Zerve AI retweeted
Most AI tools help you write. Ours helps you do research.
Today we launched the AI Co-Researcher at Zerve.
It's a multi-agent system that runs the research cycle end to end. Not a chat assistant sitting next to your notebook. A parent agent that plans the work and spins up sub-agents for systematic review, coding, analysis, replication, and drafting.
#AI #MultiAgent
Zerve AI retweeted
3 weeks until AI and Big Data Expo Global 2025!
📍 Olympia, London
🗓️ Feb 5-6, 2025
Join 7,000+ professionals to explore AI's future. Hear from Meta, Pfizer, Unilever, LinkedIn & more.
Register your pass today: ai-expo.net/global/tickets-2…
#ai #expo
Zerve AI retweeted
🎉 HUGE congratulations to @Zerve_AI, #IntelIgnite Europe batch 6 alumni, on raising $7.6M in seed #funding! Jason Hillary, Greg Michaelson and Phily Hayes – it’s an honor to be a part of your journey 🔥
Learn more: intel.ly/3Uqm8pq
#IAmIntel #DeepTech #Startups
Zerve AI retweeted
Join us for an inspiring keynote featuring two groundbreaking AI projects powered by Zerve AI, the Irish data science platform.
Limited Tickets Available: eventbrite.ie/e/analytics-su…
Zerve AI retweeted
We are just 3 weeks away from Analytics Summit 2024.
Thank you to our sponsors for your support. Your contribution helps us bring together a world-class event for the data and analytics community.
Tickets still available: lnkd.in/ecfKjb3j
Zerve AI retweeted
If something could kill Jupyter notebooks, this would be it.
Zerve is a web-based IDE. It's block-based, like a notebook, but it follows a different philosophy, and the experience is very different.
And they just released a killer feature!
You can now drag and drop any model from HuggingFace, a dataset, and fine-tune it using your infrastructure and GPUs. No privacy concerns, no data leaks, and no need to manage any infrastructure.
Fine-tune your model with your data and host it in your environment without leaving the tool.
A lot is happening in the attached screenshot, but that's an end-to-end process to fine-tune Gemma 2B.
This is huge, but that's not all:
1. Zerve is web-based, so you can access your work anywhere
2. Collaboration is a first-class citizen
3. You can deploy your code directly
4. It promotes code modularity by using blocks
5. You can use multiple languages together
6. You can run code blocks in parallel
Zerve is new, but it has the potential to change how data scientists and machine learning practitioners write code. I'm rooting for them.
The tool is free. You can start right now by visiting.
Thanks to their team for collaborating with me on this post.
Zerve AI retweeted
This is the future of data science development.
Zerve is a new web-based IDE. It's block-based like a Jupyter notebook but follows a different philosophy, and the experience is much different.
Check the attached video. I'll walk you through a simple example.
Zerve is not a fork of Jupyter. It's a completely reimagined experience where collaboration is a first-class citizen.
But there's something else:
Unlike in a regular notebook, you can deploy your models directly from Zerve. They store and cache every asset we use and generate inside a notebook, so it takes seconds to deploy your work.
A few additional notes about Zerve:
1. It's web-based, so you can access your work anywhere.
2. Collaboration is a first-class citizen.
3. You can deploy your code without going anywhere.
4. It promotes code modularity by using blocks.
5. You can use multiple languages together.
6. You can run code blocks in parallel.
Zerve organizes your code as a DAG. Each block inherits the state of every block before it. Everything runs in a serverless architecture.
Zerve is free. You can start using it right now by visiting hubs.ly/Q02qxwnh0.
Thanks to the team for answering my questions and sponsoring this post.
Zerve AI retweeted
The revolutionary Zerve IDE for data science launches today! Zerve gives ML teams a unified space to collaborate, build and deploy projects... and is free for most use-cases! In today's episode, Zerve co-founder Dr. Greg Michaelson explains all the details.
Watch here: superdatascience.com/753
Greg is a super-insightful, crisp and clear communicator; I think you'll really enjoy our conversation. More on him:
• He's Co-Founder and Chief Product Officer of Zerve, which just raised $3.8m in pre-seed funding.
