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Comment by DebtDeflation | Hacker News Reader

>puts it in a similar tier as crypto

Comparisons between AI and crypto are horribly misguided IMO.

Is AI overhyped? Sure. However -

AI/ML is creating utility everywhere in our lives - speech to text, language translation, recommendation engines, relevancy ranking in search, computer vision, etc. and seems to be getting embedded in more and more processes by the day.

Crypto never amounted to anything beyond a currency for black market transaction, a vehicle for speculation, and a platform for creating financial scams.

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Everywhere??

That’s exactly the hype talk that’s going to burst this bubble.

Here’s tech’s dirty little secret. Despite all the screams about automation and universal basic income… the exact numbers where job replacement would show are in the labor productivity numbers. If GDP stays flat or grows while the number of jobs is reduced… bingo… you’d see that number climb.

Productivity has actually stayed flat or gone down over the last 15 years. Despite the fact that we’ve had trillion dollar corporate behemoths now. Despite that fact that we’re enabling a surveillance state Orwell couldn’t imagines. Despite the polarization we see. And teen anxiety going through the roof along teen/pre-teen suicides.

When you said AI (and in my view tech in general) are everywhere, I’m guessing this wasn’t what you meant…

> When you said AI (and in my view tech in general) are everywhere, I’m guessing this wasn’t what you meant…

That person gave a list of tech they were talking about in their comment immediately afterwards: "speech to text, language translation, recommendation engines, relevancy ranking in search, computer vision, etc. and seems to be getting embedded in more and more processes by the day."

I'm not sure it's worth quibbling over whether we should use the term "everywhere" or "in many places"; the general point stands that it's found many different uses, and has done what effective tech does - fade into the background in many cases, just becoming part of our daily lives.

Sure, we're not seeing the off the wall predictions from the singularity crowd, but it seems to be tech that most people find broadly useful.

The missing productivity paradox is something that should interest everyone in tech! Like any macroeconomic observation, there is plenty of uncertainty in both the measurements (GDP ain't perfect) and the context (2 financial crises and a pandemic). But even pro-status-quo institutions like Brookings agree that Something Is Up. Their 2021 review on the topic is both a decent summary and a good source of further refs [1].

My favorite explanation is that many new technologies end up redistributing wealth rather than creating it, which certainly tracks with both subjective and quantified growth in inequality on the same time period. However, a slightly more optimistic take is that tech is aligning production better with people's preferences, so that the same productivity enables people to live more distinct lifestyles that suit them.

[1] https://www.brookings.edu/articles/how-to-solve-the-puzzle-o...

Another explanation that I find persuasive, put forward by Ezra Klein, is that productivity-sapping uses of technology grew along with the productivity-boosting ones: social media, for example, is a powerful mechanism for distracting people and destroying their attention spans.

If this is a good explanation, it begs the question of what AI might do to destroy productivity as well. If you’re constantly sexting with your AI girlfriend, who just happens to be extraordinary adept at tapping into your sexual proclivities, maybe you won’t get as many support tickets resolved as your boss was hoping.

More hypothetically, I would also expect that a world in which people spend a lot of time with screens strapped to their head, consuming an infinite stream of entertainment provided by generative AI, is not going to produce higher GDP.

> More hypothetically, I would also expect that a world in which people spend a lot of time with screens strapped to their head, consuming an infinite stream of entertainment provided by generative AI, is not going to produce higher GDP.

Yeah, I think this dovetails with the idea that IT may be satisfying preference allocations without increasing overall production. Watching 10 movies a month on a streaming service adds much less to the GDP than going to the cinema 10x, but if the selection is better it might satisfy you more. Economists sometimes attempt to measure this with "utility adjustments" which recognize increasing quality in the same goods, but it's very hard for those adjustments to account for the hidden preferences of the consumers as opposed to objective qualities of a good or service.

Information goods like social media and streaming, financial services like pay-me-later, and conveniences like next-day delivery are all examples of activities that might suit preferences without showing up in GDP. They also may enable distraction, waste, reclusiveness and impulsiveness in ways we'd like to avoid as a society. At the same time they might also help some people feel more included and less lonely or trapped by circumstance.

> put forward by Ezra Klein

The explanation sounds pretty familiar, so I might have already read/heard this from Klein, but would you mind sharing a link?

I believe he has mentioned it more than once, but one podcast that includes that discussion IIRC, and many other AI-related topics, is the April 7 episode “Why A.I. Might Not Take Your Job or Supercharge the Economy”. If you’re on iOS:

https://podcasts.apple.com/ca/podcast/the-ezra-klein-show/id...

How do those distinct lifestyles" match with rising inequality and people having a hard time buying a house or paying rent?

Inequality is a red herring. Poverty is down.

Have you looked for housing in Columbus, Ohio?

Is homelessness trending down or up? Why?

It's easier than ever to be homeless and it's generally frowned upon to forcefully institutionalize the mentally ill these days.

Wish I'd known that it was difficult to become homeless back when I was. It seemed really easy at the time, all you had to do was get evicted. Not sure how it could be easier now.

I think what they meant was that it's easier than ever to be homeless.

In many places you can't be thrown in jail for being homeless anymore. Many cities have more housing and shelters and free kitchens than ever before. Some places even give you a smartphone and basic plan. Etc.

I’m sure there are plenty of ghost towns with housing sitting empty that could be had for a song too. That probably doesn’t help if your job, family, and friends are somewhere else.

And remote work is more common than ever. Regardless, Columbus, Ohio has a very reasonable cost of living for the salaries available in the region.

Shhhh...don't need any more people here.

Ghost town?

https://www.intel.com/content/www/us/en/newsroom/news/intel-...

Nope. How am I supposed to get a job there? How about getting the money together to afford to move? I already live in a "low cost of living" area with less than half the population of Columbus, Ohio. It's still expensive as hell and there isn't a great housing situation.

Well, people are working everyday in Columbus OH.

