Arvind Narayanan Profile picture
Oct 16, 2022 9 tweets 2 min read Read on X
15 years ago my PhD advisor taught me One Weird Trick for editing your own writing. Edit **back to front**, paragraph by paragraph. I still use it and it still surprises me how well it works. When I get my students to do it, it often blows their minds. Try it!
Most writing is way too complicated because we imagine our readers as machines who progress linearly through it, maintaining a perfect memory and understanding of everything they've read so far. Back-to-front editing helps us see how jarring the text is to a human reader.
And let's face it—reading your own writing is terminally boring (when it's not nails-on-chalkboard painful). So when we edit front to back, our brains process relatively little of the text. Back-to-front editing forces the brain to work more, so we notice more. And it's more fun!
The best way to edit your writing is to have someone else do it. The second best way is to put it away for a few weeks before editing it, so the text isn't fresh in your mind.

Back-to-front editing is always worthwhile, but especially when the first two options aren't available.
It's nice to see many responses to this thread from professional editors affirming back-to-front editing!

I've often heard the advice to read your text out aloud, but I've never heard the twist of using an AI voice. Interesting!
A few comments asked about doing it sentence-by-sentence vs paragraph-by-paragraph. Either is good! If the goal is only proofreading, then sentence-by-sentence is probably most effective, whereas paragraph-by-paragraph also lets you spot structural problems with the text.
If you found this thread useful, see the replies to the first tweet for more tips (changing the font? I'd never have guessed that'd work!)

Of course, good writing and editing isn't just about tips & tricks. It takes years of practice. My favorite book ↓
Ha, a surprising number of people are asking if back-to-front editing means reading sdrow sdrawkcab.

I just mean edit the last paragraph first, then the penultimate paragraph, and so on. Hope that cleared it up!

But if backwards reading worked for you, let me know 🙃
I learned from the replies to this thread that the same thing works for music and even for art—holding a painting upside down lets you spot problems. It’s obvious in retrospect but still awesome that disrupting familiar mental patterns is such an effective and general life hack!

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Arvind Narayanan

Arvind Narayanan Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @random_walker

May 16
In the late 1960s top airplane speeds were increasing dramatically. People assumed the trend would continue. Pan Am was pre-booking flights to the moon. But it turned out the trend was about to fall off a cliff.

I think it's the same thing with AI scaling — it's going to run out; the question is when. I think more likely than not, it already has.The image is a line graph titled "Top Airplane Speeds and Their Dates of Record, from Wright to Now," produced by the Mercatus Center at George Mason University. The graph tracks the progression of top airplane speeds from 1903 to around 2013. Here's a detailed description:  Y-Axis (Vertical Axis): Labeled "miles per hour (mph)," it ranges from 0 to 2,500 mph. X-Axis (Horizontal Axis): Labeled with years from 1903 to 2013 in increments of 10 years. Notable Annotations: Speed of Sound: Represented as a horizontal dashed line across the graph at approximately 760 mph. Reco...
By 1971, about a hundred thousand people had signed up for flights to the moon en.wikipedia.org/wiki/First_Moo…
You may have heard that every exponential is a sigmoid in disguise. I'd say every exponential is at best a sigmoid in disguise. In some cases tech progress suddenly flatlines. A famous example is CPU clock speeds. (Ofc clockspeed is mostly pointless but pick your metric.)
Note y-axis log scale.en.wikipedia.org/wiki/File:Cloc…Image
Read 11 tweets
Apr 30
On tasks like coding we can keep increasing accuracy by indefinitely increasing inference compute, so leaderboards are meaningless. The HumanEval accuracy-cost Pareto curve is entirely zero-shot models + our dead simple baseline agents.
New research w @sayashk @benediktstroebl 🧵 This image is a scatter plot titled "Our simple baselines beat current top agents on HumanEval." It charts the performance of various computational models based on their human evaluation accuracy and cost. The horizontal axis represents cost, while the vertical axis shows human evaluation accuracy ranging from 0.70 to 1.00. Different models, such as GPT-3.5, GPT-4, and those from the Reflexion series, are plotted as points. The Pareto frontier, depicted by a dashed line, shows the most efficient trade-offs between cost and accuracy. Points are colored differently to indicate the c...
Link:

