AI self-improvement is coming. I just had an experience where the model automatically improved it's own prompt. Our AI generates code and prompts automatically — without my prompting, the agent realized that the output of the first run wasn't good enough, so it came up with
LLMS
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Fast AI Inference Enables Scalable Agentic Applications
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"Why does anyone need incredibly fast inference processing that can generate text faster than anyone can read? It’s because the output of one AI can become the input for another, enabling scalable applications for search, self-correcting summarization, and soon, agentic AI." –
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Create a Llama Chatbot in 3 Lines with Groq and Gradio
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@GroqInc + @Gradio llama chatbot in 3 lines pip install groq-gradio -
Fuel AI Through Curiosity and Collaboration at IBMTechXchange
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How to Fuel Your #AI Through Curiosity and Collaboration? At #IBMTechXchange, I explored the vital role of collaboration and continuous learning in driving business transformation! Discover how innovations like #Granite Models and #watsonx Code Assistant, along with
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Anthropic Raises Claude 3.5 Haiku Pricing Following Intelligence Improvements
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Something we didnt expected and we didnt ask for. "As a result, we've increased pricing for Claude 3.5 Haiku to reflect its increase in intelligence: http://
anthropic.com/claude/haiku." -
Incredible Llama AI Demo at Llamapalooza NYC Event
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An incredible demo at Llamapalooza NYC, Jet!
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Mini-Hackathons: Building in Hours with Claude AI
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After the talks came the mini-hackathon portion of the event. Side note: I think mini-hackathons are the future as you can now build what used to take two days in just a few hours using Claude.
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Fine-tuning Best Practices: Training Data for LLMs
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Fine-tuning Best Practices Series Introduction and Chapter 1: Training Data – OpenPipe https://
bit.ly/4dpABsk
#AI #MachineLearning #DeepLearning #LLMs #DataScience -
Generate Synthetic Data to Fine-Tune SLMs Effectively
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NEW Tutorial + Notebook: Beat #GPT4o with only 10 Rows of Data Lack of training data is the #1 blocker to fine-tuning a high-quality #SLM. Not anymore! Check out our latest deep dive tutorial to learn how to generate effective #synthetic datasets with only 10 sample data
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LLMs give conflicting predictions for US election winner
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Surprising results: Asking LLMs who will win the election tomorrow: o1-preview: Trump wins
Grok 2: Harris wins
Claude 3.5 Sonnet: Do your own research Curious to see if others get the same answer.