I'm not from the US nor do I wish to live there, Columbus, Ohio or otherwise.

> having a hard time buying a house

It's also much harder to get servants in that house. I wonder why...

I don't understand your comment.

if everything is so bad then it should be easier to find someone willing to work. But that's not the case today. Which means life today is probably not that bad.

As far as I know, neither the rate of homelessness has gone up nor homeownership has gone down over the past decade.

The first one wouldn't cover rents increasing but people paying them, albeit struggling.

The second one is a lagging indicator. If lots of people bought their homes when they were cheap and are still alive, it will take time for the real impact to be visible.

Agreed. Though I think that the 'struggling' part creates a lag in both aspects. I think the 'gotta have a side-hustle' trend is a strong indicator of this. I would be interested in seeing the trends in number of people working 2+ jobs (or income streams), population shifts to more affordable areas, and number of disconnects of non-essential services. From experience growing up in a poor family, I know the definition of 'non-essential' can expand greatly as desperation grows.

Edit: Tracking real numbers in homelessness is also just extremely difficult.

https://endhomelessness.org/homelessness-in-america/homeless... It's increased.

It is less about productivity and more that AIs have the potential as the ideal employees.

No time off. No health care. Operate 24/7. No unions. No work safety concerns. No lawsuits over being unfairly fired. Control over exactly how something gets done or said.

If only the AIs will stop hallucinating or can consistently comply with policies …

> If only the AIs will stop hallucinating or can consistently comply with policies

I'm starting to wonder how much this matters.

People do crazy shit on the clock all the time. Company reps do not always adhere to policy 100% of the time either. People engage in office politics, coworkers accuse others of whatever, mistakes get made. LLMs happen to emulate all of this behavior.

In theory, we could replace everybody with AI and not much would be different. Productivity increase is debatable but cost savings would be immense. The question is how much insanity we're willing to tolerate as a result.

(...and seeing what fun ensues when there are more people than available jobs.)

>The question is how much insanity we're willing to tolerate as a result.

Given our elected representatives, I don't think that's a problem. No offense to any party or person. But we've consistently proven that we can tolerate and welcome way more insanity than seems reasonable.

My thought has been that most of the IT revolution hasn't been able to produce much extra goods, its all about Information, all it can do is help us optimize existing goods producing processes. As a result much of the productivity within the Information Technology advancement, has done little in the way of actual wealth creation, apart from optimizing existing processes, which hits a limit pretty fast.

> IT revolution hasn't been able to produce much extra goods

Measuring "Goods" in units or tons is bit simplistic. Almost everything is much better that it was 15-20 years back. TV, cars, phones, computers. This difference probably should be counted as 'extra', shouldn't it?

Your second paragraph makes intuitive sense to me. For every knowledge worker that got 2x as productive in the past decade thanks to new tech alone, there's a person who left their job where they were doing productive (perhaps grindy) things to do gig work because of the flexibility it provides. It might be nice burning VC money so someone can drive you home when you've had one too many (instead of taking public transit), and having someone shop for your groceries and walk your dog and do your laundry, but the individuals doing these tasks would probably accomplish more in terms of raw productive output if they were doing more traditional jobs.

Those are all traditional jobs though.

Driving, picking/packing, animal care, doing laundry - Absolutely nothing you mention is in any way some new 21st century job that didn't exist before. They're all just normal traditional jobs.

I've seen some indication that this is a measurement problem. Tech enables computers to do things that would be originally expensive for humans to do.

Translation is an interesting example: some labor has been displaced, but not nearly all because there's still value in having human eyes carefully checking the translation of high value documents. But free translation let's regular people translate things freely - a new capability which displaced no one.

However, productivity measures human productivity and human labor. The very cheap new translation modality is therefore completely missed by productivity measurements.

Meanwhile, there's /more/ jobs available right now, despite all of this. The US has hit a historic low in unemployment and wages are going up, leading to a decline in measured productivity. Productivity is output per dollar of wages, which means we twist our hands in anxiety when workers start doing better...

Maybe you live in a monolinguistic bubble, or speak every language fluently, but when is the last time you hired a human being to translate a language you don't understand instead of using AI like Google Translate?

AI is already so ubiquitous and useful that you blindly take it for granted without even thinking.

Most companies will at least hire a human to check translation work, or at least contract one. Bad translations are something that can quickly destroy a brand in a market, and translation tools are not so fine grained to take into account dialect.

Spanish, for example, has many examples of words that are innocuous in one dialect and profane in another.

> Bad translations are something that can quickly destroy a brand in a market

Bad translations are present in product names & descriptions of at least 70% of all products on Amazon and Ebay I've seen, and it doesn't look like it hurts the business in any way.

Have you seen their sales revenues?

Big difference between "buy this $5 plastic crap widget despite its product description being barely coherent because there's only so many seconds you're willing to spare searching for 'Plastic Crap Widget' because Familiar Tech Company's algorithm puts CBSPOO ahead of VRIENGLU in this particuar search parameter combo" and "hello professionals in niche market. You will recognise the name of our product whenever you next have $xx,xxx to spend on these services, because we were the one whose ad was inadvertently extremely sexist"

I think that people who are fine with buying crappy products don't care about crappy translations.

Others, however, do care. I, for one, will pass on something that has bad translation because I take that as a proxy for the quality of the product overall.

Dealing with any international company requires having a translation office with a distinguishable stamp on every single letter. Might be slow, but they can be held accountable unlike your number soup AI

> when is the last time you hired a human being to translate a language you don't understand instead of using AI like Google Translate?

Last year, for an important letter that had to be written in Japanese, a language that I don't know. Using Google Translate for that was unthinkable, because Google Translate is pretty poor and I had no way of checking and correcting the translated text.

GDP is not productivity. If I manage to produce/sell a hundred gizmos for $1 each, displacing my competition who were producing/selling 50 gizmos for a price of $5 each, I just halvened gdp produced even though both me and people using the gizmo are more productive than before.

