Comparing LLMs by param count is like comparing
– CPUs by megahertz in the 1990s
– cameras by megapixel in the 2000s
– phones by memory in the 2010s A primitive reductionism – true enough, but maxes out Then we pivot to fit-for-purpose measures.. That lead to enduring brands.
RESEARCH
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Parameter Count Alone Cannot Measure LLM Quality
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Improved prediction function for broader interest and impact
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I think i have developed a better prediction function of what is likely to be of broader interest or higher impact, but I can't be 100% sure obviously
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GPT-3 Inference Non-Determinism at Temperature Zero Explained
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An edge-case in GPT-3 with big implications: Inference is non-deterministic (even at temperature=0) when top-2 token probabilities are <1% different. So temperature=0 output is *very close* to deterministic, but actually isn't. Worth remembering.
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AI Tools Reliability: Understanding Current Limitations and Accuracy
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Es literal lo primero que te dice la propia herramienta cada vez que la vas a utilizar. Por ahora, no es una herramienta pensada para ser 100% correcta en sus respuestas.
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Have I Been Trained: Checking Your Data in AI Models
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La web que comento es esta https://
haveibeentrained.com -
Self-Review of Research Work: Fulfilling Projects and Limitations
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New blog post, self-reviewing my research over the past few years: https://
jasonwei.net/blog/research-
i-enjoy
… In addition to work I found fulfilling, I also critique why I felt some papers I've written didn't go so well, or were inherently limited. Apologizes in advance for hot takes -
AI Today Podcast: Content Summarization and Sentiment Analysis Episode
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In this @Cognilytica #AIToday #podcast episode 'Content Summarization and Analysis, Sentiment Analysis' from the AI Glossary Series, hosts @rschmelzer & @kath0134 define Content Summarization and #Analysis and #sentimentanalysis. Full episode: https://
cognilytica.com/2022/12/28/ai-
today-podcast-ai-glossary-series-content-summarization-and-analysis-sentiment-analysis/?utm_source=dlvr.it&utm_medium=twitter
…
#AI #nlp #ML -
Google’s PaLM: A 540B Parameter Language Model Explained
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— AI Breakfast (@AiBreakfast) 29 décembre 2022
You've heard a lot about ChatGPT But in the next few weeks, you'll start to hear about another model that could be 3x more powerful than ChatGPT: PaLM Google's Pathways Language Model (PaLM) a 540-billion parameter model trained with the Pathways system Here's what we know
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PaLM 540B Architecture Code Released Open Source
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Mola, pero… ¿quién tiene capacidad de entrenar un PaLM de 540 billions (x3 el tamaño de GPT-3)? Aquí están compartiendo el código de la arquitectura y no un modelo pre-entrenado. Con lo que es un entrénalo-tú-mismo de ChatGPT.
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Generative AI: Getting More from Less, Says AI21 Labs Co-Founder
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"Generative anything is the idea that you put in a little and get a lot. It's exciting as it is wondrous" Check out this recent CTech interview with our Co-Founder & Co-CEO, Prof. Yoav Shoham: