<div dir="ltr">Roger,<br>Thanks for the info and references. <br>As the great philosopher Britney Spears once said, "Why do you have a brain if you're not willing to change it?" So for now, I'll switch my stance from "pro-emergence-in-LLMs" to "I have no idea what's going on."</div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, 9 May 2023 at 04:25, Roger Critchlow <<a href="mailto:rec@elf.org">rec@elf.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">This evening's hackernews contribution:<div><br></div><div> <a href="https://hai.stanford.edu/news/ais-ostensible-emergent-abilities-are-mirage" target="_blank">https://hai.stanford.edu/news/ais-ostensible-emergent-abilities-are-mirage</a></div><div><br></div><div>AI’s Ostensible Emergent Abilities Are a Mirage<br>According to Stanford researchers, large language models are not greater than the sum of their parts.<br></div><div><br></div><div>Which is a gloss on <a href="https://arxiv.org/abs/2304.15004" target="_blank">https://arxiv.org/abs/2304.15004</a>:</div><div><br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><span style="color:rgb(0,0,0);font-family:"Lucida Grande",Helvetica,Arial,sans-serif;font-size:13.608px">Recent work claims that large language models display emergent abilities, abilities not present in smaller-scale models that are present in larger-scale models. What makes emergent abilities intriguing is two-fold: their sharpness, transitioning seemingly instantaneously from not present to present, and their unpredictability, appearing at seemingly unforeseeable model scales. Here, we present an alternative explanation for emergent abilities: that for a particular task and model family, when analyzing fixed model outputs, one can choose a metric which leads to the inference of an emergent ability or another metric which does not. Thus, our alternative suggests that existing claims of emergent abilities are creations of the researcher's analyses, not fundamental changes in model behavior on specific tasks with scale.</span></blockquote><div><br></div><div>-- rec --</div><div> </div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, May 8, 2023 at 12:33 AM Pieter Steenekamp <<a href="mailto:pieters@randcontrols.co.za" target="_blank">pieters@randcontrols.co.za</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">Sorry, I forgot to add the url of the interview.<br><a href="https://www.youtube.com/watch?v=V6WL4X6pmCY" target="_blank">(580) The Current State of Artificial Intelligence with James Wang - YouTube</a><br><br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, 8 May 2023 at 08:27, Pieter Steenekamp <<a href="mailto:pieters@randcontrols.co.za" target="_blank">pieters@randcontrols.co.za</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr">I am very excited about the basic idea that neither Google nor any Big Tech company has the Moat as per the hackernews reference above.<br>Very interesting around this is the interview with James Wang of Cerebras James Wang about this where he makes a strong case (in my view in any case) that in future open source large language models are going to be much more prominent than those of Big Tech.<br><br>I quote from the description on Toutube about the interview:<br>"Scaling laws are as important to artificial intelligence (AI) as the law of gravity is in the world around us. AI is the empirical science of this decade, and Cerebras is a company dedicated to turning state-of-the-art research on large language models (LLMs) into open-source data that can be reproduced by developers across the world. In this episode, James Wang, an ARK alum and product marketing specialist at Cerebras, joins us for a discussion centered around the past and the future of LLM development and why the generative pre-trained transformer (GPT) innovation taking place in this field is like nothing that has ever come before it (and has seemingly limitless possibilities). He also explains the motivation behind Cerebras’ unique approach and the benefits that their architecture and models are providing to developers."<br></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, 8 May 2023 at 01:09, Merle Lefkoff <<a href="mailto:merlelefkoff@gmail.com" target="_blank">merlelefkoff@gmail.com</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div class="gmail_default" style="font-family:verdana,sans-serif">Thank you Roger. </div></div>
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