Dataiku President Krish Venkataraman discusses why AI is critical for companies and how Dataiku helps its customers manage the balance between excitement and concern for AI on #NYSEFloorTalk with @JudyKShaw.
Just announced at #EverydayAINewYork, our vision for LLM Mesh💡Read more about it here: | https://t.co/VwtKsV6ib5 | Also, if you're here IRL or watching the livestream, hear from our CTO & co-founder Clément Stenac about the LLM Mesh, the common backbone for #GenAI applications:
In my blog, I describe the full process to reveal a path on a map on scroll in 4 steps, with:
- GoogleMyMaps
- #MapShaper
- #d3js
- #scrollama
✒️ ✌️ Blog post: https://t.co/CFqw7SOZoi
#dataviz#scrollytelling
Big news: Today, we’re excited to announce a $400 million #SeriesE funding round for a $4.6 billion valuation to bring #EverydayAI to exponentially more organizations worldwide. Read more on our blog: https://t.co/zawKHRZa9d #AI#datascience#machinelearning
This just in: Dataiku is now officially a 2x Gartner Magic Quadrant LEADER! Be one of the first to check out the just-released 2021 Magic Quadrant for Data Science and Machine-Learning Platforms, courtesy of yours truly. | https://t.co/vyQxoEmkr9
In a simulated economy, an AI came up with a counterintuitive tax policy that led to a smaller gap between the rich and the poor. (from May) https://t.co/TsdJIseYDk
We’re excited to announce a $100 million Series D round led by @Stripesco_, with Tiger Global Management joining existing investors—fueling the support of our customers who understand a collaborative and end-to-end AI strategy is critical to their success. https://t.co/qI5OQScDFu
@NeilRyanPierce Depends on what you’re trying to do, complexity, scale, data accessibility, .... I use @dataiku for many #nocode data grooming and calc pipelines. You should also checkout @pipedream. I just started playing but will most likely migrate some standalone GCP serverless functions.
For our autoML reading group, we are (proof)reading some of the classic papers. And @goulagman found this (slightly) better budget allocation for Hyperband #MachineLearning#autoML https://t.co/WVlI6VzS8d !
Pursuing our exploration of Active Learning, here is an insightful reproducibility experiment by @goulagman on Diverse Mini-Batch Active Learning: https://t.co/PagJLY2OyE
Labeling data is a task all too often overlooked, and the promess of Active Learning is yet to be entirely fulfilled. Check out this review blogpost from @goulagman https://t.co/FAhOkNw4c8 !