work involves bringing models into production across various domains, including Personalization, Fraud Detection, and Natural Language Processing.
[03:46] Please like, share, leave a review, and subscribe to our MLOps channels!
[03:58] Use case evolution review
[08:24] Centralized ML strategy
[11:53] Managing zombie models effectively
[15:52] Clean data and collaboration
[21:07] Snowflake ML Integration options
[22:49] MLOps infrastructure components
[25:36] Pull vs. Push Adoption
[27:03] ML Model Monitoring Roles
[31:56] Inventory prediction
[36:00] Scaling machine learning teams
[42:09] Team expansion and structure
[48:20] Exploring effective team organization
[51:43] Blog reading insights
[54:25] Playing hard mode
[57:33] Wrap up
Making Your Company LLM-native // Francisco Ingham // #266
dimanche 6 octobre 2024 • Durée 57:54
Francisco Ingham, LLM consultant, NLP developer, and founder of Pampa Labs.Making Your Company LLM-native
// MLOps Podcast #266 with Francisco Ingham, Founder of Pampa Labs.
// Abstract
Being an LLM-native is becoming one of the key differentiators among companies in vastly different verticals. Everyone wants to use LLMs, and everyone wants to be on top of the current tech, but what does it really mean to be LLM-native?
LLM-native involves two ends of a spectrum. On the one hand, we have the product or service that the company offers, which surely offers many automation opportunities. LLMs can be applied strategically to scale at a lower cost and offer a better experience for users.
But being LLM-native not only involves the company's customers, it also involves each stakeholder involved in the company's operations. How can employees integrate LLMs into their daily workflows? How can we, as developers, leverage the advancements in the field not only as builders but as adopters?
We will tackle these and other key questions for anyone looking to capitalize on the LLM wave, prioritizing real results over the hype.
// Bio
Currently working at Pampa Labs, where we help companies become AI-native and build AI-native products. Our expertise lies on the LLM-science side, or how to build a successful data flywheel to leverage user interactions to continuously improve the product. We also spearhead Pampa-friends - the first Spanish-speaking community of AI Engineers.
Previously worked in management consulting, was a TA in fastai in SF, and led the cross-AI + dev tools team at Mercado Libre.
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Visualize - Bringing Structure to Unstructured Data // Markus Stoll // #258
mardi 3 septembre 2024 • Durée 50:38
Markus Stoll is the Co-Founder of Renumics and the developer behind the open-source interactive ML dataset exploration tool, Spotlight. He shares insights on:
AI in Engineering and Manufacturing Interactive ML Data Visualization ML Data Exploration
Follow Markus for hands-on articles about leveraging ML while keeping a strong focus on data.
Visualize - Bringing Structure to Unstructured Data // MLOps Podcast #258 with Markus Stoll, CTO of Renumics.
A huge thank you to SAS for their generous support!
// Abstract
This talk is about how data visualization and embeddings can support you in understanding your machine-learning data. We explore methods to structure and visualize unstructured data like text, images, and audio for applications ranging from classification and detection to Retrieval-Augmented Generation. By using tools and techniques like UMAP to reduce data dimensions and visualization tools like Renumics Spotlight, we aim to make data analysis for ML easier. Whether you're dealing with interpretable features, metadata, or embeddings, we'll show you how to use them all together to uncover hidden patterns in multimodal data, evaluate the model performance for data subgroups, and find failure modes of your ML models.
// Bio
Markus Stoll began his career in the industry at Siemens Healthineers, developing software for the Heavy Ion Therapy Center in Heidelberg. He learned about software quality while developing a treatment machine weighing over 600 tons. He earned a Ph.D., focusing on combining biomechanical models with statistical models, through which he learned how challenging it is to bridge the gap between research and practical application in the healthcare domain. Since co-founding Renumics, he has been active in the field of AI for Engineering, e.g., AI for Computer Aided Engineering (CAE), implementing projects, contributing to their open-source library for data exploration for ML datasets (Renumics Spotlight), and writing articles about data visualization.
