Hard agree. Even the most basic of prompt engineering questions as me fishing through Reddit in a vain quest for answers.
AI
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LangChain Self Query Retriever: Avoiding Prompt Injection in Agents
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Let's use LangChain to analyze LangChain! And show off the power of our self query retriever in the process "what did they say about prompt injection in the agents in production webinar?" Here's why vanilla semantic search would mess up the response to this query:
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Stable Diffusion generates AI Arsenal player with mixed results
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Generative AI like @StableDiffusion isn't perfect (struggles to get faces right), but suddenly I play for @Arsenal and that's not bad at all (except for them). On, and Puma is no longer the shirt manufacturer….
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Value-Driven AI: Enterprise Ecosystems and Generative Innovation
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Want a glimpse at the future of #ValueDrivenAI? This 451 Research report provides insight on topics ranging from enterprise-grade ecosystems to innovations like #GenerativeAI. Read the report now! https://
datarobot.com/resources/451-
research-datarobot-touts-value-driven-ai-for-data-scientists-ml-engineers/
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Claude Instant v1.1 Upgrade: Improved Creative Writing and Math
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Claude instant on Poe has been upgraded to @AnthropicAI
’s Claude instant v1.1. This model is an improvement over the previous iteration and is noticeably better at creative writing, math word problems, and Markdown formatting, and generally gives more nuanced responses. -
Gandalf: Password Guessing Game via Prompt Engineering
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Fun little game similar to the SQL murder mystery if you've played it: try to guess the password via prompt engineering with the difficulty going up over time. https://
gandalf.lakera.ai -
X/Twitter CEO Transition: New Executive Leadership Announced
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Excited to announce that I’ve hired a new CEO for X/Twitter. She will be starting in ~6 weeks! My role will transition to being exec chair & CTO, overseeing product, software & sysops.
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spaCy LLM Extension: Integrate Large Language Models into spaCy Pipelines
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Today we've published spaCy LLM, an extension to @spacy_io that lets you use LLMs to power spaCy components. If you've already been using LLMs in this sort of pipeline-like way, you should definitely give it a go. We have lots more in the works!
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LLMs for Annotation, Distillation, Interpretability and Production ML
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You can use the LLM for annotation or distillation, to help you train the components. LLMs should also be very helpful for interpretability and monitoring, and other tricky parts of production ML that make up much of the total project costs.
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LLM Limitations: Knowledge Gaps and Performance Constraints
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LLMs obviously feature extremely advanced natural language understanding, but for many many applications, you can't just ask the LLM your question and get out the answer. The knowledge will often be missing, or the scale and latency requirements would be infeasible.