🚀 We’re hiring a Backend Engineer at Daffy! 🚀
Come help us scale our modern donor-advised fund, build seamless integrations, and optimize our backend in Kotlin, Dropwizard & PostgreSQL.
Join a mission-driven team making giving easier for everyone.
Accenture had $1.2 billion in new bookings related to GenAI, and it has 69,000 people working in data and AI.
69,000 people who don't know anything about AI are helping the largest US companies with navigating the fast changing AI world.
One of the biggest grifts in the world.
nobody will remember:
- your salary
- how “busy you were”
- how many hours you worked
people will remember:
- if you hopped on a quick call
- when you hopped on a quick call
- how many quick calls you hopped on
- how you made them feel when you hopped on a quick call
But some places are retaliating in cheaper ways: Lancaster, CA transformed its main street into a tree-lined boulevard.
It took 8 months and cost $11.5m - generating around $273m in economic output since 2010.
This is just the beginning.
So if you’re a @DaffyGiving member, thank you for your generous involvement in our community and for helping seed a platform that we believe can positively impact millions. 🙏
If you haven’t tried Daffy yet, come join us! 💗
https://t.co/gVD8fCBsnk
Synthetic data will provide the next trillion tokens to fuel our hungry models.
I'm excited to announce MimicGen: massively scaling up data pipeline for robot learning! We multiply high-quality human data in simulation with digital twins.
Using < 200 human demonstrations, MimicGen can autonomously generate > 50,000 training episodes across 18 tasks, multiple simulators, and even in the real-world!
The idea is simple:
1. Humans tele-operate the robot to complete a task. It is extremely high-quality but also very slow and expensive.
2. We create a digital twin of the robot and the scene in high-fidelity, GPU-accelerated simulation.
3. We can now move objects around, replace with new assets, and even change the robot hand - basically augment the training data with procedural generation.
4. Export the successful episodes, and feed that to a neural network! You now have an near-infinite stream of data.
One of the key reasons that robotics lags far behind other AI fields is the lack of data: you cannot scrape control signals from the internet. They simply don't exist in-the-wild.
MimicGen shows the power of synthetic data and simulation to keep our scaling laws alive. I believe this principle apply beyond robotics. We are quickly exhausting the high-quality, real tokens from the web. Artificial intelligence from artificial data will be the way forward.
We are big fans of the OSS community. As usual, we open-source everything, including the generated dataset!
- Website: https://t.co/4pEZ2igP2u
- Paper: https://t.co/O7qi3FTBIs
- Dataset is hosted on HuggingFace (thanks @_akhaliq!!): https://t.co/E9ryjWNzBE
- Code: https://t.co/7Blv1Z5F09
MimicGen is led by @AjayMandlekar, deep dive in the thread:
1/3 Tonight I was reminded of one of the most astonishing education stats I've ever seen. The changes in math education on San Francisco led to the number of African American students taking AP math exams to go from 27 to 18 to 12 to 3 from 2017/18 to 2020/21.
Prof. Juana Sanchez is an educator in the UCLA Statistics Department -- one that cares deeply about statistics education. I remember how excited I was to see that she published a book on Time Series. It has attracted a lot of attention at #KDD2023 and I can't wait to buy a copy!
I have a teeny little announcement:
I've worked with cloud data warehouses for 9 years. And for 9 years, I've felt frustrated at the dev experience.
To fix it, I'm working on a new open source project. I'm calling it Titan.
Let me give you a sneak peak at what Titan is –
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