But your customers now have money to spend on something else. The money didn’t disappear.

I think precisely the point is that money isn't wealth.

Government can print as much of the latter as they want; wealth goes up when we can collectively buy more and down when we can collectively buy less, regardless of how many dollarpounds that is.

But GDP is measured in money, and can only connect to wealth if we get get inflation right, but that's really hard because inflation depends on what you want to buy — childcare costs don't matter if you have no kids of that age.

That said, I trust the domain experts to get this right, even though the various governments may be incentivised to claim their own preferred numbers. Even at worst, they'll have thought of vastly more influences than I can even imagine.

Especially in translation quality. Being able to run high quality translation model that does 100 languages directly without going through English on a desktop pc with a previous gen gpu (2070 in my case) is huuuuge. (I'm talking about fairseq and m2m100 for anyone interested in spinning up their own).

If I was going to name the biggest good thing AI has done to humanity so far is the ability to read internet sites in other languages like Chinese (Google sucks at it, you have to use other tools, I use an app called "tap translate screen"). Also ability to do voice to text and translation at the same time on mobile devices (currently requires online connection).

AI affects both human interfaces (text, speech, sound, images) and the ability to interpret and create data by/for humans. That's effectively the entire interface space between machine and the human-experienced world. Can you think of an area of technology that won't be affected by AI? Even unrelated technologies are going to get affected in their interfaces and tooling.

As for the rest of your comment... please don't hijack other conversations for soapboxing on the industry as a whole. Instead, submit your post and open a real conversation.

Why does GDP measure anyway? How much money do we create for billionaires?

My life is permeated by tech (and big part of it is AI) and made 100 times easier. I can buy a plane ticket to another country while waiting for a subway (did people use to take an hour to go to a special place, wait in line and talk to human to buy a ticket? I still remember this). I go there and quickly navigate in a city I know next to nothing about, find something niche, like cool local cafés in the area because GPS and google maps. I go to a restaurant and I can use google translate to understand the menu. I don't even need to type unfamiliar words, AI scans the image and translates it on the fly. The same google translate with speech recognition AI helps me to converse with a person when we don't share any common language. I can click couple of buttons and video-call my mum who lives on the other side of the world. If I need to buy something I need very rarely, I can order it online and not think where I find a shop that sells those things. Even if I don't know the right word, I can now ask chatgpt "what do you call in German that fancy thing you mount on the ceiling and attach lights to it?"

My life is _hugely_ more efficient thanks to tech and AI. Does it help me to contribute more to the abstract economic growth? I don't know, perhaps not. But I just don't care about GDP.

> GDP stays flat or grows while the number of jobs is reduced

I lack the economics knowledge to do more than parrot the response I've heard to this, so take this with the appropriate level of "hmmm":

As I understand it, the counter-claim is that the measure of GDP mostly excludes exactly the set of things that grows absurdly fast.

For example, the measure of inflation may include the cost of a smartphone in the standard basket of goods, but not the fact the GPU of a smartphone (or Apple TV) of today, operating in double precision mode, can do more than the Numerical Wind Tunnel supercomputer in 1993 costing 100 million dollars.

Or that everyone has a free encyclopaedia a hundred times the size of the Encyclopædia Britannica.

And maps which for most users are as good as Ordnance Survey, but free and worldwide, when the actual OS prices for just the UK is… currently discounted to £2,818.17, from £4,025.97.

Or that getting you genome sequenced now costs a grand rather than 3 billion. Although that might not yet even be in the basket, I don't know where the actual baskets of goods get listed in most cases, and search results aren't helping — one result, on a government website, lists "health", but even digging into the spreadsheet didn't illuminate much detail there.

That is true. Switching from buying Britannica to using Wikipedia is counted as a reduction in GDP as GDP counts what you spend and Wikipedia is free, even if it's better.

The UK basket of goods is here https://www.ons.gov.uk/economy/inflationandpriceindices/arti... and the various sublinks.

> …genome costs…

Source: This week’s Kurzgesagt, right?

Not only but also; this was a thing I was aware of this years back, but Kurzgesagt is a nice bit of easy watching when I'm eating dinner.

Good. GDP should not include any of those things. Those are tools. GDP includes outputs and impacts.

Maybe you design a wrench that is 1000x cheaper and faster to use and more reliable. Well, if it makes your car building operation 0.0001% faster, that's the impact. The details of the wrench and how impressive it is are irrelevant to any observer.

If having your genome sequenced leads to far longer or better lives then we would see the impact in productivity. Same with everything else on the list.

I don't think the rub is with AI in general. Everyone working in tech knows how pervasive ML especially has become.

I think the contention is with AI suddenly being redefined as only referring to language models, and the view that intelligence has been solved by these models.

There has clearly been a massive marketing push to label these models as the "one true AI", both from companies and from AI influencers. This is where the echo chamber exists, and it's easy to get stuck in it.

Maybe I am wrong and we have solved intelligence. But I seriously doubt it.

I agree completely, and I think the 'tipping point' came because of ChatGPT. And I think it's for two primary reasons:

1. ChatGPT was released for general-purpose use. It's not a data science team at a FAANG company or healthcare or finance enterprise using ML for a specific business need. It's there for anyone to ask it anything.

2. A design decision was made to have ChatGPT output words in "real time" instead of all-at-once after a delay. To the user, that makes it look and feel like it's consciously and actively responding to you in a way that animated ellipses do not. I never knew what it would feel like talking to an AI, but when I first used ChatGPT, I thought: this must be it.

> speech to text, language translation, recommendation engines, relevancy ranking in search, computer vision

You know very well that that's not what GP is referring to. Speech to text, natural language translation, recommendation, and computer vision are all very useful things, but also were very much real and in consumer hands long before the current hype cycle.

