Kite launches line-of-code completions, goes cloudless, secures $17M in funding

TabNine is a different approach that uses far less semantic information than Kite. It really shines when you're talking about syntactic repetition, e.g. if you check out the screenshots on their homepage. They have a page about semantic completions, but the semantics are very shallow -- basically what attributes are on the instance you're accessing.

In contrast, we've spent ~50 eng-years semantically indexing all the code on Github, building statistical type inference, and rich statistical models that use this semantic information in a very deep way. The result is that Kite can help more often, in ways that reflect a deep understanding of the semantics of the code you're writing.

The intuition here is that in natural language, context is defined locally. If you want to know whether a 'they' refers to a male or female, for example, you look at the nearby text. In contrast, the flow of data and control through code is highly non-local, which is a lot of why techniques like N-grams don't work.

This has been a very active area of research in academia since we started Kite in 2014. (Suggested google searches: [big code], [ml on code], etc.)

All that said I don't have data on how our approach would compare to N-grams, but I'm guessing if you look at some of the academic research, you'll find that NLP techniques were abandoned, despite the early papers' focus on them.

It may be useful to differentiate between what data we collect and what data we don't collect in order to clear up any confusion.

1. What we collect

We collect a variety of usage analytics that help us understand how you use Kite and how we can improve the product. These include:

* Which editors you are using Kite with

* Number of requests that the Kite Engine has handled for you

* How often you use specific Kite features e.g. how many completions from Kite did you use

* Size (in number of files) of codebases that you work with

* Names of 3rd party Python packages that you use

* Kite application resource usage (CPU and RAM)

You can opt-out of sending these analytics by changing a Kite setting (https://help.kite.com/article/79-opting-out-of-usage-metrics).

Additionally, we collect anonymized "heartbeats" that are used to make sure the Kite app is functioning properly and not crashing unexpectedly. These analytics are just simple pings with no metadata, and as mentioned, they're anonymized so that there's no way for us to trace which users they came from.

We also use third party libraries (Rollbar and Crashlytics) to report errors or bugs that occur during the usage of the product.

2. What we don't collect

* Contents (partial or full) of any source code file that resides on your hard drive

* Information (i.e. file paths) about your file system hierarchy

* Any indices of your code produced by the Kite Engine to power our features - these all stay local to your hard drive

More concretely, the StackOverflow thread for "Parsing values from a JSON file?" has almost 3 million views. We take this as evidence that programming is repetitive.

(We should probably clarify that when we say 'repetitive' we mean on a global scale, not an individual scale.)

Moreover, there are common errors you can avoid if their ranking algorithm discourages code reported/identified as bad.

Thanks for checking it out!

edit:

>When we started Kite, we were excited about the possible benefits of internet-connected programming. We were also well aware of the privacy and security concerns some people would have.

So their approach is going to continue being to ignore what they did and pretend they're cool now. Alright, well you can download the maybe-malware if you want, I'll stay as far away as I can from this company myself.

this reductive description is too vague to bear the label "legitimate interaction". context matters, no?

> I have to wonder if your goal was to upset enough people that you'd generate real attention on various news sites and get Kite a ton of free publicity before your next funding round,” @DevOpsJohn wrote

It seems to have worked out great.

Im not sure what advantage I'd get with kite.

Often I'd start using a class in the code, and then ask intelliJ to import it, rather than going to the top, and use the autocomplete tool. It can do patterns as well, even custom defined ones, with default values (https://www.jetbrains.com/help/idea/using-live-templates.htm...)

Not everyone's goal is to build with investors' money. Sometimes it is easier to succeed without it.

The example you link (from Zsh, not fish) is a fancy looking history autocompletion: in bash, just press Ctrl+r.

The parent has a point: I've spent time working with absolute beginners in programming and the first thing I was teaching them was to ignore the IDE "smarter autocompletion" and suggestions. For typing faster, sure; for suggesting anything else, not so clever.

Look, I'm all for second chances here. The past behavior of this company doesn't concern me as much as the pretty clear lack of strategy around how you plan to make money.

So this is what I've gathered so far (and correct me if I'm wrong on any of this):

- free product (based on the website)

- no serious mention of enterprise pricing or support (based again on the website)

- a promise in your TOS not to collect sensitive data (which almost all companies tend to modify, let's be honest)

- solicitation of monetization ideas on an internet forum by the CEO, having raised millions from VCs

This sounds like a product I'd stay away from if I cared about data collection.

Can you quantify how much money you're saving developers or companies who use this?

Instead, only engineer for Linux and make it available through Docker on all platforms. Since VSCode exposes hooks to interact with Docker anyway, this might make more long term sense.

So we took the approach of focusing on one demographic (Python developers) and making them really happy. We think we've reached that point, so we're excited to begin looking at how we can expand our reach. Stay tuned!