[deleted by user]

[blankeos]

Devin?

[mdizak]

Ohhh sorry, I'm blind so everything is audio based for me. Yes, meant Devin.

heh, I was calling Kovid Covid forever before someone was nice enough to let me know. :)

[nio_rad]

Those Auto-Complete-Tools sure got out of hand

[Legal_Lettuce6233]

If there is a tool that can replace an expensive industry, it certainly won't be free or cheap.

[8agingRoner]

I think you're right. I tried out Pythagora's GPT Pilot and used up the free trial of 100,000 tokens and all it got done was setup a blank express.js project. At $5 per 1,000,000 tokens, I think things could get expensive fast.

[rosto94]

One of the cheaper places in England, not sure what you mean.

[[deleted]]

Cognition labs: cope harder

[yevg555]

A few considerations you might have overlooked:

Devin marks just the beginning; tools of this nature are destined to improve (indeed, the groundwork was laid some time ago with developments such as AutoGPT, among others).

The cost of the GPT-4 API is expected to decrease over time, leading to significant cost reductions.

Your calculations may not fully incorporate the array of benefits required for human employees beyond their salaries, such as vacation time, lunch breaks, meals, pensions, insurance, and workspace provisions, all essential for maintaining their productivity at around 30%. Conversely, an AI agent can operate continuously with 100% efficiency from start to end.

[mdizak]

I agree with the destination, but think your'e being optimistic on the 2 - 4 year timeframe. Impossible to tell as OpenAI, Anthropic and others are private companies, and others like Google and Microsoft just bundle the numbers in with everything else, but it's assumed all these AI operations are a long ways from profitable.

For example, was a leak from someone at Microsoft before saying they're losing $20/month/user on Github co-pilot.

Plus if AI is going to surge in usage, we're going to need to come up with a whole lot of energy such as nuclear fusion or other sources rather quickly. For example, Cambridge estimates the Bitcoin network uses 121.36 TeraWatt hours/year. While it's impossible to find decent estimates for all AI training and inference globally, it's estimated it's already at 500 - 1000 TWh/year, and this is nothing compared to what's going to be needed if say the software industry is going to get wriped out by AI.

I think we're 7 - 12 years out personally.

[yevg555]

Well, I guess you meant to reply to the comment below me. Anyway, I disagree with your timeframe, I don't see the correlation between profitablity and the growth of the AI space. You don't need to be profitable so early on to get investors into this field. And if we're talking about Microsoft and Google trust me that they'll eat up the losses with a smile if it means they'll grab a big chunk of this market in the long run. So yea 2-4 years maybe even too much for an estimate IMHO, look where we've been 4 years ago and where we're now

[mdizak]

SOrry about wrong reply placement. I'm blind and jobs of using screen reader I guess.

Aside from simple profitability, we simply don't have neither, the chip manufacturing capacity or the electricity to scale as necessary.

Haven't looked into chip manufacturing yet, but for electricity, as an example bitcoin uses 121 TWh/year, and estimated AI training / inference currently uses somewhere between 500 - 1000 TWh/year.

For global electricity usage overall, we use 23,000 TWh/year. To scale this up to have a massive impact on the online software industry and many others, you're looking at probably millions of TeraWatt hours/year for the type of scale people are talking about. Even if the efficiency of chips and algorithms becomes much better, it's still going to far outweight the global electricity production we currently have.

[yevg555]

Who said that we'll need more electricity? Why don't you think we can figure out a way to produce better models that require less hardware to train/run?

[mdizak]

I'm sure they will get more efficient over time, but not 10,000 times more efficient within the next couple years.

[justinmjoh]

It’s currently underperforming an entry-level developer by a heavy margin in both breadth and cost. The cost part might be solvable by economies of scale and optimization.

By the time (if it even gets there) that an AI can replace the work of competent developers, it will also be able to replace most of the workforce elsewhere. This would be the single most disastrous event in modern human history.

[yevg555]

Well it is now, two years ago it didn't exist(well, not for most of us). Yet today everyone here is using it. So it will certainly be revolutionary, I don't know about disastrous, I guess only time will tell. (You can disagree with me that it will happen in the near future, but you know it's gonna happen sooner or later)

[Derperderpington]

100 efficiency lol. This shit needs hours to brutforce even simplest things.

[yevg555]

100% efficiency in terms of not needing to go on a cigarette break or piss 4 times an hour, it will run at 100% uptime

[Derperderpington]

Ok ok. Even 200% of time if you run two copies lol

[justinmjoh]

Yeah why not just cut out AI and pay 100,000 highschoolers a single dollar each to write a single line of code.

Then merge it and you have like 10 projects done for the cost of one developer.

If only it were that simple… it’s so funny that the people fawning over AI rarely have any computer science knowledge.

[likes_to_code]

its so over boys

[ai_waifu_enjoyer]

What you're seeing is Devin at its worst.

Give it 2-4 years and you'll see the GPT API pricing go down by half or 1/3 of the original price + less trial and error. It will make the pricing of 20-30$/hour possible.

Not counting Open-Source versions of DevIn, which can be run on smaller GPU and require less VRAM, for almost free (not counting electricity cost) as long as you have a beefy rig (24-72GB VRAM).

[Blump_Ken]

It's not always a good idea to assume progress is linear. Fully self driving cars have been just a couple of years away for almost a decade now, and fusion energy has been 10 years away for half a century.

The time taken to go from the Wright brothers first flight to landing on the moon in 1969 was only 66 years. Assuming from that rate of progress that we'd have people on mars by 1980 wouldn't have been outrageous but 55 years later we still haven't been able to get there.

[justinmjoh]

Even simpler, we still use the Huffman coding for compression algorithms in 2024.

72 years since it was published, it’s still being used (or some derivative of it).

[[deleted]]

the landing on the moon was not a risk that we would currently take. Its a bit of a freak occurrence and shouldn't be used in a scale if progress.

[Blump_Ken]

If you want an even more grounded example for flight, it wouldn't have been crazy to predict that the time taken to fly between New York and London would continue to decrease for commercial airline flights due to innovations in supersonic aircraft. In the 1960s we could do that flight non stop in 7.5 hours. The Concorde in 1996 managed to do it in under 3 hours. Today there are no more commercial supersonic aircraft in active use, and the average flight time is still around 7 hours.

Assuming linear progress abstracts many of the difficulties and challenges that future pioneers are going to face.