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Outerbounds
Приєднався 27 жов 2021
Building a modern, human-centric machine learning platform.
outerbounds.com
outerbounds.com
Run Metaflow Run: Dive into Metaflow Runner API
Explore the Metaflow Runner API and learn how to run and manage Metaflow runs programmatically. This video covers the Runner and NBRunner classes. These can be used in both blocking and non-blocking APIs, to start runs, performing argument checks, passing parameters, and retrieving returned values. NBRunner is a wrapper over Runner, allowing you to refer to a flow defined in a notebook cell instead of a file. Watch to understand the various use-cases and functionalities of both the Runner and NBRunner APIs with detailed demos.
Переглядів: 40
Відео
How Atomi is Revolutionizing EdTech with Outerbounds
Переглядів 912 місяці тому
We recently caught up with Thierry Wendling, Head of Ai/ML at Atomi, about all the wonderful work they're doing in the EdTech space, and how they're leveraging Metaflow and Outerbounds. For more such conversations, come join us on our community slack: slack.outerbounds.co/ 00:00 Introducing Atomi and Thierry Wendling, Head of Ai/ML at Atomi 05:40 ML/AI tooling at Atomi before Metaflow 07:28 Bes...
Seamless Data Harmonization for Limitless Informatics: MSAID's journey with Metaflow
Переглядів 872 місяці тому
In this presentation, Siegfried Gessulat, co-founder and Head of machine learning at MSAID, unveils how their team is transforming the study of proteomics through data-science. Focusing on mass spectrometry-based proteomics, MSAID highlights the crucial role of proteins as the fundamental machinery within cells. By integrating liquid chromatography with advanced machine learning techniques, MSA...
Building Efficient, Robust, Reproducible Bioinformatics Systems Using Metaflow
Переглядів 693 місяці тому
Eddie Matia from Outerbounds has a background in scientific computing, machine learning developer tools and product management. In this video Eddie explores the integration of AI, specifically transformer models, into computational biology for building reproducible and scalable computational biology systems. He discusses the amazing research happening at the intersection of Machine Learning and...
Revving Up Sales: How Carsales Boosts Profits with Metaflow
Переглядів 414 місяці тому
This Metaflow office-hours discussion showcases use of Metaflow for machine learning projects and the challenges faced at Carsales. Samuel Than shares three main use cases: Cyclops (an image recognition technology), Myfeed (a recommendation system), and Mystique (a number plate detection service). The discussion than talks about their journey to a multitenant approach using Metaflow and how it ...
Clinical disease forecasting using Metaflow at Santa Clara University
Переглядів 964 місяці тому
This talk provides a comprehensive overview of utilizing Metaflow for disease forecasting at Santa Clara University, emphasizing the complexities encountered in model development and artifact management. The collaboration between Santa Clara University and Cepheid Incorporation introduced a distinctive aspect to this initiative. Metaflow was instrumental in mitigating these challenges, facilita...
Free Live Courses: Full-Stack Machine Learning and Building Systems with LLMs
Переглядів 2,9 тис.4 місяці тому
Following the popular hands-on courses and workshops that we taught last year at SciPy, ODSC, and Uplimit, today we are announcing two new live courses that you can join online for free! The courses are taught by Hugo Bowne-Anderson whose courses on DataCamp and other platforms have been followed by over 4 million learners worldwide. The space is limited, so sign up to one or both of the course...
Building a Modern ML platform on Kubernetes using Ray, Argo, and Metaflow at CloudKitchens
Переглядів 1304 місяці тому
In this talk, the team at CloudKitchens presents how they're on a mission to make every engineering team within CloudKitchens be ML ready and how they went about building their v2.0 ML platform. They had started with basic tools and organically grown up to a point. But there were usability and scalability concerns. That's when they switched to Metaflow Ray, Argo, and Kubernetes building their n...
Building ML & AI Systems in 2024
Переглядів 2194 місяці тому
This spring at Netflix HQ in Los Gatos, we hosted an ML and AI mixer that brought together talks, food, drinks, and engaging discussions on the latest in machine learning, infrastructure, LLMs, and foundation models. This talk was by Ville Tuulos, CEO of Outerbounds.
Empowering Radiologists with AI and Metaflow
Переглядів 774 місяці тому
This spring at Netflix HQ in Los Gatos, we hosted an ML and AI mixer that brought together talks, food, drinks, and engaging discussions on the latest in machine learning, infrastructure, LLMs, and foundation models. This talk was by Jay Jha, Rad AI.
