Google still thinks of AI as a research project, or at best a way to produce better search results. They essentially created the entire current generation of the AI space and then... gave it away, because no one on the product side understood what they had actually built. Handing the reins to the DeepMind team – who have never launched a single product in their history – seems to be a doubling down on that same failed strategy.

Google doesn't need more smart AI researchers, academics or ethicists. They need product managers who understand the underlying technology and can commercialize it. They need pragmatic engineers who can execute, launch and maintain services. That has always been their problem as a company.

I was at the non-Brain part of Research and it was seen as Google Brain is the "cool", pure research one, dealing with some future abstract AI and not caring for the products, feasibility, or even if the research "could" be made practical any day.

Deepmind was an "extreme" version of it, with some animosities and politics between the two, which I didn't follow too closely. There were attempts at making Deepmind useful, called "Deepmind for Google", but the people there were... clueless. Though one really cool thing came out of it (XManager).

(I was at a closer to the product part, "Perception", which I loved. And still got to publish, explore, pursue my own research goals, etc.)

I was next to the team that created Allo’s chat bot, but they said that they had to take out most cool stuff because legal didn’t allow it to launch, so they had to dumb it down totally.

I believe the main problem was all the ethics/safety teams that just hired a lot of non-programmers, while OpenAI management treated safety as an engineering problem that has to be solved with a technical solution.

This is one of startups greatest advantages over established players.

Google didn't even bother despite having all the tech in place.

and i can't believe I'm saying this but it seems microsoft has the ability to at least deliver innovation.

iPhone scared the shit out of the phone market and today we have great phones from Samsung and Google which dominate the market. If everyone was trying to predict the smartphone market in 2007 they'd be talking about how Nokia missed the boat but excited to see their response (or Motorola/Sony/Blackberry etc). The market today won't necessarily be the market in 10yrs from now. It might be Google, they have a solid head start to be #2 and future #1, but who knows what will happen and whether that talent/advantage stays in Google.

It could just as easily be other companies we don't even consider serious players today.

Here is the top hit: https://worldpopulationreview.com/country-rankings/iphone-ma...

What is wild to me: This is a single company. Android has a huge number of makers.

One of the things I do respect Google for is providing services to poor people, but that doesn’t mean it’s a business advantage.

If you offered me control of the entire Android ecosystem or just Apples iPhone business I’d not even blink to take Apple.

I don’t know how true these things were. Did anyone else get this perception?

(I was on the XManager team in Platform.)

Internally, everyone's asking "How will this help my promo packet?"

And never got off the pre-web walled garden end-to-end business model, despite connecting to the web, and died because of it. Not exactly the best example to use to argue Microsoft missed the boat on Web-era online services.

Yes Ballmer threw everything away and IE, Hotmail, MSN Messenger, Skype and MSNBC are jokes now, but that doesn’t mean they weren’t dominant force in Bill Gates era.

At least we got Xbox and Xbox live… which seems to have barely lived by a life line. Confusing mess with Xbox vs windows vs media center PC.

I still think they could have been much more successful with the kinetic. Wii was loved for its ability to bowl and play tennis and etc. Nobody I know really wants to strap a sensory deprivation device onto their face. I don’t see VR working out but a highly evolved sensor bar that allows you to interact with humans physically present and online seems an easier pill to swallow. Never owned one but seems like Kinect is still fondly remembered in some applications.

All that said I wouldn't buy one today because I don’t need x amount of cameras and lidars and y microphones recording inside my house 24/7 and going to MSFT and whoever else.

No, it isn’t. IE, Microsoft Internet Start (Microsoft’s original web portal), and MSN (originally a separate subscription-based dialup online service that later merged with the main portal) all launched simultaneously in August 1995.

And yet here we are. If anything it’s a great example of how a “money printer” business, Google’s ad business, makes an org into a lazy, risk averse and accumulates an army of empire builders who collectively breed promo culture.

Combine that with a decade of 0% interest rates which also boosted its stock price and it’s no wonder that Google is struggling on so many fronts.

