Agentic Conversations (formally mlops.community)

Agentic Conversations (formally mlops.community)

By DemetriosTechnology
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Agentic Conversations (formally mlops.community) episodes

  • [Exclusive] Weights & Biases Round-table // Model Management in a Regulated Environment

    MLOps Coffee Sessions Special episode with Weights & Biases, Model Management in a Regulated Environment,

    fueled by our Premium Brand Partner, Weights & Biases.
    // Abstract
    Step into the fascinating world of Language Model Management (LLMs) in a Regulated Environment! Join us for an enlightening chat where we'll explore the intricacies of managing models within highly regulated settings, focusing on compliance and effective strategies.
    This is your opportunity to be part of a dynamic conversation that delves into the challenges and best practices of Model Management in Regulated Environments. Secure your spot today and stay tuned for an enriching dialogue on navigating the complexities of navigating the regulated terrain. Don't miss out on the chance to broaden your understanding and connect with peers in the field!
    // Bio
    Darek Kłeczek
    Darek Kłeczek is a Machine Learning Engineer at Weights & Biases, where he
    leads the W&B education program. Previously, he applied machine learning
    across supply chain, manufacturing, legal, and commercial use cases. He also
    worked on operationalizing machine learning at P&G. Darek contributed the first Polish versions of BERT and GPT language models and is a Kaggle Competitions Grandmaster.
    Mark Huang
    Mark is a co-founder and Chief Architect at Gradient, a platform that helps companies build custom AI applications by making it extremely easy to fine-tune foundational models and deploy them into production. Previously, he was a tech lead in machine learning teams at Splunk and Box, developing and deploying production systems for streaming analytics, personalization, and forecasting. Prior to his career in software development, he was an algorithmic trader at quantitative hedge funds where he also harnessed large-scale data to generate trading signals for billion-dollar asset portfolios.
    Oliver Chipperfield
    Oliver Chipperfield is a Senior Data Scientist and Team Lead at M-KOPA, where he utilizes his expertise in machine learning and data-driven innovation. At M-KOPA since October 2021, Oliver leads a diverse tech team, making improvements in credit loss forecasting and fraud detection. His career spans multiple industries, where he has applied his extensive knowledge in Python, Spark, R, SQL, and Excel. He also specialized in the building and design of production ML systems, experimentation, and Bayesian statistics.
    Michelle Marie Conway
    As an Irish woman who relocated to London after completing her university studies in Dublin, Michelle spent the past 12 years carving out a career in the data and tech industry. With a keen eye for detail and a passion for innovation, She has consistently leveraged my expertise to drive growth and deliver results for the companies she worked for.
    As a dynamic and driven professional, Michelle is always looking for new challenges and opportunities to learn and grow, and she's excited to see what the future holds in this exciting and ever-evolving industry.
    // MLOps Jobs board
    https://mlops.pallet.xyz/jobs
    // MLOps Swag/Merch
    https://mlops-community.myshopify.com/
    // Related Links
    Fine-Tuning LLMs: Best Practices and When to Go Small // Mark Kim-Huang // MLOps Meetup #124 - https://youtu.be/1WSUfWojoe0
    --------------- ✌️Connect With Us ✌️ -------------
    Join our slack community: https://go.mlops.community/slack
    Follow us on Twitter: @mlopscommunity
    Sign up for the next meetup: https://go.mlops.community/register
    Catch all episodes, blogs, newsletters, and more: https://mlops.community/
    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
    Connect with Darek on LinkedIn: https://www.linkedin.com/in/kleczek/
    Connect with Mark on LinkedIn: https://www.linkedin.com/in/markhng525/
    Connect with Oliver on LinkedIn: https://www.linkedin.com/in/oliver-chipperfield/
    Connect with Michelle on LinkedIn: https://www.linkedin.com/in/michelle-conway-40337432

    59 min
  • Building the Future of AI in Software Development // Varun Mohan // #195

    MLOps podcast #195 with Varun Mohan, CEO of Codeium, Building the Future of AI in Software Development, brought to us by QuantumBlack.


    // Abstract

    This brief overview traces the evolution of Exafunction and Codeium, highlighting the strategic transition. It explores the inception of Codeium's key features, offering insights into the thoughtful design process. This emphasizes the company's forward-looking approach to preparing for a rapidly advancing technological landscape. Additionally, it touches upon developing essential MLOps systems, showcasing the commitment to maintaining rigor and efficiency in the face of evolving challenges.


