DeepSeek just dropped V4! Two open-source MoE models with 1M context windows under MIT license. DeepSeek-V4-Pro: 1.6T total parameters (49B active per token), pre-trained on 33T tokens. This makes it the largest open-source model available – bigger than Kimi K2.6 (1.1T) and
@sumanth_077
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Real-time synthesis latency optimization through streaming preprocessing
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Right, preprocessing breaks streaming latency, doing it during synthesis keeps it real-time
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Generated Speech Examples Showcase Real AI Voice Technology
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You can even hear and compare real generated speech examples here:
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Text Normalization for Production Voice AI Agents
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Inline text normalization for Voice AI agents! Real-time TTS models still struggle with non-standard text. Numbers, dates, currencies, abbreviations – the structured text that shows up in every production voice agent. "$42.50" should sound like "forty-two dollars and fifty
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Harness Tools and Memory Enable Effective AI Agent Function
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Right, harness adds the tools and memory that make it actually work
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OpenHarness: Open-Source Agent Harness for AI Systems
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Lightweight agent harness for building AI agents! OpenHarness is an open-source agent harness that gives LLMs tools, memory, permissions, and coordination. Here's the concept. The model provides intelligence. But to be a working agent, it needs tools to interact with the world,
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Intuitive Task Assignment Interface Improves Over CLI Commands
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Makes task assignment way more intuitive than CLI commands
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Multica Makes Coding Agents Accessible to Non-Technical Users
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Turn coding agents into real teammates! Multica is a native desktop app that brings coding agents like Claude Code, Codex, and OpenCode to non-technical users through a visual interface. Here's the problem with coding agents today. 95% of knowledge workers can't use them. Not
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CLAUDE.md Framework Makes Claude Code 10x More Powerful
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A single 𝗖𝗟𝗔𝗨𝗗𝗘.𝗺𝗱 file that makes Claude Code 10x more powerful! This repo distills Andrej Karpathy's observations on LLM coding pitfalls into four actionable principles. The problem Karpathy identified: LLMs make wrong assumptions without asking. They overcomplicate
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Colab Notebook Setup for AI Experimentation
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Glad it helps. The Colab notebook has all the setup already done, so it's pretty straightforward to start experimenting