Google Colab will soon introduce AI coding features

https://blog.google/technology/developers/google-colab-ai-coding-features/

by todsacerdoti • 3 years ago

282 154 3 years ago

blog.google

nextworddev3• 3 years ago

Is this another "beta" feature? It says it's available today, but I don't see it.

Source: currently a Colab pro subscriber based in the U.S., but don't see the AI features in my Colab notebook

neom• 3 years ago

It specifically says in multiple areas of the article that it's not available today.

"Google Colab will soon introduce..."

"Access to these features will roll out gradually in the coming months, starting with our paid subscribers in the U.S. and then expanding into the free-of-charge tier. We'll also expand into other geographies over time. Please follow @googlecolab on Twitter for announcements about new releases and launches."

cperry12• 3 years ago

not yet available; it'll roll out sequentially in the coming weeks as we sort out capacity and polish.

nailer2• 3 years ago

How far away is the VS code plugin?

greatpostman5• 3 years ago

I really think the current paradigm of literally typing if else logic all day into programs, and then getting paid huge money to do so will go away. Programming is going to be much higher level and accessible, though still complex. It will take five years or so.

Edit:

My prediction is essentially that:

You give it a set of requirements for an api, with edge conditions written in plain English. Test cases are provided. And the vanilla api is generated. We aren’t that far from this. It’s going to happen. Programmers may go in and tweak the generated code. When the requirements change, you pass in the old code as context.

Complex software will require human coding. But most programmers are in denial about how complex the code they’re writing actually is.

Requimemts gathering is notoriously tricky, but you won’t need engineers for it. Welcome to the age of the PM

nextworddev3• 3 years ago

The bi-furcation of programmer careers will intensify.

Think of it like hedge fund traders vs stay-at-home retail traders.

The closer you are to the core AI stack, the more you will get paid - kind of like hedgefund traders.

If you are just copy pasting ChatGPT mostly, then you will get disintermediated at some point.

greatpostman5• 3 years ago

I disagree with this as well. The number of people legitimately working on LLMs right now is probably only in the hundreds. One or a few huge models will do all the programming automation. But yes, high paying developer jobs will exist. The rest will not pay as well, and with much worse job security. This field is going to change very fast

frozenport• 3 years ago

Wow you were doing that?

And I’m sitting around here architecting code, rewriting graphs, and gathering input from stakeholders.

danwee• 3 years ago

That's what they thought 50 years ago. Programming is not anymore "mov eax,1" and "int 0x80". Programming nowadays is much more highly accessible than it was 50 years ago... but still only a few (programmers) do it. AI is not going to change that (i.e., nor my manager nor my mother are suddendly going to "program" anything using high-level constructs)

boredemployee4• 3 years ago

You may be right, you may be wrong.

Only time will tell (and I think it will tell really really soon).

pphysch2• 3 years ago

Yeah, generating some Python with Codey is just adding another layer to an already substantial stack.

Natural language is translated into Python which is interpreted as C which was compiled into bytecode which is...

We still need experts at every layer.

zelag• 3 years ago

Who is typing if else logic all day into programs? Not even as a junior did I do this.

greatpostman5• 3 years ago

Programming is essentially if else logic

adammarples• 3 years ago

Thinking logically isn't going out of fashion any time soon. Excel lets you fit increasingly higher order polynomials to a time series graph but you still need someone to tell them that's not a good forecast

brigadier1322• 3 years ago

Here's a different 10-year prediction. AI will become good enough to be useful for programmers but not good enough to run on its own and will remain an assistant. Given that there is a shortage of programmers, more software will be written than ever. More software will beget more software engineers. Because the output of software engineers will rise, each individual software engineer will become more valuable to their business and salaries will rise.

