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I love the idea. The implementation did not produce the expected results ( article shown on HN - https://amp-economist-com.cdn.ampproject.org/c/s/amp.economi... ). That said. Keep at it. It seems like a viable and valuable service.
Earlier quoted context omitted.
Can you please let me know the article that you tested it on? Maybe you could try the advanced summarizer and see if it gives useful results.
https://p.migdal.pl/2020/03/02/types-tests-typescript.html https://p.migdal.pl/2017/07/23/dating-for-nerds.html https://p.migdal.pl/2016/03/15/data-science-intro-for-math-p... https://medium.com/@szopa/train-for-a-mars-mission-how-to-su... (here I admit that the first two are good)
It actually did better than I expected with the paper "Bypassing memory safety mechanisms through speculative control flow hijacks" [0]
I copied and pasted the text from sections 3-7 (Case Studies - Conclusion) and Section 2 on its own (describes the attack)
It did pull out some important statements, better than I expected. Probably won't save me much time, but I was quite disappointed by the fact that the Advanced and Basic versions were the same for both which kinda felt a bit cheap to get the same results especially since it still cost to get that advanced result. Maybe including information about how the basic version is restricted and what the advanced does better would make it easier to know when the advanced version won't be useful.
I also tested with a random write-up I'll be covering tomorrow "Breaking the Competition" [1] I had higher hopes for this since it was more of a blog-ish post. I did get different results for basic and advanced with this one, but the result was basically non-sense, worse than expected, and worse than the paper summary.
Overall, probably not something that I'll end up using, but technical content also isn't the intended use-case which is totally fair. I'll also add that one feature that I looked for immediately was API access as I'd have wanted to integrate this into an app I use to plan episodes.
- [0] https://arxiv.org/pdf/2003.05503v1.pdf
- [1] https://medium.com/ctf-writeups/breaking-the-competition-bug...
I’ve noticed an increase in services like this lately. What gives? Is there some sort of ML serverless offering made available on GCP?
Also, when it comes to summarization- you don’t really need to infer each run, you can throw up a pretty simple caching system. Which means repeat requests are far cheaper and faster.
I used cloudflare workers as a proxy / caching layer with KV in front of an AWS lambda to do article extraction and SageMaker spinup (with a small cache on the AWS side too- to catch in progress jobs)
Did a fairly poor job on this Ars article https://arstechnica.com/science/2020/03/what-monty-pythons-m...
You could try the advanced summarizer. It gives better results.
* It's intended in part as a commemoration on the 50-year anniversary of the sketch, but also to draw attention to the need for a more streamlined peer review process for grants in the health sciences.
* "So, put together a Monty Python fan with a creative scientific mind and an expert in gait analysis, and this paper is what you get," Butler told Ars. Or, as they wrote in their paper, "It really is the silliness of the sketch that resonates with us, and extreme silliness seems more relevant now than ever before in this increasingly Pythonesque world."
* First aired on September 15, 1970, on BBC One, the sketch opens with Cleese's character buying a newspaper on his way to work—which takes him a bit longer than usual since his walk "has become rather sillier recently." Waiting for him in his office is a gentleman named Mr. Putey (Michael Palin) seeking a grant from the Ministry to develop his own silly walk.
* (Note: the name is spelled "Pudey" in the paper but we're going with the Wiki spelling.) Mr. Putey demonstrates his silly walk-in-progress, but the Minister isn't immediately impressed.
Advanced
* One of the best-known sketches from Monty Python's Flying Circus features John Cleese as a bowler-hatted bureaucrat with the fictional Ministry of Silly Walks.
* Waiting for him in his office is a gentleman named Mr. Putey (Michael Palin) seeking a grant from the Ministry to develop his own silly walk.
* For their own gait analysis, Butler and Dominy studied both Mr. Putey's and the Minister's gait cycles in the video of the original 1970 televised sketch, as well as the Minister's gaits from a 1980 live stage performance in Los Angeles.
* Butler and Dominy found that the Minister's silly walk is much more variable than a normal human walk—6.7 times as much—while Mr. Putey's walk-in-progress is only 3.3 times more variable.
* The sketch might be satirizing bureaucratic inefficiency, but Cleese's Minister is essentially engaging in a hyper-streamlined version of the peer review process in his meeting with Mr. Putey that (the authors concluded) resulted in a fair assessment.
I get an error. I’m on Safari mobile on iOS 13.4. I use content blockers, BlockBear and Firefox Focus - not sure if that’s relevant or not. Method Not Allowed The method is not allowed for the requested URL.
Thank you for letting me know. Are you using the extension or the web app?
1. Split the text into words
2. Rank each word based on how many times it appears in the text. For example, a word that appears 10 times gets 10 points, and so on.
3. Rank sentences based on the sum of the scores of each word inside them.
4. Return the top N sentences by score (N is up to the user), in the order in which they appear in the text.
For extra fancyness, exclude the most common articles and prepositions and give 2 points to proper nouns.
Works surprisingly well.
Nice landing page. If you Google "summarizer", you will find dozens of similar services for free. The mechanism behind it is very simple. A couple a years ago I built one from scratch in about 2 hours, then I accidentally deleted it and rewrote it in 15 minutes. Here's how most of them work: 1. Split the text into words 2. Rank each word based on how many times it appears in the text. For example, a word that appears…
The SMMRY page points out some extra NLP-related grunt work in addition to the high-level steps you list, like:
>Associate words with their grammatical counterparts. (e.g. "city" and "cities")
>Detect which periods represent the end of a sentence. (e.g "Mr." does not).
[1] https://www.reddit.com/r/autotldr/comments/31b9fm/faq_autotl...