Generative AIs are in their hype cycle. IMO the tech is overhyped to hell and back, but it will still probably yield better results than Crypto, there are legitimate uses for it. But those uses need to be ok with an 80% correct solution, which is not sufficient for all the things LLM hypelords are saying they can be used for and there is no path forward for closing that 20% gap.

Bitcoin still has the potential to become the worlds reserve currency. That’s pretty legit.

No, it really doesn't.

It absolutely does. What leads you to believe that it doesn’t?

Comically low transaction rate, obscenely high power consumption, extreme concentration of BTC holdings in the hands of a small number of people (and companies who have very little influence of global politics), arbitrary growth rate and cap with no correspondence to economic growth, extreme volatility , inconsequentially small use for legal trade, but above all the complete and utter disinterest in it as a reserve currency outside a small echo chamber that has far more BTC to sell than involvement in international trade.

Fortnite Bucks, Mt Gox trading cards, skulls of adult humans and guano also "have the potential to become the world's reserve currency", but it seems unreasonable to put the burden on proof on the people arguing that they won't be.

Easy to prove every point you’ve dropped here wrong. But your TL/DR is: you don’t like bitcoin.

Please proove it, since it is so easy.

Governments and institutions mostly don't like it, that's a pretty big reason.

Can’t argue your point on governments. It will be interesting to see how it all plays out when Bitcoin reaches the next leg up.

So you aren’t infuriated by automated phone systems? Because let me tell you, the number of companies whose reputation has survived me having to deal with their fucking phone robot can be counted on my middle finger.

... can be counted on my middle finger

Fabulous, I'll be stealing that ...

Probably an extremely large number of companies can be counted on something as ginormous as the average human middle finger; I could probably fit 20 if I write really tiny and could fit a lot more with access to other devices.

Someday, cosmetic geneticists will offer to sell you extra middle fingers.

I would be grateful beyond even my wildest measure (two middle fingers).

Robotic extra thumbs available now: https://www.youtube.com/watch?v=GKSCmkCE5og

It takes more muscles to frown than to smile, but it takes more parts to make a thumbs up than to flip someone off.

It was a very Higgins moment. “Did you like that? I just made it up!”

Crypto has been quite useful for me personally, from VPN payments to donating to locally forbidden causes.

AI only does bad things to me so far: surveillance, spam, fakes, search results poisoned, twitter and reddit closed up because of it etc.

Where is my automatic captcha solver? Where is a robot that will get me to a live person in a support call? Where is a spam filter that doesn't send all useful emails to spam? Where is a filter to hide fake reviews on Amazon? To fight against Amazon's crazy product ranking system? Such useful things are nowhere on the horizon.

As soon as Amazon starts losing money in fake reviews, you bet they will miraculously have a solution in a weekend.

Until then, you’ll get a lot of “it’s a really hard problem to solve!” Coupled with zero progress.

The thing is, if there was a real useful AI, it could filter stuff on my end, independent of Amazon.

Off-topic:

> Where is a filter to hide fake reviews on Amazon?

While it[1] doesn’t hide, it can generate some insightful information about fake reviews for me.

Disclaimer: Not affiliated, only a happy person using FakeSpot since this year.

[1] https://www.fakespot.com/

This—100%. The AI revolution with LLMs is creating a new type of interface with computers—the AI interface. Will it kill us all? Eh, probably not. Will it completely change human civilization forever? Eh... maybe not? (But also maybe).

But what it already has begun to do, and will continue to do is change the way we interact with computers. The era of having a personal voice assistant that is capable, adaptable, and intuitive is VERY close and that is something that's exciting. Siri and Alexa are going to look downright primitive compared to what we'll have in the next 2-5 years and that is going to be VERY mainstream, and VERY useful for huge swaths of the population.

Crypto still hasn't proven itself to be useful in any way shape or form that isn't immediately over-shadowed by a different medium.

> The era of having a personal voice assistant that is capable, adaptable, and intuitive is VERY close and that is something that's exciting.

Intuitive to use? Or has intuition?

There might be sufficient overlap between all such concepts that a distinction hardly matters anyway: if the assistant says what's most likely to come next according to a LLM, or if a person says what they think should come next based on intuition, the listener would probably find each to be about equally intuitive to converse with due in large part to each of those qualities.

> There might be sufficient overlap between all such concepts that a distinction hardly matters

“Intuitive to use” roughly means that it is easy for a human to interact with.

“Intuition” is the ability to understand something immediately, without the need for conscious reasoning.

And that actually anyone wants?

Google and Amazon have tried to sell theirs for a long time. And none were actually selling much. Amazon admitted to be selling theirs at a loss. Facebook has tried their own - and quickly cancelled them. Google's is in every Android device - and yet pretty much nobody uses them. Even Apple's Siri is more annoyance than help.

That something can be built doesn't mean it will sell or that people will actually want to use it. If you create a solution looking for an imaginary problem that your marketing thinks is what people want instead of a solution that solves a real existing problem, you do get a solution looking for a problem ...

Also, answering questions and communicating in natural language is the easy part of such assistant. For the thing to be useful it must be able to actually do something too. Which is incredibly difficult beyond the (closed) ecosystem of its vendor. Thirdparty integrations are usually driven by who pays the manufacturer for the SDK and partner contract (seen as a marketing opportunity), not by what the users actually want it to integrate with. Hoping for one of these with an open API that anyone could integrate whatever they want with, I am not holding my breath here.

> Hoping for one of these with an open API that anyone could integrate whatever they want with, I am not holding my breath here.

OpenAI is already on it. The latest gen of GPT-3 and -4 are finetuned to respond to "do this thing" commands with JSON structured to:

- provide the name of a given function call

- provide arguments to that function call

it's "early stage", which in this case probably means "good enough to be useful within a month or two", given the rate at which these things have been developing.

Anecdotally, I've been playing with giving the models instructions like:

"When asked to perform a task that you need a tool to accomplish, you will call the tool according to its documentation by this format:

TOOL_NAME(*args)

Below you will find the documentation for your tools."

