I tried Neeva, and the quality of results was just not there. Would have been happy to pay.

"It is one thing to build a search engine, and an entirely different thing to convince regular users of the need to switch to a better choice."

This line in post doesn't seem intellectually honest about why I think Neeva failed: it was never a 10X better experience. e.g. ChatGPT isn't complaining about acquiring users.

I believe Google when they say competition is just one click away. A bunch of things I would have asked Google now go to ChatGPT.

> ...it was never a 10X better experience.

True that new products need to be substantially better than the market leader to thrive (I particularly like this write up on the topic: Delta 4 theory of successful startups https://archive.is/WK96N ).

And Neeva might have been targeting a different, narrow niche (https://archive.is/ScazW) for which the product was 10x better?

> e.g. ChatGPT isn't complaining about acquiring users.

ChatGPT wasn't built to kill web search, but rather a super-capable, web-based conversation bot? Funny how that had Google on code red. Reminds me of, Amazon, eBay, and Alibaba: The right and the wrong way to compete with a locked market: https://archive.is/rY3NR

- You can develop a very deep understanding of a sequence by observing how each element interacts with each other over many sequences.

- This understanding can be encapsulated in "compressed" low dimensional vector representation of a sequences.

- You can use this understanding for many different downstream tasks, especially predicting the next item in a sequence.

- This approach scales really well with lots of GPUs and data and is super applicable to generating text.

The quality delta is so huge that it's in a different league.

Replit's model seems to have focused on being cheap to train and run. StarCoder seems to be vastly better on quality.

If so, it’s a shame this post is getting comparatively little attention. Hopefully the quality will be enough for it to make a big splash somewhere.

In other words, a shallow big == bad without taking specfic context into consideration?

Imo I want competition and choice as a consumer. This basically sets things up so that consoles become a non competitive market because Xbox lacks exclusives that Sony has.

About emails:

No for ads.

Yes for training models for Smart Reply, from: https://arxiv.org/pdf/1606.04870.pdf

Privacy Note that all email data (raw data, preprocessed data and training data) was encrypted. Engineers could only inspect aggregated statistics on anonymized sentences that occurred across many users and did not identify any user. Also, only frequent words are retained. As a result, verifying model’s quality and debugging is more complex.

I think the article should more accurately be titled as how to do a small scale feature tuck in / acquihir-ish soft landing.

The intro talks about 9-figure deals, which seems a bit higher than an acquihire to me. 7-8 figures sure.

I had a similar experience with an Adwords account getting banned for "Circumventing systems", and we were completely confused as to why we got the rejection.

And then the appeals process after that was just like yours: copy pasta email without any explanation about how to fix the problem.

A past project used OR Tools. I generally liked it. It was a bit confusing at times and the documentation was a bit cryptic for using some of the advanced features, though the community was good about answering questions.

In general, I would recoment OR Tools.

The post is about Spotify, not Shopify.

The real problem is that the LatestInML subreddit is effectively an ad for the extension.

Solution: don't subscribe to that Subreddit.