Practical AI – Episode #290
Towards high-quality (maybe synthetic) datasets
with Ben Burtenshaw & David Berenstein from Hugging Face
As Argilla puts it: “Data quality is what makes or breaks AI.” However, what exactly does this mean and how can AI team probably collaborate with domain experts towards improved data quality? David Berenstein & Ben Burtenshaw, who are building Argilla & Distilabel at Hugging Face, join us to dig into these topics along with synthetic data generation & AI-generated labeling / feedback.
Featuring
Sponsors
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Notes & Links
Chapters
| Chapter Number | Chapter Start Time | Chapter Title | Chapter Duration |
| 1 | 00:00 | Welcome to Practical AI | 00:44 |
| 2 | 00:44 | Sponsor: Fly | 03:06 |
| 3 | 03:56 | What does data collaboration mean? | 03:22 |
| 4 | 07:18 | Understanding your data | 02:40 |
| 5 | 09:58 | How to start curating data | 03:14 |
| 6 | 13:12 | Practical steps to scale | 03:30 |
| 7 | 16:52 | Sponsor: WorkOS | 03:21 |
| 8 | 20:23 | Traditional & new usecases | 04:28 |
| 9 | 24:51 | Virtues of smaller models | 02:13 |
| 10 | 27:04 | What Argilla looks like | 03:52 |
| 11 | 30:55 | User backgrounds | 03:26 |
| 12 | 34:21 | The non-technical POV | 03:50 |
| 13 | 38:23 | Sponsor: Eight Sleep | 02:31 |
| 14 | 41:09 | AI feedback | 03:41 |
| 15 | 44:50 | Hallucination issues | 01:20 |
| 16 | 46:10 | What is Distilabel | 03:58 |
| 17 | 50:08 | Usage & adoption | 02:47 |
| 18 | 52:55 | Where things are going | 02:39 |
| 19 | 55:34 | This is muy bueno | 00:42 |
| 20 | 56:15 | Outro | 00:46 |