Tired of AI-Generated content sounding robotic? Use Dependency Grammar in your prompts instead! Copy the prompt below: Use the dependency grammar linguistic framework rather than phrase structure grammar to craft a [ARTICLE/POST/EMAIL/ETC.]. The idea is that the closer
LLMS
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AI Math Olympiad Competition: Gemma 2B KerasNLP Starter Notebook
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Are you doing the AI Math Olympiad competition on Kaggle? Here's a notebook to get you started with Gemma 2B with KerasNLP:
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Generative AI Technologies: GANs, GPT, and Machine Learning Tools
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Generative AI. GAN. GPT. #BigData #NLProc #Analytics #DataScience #AI #MachineLearning #IoT #IIoT #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding #100DaysofCode https://
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Humans Make Mistakes Too: LLMs vs Human Error Discussion
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“but humans make mistakes, too” is so common a reply, I have written a discussion comparing humans and LLMs:
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Human Cognitive Errors vs LLM Hallucinations Explained
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So many people are confused about the relation between human cognitive errors and LLM hallucinations that I wrote this short explainer: Humans say things that aren't true for many different reasons
• Sometimes they lie
• Sometimes they misremember things
• Sometimes they fail -
Replicate and Infomaniak for hosting LLMs
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Replicate is all you need. Otherwise check out @infomaniak to host LLMs, they have cool stuff.
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Groq Predicts Exciting Second Half of 2024 with Growth
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The rest of 2024 is going to be a lot of fun as we keep building out more capacity, we see open source providing more models, and the dev community is hitting it's creative stride making amazing apps. We're not even halfway into the year and it's ⚡️⚡️⚡️ right now! https://t.co/UlXXTpGTzr pic.twitter.com/wYU6dr8IaF
— Groq Inc (@GroqInc) 21 avril 2024The rest of 2024 is going to be a lot of fun as we keep building out more capacity, we see open source providing more models, and the dev community is hitting it's creative stride making amazing apps. We're not even halfway into the year and it's right now!
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RAG Reduces Hallucination in LLM Structured Outputs
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7/ Reducing Hallucination in Structured Outputs via RAG – shows that RAG can enable deploying powerful LLM-powered systems in limited-resource settings while mitigating issues like hallucination and increasing the reliability of outputs.
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Emerging AI Agent Architectures: Reasoning, Planning, and Tool Calling
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8/ Emerging AI Agent Architectures – a summary of emerging AI agent architectures; it focuses the discussion on capabilities like reasoning, planning, and tool calling which are all needed to build complex AI-powered agentic workflows and systems.
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LLM In-Context Recall Depends on Prompt Formulation
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9/ LLM In-Context Recall is Prompt Dependent – finds that a model's recall performance is significantly affected by small changes in the prompt; the interplay between prompt content and training data can degrade the response quality.