    // Bio

    Varun Mohan developed a knack for programming in high school, where he actively participated in various competitions. This passion for programming was shared with his now co-founder, with whom he frequently competed. Their common interest in programming and competition led them to attend MIT together, where they undertook more programming challenges. After college, they ventured into the Bay Area, where they continued to compete and further cultivate their programming abilities.


    // MLOps Jobs board

    jobs.mlops.community

    // MLOps Swag/Merch

    https://mlops-community.myshopify.com/


    // Related Links

    Websites: codeium.com, https://exafunction.com/⁠


    --------------- ✌️Connect With Us ✌️ -------------

    Join our Slack community: https://go.mlops.community/slack

    Follow us on Twitter: @mlopscommunity

    Sign up for the next meetup: https://go.mlops.community/register

    Catch all episodes, blogs, newsletters, and more: https://mlops.community/


    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

    Connect with Varun on Twitter: https://www.linkedin.com/in/varunkmohan/


    Timestamps:

    [00:00] Varun's preferred coffee

    [00:15] Takeaways

    [02:50] Please like, share, and subscribe to our MLOps channels!

    [03:05] QuantumBlack ad by Nayur Khan

    [05:51] Varun's background in tech

    [10:55] Language Models Advancement

    [14:17] GPU scarce world

    [18:23] Vision and Pain Points

    [19:18] Fine-tuning Challenges in NLP

    [21:04] ML and AI Caution

    [21:49] MLOps: App vs Infra

    [23:53] Data Engineering Abstraction Evolution

    [26:12] Codeium and Scaling Discussion

    [31:59] API, Cloud, Computation

    [34:20] Codeium scaling

    [35:11] Reserved GPUs, companies self-hosting products

    [38:00] Open-source code Codeium training

    [40:03] Protecting IP Licenses

    [41:32] ML Challenges: Data, Bias, Security

    [44:37] Evaluating code

    [48:29] Getting values from Codeium

    [49:49] Exafunction ML AI Production

    [52:17] AWS Creation

    [53:58] Feature flags and MA AI lifecycle

    [56:34] Coding problem

    [58:40] New software architectures

    [1:03:28] Wrap up

    1 hr 5 min
  • AI in Education Fireside Chat // LLMs in Production Conference 3

    // Abstract

    Explore the transformative role of AI in EdTech, discussing its potential to enhance learning experiences and personalize education. The panelists share insights on AI use cases, challenges in AI integration, and strategies for building a differentiated business model in the evolving AI landscape. The discussion looks ahead at how the latest wave of GenAI is set to shape the future of education. Join us to understand the exciting prospects and challenges of AI in EdTech.
    Moderator: Paul van der Boor
    // Bio
    Klinton Bicknell
    Klinton Bicknell is the Head of AI  @duolingo . He works at the intersection of artificial intelligence and cognitive science. His research has been published in venues including ACL, PNAS, NAACL, Psychological Science, EDM, CogSci, and Cognition, and covered in the Financial Times, BBC, and Forbes. Prior to Duolingo, he was an assistant professor at Northwestern University.
    Bill Salak
    Bill Salak has more than 20 years of experience overseeing large-scale development projects and more than 24 years of experience in web application architecture and development. Bill founded and served as CTO of multiple Internet and web development companies, leading technology projects for companies including Age of Learning, AOL, Educational Testing Systems, Film LA, Hasbro, HBO, Highlights for Children, NBC-Universal, and the U.S. Army.
    Bill currently serves as the CTO of  @Brainly-app , the leading learning platform worldwide with the most extensive Knowledge Base for all school subjects and grades.
    Yeva Hyusyan
    Yeva Hyusyan is the Co-Founder and CEO of  @Sololearn , the most engaging platform for learning how to code.
    Prior to co-founding SoloLearn, Yeva established a startup accelerator for mobile games, consumer apps, and ag-tech solutions. In a previous role, she implemented programs for the World Bank and the US Government in business and education. Later, she served as a General Manager at Microsoft, where she led sales, developer ecosystem development, and strategic partnerships.
    Yeva holds an MBA in Corporate Strategy from Maastricht School of Management in the Netherlands, an MS in International Economics from Yerevan State University in Armenia, and completed the Executive Program at Stanford University's Graduate School of Business.
    // Sign up for our Newsletter to never miss an event:
    https://mlops.community/join/
    // Watch all the conference videos here:
    https://home.mlops.community/home/collections
    // Check out the MLOps Community podcast: https://open.spotify.com/show/7wZygk3mUUqBaRbBGB1lgh?si=242d3b9675654a69
    // Read our blog:
    mlops.community/blog
    // Join an in-person local meetup near you:
    https://mlops.community/meetups/
    // MLOps Swag/Merch:
    https://mlops-community.myshopify.com/
    // Follow us on Twitter:
    https://twitter.com/mlopscommunity
    //Follow us on Linkedin:
    https://www.linkedin.com/company/mlopscommunity/