Building a Data and ML Platform at BENlabs
Переглядів 1,2 тис.4 місяці тому
This spring at Netflix HQ in Los Gatos, we hosted an ML and AI mixer that brought together talks, food, drinks, and engaging discussions on the latest in machine learning, infrastructure, LLMs, and foundation models. This talk was by by Jon Daniels and Eric Riddoch, BENlabs.
Fast (and Furious) Data with Metaflow
Переглядів 1734 місяці тому
This spring at Netflix HQ in Los Gatos, we hosted an ML and AI mixer that brought together talks, food, drinks, and engaging discussions on the latest in machine learning, infrastructure, LLMs, and foundation models. This talk was by David Berg and Chaoying Wang, Netflix.
NVIDIA Triton Inference Server and its use in Netflix's Model Scoring Service
Переглядів 2,1 тис.4 місяці тому
NVIDIA Triton Inference Server and its use in Netflix's Model Scoring Service
Welcomer to Netflix HQ: Metaflow Stories
Переглядів 1484 місяці тому
Welcomer to Netflix HQ: Metaflow Stories
Running Large Pipelines to Analyze Cloud Costs in Data and AI
Переглядів 695 місяців тому
Running Large Pipelines to Analyze Cloud Costs in Data and AI
Revolutionizing Healthcare Machine Learning with Metaflow at Prolaio
Переглядів 875 місяців тому
Revolutionizing Healthcare Machine Learning with Metaflow at Prolaio
AI Camp, Melbourne: How Carsales Uses Metaflow to move ML from prototype to production
Переглядів 1115 місяців тому
AI Camp, Melbourne: How Carsales Uses Metaflow to move ML from prototype to production
Building the World’s Leading Verification Platform for Soil-Based Carbon Removal
Переглядів 856 місяців тому
Building the World’s Leading Verification Platform for Soil-Based Carbon Removal
On-Premise Multi-Tenant, Secure, Cost-Effective Data Science Platform with Metaflow and Kubernetes
Переглядів 1346 місяців тому
On-Premise Multi-Tenant, Secure, Cost-Effective Data Science Platform with Metaflow and Kubernetes
Build observable ML/AI systems with Metaflow cards - a short demo
Переглядів 8237 місяців тому
Build observable ML/AI systems with Metaflow cards - a short demo
Building a Modern Power Company using Data Science and Metaflow: Equilibrium Energy
Переглядів 2978 місяців тому
Building a Modern Power Company using Data Science and Metaflow: Equilibrium Energy
Insuring Success: Vouch's GenAI and LLMs Revolutionize Small Business Coverage
Переглядів 548 місяців тому
Insuring Success: Vouch's GenAI and LLMs Revolutionize Small Business Coverage
AI Cowboy -- Made with OSS Python software
Переглядів 2458 місяців тому
AI Cowboy Made with OSS Python software
Making Data Scientists More Productive at Tala
Переглядів 2248 місяців тому
Making Data Scientists More Productive at Tala
Which OSS LLMs is Jeremy Howard most excited about?
Переглядів 1948 місяців тому
Which OSS LLMs is Jeremy Howard most excited about?
The risk to foundation models of regulatory capture and the EU AI Act
Переглядів 1558 місяців тому
The risk to foundation models of regulatory capture and the EU AI Act
How to actually make LLMs uncool again
Переглядів 1448 місяців тому
How to actually make LLMs uncool again
Fantastic chat. I always enjoy listening about and reading Chip's work.
Incredible chat, folks! Lots to learn. Thanks
thanks guys wasnt expecting seeing Hugo here :D
It would be helpful to start by explaining why we need a runner
Is there any where we can see the repo for the ai-examples with pixi? Whisper is very interesting and we would love to see how that was set up as a good starting point for us if that is something that is public of course
Great Data/ML Platform recipe Jon and Eric! Can't wait to bring it to my kitchen to try it on :)
where is the link ?
I love listening to Simon. So dear host, please let the guest talk and find a way to drive the conversation without interrupting them so much.
Hello Hugo, is this event in-person ONLY? If yes, where exactly?
it's online: please follow the link in the video description :)
Will registrants get access to a video copy after the fact?
As each session is intended to be as interactive as possible, we won't share the videos. But we will have further workshops!
why the link is not working ? :(
which link isn't working for you?
@@outerbounds the tutorial link , the sandbozx one
Way to go Eric!!
Every time I hear Simon talk I get super excited and sometimes I don't even know what I'm excited about. But, I just know something has happened and that my spare time over the next week is accounted. Simon rocks!!!