tudorw• 3 years ago

Having played a bit with coding with AI I like this view, it's powerful, but context will always be an issue, turning real world problems into working code is a skill in it's own right, that will not change, superpowered yes, for me it's all the 'dull' parts of typing stuff out that I look forward to missing, from an early study on impact in the workplace, using a 2 year study of a call centre, the result was large improvement for less skilled staff as knowledge of best practice from those really excelling at customer service was rapidly propagated to juniors, seniors saw a much smaller increase in performance metrics. Now there is no excuse for me not to get AI to write my comments, a bunch of tests and some API's and database interconnects, etc. I've always taken a modular iterative approach, create a working basic model with a good foundation then extend it keeping it working as I build up to the final deliverable. Tempting just to go and sit in a cave for a couple of months and come back when the tools are a little more refined :)

adventured5• 3 years ago

10-15 years out AI will be good enough to wipe out at least half of all software developers on the planet (that is, people writing actual code). That's not a risky prediction, that's very easily going to be the case.

Those people have nowhere to go to match what they're earning now. Maybe support review roles (which won't pay particularly well), where they approve decisions by the AI that are held up for human approval.

The bottom half of software developers won't have AI assistants. The AI will have them as human assistants (required by corporations for control/safety/oversight purposes).

The ~50%-25% bracket will build software using AI tools and will rarely write the actual code.

In the top ~25% bracket (in terms of skill) you'll have software developers that are still paid very well and they'll directly write code, although not always. That group will be the only one remaining that is paid like today's software developers get paid.

Software developer in the future will most commonly mean someone who builds software via AI tools (with the AI writing nearly all of the actual code). Human software developers will be glorified prompt wizards (with required degrees; it won't be a great job).

For the median software developer, the peak has already been reached (in terms of pay and job security).

Emerging market software developers will be hammered before their economies can fully benefit from the relatively high pay of the industry (from off-shoring work from big tech).

The golden run is over for the bottom 3/4 of software developers. Prepare for it. Get used to it. In the developed world the ladder up and out of the middle class via software development is going to go away (and quickly).

To regularly write code in the future you'll have to be damn good. Good enough, and knowledgeable enough, to be better at what you're doing than an AI with a handler (human assistant). You'll be writing the AI systems that govern everything and it'll be increasingly regulated, with more government licensing (plausibly formal AI engineer licensing and actual accountability, because the risks will go way up).

beoberha• 3 years ago

What do you mean by “higher level”? AI code generation tools are extremely useful to people who know how to code, but how is it useful if you can’t understand the code it spits out. They are far from bug free and prompting it to handle complex business logic is tricky. If the higher level paradigm is simply English, then I don’t see it. If something else, I’m curious what you foresee.

greatpostman5• 3 years ago

You give it a set of requirements for an api, with edge conditions written in plain English. Test cases are provided. And the vanilla api is generated. We aren’t that far from this. It’s going to happen. Complex software will require human coding. But most programmers are in denial about how complex the code they’re writing actually is

nemothekid3• 3 years ago

You give it a set of requirements for an api, with edge conditions written in plain English. Test cases are provided. And the vanilla api is generated.

Sometimes I wonder where some of the posters here work or if I'm working in a dystopia.

You give it a set of requirements for an api with edge conditions written in plain English

This part is the job! If my job was 100% writing logic, it would be infinitely easier. Defining the requirements, evaluating the tradeoffs, discovering the edge conditions is where the bulk of my time goes. The only time someone did this for me was when I was a junior developer. Maybe I'm overestimating things, but I find it hard to believe that most engineers pulling huge salaries are just shuffling around fields on JSON API. Do you really need AI to expose a CRUD interface to Postgres?

Edit:

This idea that LLMs will replace engineers (or lawyers, or any traditionally "skilled" field) is hype. It's the same mistake that the customer makes when he's shocked that he gets a bill for $10,000 for replacing a screw in his car engine. You are conflating the actual physical labour requirements of the job (sitting down and coding) with the actual knowledge value that is being used when you do the job.

