AutoVRse

We are super excited to announce the official list of winners in the Asia region!

Startups Of The Year 2023: Asia Winners

Mamba sets a new benchmark for audio waveform modeling and autoregressive speech generation, surpassing SaShiMi and other models. 

Study Demonstrates Mamba’s Breakthrough Performance in Autoregressive Speech Generation

Recently, neural audio codec model, have replaced conventional acoustic representations with a high-compressed audio codec.

Neural Codec Language Models and Non-Autoregressive Models Explained

Once trained, LLMs are often deployed as a conditional generation service (e.g., completion API [34] or chatbot.

LLM Service & Autoregressive Generation: What This Means

I’m running geth and <a href="http://themillionetherhomepage.com/0xF51f08910eC370DB5977Cff3D01dF4DfB06BfBe1" target="_blank">TheMillionEtherHomepage.com</a> back-end on a low-cost Digital Ocean (DO) Ubuntu droplet. I use <strong>monit</strong> to autorestart geth and send email alerts when something goes wrong with the processes.

How to monitor geth and autorestart it on crashes with monit

Mamba, a selective SSM model, outperforms HyenaDNA in long-sequence DNA modeling, excels in speech generation benchmarks, and delivers superior efficiency 

Mamba’s Performance in DNA, Audio, and Speed Benchmarks

Mamba, a selective SSM, is benchmarked across synthetic tasks, language modeling, DNA sequence classification, and speech generation. 

Out with Transformers? Mamba’s Selective SSMs Make Their Case

Discover how Selective State Space Models (SSMs) optimize sequence modeling by balancing efficiency and effectiveness. 

Transformers Are Powerful, but Selective State Space Models Just Might Be Smarter

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