George Hotz is looking to build a machine + software that you can buy for the price of a small car, run off house electricity and use to train something like Llama from scratch. TinyGrad and TinyBox.
In the past two months - Mark Zuckerburg said the next Llama will be state of the art. GPU Sales also show Meta in the lead, tied with MS.
Why every start up losses ideas, 100 % commerce, return my money from dalle 2, if not go f**k yourself closedAI
Totally closed org, they're threatened that someone others will achieve the same level of AI development. The revolution is coming soon. I highly prob that my opinion here will vanish, but revolution is coming.
❄️💙🎄😊
Emo-Robo-Whiney-Country-Data-Core 🤖
This was fantastic. A lot to learn from Jeremy
1:02:00 I like this argument: some people love having more power than others...they really dedicate themselves to it...Ensuring openness and democracy allow the rest of us to invest in defense...cos its much easier to work on defense than attack...and stop the attack path when such people go crazy...
You can't have an LLM just randomly generating text about a product, there are laws that govern that
As of the last few weeks ChatGPT with GPT4 has been garbage. It just like when you google a question and get a vague, off topic list of possibilities. It used to be specific.
the guy just hates open ai
you love it ?
that’s one way to categorize what you don’t like hearing
Me too, mostly moron ping AI search engine
Of course certain people want to lobotomize AI. They cannot let the general population have such a truth oracle. AI could set is free, and that can never be. When they say AI will destroy the world, they mean THEIR world. It's their status-quo they are worried about.
Could i run mistral 7B on raspberry pie ?
37:37 mistral 7B
was there a name for that technique jeremy mentioned for the good model training the "shit" model?
Distillation?
Q*anon I'm dying 😂
Share Spotify link, it's trouble to hear while traveling
what a dystopian vision
I listened with interest, and Jeremy is an actual expert. But I am not persuaded that superintelligent AI is far away, or that an AI on every desktop offers much protection. If anything, AI for all is going to accelerate the discovery of architectures for efficient learning and agentic AI, and that's just getting closer and closer to the conditions for successfully self-enhancing AI. And superintelligent AI seems likely to overwhelm humanity even if we are assisted by AIs of human intelligence. So we still need something like "superalignment". Futhermore, even if superintelligent AI that surpasses humans-with-AI is somehow chimerical, won't humans-with-AI overwhelm humans-without-AI? And I also note that democratic processes seem to have a very small part in determining the outcome of humanity's AI adventure. AI is driven forward by money and power now, decentralization depends on the boldness and ingenuity of maverick techies, and either way, the whole thing is an enormous experiment in creating nonbiological thinking beings, potentially giving away humanity's chief evolutionary advantage to entities that aren't even DNA-based.
Any scenario that sounds like it belongs in a movie is completely unrealistic
@@VoltLover00exactly. It's clear some people never programmed before because building anything sufficiently large of sophisticated is extremely janky.
@@VoltLover00 Space tourism, blue LEDs, and Tom Cruise flying a jet fighter for real. They all belonged in a movie until they didn't ;-) I don't think it's particularly speculative that humans-with-AI could overwhelm humans-without-AI, since that is already the case with many forms of technology. For that matter humans-with-money in general overwhelm humans-without-money, and AI is just one of the techniques they might use to achieve that. But there's a whole bunch of dangers we have to get past before we even reach the danger of AI replacing humans. We already have systems such as electrical grids that people rely on for life and that aren't always well understood (hence the 2003 blackout). Adding AI to safety-critical systems such as the electrical grid or international finance, is almost certainly going to result in at least one major foot-shooting by humanity. But to varying degrees that's how all progress works.
Hi, really enjoyed the talk. Does Jeremy has an X account I could follow? Thanks
@jeremyphoward
Is that a Tim tam Hugo was eating in the beginning 😂?
I think he ate 2 or 3 double coated tim tams actually and Jeremy got jealous!
Great talk mostly though the bellyaching was a bit cringe….
I mean he is trying to make LLMs uncool so being mid and cringe is right on target.
Starting my own AAA, any hot tips?
I got lost from where you found the Jupyter notebook page. It suddenly appeared in the video from somewhere. Didn't find it so the rest of the video was mute for me.