For example, take a look at Redis. Redis is a great codebase, especially for those that want to learn C. It's simple - there are exceedingly few mind-bending, hardcore, engineering algorithms in Redis. Antirez is an amazing software engineer, but Redis is not the fastest database, nor is it most durable. But what you see is the meticulous application of understanding engineering tradeoffs; there are things Redis does incredibly well and things that it doesn't that is made easier by the overall architecture of the code. How would you even begin to prompt this to an LLM? Again the code isn't complex, but the engineering is, and the act of turning those ideas and communicating them either to an LLM or to a C compiler, is engineering.

No one comes home from a long day and says "Honey, I'm tired I spent all day typing JSON schemas and function signatures".

fdgsdfogijq3• 3 years ago

Someone non-technical can do the requirements gathering.

mdorazio• 3 years ago

or if I'm working in a dystopia

Going to guess you're both young and working at a tech company as opposed to a big company that also does some tech things.

Prior to the rise of Agile and the decrease in waterfall-style development the role of Business Analyst was very popular. It still is at many companies that do need to do waterfall development, but less so these days. The Business Analyst (BA) role is semi-technical and requires some subject matter expertise, but generally doesn't do much actual writing of code. Instead it's focused on requirements gathering, wireframe creation, test case creation & running, bug logging, and status reporting. I know you're probably saying "that's at least half of my job!" and you're right, but now go and look at the difference in pay between a BA and a developer. It turns out that if you remove the "actually writes code" part of the job, it's not worth nearly as much and I think that's what the comment above is trying to express.

zitterbewegung• 3 years ago

Since people are bad at describing what they want there will be some kind of person that deals with the business and makes the computer work.

Already we have prompt engineering. And also we could have said the same thing for people who write in assembly language, and each higher level language and also programs that are designed to be low code . I see that this is a new type of spreadsheet but scaling these up or using these programs aren’t going to make coders / software engineers / data scientists go away in fact historically we have seen the opposite.

StefanWestfal3• 3 years ago

A possibility, and I think the way we work will evolve as well. But coming from a more "numerical" background, I can imagine a different route. Twenty years or longer ago, people who wanted to process a larger amount of data needed to understand low-level details, compilers, C/C++/Fortran, mathematical details, and so on. Today, we have JAX, scikit-learn, and many more tools. But these tools did not make the old 'numerical' people jobless; instead, their jobs evolved. Today, we have more data scientists than ever. You can create your own app faster than years ago, including hosting, persistent storage, load balancing, ... And again, we have more web developers than ever. The same goes for jobs like DevOps and other jobs that I probably don't even know. The level of abstraction got higher as you better now what the algorithm is doing but you do not need to implement it again. The point is the field will evolve, and right now, it may be the biggest jump ever, but that does not mean jobs will go away. We might end up in a situation like self-driving, where we are really close but still missing the last bit and need human intervention. I hope LLMs will solve the tasks that have been solved many times before, like bootstrapping a CRUD app, and we can focus on the edge cases and niche problems.

analog31• 3 years ago

Who will write in plain English? Granted I'm not in software development, but work in an adjacent area. Communicating requirements is already a hard, unsolved problem.

In an adjacent discussion about ChatGPT, we will look forward to when nobody learns to write in plain English any more.

lvl102• 3 years ago

People who get paid well in this business get paid for the big picture stuff. Architecture. Writing good code was never that valuable. My two cents.

weatherlite3• 3 years ago

Complex software will require human coding. But most programmers are in denial about how complex the code they’re writing actually is.

I think it's just a matter of time till all software becomes complex, e.g a codebase worked on by a few dozens people for 10 years will have a non trivial level of complexity. Not disagreeing or anything, the machines might be able to do this well, we'll see. It will have to improve by a lot, like almost no hallucinations. But there could be many shades in between. Instead of completely replacing developers in 5 years which I personally find unlikely, it can replace 50% of them.

dpistole• 3 years ago

"paid huge money to literally write if/else"

"most programmers are in denial about how complex the code they’re writing actually is"

I can taste the salt

abeppu• 3 years ago

I think this is a sad vision of the future not because a lot of programmers will be forced to do something else, but because it seems like this represents a fundamental failure for formal methods. We're hurtling towards a world where we automatically generate low-quality, buggy code, produced by stochastic parrots who mimic code written in possibly a different era by humans tackling different problems.