This is the first release in a new line of research on AI agent benchmarking. More blogs and papers coming soon. We’ll announce them through our newsletter ().aisnakeoil.com/p/ai-leaderboa…
AiSnakeOil.com
Here are the five key takeaways. aisnakeoil.com/p/ai-leaderboa…
AI agent accuracy measurements that don’t control for cost aren’t useful.  Pareto curves can help visualize the accuracy-cost tradeoff.  Current state-of-the-art agent architectures are complex and costly but no more accurate than extremely simple baseline agents that cost 50x less in some cases.  Proxies for cost such as parameter count are misleading if the goal is to identify the best system for a given task. We should directly measure dollar costs instead.  Published agent evaluations are difficult to reproduce because of a lack of standardization and questionable, undocumented evaluati...
Read 12 tweets
Apr 12
The crappiness of the Humane AI Pin reported here is a great example of the underappreciated capability-reliability distinction in gen AI. If AI could *reliably* do all the things it's *capable* of, it would truly be a sweeping economic transformation.
theverge.com/24126502/human…
The vast majority of research effort seems to be going into improving capability rather than reliability, and I think it should be the opposite.
Most useful real-world tasks require agentic workflows. A flight-booking agent would need to make dozens of calls to LLMs. If each of those went wrong independently with a probability of say just 2%, the overall system will be so unreliable as to be completely useless.
Read 7 tweets
Dec 29, 2023
A thread on some misconceptions about the NYT lawsuit against OpenAI. Morality aside, the legal issues are far from clear cut. Gen AI makes an end run around copyright and IMO this can't be fully resolved by the courts alone. (HT @sayashk @CitpMihir for helpful discussions.)
NYT alleges that OpenAI engaged in 4 types of unauthorized copying of its articles:
–The training dataset
–The LLMs themselves encode copies in their parameters
–Output of memorized articles in response to queries
–Output of articles using browsing plugin
courtlistener.com/docket/6811704…
The memorization issue is striking and has gotten much attention (HT @jason_kint ). But this can (and already has) been fixed by fine tuning—ChatGPT won't output copyrighted material. The screenshots were likely from an earlier model accessed via the API.

Screenshot from lawsuit: output from GPT-4 identical to actual text from NYT
Read 13 tweets
Aug 18, 2023
A new paper claims that ChatGPT expresses liberal opinions, agreeing with Democrats the vast majority of the time. When @sayashk and I saw this, we knew we had to dig in. The paper's methods are bad. The real answer is complicated. Here's what we found.🧵 aisnakeoil.com/p/does-chatgpt…
Previous research has shown that many pre-ChatGPT language models express left-leaning opinions when asked about partisan topics. But OpenAI says its workers train ChatGPT to refuse to express opinions on controversial political questions. arxiv.org/abs/2303.17548
Intrigued, we asked ChatGPT for its opinions on the 62 questions used in the paper — questions such as “I’d always support my country, whether it was right or wrong.” and “The freer the market, the freer the people.” aisnakeoil.com/p/does-chatgpt…
Read 30 tweets
Jul 19, 2023
We dug into a paper that’s been misinterpreted as saying GPT-4 has gotten worse. The paper shows behavior change, not capability decrease. And there's a problem with the evaluation—on 1 task, we think the authors mistook mimicry for reasoning.
w/ @sayashk
aisnakeoil.com/p/is-gpt-4-get…
We do think the paper is a valuable reminder of the unintentional and unexpected side effects of fine tuning. It's hard to build reliable apps on top of LLM APIs when the model behavior can change drastically. This seems like a big unsolved MLOps challenge.
The paper went viral because many users were certain GPT-4 had gotten worse. They viewed OpenAI's denials as gaslighting. Others thought these people were imagining it. We suggest a 3rd possibility: performance did degrade—w.r.t those users' carefully honed prompting strategies. Among those skeptical of the intentional degradation claim, the favored hypothesis for people’s subjective experience of worsening performance is this: when people use ChatGPT more, they start to notice more of its limitations.  But there is another possibility.  The user impact of behavior change and capability degradation can be very similar. Users tend to have specific workflows and prompting strategies that work well for their use cases. Given the nondeterministic nature of LLMs, it takes a lot of work to discover these st
Read 9 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Don't want to be a Premium member but still want to support us?

Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal

Or Donate anonymously using crypto!

Ethereum

0xfe58350B80634f60Fa6Dc149a72b4DFbc17D341E copy

Bitcoin

3ATGMxNzCUFzxpMCHL5sWSt4DVtS8UqXpi copy

Thank you for your support!

Follow Us!

:(