most llm agents are still toys. almost anything can be done faster yourself. this has to invert. we're still missing the context layer: an llm agent that can book a flight is not useful. an llm agent that knows your calendar, budget, and when you'd want to fly is getting there
LLMS
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Attention Is All You Need: Seminal Transformer Paper From 2017
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Here's the original Attention Is All You Need paper from June 2017 https://
arxiv.org/abs/1706.03762 -
Transformer Architecture: Foundation of Modern Generative AI
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In 2017, a team of eight researchers on the Google Brain team (now part of Google Deepmind) published a research paper titled, Attention is All You Need. That paper invented the Transformer architecture that became the basis for ChatGPT from OpenAI (GPT stands for Generative
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ChatGPT prompt makes you more productive than 20 employees
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This ChatGPT prompt will make you more productive than a team of 20 employees. Follow the thread:
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AI Tools Demonstrate Human-Like Creativity and Empathy at Davos
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"These tools allow us to do things that software have never been able to do before. They are creative, empathetic, and they act much more like humans than a traditional database". Enjoyed chatting with @andrewrsorkin @SquawkCNBC today at Davos #WEF24
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ChatGPT introduces refined search functionality with detailed metrics
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ChatGPT unveils refined search with detailed GPT metrics WDYT?
Useful: Like Not useful: Reply https://
buff.ly/3S4ajTN -
Meta’s Self-Rewarding Language Models Paper Released
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Iterative self-improvement LLMs from Meta? “[in order to] achieve superhuman agents, future models require superhuman feedback” Self Rewarding Language Models paper just dropped. Link in alt.
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Databricks MLflow Enhancing GenAI Application Quality Components
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With the Data Intelligence Platform, Databricks and MLflow are helping to enhance the quality of the core components of #GenAI applications — including Prompts, Retrieval System, and Foundation #LLM. Learn how
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Stable LM 2 1.6B Multilingual Small Language Model Released
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Today, we’re releasing Stable LM 2 1.6B, a state-of-the-art 1.6 billion parameter small language model trained on multilingual data in English, Spanish, German, Italian, French, Portuguese, and Dutch. This model’s size and speed reduce hardware limitations, allowing all to easily
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Native 2048x Fast Model Development Without Upscaling
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I’m hoping for a native 2048x fast model, not an upscaler.