...and I've gotten it working pretty damn well (not even with the JSON-finetuned models, mind you). All you really need is python-style docstrings and a minimal parser and you're off to the races. I recommend anyone interested play with it a bit.

Early stage might mean good enough to use in a month or two or it might mean “full self driving this year”. There isn’t any way to tell until it happens.

And everyone will want to funnel their data and pay OpenAI/Microsoft in order to be allowed to implement a basically slightly better Alexa?

Dream on.

This is not a technical problem, this is a business problem. Sadly a lot of engineers don't understand that.

Oh, I think you've misunderstood me. Business problems are someone else's gig - I have no intention in making this a product or making money off it. It's for me.

The thing is, I've managed to get this working as an interface for a whole segment of stuff that was a pain in the ass before. My task list is all in one place for the first time, and it talks! With words! I have a pair programmer, who is excited to do stuff, on the command line, 24/7. They also have encyclopedic knowledge of anything that isn't a super deep cut, so I can move through more spaces and find solutions that I never would have dreamed of due to the cognitive load of sifting through textbooks and documentation just to create a [ insert more or less anything here].

If you're looking at the folks here who are getting excited and wondering "What's up with *them*?, this is it. It's not about the Next Big Thing so much as it's about "Holy shit, computers are magic again". For themselves.

Of course, I can speak for some of us. For sure, the hungry lets-make-a-startup folks exist and are currently working on doing that - and that's fine. But to me that's boring. Commerce and markets and economies are toxic to creativity. I've tried Bing-with-GPT and it's AWFUL compared to GPT-4, despite being sorta the same underlying thing.

I'm perfectly happy paying OpenAI to use the thing they built, for myself, for now. I am seriously looking forward to migrating to locally run models, once we get there (and we will).

Just before the point they built this, I was already chaining queries together to do this. I built a plugin system with bits of JS code that are eval'd and arguments injected.

They couldn't have released this at a better time, I have about 30 plugins and i'd say it manages to get the right one about 90% of the time as opposed to about 70 with my hacked together version (but I guess I wrote it and know what to say so maybe that's a bit skewed)

I've found that GPT really like "google style" python documentation. You need to have a chunk of system prompt explain that it should be 'using the tools according to their documentation etc etc', but once you've dialed that in a little stuff like this works a charm (the docstring is what the LLM sees):

@Tool

def add_todo(title, project=None) -> str:

    """
    Add a new TODO.

    Args:
        title (str): A brief description of the task
        project (str, optional): A project to add the todo to, if requested
    """

    logger.debug(f"Adding task: {title}")
    task = Task(tw, description=title, project=project)
    task.save()
    return f"Added [ {title} ] to the { project + ' ' if project else '' }TODO list."

> Intuitive to use? Or has intuition?

I don't really see either of those things as a real possibility. Within my lifetime, anyway.

This is a perfect example of an AI-hype comment.

You’re treating it as a fact that LLM are going to replace existing products, at some unknown future date.

“In 5 years, all code will be written by AI”

“In 5 years, LLM will replace Siri and Alexa”

“In 5 years, AI will replace [sector of jobs]”

The thing that frustrates me about these statements is that you don’t know what AI technology is going to look like in 5 years, so stop treating it like a fact. It’s possible LLM are useful in all of these places, but we don’t know that yet.

Exactly. The AI bros here are doing the same thing as the crypto bros and almost all of them don't even know it.

Pontificating their nonsense around the hype about LLMs to the point where they don't even trust it. The same thing they did with ConvNets and they still don't trust that either since they both hallucinate, frequently.

I can guarantee you that people will not trust an AI to fly a plane without any human pilots on board end-to-end (auto-pilot does not count) and it is simply due to the fundamental black-box nature of these so-called 'AI' models being untrustworthy in high risk situations.

I'd like to point out that humans, too, are not trustworthy in high risk situations. For this we have procedures, deterministic automation and so on.

I like to think of capable LLMs as pf gifted interns. I can expect decent results if I explain well enough, but I need processes around them to make sure they are doing what they are told. In my industry thats enough to produce a noticeable productivity gain, and likely some reduction of employment as its a low margin cut throat business relying on low grade knowledge workers. I see the hype and honestly cant stand it, but its measureably impacting my industry and the world around me.

> I'd like to point out that humans, too, are not trustworthy in high risk situations. For this we have procedures, deterministic automation and so on.

Except humans can transparently explain themselves and someone can be held to account when something goes wrong. Humans have the ability to have differing opinions and approaches to solve unseen problems.

An AI however cannot explain itself transparently and just resorts to regurgitating whatever output it has been trained on and black-box AI models have no clear method of any transparent reasoning meaning that it cannot be held to account.

Any unseen problem it encounters, it falls back to fixed guardrails and just repeats a variation or re-wording on what it already has said. Especially LLMs.

> Except humans can transparently explain themselves and someone can be held to account when something goes wrong

Except humans are excellent at finding excuses to avoid explaining themselves and being held to account, or to justify some misguided belief based on whatever output they have been "trained on" in their past.

People often seem to apply standards to AI in terms of rationality and reliability which even many humans cannot achieve, using terms like "hallucination" when we've seen humans do the exact same by confidently talking about things they know nothing about. Everyone laughed at Bing insisting on a wrong date to avoid admitting it's wrong about the Avatar 2 release, when that's very typical behaviour of humans in certain situations.

I'm not trying to make LLMs seem better than they are, but parts of its weaknesses are not surprising given the training data.

GPT4 just wrote a python script for me that downloaded a star catalogue, created a fish eye camera model, and then calculated the position of the camera relative to the stars by back propagating the camera position and camera parameters to match the star positions.

All I did was hold it's hand, it wrote every line of code. You are living in fantasy land if you think we will be writing lines of code in 10 years.

Do you know if it works?