    31 min
  • [Exclusive] Tecton Round-table // Get your ML Application Into Production

    Join our conference: https://home.mlops.community/public/events/llms-in-production-part-iii-2023-10-03


    MLOps Coffee Sessions Special episode with Tecton, Get your ML Application Into Production, sponsored by Tecton.

    // Abstract
    Getting an ML application into production is more difficult than most teams expect—but with the right preparation, it can be done efficiently! Join us for this exclusive roundtable, where 4 machine learning experts from Tecton will discuss some of the most common challenges and best practices to avoid them.
    With over 35 years of combined experience in MLOps at companies like AWS, Google, Lyft, and Uber, and 15 years of experience at Tecton spent helping customers like FanDuel, Plaid, and HelloFresh getting ML models into production, the presenters will share how factors like organizational structure, use cases, tech stack, and more, can create different types of bottlenecks. They’ll also share best practices and lessons learned throughout their careers on how to overcome these challenges.
    // Bio
    Kevin Stumpf
    Kevin co-founded Tecton where he leads a world-class engineering team that is building a next-generation feature store for operational Machine Learning. Kevin and his co-founders built deep expertise in operational ML platforms while at Uber, where they created the Michelangelo platform that enabled Uber to scale from 0 to 1000's of ML-driven applications in just a few years. Prior to Uber, Kevin founded Dispatcher, with the vision to build the Uber for long-haul trucking. Kevin holds an MBA from Stanford University and a Bachelor's Degree in Computer and Management Sciences from the University of Hagen. Outside of work, Kevin is a passionate long-distance endurance athlete.
    Derek Salama
    Derek is currently a Senior Product Manager at Tecton, where he is responsible for security, collaboration experience, and Feature Platform infrastructure. Prior to Tecton, Derek worked at Google and Lyft across both ML infrastructure and ML applications.
    Eddie Esquivel
    Eddie Esquivel is a Solutions Architect at Tecton, where he helps customers implement feature stores as part of their stack for operational ML. Prior to Tecton, Eddie was a Solutions Architect at AWS. He holds a Bachelor’s Degree in Computer Science & Engineering from the University of California, Los Angeles.
    Isaac Cameron
    Isaac Cameron is a Consulting Architect at Tecton. Prior to Tecton, he was a Principal Solutions Architect at Slalom Build, focusing on data and machine learning, where he built his own feature platform for a large U.S. airline and has enabled many organizations to build intelligent products leveraging operational ML.
    // MLOps Jobs board
    https://mlops.pallet.xyz/jobs
    // MLOps Swag/Merch
    https://mlops-community.myshopify.com/
    --------------- ✌️Connect With Us ✌️ -------------
    Join our slack community: https://go.mlops.community/slack
    Follow us on Twitter: @mlopscommunity
    Sign up for the next meetup: https://go.mlops.community/register
    Catch all episodes, blogs, newsletters, and more: https://mlops.community/
    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/
    Connect with Kevin on LinkedIn: https://www.linkedin.com/in/kevinstumpf/
    Connect with Derek on LinkedIn: https://www.linkedin.com/in/dereksalama/
    Connect with Eddie on LinkedIn: https://www.linkedin.com/in/eddie-esquivel-2016/
    Connect with Isaac on LinkedIn: https://www.linkedin.com/in/isaaccameron/
    Timestamps:
    [00:00] Introduction to Kevin Stumpf, Derek Salama, Eddie Esquivel, and Isaac Cameron
    [02:48] Challenges of traditional classical ML into production
    [10:21] Infrastructure cost
    [16:50] Bridging Business and Tech
    [19:23] ML Infrastructure Essentials
    [29:38] Integrated Batch and Stream
    [35:12] Scaling AI from Zero
    [36:23] Stacks red flags
    [45:53] Tecton: Features Quality Monitoring
    [49:06] Building Recommender System Tools
    [53:19] Quantify business value in ML
    [54:40] Wrap up

    56 min
  • DSPy: Transforming Language Model Calls into Smart Pipelines // Omar Khattab // #194

    MLOps podcast #194 with Omar Khattab, PhD Candidate at Stanford, DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.