The Future of Feature Stores and Platforms // Mike Del Balso & Josh Wills // # 186
mardi 31 octobre 2023 • Durée 01:11:14
MLOps podcast #186 with Mike Del Balso, CEO & Co-founder of Tecton and Josh Wills, Angel Investor, The Future of Feature Stores and Platforms.
// Abstract
Mike and Josh discuss creating templates and working at a detailed level, exploring Tecton's potential for sharing fraud and third-party features. They focus on technical aspects like data handling and optimizing models, emphasizing the significance of quality data for AI systems and the necessity for cohesive feature infrastructure in reaching production stages.
// Bio
Mike Del Balso
Mike is the co-founder of Tecton, where he is focused on building next-generation data infrastructure for Operational ML. Before Tecton, Mike was the PM lead for the Uber Michelangelo ML platform. He was also a product manager at Google, where he managed the core ML systems that power Google’s Search Ads business.
Josh Wills
Josh Wills is an angel investor specializing in data and machine learning infrastructure. He was formerly the head of data engineering at Slack, the director of data science at Cloudera, and a software engineer at Google.
Lessons on Data Science Leadership // Luigi Patruno // #185
vendredi 27 octobre 2023 • Durée 01:13:31
MLOps podcast #185 with Luigi Patruno, VP of Data Science at 2U, Inc., Lessons on Data Science Leadership.
// Abstract
Picture this: you've got data products to manage, and you're in charge of a team. It's not all sunshine and rainbows, right? Luigi dives into the nitty-gritty of the challenges - from juggling data projects to wrangling the team dynamics. It's a real adventure, let me tell you!
// Bio
Luigi Patruno is a results-driven data science leader passionate about identifying value-add business opportunities and converting these into analytical solutions that deliver measurable business outcomes. As a leader, he focuses on defining strategic vision and, through motivation and discipline, driving teams of highly quantitative data scientists, machine learning engineers, and product managers to achieve extraordinary results. He is currently the VP of Data Science at 2U, where he leads the data science department focused on optimizing business operations through advanced analytics, experimentation, and machine learning. He enjoys teaching others how to leverage data science to improve their businesses through public speaking, teaching courses, and writing online at MLinProduction.com.
Data Platforms in MLOps: Translating Business Goals into Product Decisions // Richa Sachdev // #184
mardi 24 octobre 2023 • Durée 42:48
MLOps podcast #184 with Richa Sachdev, Executive Director- Data Operations and Automation at JP Morgan Chase, Data Platforms in MLOps: Translating Business Goals into Product Decisions.
// Abstract
Richa, with her background in software engineering and experience in the financial sector, shares her insights on optimizing the end-user experience and the importance of understanding business goals and metrics. She discusses her journey in converting legacy applications, working with data platforms, and the challenges of integrating different databases. Richa also explores the role of automation in streamlining processes and improving customer interactions in the reward space. Join us as we unravel the fascinating world of MLOps and uncover the strategies and technologies that drive success in this ever-evolving field.
// Bio
A passionate and impact-driven leader whose expertise spans leading teams, architecting ML and data-intensive applications, and driving enterprise data strategy. Richa has worked for a Tier A Start-up developing feature platforms and in financial companies, leading ML Engineering teams to drive data-driven business decisions. Richa enjoys reading technical blogs focused on system design and plays an active role in the MLOps Community.
MLOps podcast #183 with Ketan Umare, CEO of Union.AI, MLOps vs ML Orchestration, co-hosted by Stephen Batifol.
// Abstract
Let's explore the relationship between Union and Flyte, emphasizing the significance of community-driven development and the challenge of balancing feature requests with security considerations. This conversation highlights the importance of real-time data and secure data handling in orchestrating machine learning models. The Flyte community's empathy and support for newcomers underscore the community's value in democratizing machine learning, making it more accessible and efficient for a broader audience.
// Bio
Ketan Umare is the CEO and co-founder at Union.ai. Previously, he had multiple Senior roles at Lyft, Oracle, and Amazon ranging from Cloud, distributed storage, Mapping (map-making), and machine-learning systems. He is passionate about building software that makes engineers' lives easier and provides simplified access to large-scale systems. Besides software, he is a proud father and husband, and enjoys traveling and outdoor activities.
