What is @MosaicML
's philosophical approach to developing LLMs? Is it like OpenAI: throw everything at the wall and see what sticks? More conservative, like Anthropic, Cohere, etc.? Or like FB, which open-sources everything and lets people figure out use cases? @PrajnaPrayas
@replit
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MosaicML’s LLM Development Philosophy: Aggressive vs Conservative Approach
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Securing AI Agents: Data Permissioning and Leak Prevention
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We want to build AI agents that use internal data to create external interfaces (i.e. customer service bots). How should we be thinking about permissioning? How do we prevent agents from leaking internal data sources via prompt engineering or simply a mistake? @strandbrown
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Open vs Closed Source AI Models: Benefits and Trade-offs
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What are the benefits and trade-offs between open source and closed source models?
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How Replit Integrates MosaicML for AI Development
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How does Replit leverage MosaicML? @YamiToughCookie
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LLMs Deep Dive: Continuing Conversation Beyond Q&A
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We had such a great conversation with @jefrankle and couldn't get to the audience Q+A! Let's keep digging into LLMs by answering some of your questions!
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Replit AI Hackathon Coming to Chicago July 8th
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Replit AI hackathons are on the move. Next stop: Chicago, July 8th. See you there!
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Model shape importance beyond size in AI architecture
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@pirroh @jefrankle Why should model shape be considered in addition to model size?
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LLM Foundry: Open Source Commitment Over Proprietary Secrets
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"We don't make our money by keeping secrets…LLM Foundry is an embodiment of our commitment to open source…" – @jefrankle
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LLM Foundry: Open Source Foundation for Large Language Models
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What's LLM Foundry? See it for yourself: https://
github.com/mosaicml/llm-f
oundry
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Replit Releases Open-Source Code LLM Model v1.3b
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Take a look at Replit's open-source LLM: https://
huggingface.co/replit/replit-
code-v1-3b
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