Modal

At Modal, our belief is that if you hire smart people who care about the product, you actually don't need a lot of management. As our founder Erik said recently on the 1 to 100 podcast, "Smart people with a mission, you don't have to manage them that closely up to a point. Of course, as you get bigger, there's a minimum viable bureaucracy where you have to add a little bit of project planning and stuff like that. But largely speaking, you can hold back to a remarkable degree." This approach is inspired by his experience at Spotify, where he recalls, "I didn't know who my manager was for the first two years at Spotify. No one told me." While that extreme might not work for everyone, here at Modal, we strive to: - Hire exceptionally strong people - Give them the liberty to figure out what they should do - Rely on self-organization and passion for the product How does your company balance autonomy with structure as you scale? What's your experience with "minimum viable bureaucracy"? https://lnkd.in/gGhK-fRF #StartupCulture #Hiring #LeadershipStrategy

If you've been wondering what the difference between LoRA and QLoRA is and which one to use when fine-tuning LLMs, our new blog post has it all covered! Takeaways: - If you have access to hardware with enough VRAM for the model you want to fine-tune, use LoRA. (Click through for a table with the required memory for different model sizes). - If you don’t have enough space, for example, if you only have access to a free T4 on Google Colab, try qLoRA. https://lnkd.in/ezN9fHwb #llms #chatgpt #finetuning #ai

Frontend engineers have hot reloading. Backend engineers have unit tests. Data engineers, on the other hand, have to write a cron job, create a PR, deploy the changes, watch the job run for hours to see if it fails, add debug print statements if it does, look at the code, tweak the code, just to get some feedback on the work they've done. Speeding up that feedback loop is one of the things that inspired our founders Erik Bernhardsson and Akshat Bubna to build Modal. First up towards that goal: getting containers in the cloud launched quickly! In a new article on the Modal blog, we cover how we achieved blazing-fast container launches with some clever optimizations. https://lnkd.in/eF7wMjHe #docker #containers #kubernetes #ai #cloudcomputing

nobody will remember: - your salary - how “busy you were” - how many hours you worked people will remember: - how effortlessly you scaled - how fast your cold boots were - that time you scaled up to 1000 H100s

We're super excited to launch our new interactive code playground, built by Rachel Park, that lets you write and execute code on Modal directly from your web browser - no installation required! The playground makes it easy to take Modal for a spin, whether you're a curious developer trying us out for the first time or an experienced user looking to experiment with new features. 🔍 Want to know how we built it? (And made it secure enough to run arbitrary code)? Check out our blog post, where we break down the magic that powers this playground. Ready to give it a try? Dive into the Modal playground and start exploring today! 🚀 👉 Read the full blog post and try it out here! https://lnkd.in/euhwXUxP #cloudcomputing #coding #python #devtools #Modal

Shoutout to the team at Modal. After 20 years of looking for good infrastructure tooling for ML, I think I may have finally found it. Modal is insanely quick to spin up with just a few intuitive python decorators. Abstracts away docker, provisioning, scaling up, parameter sweeps, monitoring, etc. Great work Erik Bernhardsson and team!

OpenAI's Whisper is the OG open-source speech-to-text library, but if you're building an app in production these days, you likely won't be using the library directly. That's because it's not the most performant option, and it's missing functionality like speaker diarization and word-level timestamps. Instead, you should use one of the many Whisper variants that have been published by community members over the last two years, which provide additional features and performance speedups. In a new article on the Modal blog, we cover the main Whisper variants, like WhisperX from Max Bain, and Whisper JAX from Sanchit Gandhi, their pros and cons, and how you can run them on Modal's serverless infrastructure. Note: The open-sourced Whisper library is separate from the hosted speech-to-text endpoints offered by OpenAI, which are backed by Whisper models. There are also a number of startups like Deepgram and AssemblyAI that offer transcription on-demand via API. https://lnkd.in/e__m5b3Q #ai #chatgpt #whisper #transcription #asr #speechtotext #stt

Mirror, mirror on the wall, which is the fairest LLM fine-tuning framework of them all? In a new article on our blog, we break down the pros and cons of three of the most popular LLM fine-tuning libraries: Axolotl from Wing Lian, Unsloth AI from Daniel Han, Torchtune from Rafi Ayub and Rohan Varma at AI at Meta Takeaways: If you are a beginner: Use Axolotl. If you have limited GPU resources: Use Unsloth. If you prefer working directly with PyTorch: Use Torchtune. If you want to train on more than one GPU: Use Axolotl. https://lnkd.in/epYqNufp #ai #finetuning #llms #chatgpt #pytorch

🚀 Exciting news: We're slashing prices on CPUs and our most powerful GPUs by 15-30%! 📉💰 Why? The GPU market has evolved, and we're passing the savings on to you. This is a win for AI builders and consumers alike! When? New users: Effective immediately Existing users: Phased rollout, with some changes coming in September Building the future of AI just got more accessible. Let's innovate together! 💡 Read more here: https://lnkd.in/eGgYnsMv

it's hard to find GTM leaders who are also deeply technical at their core 🛠 Modal is for developers though, so it was important that our first GTM hire be someone who could really understand the magic behind our product and communicate that in a compelling way to our customers thrilled to have Alec be that person! time to crank up the heat on our PLG 🔥