Forget about being employed producing software in a world where these are the norms, I don't think I'd want to be a software _user_.

I'd love for programming to be higher level and accessible, but I wish the process were:

- write a _specification_ that describes functionality, invariants, etc

- generate signatures compatible with that specification

- interactively seek implementation-relevant information from the designer, e.g.

  - "I see Users can have an unbounded collection of Bars, which can each reference an unbounded number of Wugs. How many Bars do you suppose a typical User would have? How many Wugs per Bar and how many Bars will reference each Wug? How large is a Wug typically?"

  - "Which of these DB queries do you expect to be run most/least frequently?"

  - "This API method allows for pagination. How often do you expect a user to page beyond k?"

- generate tests

- generate code aligning with signatures, _and which cause tests to pass_ (i.e. program synthesis from examples)

- static analysis / abstract interpretation / model checking to confirm that some invariants are respected

- explicitly reporting which invariants or properties were not able to be confirmed automatically which a human may need to confirm via an ad-hoc analysis

Software is one of the domains where we can actually do a lot of sophisticated automated reasoning, but the current trend of ML code generation as text completion ignores basically all of that, and this seems like a giant waste.

Mizoguchi• 3 years ago

I've been using ChatGPT to generate scripts I sometimes need(ed) to write for testing and troubleshooting purposes.

For example parsing files, pulling data from a table and dumping it in a CSV, monitor performance counters or network activity, backing up and copying files etc.

I don't consider this part of my job, but it's stuff I need to do often and I'm glad it can now be delegated to a bot.

It also means new hires and co-ops have more interesting things to do.

Today for the first time I used code from ChatGPT in a working solution.

Nothing too advanced, a small routine to interpolate a vector.

It took me literary a minute to write the prompt and another maybe 5-10 to adapt it and test it.

I see myself using ChatGPT more and more for this type of things, automation scripts and very specific, simple routines in production code.

However this is not 5% of the stuff I do, for the other 95% there's simply no AI advanced enough to do it and there won't be any for several years or decades or maybe ever.

Now those working purely in CRUD applications from functional specs given my others, better to start switching to something that demands design skills and process know-how.

falcor84• 3 years ago

I'm tired of Google announcing something in the future; wake me up when it's actually out.

xena• 3 years ago

Are you kidding? Google's main product is waiting lists.

davidhs• 3 years ago

The Brits love it.

akiselev• 3 years ago

There's Google Wait, Wait+, GWait, Hangwait, Wate, Wait4it, Google Weight List, Alphawait, and last but not least GWait Hangwait.

Am I missing any?

barumrho• 3 years ago

wait until you gotta wait for the waitlist.

cperry12• 3 years ago

we debated this; this is going to be a sequential rollout based on availability/capacity, and it seemed better to broadcast it was coming earlier b/c we're not going to have a "launch event" moment.

reaperducer• 3 years ago

So it's a soft opening. Like an out-of-town preview.

AbrahamParangi• 3 years ago

Arguably it would be good to not announce till it’s both available because even once released, expectations are going to be extremely high due to copilot.

gerash• 3 years ago

You could announce it when it's available to at least one user. "In the coming months" kills the excitement.

tomkaos• 3 years ago

I always know about google product too soon or too late. When the new product is not available yet and when they announce they kill it.

anotherpaulg4• 3 years ago

(Shamelessly spreading the word about my open source tool)

You can do GPT-4 powered coding chats in your terminal today with aider. It's not free in the sense that you need a gpt-4 api key, which openai charges you for. But it's a pretty great way to collaborate with AI on code.

https://github.com/paul-gauthier/aider

worldsayshi• 3 years ago

Neat! This interface look simpler than most alternatives I've seen lately.