The github repository (which contains setup instructions) is in the UA-cam video description: github.com/outerbounds/generative-ai-summit-austin-2023
That's a big reference page with god knows what on it - not a notebook - wtf is "setup", its not a notebook?- OK OK I "should" know I suppose. How can you be so inarticulate? - an LLM would give me exactly what I'm looking for I'm 100% sure. But you just can't grasp it. Sorry autist. Long live LLMs they grok language and communication. Apols, you're just another half-functioning human I guess. They end up in tech usually.@@outerbounds
Very good workshop! Appreciate y'all uploading this
🎯 Key Takeaways for quick navigation: 00:00 🎉 *Introduction and Background* - Ville Tuulos introduces the topic of building production systems with generative AI and data science. - He discusses the evolution of online shopping experiences, emphasizing the need for more human-like interactions in e-commerce. - Ville highlights the potential of AI and generative models in transforming user experiences. 05:10 🛋️ *Reimagining Online Shopping* - The shift towards more immersive and human-like online shopping experiences. - Exploring the possibilities of interactive product visualization and personalization. - The importance of leveraging generative AI to create unique and engaging customer interactions. 09:03 🤖 *Building Sophisticated AI Systems* - The technical challenges involved in creating AI-driven e-commerce experiences. - Emphasis on the need for custom AI solutions rather than relying on off-the-shelf models. - The importance of data governance and quality for AI applications. 12:05 📈 *Maximizing Revenue and User Experience* - Strategies for optimizing revenue through AI-driven product recommendations and marketing. - The shift of content generation responsibility from non-technical departments to AI engineers. - The growing complexity of business operations and the role of AI in different domains. 16:47 🛠️ *Challenges and Infrastructure* - The realization that AI and generative systems pose complex challenges for various projects. - The need for common infrastructure and tooling to support multiple AI initiatives. - Practical considerations for scaling AI development across different domains and industries. 19:05 📜 *Building Production Systems within Existing Frameworks* - Adapting to privacy laws and compliance requirements. - Navigating the challenge of increased computational demands in modern systems. - The fragmentation and heterogeneity of compute resources in today's landscape. 20:00 🔄 *Adapting to Diverse Compute Needs* - The absence of a one-size-fits-all approach for compute resources. - The need for CPUs, GPUs, distributed training, and specialized hardware. - The evolving complexity of compute requirements. 21:11 🛠️ *Orchestrating Interrelated Components* - The importance of orchestrating multiple interrelated components in real-world systems. - Examples of component orchestration in tasks like inventory forecasting. - Managing complex pipelines involving data processing, feature engineering, training, and more. 22:10 🔄 *Iterative Development and Tracking* - Emphasizing the need for iterative development in building production systems. - Tracking code, models, and data changes over time. - The importance of continuous improvement in AI and ML projects. 23:18 🚀 *Operating AI Systems in Production* - Challenges of operating large-scale AI systems in production. - Connecting systems to upstream and downstream services and databases. - The need for robust observability layers for distributed systems. 24:17 📦 *Managing Software Supply Chain Complexity* - Addressing the increasing complexity of the software supply chain in ML and AI. - Challenges with dependency management in a rapidly evolving library ecosystem. - The limitations of traditional containerization in handling dynamic libraries. 25:26 🔄 *Unifying Concerns with Frameworks* - The need for unified frameworks to address concerns in ML and AI system development. - Drawing parallels with the evolution of full-stack engineering in the JavaScript ecosystem. - The potential for frameworks to simplify the development of AI-driven systems. 26:49 🌐 *Resources and Announcements* - Encouraging exploration of Metaflow and its relevance to AI system development. - Mentioning upcoming announcements related to distributed training and integration. - Highlighting the active open-source community around Metaflow. 27:33 📢 *Call to Action* - Inviting the audience to start building AI-driven systems. - Offering assistance and access to open-source resources. - Emphasizing the role of AI in optimizing business processes across various departments. Made with HARPA AI
This is a fantastic session. I would love to see Bindu Reddy take part in upcoming panel discussions.
Great! My reaction was: this would work great if a run only produced one model, but if I remember correctly, the recommended pattern for hyper parameter tuning is to have one flow that fans out and trains many models. At that point you might be the sort of group that goes for a dedicated model registry tool like MLFlow, CometML or SageMaker registry, but is there a way to make tagging in multi model runs can work natively in Metaflow?
"Promosm" 💦
from Austin Texas
Incredible conversation, folks! Thanks
I am Olaniyan remilekun from Nigeria
Hey is there any javascript integration
Looks great, can you share please a video how to configure everything? For me thats currently a big hussle, and I don't know which parameter to set. Will be a big help for using metaflow.
Nice please let me know the VS Code theme that is used
Great tutorial, links and program worked fine for me. Thanks for sharing.
i want to start making soft and rapping i have an acer laptop. does soft soft co with good softs already?