Lets see it and lets see the prompts you used.

> You are living in fantasy land if you think we will be writing lines of code in 10 years.

I was with you until that sentence. No, LLMs will not write all our code and the reason is very simple: coding is easier than reviewing code. Not to mention the additional complexities and weirdness that we've always dealt with without even thinking about it.

We can see in Photoshop what's coming for developers: context-sensitive AI autocompletion and gap filling. Copilot but more mature and integrated, perhaps with additional checks that prevent some bugs being inserted. And troubleshooting, the area where I think we can profit the most.

that's all stuff that would be impressive for a single human to be able to produce instantly (because nobody remembers all these APIs), but that's still formulaic enough that it's not hard to imagine why ChatGPT succeeds at it

but will ChatGPT help you debug and fix a production issue that came about due to a Kafka misconfiguration? will it be able to find the deadlock in your code that is causing requests to be dropped? will it suggest a path forward when you need to replace an obscure library that hasn't been updated in 5 years? will it be able to make sense of seemingly contradictory business requirements?

That's not exactly the complexity of typical software that must solve an actual, difficult, business problem.

Wake me up when ChatGPT is able to write and maintain a POS system, or an online store with attached fulfillment management. Anything that goes beyond a fancy 100-line script. Anything that people actually hire teams of senior devs, business analysts and software architects for.

GPT-4 writes 100% of my code now. Staring at a monitor, hunched over, tapping on a keyboard?

Stone ages. That’s not 5 years from now. That’s today.

Can you elaborate what your process is? Some context would be nice as well. Like, what kind of language, what kind of project? I'm genuinely interested.

Pretty sure they're joking

Do you work much with legacy systems, internal libraries and work with a large team?

I do and ChatGPT code is rarely useful for me. I can prompt it well enough to do language related stuff for me, but the code it can write for me is more like a highly custom boilerplate that I still need to refactor.

Even for green field private projects, at first it looks fine, bit the bugs are more likely to be traced back to these snippets than not.

You are either full of shit, or your "coding" is pretty basic, or your code is full of bugs and you don't care.

I can't trust GPT, and neither can you. But if it really can do all your coding for you, what stops your employer from replacing you with a secretary from a temp agency?

It's so stupid for engineers to say that ChatGPT codes for them. They are shooting themselves in the face. They are devaluing the entire profession. Why? My reaction to all those breathless online demos was to point out the difference between what they were showing and what an engineer really does. Your reaction is to act like being a prompt jockey is the new way of engineering. How does that give you pride in yourself?

What would you prefer to talk about? We don’t have to make predictions and discuss their potential, or at least you don’t have to join those discussions.

A lot of these comments aren’t predictions. They’re assuming that openAI will create AGI in the next 5 years and they want to discuss the implications of that.

Personally, I think LLMs are a step forward, but I suspect that GTP-4 is close to the limit of what’s possible with LLMs. I don’t think we’re going to see AGI from the same approach.

LLM is obviously useful for something like Siri, Alexa or Google Assistant, or so you would think.

There doesn't seem to be a rush because it makes the implementation a lot more expensive, and those things are, I suspect, not profitable products (revenue sources) to their respective companies. They are a kind of enhancement to a layer of products and services; people take them for granted now and so you can't take them away.

A smarter Google Assistant would do nothing for Google's bottom line, and in fact it would cost more money to operate.

If it's not done right, it could ruin the experience. For instance, it cannot have worse latency on common queries than the old assistant.

I do know, for a fact, that having a more capable and powerful voice assistant than, the already fairly capable, Siri, will be a game-changer (for me at a bare minimum, but I’m not that special so I think it’s safe to extrapolate that to more people).

That’s a fact.

I also know that voice-interfaces to date have been incredibly stiff and there is ample room for improvement. I know, for a fact, that having AI enable better voice interfaces will make computing better and more accessible. I have a hard time understanding how those are hype-driven comments and/or opinions.

We do know these things for a fact. Not being able to articulate exactly which breakthroughs will be most important doesn’t make it hype.

> The era of having a personal voice assistant that is capable, adaptable, and intuitive is VERY close

Year of the voice assistant is getting close to year of Linux on desktop.

What you’re promising has been promised time and time again, received endless hype cycles then collapsed once people realised the limits of the technology. Yes, this time the tech is much more capable than what came before but I’m inclined to believe we’ll yet again find a limit that means we’re using it for some things but our lives still aren’t drastically changed.

What you’re missing is that with LLMs the chief obstacle with voice assistants changed overnight from “how do we develop a system that can easily interact in natural language” (at the time, a very hard and possibly unsolvable problem) to “how do we expose our systems to API-driven input/output” (a solvable problem that just takes time).

Case in point, I asked Siri to change my work address. She stated that I needed to use the Contacts app to do that. This is not very helpful. The issue here is not Siri’s inability to understand what I want, it is that the Contacts app does not support this method of data input. Siri is also probably not very good at extracting structured address information from me via natural language, but the new LLMs can do this easily.

> The issue here is not Siri’s inability to understand what I want, it is that the Contacts app does not support this method of data input

…which is something an LLM won’t help with.

“Just design an open ended API capable of doing absolutely anything someone might ask ChatGPT to do” is not the simple task you’re making it out to be!

There's a reason why people describe ChatGPT as a "research tool": you often need to do a bunch of iterations to get it to do the correct thing. And that's fine because it's non-destructive. But it's very far from a world where you can let it loose on a production, writable database and trust that it's going to do the correct thing.

I'm sure I've seen a headlock that someone connected their screen reader to GPT and it totally could do that kind of thing…

No idea how well, so I assume "badly"; but the API is already there.

(headline, not headlock; and now too late to edit)

50% of the time Siri’s inability to understand what I want is the issue, and I don’t even try that much, given the bad experience.

> Crypto still hasn't proven itself to be useful in any way shape or form that isn't immediately over-shadowed by a different medium.