Do you know how it deals with source files that are larger than the context window?

anotherpaulg4• 3 years ago

Thanks for checking it out.

Right now aider doesn't even try and deal with files larger than the context window. For gpt-4, that's 8k tokens or about 32kbytes. Which is pretty reasonable.

According to the data in [1], the average source file in github is less than 14KB. It's worth noting that they explicitly discarded small files with less than 10 lines. So the true average is probably much lower.

Regardless, I haven't found the gpt-4 context window issue to be problematic in practice yet. You do need to be careful about how many files you "add to the chat" at once. But that's not hard. For sure there are cases where you would need to refactor a large file before you could use it with aider.

I am certainly interested added context window management features to aider. I have previously explored a bunch of approaches for this with gpt-3.5-turbo. I shared some notes about these experiments previously on HN [2].

[1] https://hoffa.medium.com/400-000-github-repositories-1-billi...

[2] https://news.ycombinator.com/item?id=35441666

calny• 3 years ago

This looks great, thanks for sharing. Esp interested in:

Complex Multi-file Change with Debugging: A complex code change involving multiple source files and debugging.[0]

[0] https://aider.chat/examples/complex-change.html

anotherpaulg4• 3 years ago

Thanks for checking out the chat transcripts!

Ya, that one is some real work I was doing on the tool itself by using the tool. I use aider extensively while I code now. Aider has authored 150+ commits in that repo in the last week or so.

Many of the other transcripts are more "toy problems" to help convey the experience of working with aider to folks unfamiliar with the tool.

balls1872• 3 years ago

The animated gif for the first example leaves a lot to be desired.

The UX: Click a button, type in a prompt, click another button. The speed just to generate 2-3 lines of code.

And AI generated code with no basic error handling.

pphysch2• 3 years ago

That's the free UX. Paid users get a seamless Copilot-style autocomplete experience.

Clever use of intentional UX friction IMO. It does cost money to run these models.

balls1872• 3 years ago

And, free users are providing training data back to Google for free.

Certainly google should monetize; but not off removing artificially bad UX.

cperry12• 3 years ago

gotta start somewhere. we're in a sprint this week working on different UX patterns.

meghan_rain2• 3 years ago

Democratizing machine learning for everyone: Anyone with an internet connection can access Colab, and use it free of charge. Millions of students use Colab every month to learn Python programming and machine learning. Under-resourced groups everywhere access Colab free of charge, accessing high-powered GPUs for machine learning applications.

Ugh, cringe. Just say this is a panic swing at an existential threat (OpenAI) and you're trying to commiditize them.

cperry12• 3 years ago

lol been working on this since 2021; I have a small team and we do our best.

striking• 3 years ago

Deep respect for reading the comments and showing up for your team.

meghan_rain2• 3 years ago

then i take it all back, thanks for your work, the outcome looks very useful, looking forward to using it :)

indigodaddy• 3 years ago

Not free for gpt-4, but there is also cursor.so (no affiliation/never used but looked interesting when I stumbled on it last week)

barbazoo• 3 years ago

If you're not paying for it, you're the product

sharemywin• 3 years ago

your data is they could give 2 shits about you. They take care of pigs before they slaughter them.

astrange2• 3 years ago

Google doesn't need to care about "your data" particularly, they show you ads.

astrange2• 3 years ago

You can pay for Colab.

nlstitch• 3 years ago

Yeah something about being vendor locked by Google into the "Democratisation of ML" does not sound appealing at all.

assane101• 3 years ago

How is it vendor locking if you are writing Python code you can pull out any time ?

cperry12• 3 years ago

+1 all Colab files are the standard Jupyter .ipynb extension: we very much want to avoid any notion of lock-in. We bundle them all into a folder for you in Drive: it takes you like a second to take all of your work to any competitor.

oli56792• 3 years ago

I find VS-code running notebooks with Colab plugin installed pretty helpful for this type of thing already.