• Previously spent 7 years as DataRobot’s Chief Customer Officer and 4 years as Senior Director of Analytics & Research for Travelers.
• Was a baptist pastor while he obtained his PhD in Applied Statistics from The University of Alabama — that perhaps explains some of the variance in how he’s such a silver-tongued communicator!
Today’s episode will appeal most to hands-on practitioners like data scientists, machine learning engineers and software developers, but may also be of interest to anyone who wants to stay on top of the latest approaches to developing and deploying ML models.
In this episode, Greg details:
• Why his swish new Zerve IDE is so sorely needed.
• How their open-source Pypelines project uniquely generates Python code for Automated Machine Learning.
• Why AutoML is not suitable to most commercial use cases.
• Why most commercial A.I. projects fail and how to ensure they succeed.
• The straightforward way you can develop speaking skills as slick as his.
Thanks to @Oracle and @AiProphets for supporting this episode of Super Data Science, enabling the show to be freely available on all major podcasting platforms as well as the video version we publish on YouTube. This is episode #753!
#superdatascience #datascience #machinelearning #softwaredevelopment
Zerve AI retweeted
We’re so excited for Zerve, Intel Ignite Europe batch 6 participant, who have launched into general release and on @ProductHunt! Here’s the link to Upvote: lnkd.in/emunSqAT
Zerve AI retweeted
3/3 💡 Excited to see how Zerve's DAG structure and serverless architecture will enhance modularity and efficiency in coding projects. The potential for community-driven innovation here is immense. Can't wait to dive in! #FutureOfCoding #MachineLearning
Zerve AI retweeted
🤖 Introducing Zerve AI - the perfect blend of Jupyter, Figma, and VSCode! 🚀 Discover the ultimate AI tool with a touch of design and unbeatable coding capabilities. ✨ Check it out at aitoppicks.com and let your creativity and productivity soar! #AI #Productivity @Zer
Zerve AI retweeted
Zerve AI is the Platform Architected for Real #DataScience and #AI Development! What is "Real" about that? Well, that means it's built for Code-First Data Teams who love coding with Jupyter Notebooks, and also with VS Code and Figma. So, imagine converging all of those into one platform! Well, you don't have to imagine it. You can do it. Now! On Zerve!
Get started here with Early Access and their FREE use plan: hubs.ly/Q02hBzSQ0
I tried it out. See a sample screenshot from my first session below. It was super eazy-peazy to get started, import libraries, perform numerous coding tasks in different blocks, connect them, derive new products from datasets created in another block, present my results, share the results, and continue further exploratory analysis (or enable a colleague to continue where I left off).
Zerve’s Data Science Development Environment gives data science and #ML teams a unified space to explore, collaborate, build, and deploy data science & AI projects like never before.
I am a Zerve partner. And I love what they have created.🥰
Zerve AI retweeted
I love notebooks, and Visual Studio Code made them much better, but after using Zerve, they feel outdated.
Zerve is a new web-based IDE. It's block-based like a notebook but follows a different philosophy, and the experience is much different.
It's not a fork of Jupyter, and it's not an improvement. It's a completely reimagined experience. This comes with an important advantage:
Zerve allows teams to collaborate on the same project without breaking each other's work. This is one of Jupiter's Achilles heels. Zerve's architecture solved it from the ground up.
The team sponsored this post and gave me early access to the tool to try it. I imported some of my notebooks and reproduced some common scenarios I frequently use.
I feel this can change how data scientists and machine learning practitioners write code.
Here are a few notes:
1. It's web-based, so you can access your work anywhere.
2. Collaboration is a first-class citizen.
3. You can deploy your code without going anywhere.
4. It promotes code modularity by using blocks.
5. You can use multiple languages together.
6. You can run code blocks in parallel.
Zerve organizes your code as a DAG. Each block inherits the state of every block before it. Everything runs in a serverless architecture.
The tool just came out, so we don't know how the community will use it.
It's free. You can start right now by visiting hubs.ly/Q02hBzgs0.
I can't wait for more people to try it and share what they think!