Seems like it has proven very useful for Stripe [0], Moneygram [1], TicketMaster [2], etc.

Unlike AI which continues to consume tons of resources to burn the entire world down to the ground without any viable efficient methods of training, inference or fine-tuning their AI models in the past decade with its chatbot hype and gimmickry [3], crypto does not need to consume tons of CO2 to operate, thanks to alternative and greener consensus algorithms available in production today. [4]

Being 'useful' is not an excuse to destroy the planet around untrustworthy AI models getting themselves confused over a single pixel or hallucinating in the middle of the road.

[0] https://stripe.com/gb/use-cases/crypto

[1] https://stellar.org/moneygram

[2] https://business.ticketmaster.com/business-solutions/nft-tok...

[3] https://gizmodo.com/chatgpt-ai-water-185000-gallons-training...

[4] https://consensys.net/blog/press-release/ethereum-blockchain...

I mean. We can compare the hype pattern between the two and still acknowledge that one has utility while the other doesn't.

Both have resulted in a bunch of hopefuls starting companies, in order to attract mountains of venture capital. Companies that will only have a loose connection to the tech that drives the hype.

The same could be said about the microprocessor or any other tech innovation throughout history. They all lead to new companies chasing investment dollars.

Is there any insight from this observation?

> Is there any insight from this observation?

Yes: be deeply skeptical of anyone claiming tech they are personally invested in is revolutionary.

If someone believes a technology is revolutionary, investing money in it is the most rational thing to do, right?

> AI/ML is creating utility everywhere in our lives - speech to text, language translation, recommendation engines, relevancy ranking in search, computer vision, etc. and seems to be getting embedded in more and more processes by the day.

For most people that's a promise for the future, but beside some translation tools (who are far from perfect) there is not much.

For instance: semantic search is and was a big topic, but so far even ChatGPT is not a real answer, Stable Diffusion is very nice if you want to produce some cartoon alike graphics or some porn deepfakes, but just not ready for simple common photo editing tasks. OCRs have gotten better, but still nothing that "by magic" makes a badly scanned piece of paper into an almost-native clean pdf and so one.

Yes, there is much progress and potential, but not much for real world usages.

I hate to point this out but as a regular user, recommendation engines and search have not gotten better in the last, say, 10 years. (Although that may not be true in terms of selling advertising and propaganda, both of which I tend not to pay a lot of attention to.)

Likewise, speech to text and language translation are more available, but they're still pretty bad. And computer vision is much better than 10 years ago, but I wouldn't bet anyone's life on it.

And yet, the hype train is still gaining momentum. Having been through more than my share of AI winters, I can feel another one coming and it's going to be bad.

I agree with you, but I started predicting an AI winter in like 2016. I thought the failure of self driving would kill it, but apparently not.

I've predicted 9 of the last 1 AI winters.

I'm not necessarily arguing that they're the same, but let's be honest with ourselves - crypto said the _same_ things as it was ramping up. Just replace all the applications of AI you listed with the many hypothetical use-cases crypto-pushers were listing out.

As always, sounds cool. Actually do some of it and then let's talk more.

Crypto pushers pushed two contradictory messages: 1. hodl, don't sell, don't spend! 2. Try to replace fiat with crypto in your life!

No wonder that its adoption for legal purposes didn't go anywhere.

Saving more than spending has also been popular advice for fiat, at times. More for medium/long-term personal purposes at the expense of immediate macro purposes, but I think that applies to both systems.

Central banks inflate their currencies on purpose to discourage hodling. Short term savings for emergencies are good. But by hodling fiat long term - you are just losing money.

Cryptobros thought that they are smarter than central banks and didn't bother to implement proper monetary policy in the Bitcoin protocol to prevent its volatility.

> But by hodling fiat long term - you are just losing money.

Real interest rates are typically positive, so no, you are not.

The concept of hodling fiat could mean cash under the mattress or could mean an interest-bearing account. It's ambiguous.

“Proper monetary policy”

Want to elaborate? Bitcoins monetary policy is beautiful in its simplicity and predictability. In that sense, it stands in stark contrast to fiat.

A proper monetary policy would ensure price stability and predictable inflation. Bitcoin price has been all over the place, and its volatility makes it both a bad investment and a bad currency.

Bitcoin is priced in fiat which is itself volatile. Bitcoin must detach from fiat to gain true stability.

You're conflating the wallstreetbets crowd with the crypto crowd who are kinda polar opposites.

Some of the applications crypto folks were going on about: decentralization (of course) until the IRS started taxing your crypto transactions; helping 3rd world countries with weak currencies (partially happened); international trade (quickly became untrue and monitored by government agencies), ledgers for tech companies (they can all already build audit trails. i've yet to see many applications where companies are willing to give up control over their trust to a 3rd party system with no scrubbing functionality. looking at you, AWS status page).

Like I said, same vibe, different applications. Until some are built it's all just hype and conjecture. The applications we've seen work well are already well-accepted for their faults (content generation, summarization, etc)

Its adoption is growing every day. Read up on bitcoin lightning network growth.

The thing is that the specific technologies behind all of those very practical improvements are not what's being hyped up this bubble. Speech recognition, for example, usually involves a lot of audio preprocessing, followed by some form of RNN/LSTM/Transformer to generate candidates, followed by beam search to score and choose from candidates.

If you are a machine-learning practitioner, you should be familiar with all of those techniques and how they are used so that you can solve practical problems with them. But if you just read about AI in the news and figure you're going to found the next great startup and make a billion off it, you'll probably start by feeding a whole bunch of data into Tensorflow and then getting useless garbage out of it.

This hype bubble is specifically about LLMs, extremely large-parameter transformers that are trained on all the data OpenAI or Google can get their hands on. And then supposedly if you ask them the right questions, you will get useful answers back. For people that put in the time and experimentation to actually find the right questions and the right applications, that will probably be true - but the hype is that this will change everything, and it most certainly will not, just in the same way that beam search is frequently useful but it definitely does not change everything.