(1) run notebook in VS-code https://code.visualstudio.com/docs/datascience/jupyter-noteb...

(2) install Github Copilot extension https://marketplace.visualstudio.com/items?itemName=GitHub.c...

and then it can quite often achieve what you want with just a comment or some previous code snippets.

Then if you load in pandas and a DataFrame you want to analyse, it quite often suggests the next stage of your data-analysis work, either right away, as you write the first step in some chain of pandas methods.

hn_throwaway_99• 3 years ago

I find VS-code running notebooks with Colab plugin installed pretty helpful for this type of thing already.

I think you meant "with the Github Copilot plugin installed".

BudaDude• 3 years ago

I got excited for a moment to run Colab in vscode. I was sad to see it was typo

oli56792• 3 years ago

You’re completely right. It was a typo that causes confusion

sva_• 3 years ago

Hint: VS Code Jupyter even allows connecting to remote kernels, so you can access some remote GPU from within the editor.

I think Colab doesn't support this, but Paperspace Gradient for example does.

https://docs.paperspace.com/gradient/notebooks/notebooks-rem...

version_five• 3 years ago

"We won't charge you for providing us with training data"

Also, I'm sure they have ways around it, but I'd imagine colabs are a poor source of "good" code to use for further model training, both because of the kind of code you write in notebooks and the demographic that would make up colab users. It sort of fits with the idea that autocomplete might be good at writing short functions that do some specific thing, but not much help actually writing a full program.

neets• 3 years ago

Train the AI by using AI, things are getting pretty META

omeze2• 3 years ago

Free of charge, unless they don’t like what sort of programs you run! Google bans certain open source AI models in Colab, like Pygmalion. See https://colab.research.google.com/github/PygmalionAI/gradio-...

dymk• 3 years ago

What's the problem here? They get to choose how they offer their free service?

omeze2• 3 years ago

The problem for users (not google) is that its an arbitrarily enforced restriction. Of course companies can do whatever they want. Google could ban all programs that import PyTorch on their free tier, too. Totally their choice. It’s also my choice to mention that people should look into alternatives like Replit if they’re worried about a cool notebook they made on Colab randomly getting them in Google TOS trouble.

ztgasdf3• 3 years ago

Would be nice to try, until I got banned yesterday for trying to connect two Colab runtimes together via SOCKS5. Turns out connecting to any proxy at all immediately suspends your Colab usage for "suspected abusive activity"!

cperry12• 3 years ago

appeal in product and we're usually pretty forgiving

ztgasdf3• 3 years ago

Already did, but I accidentally did this once before and appealed and got unbanned some hours later. It's been almost 48 hours since now, so I don't think they're too forgiving for repeat offenses.

aorth• 3 years ago

Was it also trained on my/our open-source code repositories and Creative Commons StackOverflow answers? https://stackoverflow.com/help/licensing

Does it provide any attribution?

seydor• 3 years ago

Alexa build me a Google (or is it the other way around?)

As more people use automated programmaking, most of the code will be low level spaghetti in procedural languages, because it is easier for the model to reason with it (without needing huge buffers to know about abstractions). We will see a lot of generated Javascript, PHP, even a return of Win32. Who cares if they are tedious for humans to read and fix, now the AI can do all kinds of advanced search/replace in the code. And maybe at some point they 'll be generating machine code directly

dang2• 3 years ago

"soon introduce"

This looks like an announcement of an announcement, which isn't on topic for HN. https://hn.algolia.com/?dateRange=all&page=0&prefix=true&sor...

On HN, there's no harm in waiting for the actual thing: https://hn.algolia.com/?dateRange=all&page=0&prefix=false&so...

jsnell2• 3 years ago

I don't think that's the case. This is the official announcement of a product, with details on how the product works, and I doubt they'll be writing anything particularly more meaty when they proceed through various rollout stages.

The way I've understood the "announcement of an announcement" rule in the past is that it is for reports/rumors that somebody is company to release something, or a company sending a teaser for a future event where they'll announce something.