MLOps podcast #182 with GetYourGuide's Jean Machado, DataScience Manager, Meghana Satish, MLOps Engineer, Olivia Houghton, Machine Learning Operations Engineer, Theodore Meynard, Data Science Manager, MLOps@GetYourGuide.
// Abstract
Join a team to talk about the journey of GYG with MLOps, from the conception of their platform to the creation of the MLOps engineer role, and to their current stack state.
// Bio
Jean Machado
Jean Carlo Machado is a Data Science Manager at GetYourGuide for the Growth Data Products team and the Machine Learning Platform Team. He is privileged to be able to work on turning ideas in data science from inception to production. Before GYG, Jean was working in a startup in Brazil, building its infrastructure from the ground up. Jean also likes community building and using technology for social good.
Meghana Satish
Meghana Satish is currently working as an MLOps Engineer at GetYourGuide. She has previously held positions at Amazon AWS in Berlin and Microsoft IT in Hyderabad. In addition to her career in technology, Meghana is also a talented singer, dancer, and yoga practitioner.
Olivia Houghton
Olivia has been working as an MLOps engineer at GetYourGuide for the past year and a half or so. Olivia's main work is in building and managing their activity ranking service.
Theodore Meynard
Theodore Meynard, Data Science Manager at GetYourGuide, leads the evolution of their ranking algorithm, enriching customer experiences. His hands-on journey from data scientist to leader has honed his expertise in MLOps and real-time ML. Beyond work, he's a co-organizer of PyData Berlin, underlining his commitment to community and collaborative learning.
The Centralization of Power in AI // Kyle Harrison // # 181
vendredi 13 octobre 2023 • Durée 01:01:34
MLOps podcast #181 with Kyle Harrison, General Partner at Contrary, The Centralization of Power in AI.
// Abstract
Kyle Harrison delves into the limitations imposed by language, underscoring how it can impede our grasp and manipulation of reality while stressing the critical need for improved language model performance for real-time applications. He further explores the perils of centralizing power in AI, with a specific focus on the "Openness of AI", where concerns about privacy are brought to the forefront, prompting his call for businesses to reconsider their reliance on it. The discussion also traverses the evolving landscape of AI, drawing comparisons between prominent machine learning frameworks such as TensorFlow and PyTorch. Notably, the episode underscores the vital role of open-source initiatives within the AI community and highlights the unexpected involvement of Meta in driving open-source development.
// Bio
Kyle Harrison is a General Partner at Contrary, where he leads Series A and growth-stage investing. He joined Contrary from Index, where he was a Partner, and before that, he was a growth investor at Coatue. His portfolio includes iconic startups and public companies, including Ramp, Replit, Cohere, Snowflake, and Databricks. He also regularly shares his analysis on the venture capital landscape via his Substack Investing 101.
Adventures in Building CLIP & Other (Largeish) LMs // Sachin Abeywardana // #180
mardi 10 octobre 2023 • Durée 01:06:37
MLOps podcast #180 with Sachin Abeywardana, Deep Learning Engineer at Canva AI, Adventures in Building CLIP and Other (Largeish) Language Models sponsored by Prem AI.
// Abstract
Sachin takes us on an adventure, sharing insights on the pitfalls of not understanding the broader product and the importance of incorporating AI and machine learning capabilities. From the use of AI models for grammar correction and code generation to the fascinating Clip model and the challenges of balancing work and family life, this episode promises to be both informative and thought-provoking.
// Bio
Sachin is the father of two beautiful children. He completed his PhD in Bayesian Machine Learning at the University of Sydney in 2015. In 2016, he discovered Deep Learning and hasn't looked back. He currently works as a Senior Machine Learning Engineer at Canva and is mainly focusing on NLP problems.
[43:04] Criticisms of the current architecture limitations
[45:58] Insufficient exploration of Transformers
[47:42] Explaining GraphML
[52:35] Fine-tuning ChatGPT2
[57:54] Leading ML Engineers and teams
[59:40] Being practical with Math
[1:05:52] Wrap up
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