LLMs
sari and
LLMs
Large Language Models Understand and Can be Enhanced by Emotional Stimuli
Cheng Li, Jindong Wang, Yixuan Zhang, Kaijie Zhu, Wenxin Hou, Jianxun Lian, Fang Luo, Qiang Yang, Xing Xiereadwise-assets.s3.amazonaws.comThere’s a lot of hype around AI, and in particular, Large Language Models (LLMs). To be blunt, a lot of that hype is just some demo bullshit that would fall over the instant anyone tried to use it for a real task that their job depends on. The reality is far less glamorous: it’s hard to build a real product backed by an LLM .
Phillip Carter • All the Hard Stuff Nobody Talks About When Building Products With LLMs
NFX’s Generative Tech Open Source Market Map
docs.google.comPeople are intrigued by LLMs’ ability to generate new text, change styles, and generally chat. While impressive, turning text written in one style into text written in your own voice (or into legaleze) is essentially taking unstructured data and turning it into more unstructured data. I’m surprised about the lack of attention to doing the exact... See more
Matt Hartman • The power of AI is its ability to turn unstructured data into structured data
Weird GPT token for Reddit user davidjl123, “a keen member of the /r/counting subreddit. He’s posted incremented numbers there well over 163,000 times. Presumably that subreddit ended up in the training data used to create the tokenizer used by GPT-2, and since that particular username showed up hundreds of thousands of times it ended up getting
... See more"the best use case of LLMs is bullshit"
I've learned so much from @hubermanlab, but podcasts make recall and discovery challenging.
Huberman AI uses the latest models from @openai to search every episode with Google-level accuracy and summarize the results.
https://t.co/1nctiAIuGO https://t.co/VpjnY2NcpM
riley tomasektwitter.com