This episode dives into Google’s Gemma 2, which claims to outperform GPT-3.5 while tackling responsible AI practices. We explore Black Forest Labs' Flux model, featuring 12 billion parameters and tailored versions for various users. Olivia sheds light on the ethical concerns surrounding the resurgence of pseudoscience in machine learning, particularly physiognomy. Lastly, Belinda reviews critical research on AI safety, advocating for clearer metrics to prevent misleading claims about safety advancements.
Contact: sergi@earkind.com
Timestamps:
00:34 Introduction
01:37 Google’s tiny AI model bests GPT-3.5
02:48 Announcing Flux by Black Forest Labs: The Next Leap in Text-to-Image Models
04:28 The reanimation of pseudoscience in machine learning and its ethical repercussions
06:06 Fake sponsor
08:04 MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts
09:55 Spectra: A Comprehensive Study of Ternary, Quantized, and FP16 Language Models
11:41 Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
13:33 Outro