But slick promoters will nevertheless manage to use people's lack of knowledge to redirect billions of dollars in capital into their and their employees' pockets, the same way that slick promoters used crypto to redirect billions of dollars in capital into their and their employees' pockets.

You're so so so right! Things practical in AI is not hyped.

OpenAI which is funded by Microsoft and promoted by Microsoft account executives creates hype as if it's open although nothing, including its so-called open-source Whisper, is open. People feeding Microsoft pretend that "they" are revolutionizing the world. NVIDIA and Microsoft are making money out of these large models and positioning the bigger as the better.

The thing is, it's perfectly possible for something to possess hybrid qualities.

In the case of AI: both potentially quite useful (unlike crypto) and incredibly, toxically overhyped (just like crypto).

Ironically, the fact that a lot of people think "You it's actually kind of useful sometimes, therefore you can't compare it crypto/web3" is part of the engine that drives the hype.

Agreed, and when people seem to simply correlate them on no other quality than being widely observed in popular culture they lose me entirely.

The tech religious overhype train is here to stay. There has never been a more established need for calm honesty.

> Crypto never amounted to anything beyond a currency for black market transaction

Do you understand what a massive impact that has been? It has disrupted one of the largest industries on the planet, which is drug trafficking.

Did it disrupt the whole industry? Only the payment part of it, no?

Well no because the dark markets enabled any small dealer to sell worldwide.

With crypto people can buy drugs anonymously. You couldn't do that before.

I mean... sure, it outcompeted Tide detergent. But the illegal drug trade has historically used all kinds of currencies. I'd say "disrupted" is hugely overstating the case.

If you looked at Donald Trump Jr's runny nose and "impassioned" behavior, you wouldn't think that.

"Cocaine News" with Donald Trump Jr. | The Daily Show:

https://www.youtube.com/watch?v=47yFRXZqB0g

Don Jr. Swears He’s Not on Coke—He’s Just ‘Impassioned’:

https://www.thedailybeast.com/donald-trump-jr-is-tired-of-co...

So what fraction of all drugs are now paid for with cryptocurrency at retail? Over 50%? 25%? Presumably you must know the figure, if you're asserting the industry has been disrupted.

You are at liberty to believe what pleases you the most. If you're interested in finding the truth, you'll have to first understand that drug markets are underground, which means you will not find any verified accounting. The UN estimated [1] in 2020 the size of the darknet drug trade to about $315 million per year or at most $725 million per year - which is nothing compared to the overall drug trade, but disruptive for certain categories of drugs that are easily sent by mail.

People are buying drugs on the darknet, who would never buy it on the streets or want to be associated with regular drug users.

[1] https://www.unodc.org/res/wdr2021/field/WDR21_Booklet_2.pdf

Financial services is the biggest industry on the planet but as soon as crypto is involved “a vehicle for speculation“ is invalid

So speaking of echo chambers…

It's not as clear cut really.

Overall economic productivity didn't shoot up in the last decade despite the dramatic progress we had in software and hardware (e.g. [1]), and it's not clear that AI/ML will dramatically change that. Yes searching pictures on my iphone by text is convenient and Netflix recommendations might be more addictive, but the path from that to ubiquitous economic prosperity, safety, and comfort (the technoutopia many here are striving for) is not clear at all. It's also not very clear if those marginal improvements are worth the substantial share of total human brainpower thrown at them.

[1] https://www.aei.org/economics/good-news-bad-news-on-us-produ...

And a tool to resist inflation and protect assets against theft, bank closures or government raids in countries where people are just barely surviving. You have a pretty Anglocentric viewpoint.

So, you're pretty much saying:

    AI is just like crypto, but better!

Not sure that's reaaaaaaaaaally going to bring people around.

What an asinine thing to say and it exhibits your lack of willingness or ability or willingness to understand both AI and cryptocurrency.

> Comparisons between AI and crypto are horribly misguided IMO.

Nope. The hype around AI by the AI bros is totally similar with the crypto bros back then.

> AI/ML is creating utility everywhere in our lives - speech to text, language translation, recommendation engines, relevancy ranking in search, computer vision...

Yet I guarantee that you don't trust any of their outputs for any serious applications and you need to constantly check for it's reliability since its output is often wrong, inaccurate or even outright nonsense. You don't trust it yourself, which that is the problem of this entire hype cycle.

On top that, it is all at the expense of the planet getting incinerated with no efficient alternatives to counter the amount of extreme waste of resources that these systems are consuming. [1] [2]

> Crypto never amounted to anything beyond a currency for black market transaction, a vehicle for speculation, and a platform for creating financial scams.

'never'

So Moneygram, Stripe, Checkout.com, etc using it is 'never amounted to anything'? If it was only for financial scams, all of them would have stopped using it a long time ago.

They simply didn't because financial scams on a transparent public ledger is a scammers nightmare and sounds like a very poor platform for creating financial scams.

But maybe you need to look outside of the AI bubble and see the trillions of dollars in which the banks have allowed in actual black market transactions by criminals in the FinCEN files [0] which is nothing compared to crypto.

[0] https://www.standard.co.uk/tech/ai-chatgpt-water-usage-envir...

[1] https://www.nytimes.com/2020/09/20/business/fincen-banks-sus...

[2] https://gizmodo.com/chatgpt-ai-water-185000-gallons-training...

AI will end up as Clippy 2.0 just as Crypto ended up as an overly secure payment processing platform.

I can evade taxes and government surveillance using crypto. That's value added for me.

>recommendation engines, relevancy ranking in search

Both don't seem to work.

> Is AI overhyped?

calling something "hype" should not be a stand-in for data

Bitcoin has the potential to become the world’s reserve currency. Your smug dismissal of it is ignorant at best.

Consider how power structures (eg nation states) may change in such a future.

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