gavelin

5 ms·

1.
by gavelin 5y ago
Gut wrenching story! The overemphasis on NDAs these days is concerning, particularly in instances like yours where someone is clearly looking to claim ownership of an idea without the desire to put any effort towards developing it. The more
2.
Startup Legal Headache?
1 points by gavelin 5y ago|2 comments
3.
by gavelin 6y ago
Thank you for the support—means a lot to me. I wrote the piece after finding that recent journalism on GPT-3 did not provide a sufficiently accurate snapshot of how vanilla GPT-3 scores on legal tasks (not to mention the misleading snapshot
4.
by gavelin 6y ago
A bright-line rule like "It is unlawful to exceed 65MPH in any vehicle on Highway 101" has a pretty narrow meaning and could be concretely decomposed sufficient for the average human to understand. I think you are right to point o
5.
by gavelin 6y ago
You are quite correct that fine-tuning is necessary to improve accuracy. I did not intend to dismiss that. The point I intended to make there is that it would be nice to be able to see whether, when interpreting a statute, GPT-3 relied heav
6.
by gavelin 6y ago
Correct. I hope that meant that this was more accessible than the average write-up (and not less accurate!) :)
7.
by gavelin 6y ago
Thanks for the paper link! I think your reasoning of hardwiring boilerplate to an expert-vetted (or written) summary is a much more accurate approach. If only we could scrape the clause explanation footnotes from quality sources I would not
8.
by gavelin 6y ago
Tarq0n: Also a great point. The question then is whether the attention mechanism is being triggered on the proper word or character sequences. Lawyers employ a form of attention mechanism when “issue spotting.” For example, in a non-compete
9.
by gavelin 6y ago
minimaxir: Great insight and probably merits an edit for precision. My understanding is that Byte-Pair encoding is done at the character and word level (and maybe even the sub-character level), but not at the higher-level representations su
10.
by gavelin 6y ago
Great link. Thank you for sharing this.
11.
by gavelin 6y ago
Thank you for reading!
12.
by gavelin 6y ago
"tl;dr" may very well be the problem! There is a tendency of many tl;dr summaries on the web to oversimplify and skew concepts. If those are included in GPT-3's dataset, GPT-3's output will try to match the dataset style
13.
by gavelin 6y ago
Good tip! I repeated a few inputs to see if the variation was significant enough to warrant including that, and as your intuition suggested, it was not with the parameters I selected. A more robust experiment should definitely include repea
14.
GPT-3, Esq? Evaluating AI Legal Summaries [pdf](davidvictorrodriguez.com)
51 points by gavelin 6y ago|41 comments