    // Abstract

    The ML community is rapidly exploring techniques for prompting language models (LMs) and for stacking them into pipelines that solve complex tasks. Unfortunately, existing LM pipelines are typically implemented using hard-coded "prompt templates", i.e., lengthy strings discovered via trial and error. Toward a more systematic approach for developing and optimizing LM pipelines, we introduce DSPy, a programming model that abstracts LM pipelines as text transformation graphs, i.e., imperative computational graphs where LMs are invoked through declarative modules. DSPy modules are parameterized, meaning they can learn (by creating and collecting demonstrations) how to apply compositions of prompting, finetuning, augmentation, and reasoning techniques. We design a compiler that will optimize any DSPy pipeline to maximize a given metric. We conduct two case studies, showing that succinct DSPy programs can express and optimize sophisticated LM pipelines that reason about math word problems, tackle multi-hop retrieval, answer complex questions, and control agent loops. Within minutes of compiling, a few lines of DSPy allow GPT-3.5 and llama2-13b-chat to self-bootstrap pipelines that outperform standard few-shot prompting and pipelines with expert-created demonstrations. On top of that, DSPy programs compiled to open and relatively small LMs like 770M-parameter T5 and llama2-13b-chat are competitive with approaches that rely on expert-written prompt chains for proprietary GPT-3.5. DSPy is available as open source at https://github.com/stanfordnlp/dspy


    // Bio

    Omar Khattab is a PhD candidate at Stanford and an Apple PhD Scholar in AI/ML. He builds retrieval models as well as retrieval-based NLP systems, which can leverage large text collections to craft knowledgeable responses efficiently and transparently. Omar is the author of the ColBERT retrieval model, which has been central to the development of the field of neural retrieval, and author of several of its derivative NLP systems like ColBERT-QA and Baleen. His recent work includes the DSPy framework for solving advanced tasks with language models (LMs) and retrieval models (RMs).


    // MLOps Jobs board

    jobs.mlops.community

    // MLOps Swag/Merch

    https://mlops-community.myshopify.com/

    // Related Links

    Website: https://omarkhattab.com/DSPy https://github.com/stanfordnlp/dspy


    ⁠--------------- ✌️Connect With Us ✌️ -------------

    Join our Slack community: https://go.mlops.community/slack

    Follow us on Twitter: @mlopscommunity

    Sign up for the next meetup: https://go.mlops.community/register

    Catch all episodes, blogs, newsletters, and more: https://mlops.community/


    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

    Connect with Omar on Twitter: https://twitter.com/lateinteraction


    Timestamps:

    [00:00] Omar's preferred coffee

    [00:26] Takeaways

    [06:40] Weight & Biases Ad

    [09:00] Omar's tech background

    [13:35] Evolution of RAG

    [16:33] Complex retrievals

    [21:32] Vector Encoding for Databases

    [23:50] BERT vs New Models

    [28:00] Resilient Pipelines: Design Principles

    [33:37] MLOps Workflow Challenges

    [36:15] Guiding LLMs for Tasks

    [37:40] Large Language Models: Usage and Costs

    [41:32] DSPy Breakdown

    [51:05] AI Compliance Roundtable

    [55:40] Fine-Tuning Frustrations and Solutions

    [57:27] Fine-Tuning Challenges in ML

    [1:00:55] Versatile GPT-3 in Agents

    [1:03:53] AI Focus: DSP and Retrieval

    [1:04:55] Commercialization plans

    [1:05:27] Wrap up

    1 hr 6 min
  • Fireside Chat with LLM Startups // LLMs in Production Conference 3