The standard has never been that the product needs to already be generally available to be on-topic. If that were the standard, when could we discuss say a new iPhone? Not when it's talked about on the big Apple stage. Or as another example consider yesterday's discussion of the changes to the Google account deletion policy. No accounts will be deleted for 9 months, was it an announcement of an announcement?

dang2• 3 years ago

Ok, I've rolled back that penalty. https://news.ycombinator.com/item?id=35978216 confirms what you've said.

The comments in this thread are nearly entirely generic, though.

bushbaba• 3 years ago

Google should learn from Apple and their prior Gmail launch how the announcement should have a clear call to action. Else they created buzz that was not capitalized on.

theonlybutlet• 3 years ago

It's all about the share price when it comes to Google these days. Don't think they're concerned with long term gain.

renewiltord2• 3 years ago

The way that I do this right now is use Copilot in IntelliJ for notebooks that I execute on a remote server. This does the job.

pprotas• 3 years ago

What kind of remote server do you use?

renewiltord2• 3 years ago

IntelliJ can connect to a Jupyter server. That's what I use. As for hardware, it's just some generic Linux box with lots of RAM - nothing special.

And strictly I use Pycharm from the IntelliJ suite.

If you mount the remote FS locally (I use NFS) you can even stop writing locally and continue on your server's Jupyter web interface.

candiodari• 3 years ago

I'm sure it'll be available in 180 countries: the US, the United States, America, New York, Washington, Wisconsin, ...

(sorry frustrated bard-non-user in the EU speaking ...)

pram• 3 years ago

Don’t worry. Bard isn’t very good, you’re not missing out on much.

cperry12• 3 years ago

sorry, US first :(

blame the lawyers and TPU capacity

miohtama2• 3 years ago

Hopefully the AI knows how to update Colab to newer Python versions!

nomel• 3 years ago

3.10 is supported. I suspect it's others [1] preventing 3.11.

[1] https://pyreadiness.org/3.11/

cperry12• 3 years ago

We had a couple SWEs move us from 3.7 to 3.10 over the past six months, removing years of tech debt. This comment is dead wrong. We'll upgrade to 3.11 when they push their final regular bug fix release in April 2024.

Make fun of my stupid blog post all you want, but my eng partners are awesome!

miohtama2• 3 years ago

Thank you. We stopped using Colab some time ago because it was stuck on old Python versions. Happy to see the train moving again.

ilaksh• 3 years ago

Does this mean that Codey will be available soon via the Vertex/PaLM 2 API?

mark_l_watson• 3 years ago

I saw this announcement a few days ago and I am enthusiastic. Even though I only use Colab 3 or 4 hours a month, it is a good product and so I happily pay $10/month for it. I hope Codey is available on the $10 plan.

I have been using CoPilot for about a year (mostly in Emacs, sometimes in VSCode) and I find it very useful, so I am especially excited to see what Google offers.

I also find myself using Bing+ChatGPT a lot for writing short functions in a variety of programming languages. All of these tools, at least for me, eliminate most of the tedium in my programming projects.

cperry12• 3 years ago

we'll start on Pro+, but plan to support Pro as well, including w/ autocompletions (those may slip if cost/usage comes in too high, but so far in dogfooding it's very reasonable).

neilv• 3 years ago

Colab will use Codey,

"OK, team. With our founding cash cow threatened, we're at a critical juncture that could preserve or break us. If we're to survive, we must make the most of every factor of success at our disposal. This includes branding, and that's why we hire you, some of the best in the world at it. First major disruptive tech up for branding is a code LLM. Brainstorm now."

"Codey McCodeface!"

"Looks like we can go home early."

Jackson__• 3 years ago

Soon meaning hopefully with the release of palm 3? From the few tests I ran with palm 2 in bard, it's... well not absolutely horrible, but still quite a bit worse than ChatGPT3.5.

Google Colab will soon introduce AI coding features

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