arxiv.org/abs/2108.06209 BERT, but for audio. W2v-BERT applies the same Masked Language Modelling objective but to audio.

arxiv.org/abs/2406.04904 Interesting paper on voice cloning.

The paper: Speak, Read, and Prompt is 🔥 the fact that they repurpose speech synthesis as translation problem is just mind-boggling 🤯

You can either maximise the likelihood of a data distribution or minimise the Negative Log Likelihood (NLL) 📝

Euclidean vs Geodesic Distance.

Me right now, after understanding the difference between KL divergence and Cross Entropy.

The opposite of probabilistic is deterministic 🔥

Here’s an idea: take Nigeria’s most popular card game, turn it into a web app, and let people play just by sharing a link. And you know Whot? Make it open source. Can you guess whot I’ll be speaking about at #oscafest25 by Oscahq uvJensen. Source code: github.com/EteimZ/whot/tr…

Whot isn’t just a card game. It’s a game of interaction. Most software implementations miss that, so I built an open-source version you can play over a phone call. I’ll be speaking about it at Open Source Community Africa 25 in my talk “Here’s Whot Happened.” See you there #oscafest25

Day 1 of #OSCAFest25 by Open Source Community Africa was 🔥🔥🔥 Day 2 is definitely going to be a bang 💥 I’ll be speaking today in the Orbital Room at 4:35 PM. The title of my talk is “Here’s Whot Happened”.

A Story of Imperfection: Understanding Imperfect Information Games Or A Story of Imperfection: Decision-Making When the Pieces are Meeting

Had an amazing time at #OSCAFest25 by Open Source Community Africa Day 1 highlight → the mentorship session 🙌🏿 Day 2 highlight → giving my talk and sharing Whot Happened 🎤 Big congrats to the organizers, volunteers, and speakers. Already looking forward to the next #OSCAFest

My graphics skills are limited, yet I managed to outperform state-of-the-art models. Benchmarks aside, there’s still a long road ahead.

I ran the same tests from the GPT-4o Image announcement blog on Nano Banana. Overall, the results were impressive. Its biggest strength is image editing, while its weakest point is text rendering. Read my full breakdown 👉🏿 neurlcreators.substack.com/p/how-nano-ban…

Nano Banana 🍌 gave me dreads. Should I keep it?

Help this little guy select the right action to take 😢

The equation spells its name.

BERT is just a Single Text Diffusion Step! (1/n) When I first read about language diffusion models, I was surprised to find that their training objective was just a generalization of masked language modeling (MLM), something we’ve been doing since BERT from 2018. The first