    // Abstract

    Martian is focused on building a model router to dynamically route every prompt to the best LLM for the highest performance and lowest cost.
    Corti, the Al Co-Pilot for health care uses Al to improve patient care, demonstrating the potential of Al in healthcare and medical decision-making. They recently raised $60M, with Prosus being one of the lead investors.
    Transforms is pioneering in synthetic entertainment, showing how Al can transform the way we create and consume media.
    Moderator: Paul van der Boor
    // Speakers
    Sandeep Bakshi
    Head of Investments, Europe  @prosusgroup3707 
    Shriyash Upadhyay
    Founder @Martian
    Lars Maaløe
    Co-Founder & CTO at Corti | Adj. Assoc. Professor of Machine Learning @ Corti
    Pietro Gagliano
    President & Founder @Transitional Forms
    // Sign up for our Newsletter to never miss an event:
    https://mlops.community/join/
    // Watch all the conference videos here:
    https://home.mlops.community/home/collections
    // Check out the MLOps Community podcast: https://open.spotify.com/show/7wZygk3mUUqBaRbBGB1lgh?si=242d3b9675654a69
    // Read our blog:
    mlops.community/blog
    // Join an in-person local meetup near you:
    https://mlops.community/meetups/
    // MLOps Swag/Merch:
    https://mlops-community.myshopify.com/
    // Follow us on Twitter:
    https://twitter.com/mlopscommunity
    //Follow us on Linkedin:
    https://www.linkedin.com/company/mlopscommunity/

    32 min
  • LLMs in Biomaterials Production // Pierre Salvy // #193

    MLOps podcast #193 with Pierre Salvy, Head of Engineering at Cambrium, LLM in Material Production, co-hosted by Stephen Batifol.


    // Abstract

    Delve into the world of proteins, genetic engineering, and the intersection of AI and biotech. Pierre explains how his company is using advanced models to design proteins with specific properties, even creating a vegan collagen for cosmetics. By harnessing the potential of AI, they aim to revolutionize sustainability, uncovering a future of lab-grown meats, molecular cheese, and less harmful plastics, confronting regulatory barriers, and decoding the syntax and grammar of proteins.


    // Bio

    Head of Engineering at Cambrium, a biotech company utilising genAI to design sustainable protein biomaterials for the future. Pierre spent the last decade researching ways to make computers calculate better biological systems. This is a critical step to engineering more sustainable ways to make the products we use every day, which is their mission at Cambrium.


    // MLOps Jobs board

    jobs.mlops.community

    // MLOps Swag/Merch

    https://mlops-community.myshopify.com/

    // Related Links

    Website: cambrium.bio


    --------------- ✌️Connect With Us ✌️ -------------

    Join our Slack community: https://go.mlops.community/slack

    Follow us on Twitter: @mlopscommunity

    Sign up for the next meetup: https://go.mlops.community/register

    Catch all episodes, blogs, newsletters, and more: https://mlops.community/


    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

    Connect with Stephen on LinkedIn: https://www.linkedin.com/in/stephen-batifol/

    Connect with Pierre on LinkedIn: https://www.linkedin.com/in/psalvy/


    Timestamps:

    [00:00] Pierre's preferred coffee

    [00:10] Takeaways

    [05:10] Please like, share, and subscribe to our MLOps channels!

    [05:25] Weights and Biases ad

    [07:52] Ski story

    [09:54] Pierre's career trajectory

    [13:35] From employee #2 to hiring a team

    [14:42] From employee #2 to head of engineering

    [15:50] Uncomfortable things to say are essential for growth and effectiveness

    [18:27] From biotech to engineering

    [21:10] LLMs at Cambrium

    [24:26] Slackbot

    [25:43] Quick and Easy Solutions

    [26:47] Products created at Cambrium

    [31:56] Impact of EU Regulation on Cambrium

    [35:39] 2nd Biotech Winter

    [36:35] Cost of error vs service not working

    [38:00] Protein Synthesis and Mutations

    [40:03] Large-Scale System Engineering Challenges

    [43:28] Expensive Factors in Experiments

    [44:39] LLMs vs Protein Models

    [47:03] Protein Design with LLMs

    [49:43] Eco-Friendly Product Vision

    [53:28] Space glue

    [54:00] Wrap up

    55 min
  • Product Engineering for LLMs // LLMs in Production Conference Part III // Panel 2

    // Abstract

    A product-minded engineering perspective on UX/design patterns, product evaluation, and building with AI.
    // Bio
    Charles Frye
    Charles teaches people how to build ML applications. After doing research in psychopharmacology and neurobiology, he pivoted to artificial neural networks and completed a PhD at the University of California, Berkeley in 2020. He then worked as an educator at Weights & Biases before joining @Full Stack Deep Learning, an online community and MOOC for building with ML.
    Sahar Mor
    Sahar is a Product Lead at  @stripe  with 15y of experience in product and engineering roles. At Stripe, he leads the adoption of LLMs and the Enhanced Issuer Network - a set of data partnerships with top banks to reduce payment fraud.
    Prior to Stripe he founded a document intelligence API company, was a founding PM in a couple of AI startups, including an accounting automation startup (Zeitgold, acq'd by Deel), and served in the elite intelligence unit 8200 in engineering roles.
    Sahar authors a weekly AI newsletter (AI Tidbits) and maintains a few open-source AI-related libraries (https://github.com/saharmor).
    Sarah Guo
    Sarah Guo is the Founder and Managing Partner at @Conviction, a venture capital firm founded in 2022 to invest in intelligent software, or "Software 3.0." Prior, she spent a decade as a General Partner at Greylock Partners. She has been an early investor or advisor to 40+ companies in software, fintech, security, infrastructure, fundamental research, and AI-native applications. Sarah is from Wisconsin, has four degrees from the University of Pennsylvania, and lives in the Bay Area with her husband and two daughters. She co-hosts the AI podcast "No Priors" with Elad Gil.
    Shyamala Prayaga
    Shyamala is a seasoned conversational AI expert. Having led initiatives across connected home, automotive, wearables - just to name a few, she's put her work on research into usability, accessibility, speech recognition, multimodal voice user interfaces, and has even been published internationally across publications like Forbes. Outside of her research, she's spent the last 18 years designing mobile, web, desktop, and smart TV interfaces and has most recently joined  @NVIDIA  to work on deep learning product suites.
    Willem Pienaar
    Willem is the creator of @Feast, the open-source feature store and a builder in the generative AI space. Previously Willem was an engineering manager at Tecton where he led teams in both their open source and enterprise initiatives. Before that Willem built the core ML systems and created the ML platform team at Gojek, the Indonesian decacorn.
    // Sign up for our Newsletter to never miss an event:
    https://mlops.community/join/
    // Watch all the conference videos here:
    https://home.mlops.community/home/collections
    // Check out the MLOps Community podcast: https://open.spotify.com/show/7wZygk3mUUqBaRbBGB1lgh?si=242d3b9675654a69
    // Read our blog:
    mlops.community/blog
    // Join an in-person local meetup near you:
    https://mlops.community/meetups/
    // MLOps Swag/Merch:
    https://mlops-community.myshopify.com/
    // Follow us on Twitter:
    https://twitter.com/mlopscommunity
    //Follow us on Linkedin:
    https://www.linkedin.com/company/mlopscommunity/

    32 min
  • Enterprises Using MLOps, the Changing LLM Landscape, MLOps Pipelines // Chris Van Pelt // #192

    MLOps podcast #192 with Chris Van Pelt, CISO and co-founder of Weights & Biases, Enterprises Using MLOps, the Changing LLM Landscape, MLOps Pipelines sponsored by Weights & Biases.


    // Abstract

    Chris provides insights into his machine learning (ML) journey, emphasizing the significance of ML evaluation processes and the evolving landscape of MLOps. The conversation covers effective evaluation metrics, demo-driven development nuances, and the complexities of ML Ops pipelines. Chris reflects on his experience with Crowdflower, detailing its transition to Weights and Biases and stressing the early integration of security measures. The discussion extends to the transformative impact of ML on the tech industry, challenges in detecting subtle bugs, and the potential of open-source models and multimodal capabilities.


    // Bio

    Chris Van Pelt is a co-founder of Weights & Biases, a developer MLOps platform. In 2009, Chris founded Figure Eight/CrowdFlower. Over the past 12 years, Chris has dedicated his career to optimizing ML workflows and teaching ML practitioners, making machine learning more accessible to all. Chris has worked as a studio artist, computer scientist, and web engineer. He studied both art and computer science at Hope College.


    // MLOps Jobs board

    jobs.mlops.community

    // MLOps Swag/Merch

    https://mlops-community.myshopify.com/

    // Related Links

    Website: https://wandb.ai/site


    ⁠--------------- ✌️Connect With Us ✌️ -------------

    Join our Slack community: https://go.mlops.community/slack

    Follow us on Twitter: @mlopscommunity

    Sign up for the next meetup: https://go.mlops.community/register

    Catch all episodes, blogs, newsletters, and more: https://mlops.community/


    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

    Connect with Chris on LinkedIn: https://www.linkedin.com/in/chrisvanpelt/


    Timestamps:

    [00:00] Chris' preferred coffee

    [00:33] Takeaways

    [03:50] Huge shout-out to Weights & Biases for sponsoring this episode!

    [04:15] Please like, share, and subscribe to our MLOps channels!

    [04:25] CrowdFlower

    [07:02] Difference between CrowdFlower and Trajectory

    [09:13] Transition from CrowdFlower to Weights & Biases

    [13:05] Excel spreadsheets being passed around via email

    [15:45] Evolution of Weights & Biases

    [19:24] CISO role

    [22:23] Advise for easy wins

    [25:32] Transition into LLMs

    [27:36] Prompt injection risks on data

    [29:42] LLMs for New Personas

    [34:42] Iterative Value Evaluation Process

    [36:36] Iterating on New Release

    [39:31] Evaluation survey

    [43:21] Landscape of LLMs and its evolution

    [45:40] Conan O'Brien

    [46:48] Wrap up

    48 min
  • Building Defensible AI Apps // Gregory Kamradt // #191

    MLOps podcast #191 with Gregory Kamradt, Founder of Data Independent, Building Defensible AI Apps sponsored by Milvus Vector Database.


    // Abstract

    Demetrios engages in a captivating conversation with Gregory Kamradt, an AI visionary deeply immersed in technology and product development. The discussion spans various challenges businesses encounter in implementing AI, the transformative potential of AI in revolutionizing business processes, and the growth and possibilities associated with OpenAI. Gregory shares insights into his latest project, a smart companion app designed to analyze and summarize startup pitches. The episode unfolds as a rich source of knowledge, exploring diverse topics such as AI experimentation, the concept of an AI gateway, the future of finely tuned models for niche applications, and insights into the intricate landscape of AI within big tech, including Google's strategic direction and OpenAI's copyright protection measures.


    // Bio

    Greg has mentored thousands of developers and founders, empowering them to build AI-centric applications. By crafting tutorial-based content, Greg aims to guide everyone from seasoned builders to ambitious indie hackers. Greg partners with companies during their product launches, feature enhancements, and funding rounds. His objective is to cultivate not just awareness, but also a practical understanding of how to optimally utilize a company's tools. He previously led Growth @ Salesforce for Sales & Service Clouds in addition to being early on at Digits, a FinTech Series-C company.


    // MLOps Jobs board

    jobs.mlops.community


    // MLOps Swag/Merch

    https://mlops-community.myshopify.com/


    // Related Links

    Website: https://gregkamradt.com/

    Greg Kamradt (Data Indy): https://www.youtube.com/@DataIndependent

    Milvus Vector Database: https://zilliz.com/what-is-milvus


    ⁠--------------- ✌️Connect With Us ✌️ -------------

    Join our Slack community: https://go.mlops.community/slack

    Follow us on Twitter: @mlopscommunity

    Sign up for the next meetup: https://go.mlops.community/register

    Catch all episodes, blogs, newsletters, and more: https://mlops.community/


    Connect with Demetrios on LinkedIn: https://www.linkedin.com/in/dpbrinkm/

    Connect with Greg on LinkedIn: https://www.linkedin.com/in/gregkamradt/


    Timestamps:

    [00:00] Greg's preferred coffee

    [00:12] Takeaways

    [02:56] Quick word from our sponsor

    [04:22] DevDay

    [06:19] YouTube's unique perspective on the technological revolution

    [09:34] GPT assistance

    [13:36] AI Streamlining Fax Orders

    [18:13] AI Marketplace Dynamics: GPT vs. Specialized

    [22:04] Data Tooling Platform Challenges

    [27:17] The Shield against copyright

    [29:27] Llama Index vs OpenAI

    [31:56] DS Pie and Compiler Tangent

    [34:31] Orchestration Layer is dead!

    [36:49] Personalized AI Models: Understanding Integration

    [38:00] AI Defensibility

    [43:00] Green Field AI Opportunities

    [46:57] LLMs for live event pitch

    [53:38] Exciting content creation process

    [58:03] New context window benchmark

    [1:02:23] AI Gateway

    [1:04:35] Wrap up

    1 hr 6 min

About Agentic Conversations (formally mlops.community)

From the publisher's feed

Relaxed conversations and technical deep dives around AI Agents. This Show is brought to you by the Agentic AI Foundation where the leading agentic open-source projects like MCP, Agents.md, and Goose…

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