CopilotX with its OpenAI collab will be the real winner - if it ever gets released to those on the waitlist. I’m not aware of anyone who got in yet, which leads me to believe it doesn’t yet exist.

CopilotX is not a paradigm shift, it's a version change from GPT-3 to GPT-4.

I don’t know about you, but Copilot is part of my daily work, while OpenAI ChatGPT is still more or less a toy to me.

Say Copilot makes an engineer 2x as productive, their all-in salary is $500k to make the math easy, 1,000 MS sw engineers are using it, and Copilot took $5mm to train (GPT-3 took $4.6mm). Those 1k MS employees now being twice as productive are doing the work of an extra 1k people at $500k, or $500 million's worth in a year. That means $5 million in Copilot training costs are paid for in... 4 days. I have no inside information, so those number are all made up, but I'm pretty sure the initial training costs have already been paid off internally.

We also don't know how many multiples of $5mm it took to produce the initial version of Copilot, nor how many subsequent training runs there have been.

Point is, any significant productivity gains made, across an organization the size of Microsoft engineering, easily pays for big expensive training runs.

The nice effect is that the AI makes people more confident to try things and go out of their comfort zone. Maybe the quality of the end product will be higher.

And as for the big multi-billion investment in OpenAI, they may have more than made that back up on their valuation already. Plus the deal was structured that OpenAI would pay it's revenues into Microsoft till the investment was paid back and MS would sill end up with a 49% stake.

All in all, sounds like a smart investment from MS and, cerry on top, managed to majorly embarrass a main rival.

ChatGPT is also one of the fastest growing consumer products in history by number of users. At $20 a month for plus, it could be a significant revenue stream.

Then add all the companies like Duolingo and Snapchat that are using GPT as well.

If you don’t see this as explosive growth, then I don’t know what to tell you.

Why?

edit: order of magnitude was wrong on costs per day.

You are talking about a revolutionary product that literally dominates mindshare from consumers to students to CEOs to governments. Its a pure monopoly that has insanely wide utility and instantly obvious value proposition.

It doesn't matter how revolutionary GPT-4 is, people's willingness to pay for anything is generally very low. ChatGPT premium is also a very expensive subscription for a consumer product!

At the very minimum, I can already see every university and high school student paying for GPT-4. Its a way way way more powerful essay writer and personal tutor than GPT3.5, that alone is incentive to upgrade. For only $20 a month.

Know what GPT-4 currently is insanely capacity limited. So far, the limitation is not on the demand side, but the supply side.

Getting 100 million users in 3 months with 0 marketing or network effects already annihilates existing records, getting 10% conversion is nothing special.

https://twitter.com/visakanv/status/1113154447050334208

Reference?

"Profitable" means they're making more money than they're using, at this moment.

Profit has a strict definition of $revenue - $cost, for a business operation as a whole, which leaves money in the bank at the end of the month.

They could be making more money for a single query than the cost of compute time for that single query, but that may not cover the engineering and idle servers. They could be running at a loss with the assumption that they can improve efficiency per transaction soon. They could be running at a "loss" because they're giving some of the compute away for free right now, to improve the training with the user responses. Or maybe they are making fistfuls of money. "Profitable" has a strict meaning, shouldn't be assumed, and definitely isn't required, at this point in their operation.

I'm very interested to know if they are profitable, at the moment, but I don't think that's been publicly disclosed yet, and I can't find anything. A reference is required.

Very reasonable assumptions. You will never get certainty, even if they say they're profitable maybe they're just lying for investors. If you see their bank account total go up every month maybe it's a ponzi scheme.

For my heuristics, if not profitable, at least close, and definitely a major success in acquiring market share and customer mind share.

If you want to claim the latter as evidence then fair enough, I would call it speculation.

In either case there is no need to resort to petty insults.

They’ll figure it out.

I wouldn't underestimate the degree to which this is by design, from the very top of Google. Different Google and other Alphabet companies' executives more than once told me they just weren't interested in products that didn't have an obvious path to more than 1 billion users. The companies don't have a clue how to make money retail. If they can't print money with an idea, they don't have the tools and skills to bring it to market.

You’re right; my statement is not scientifically accurate

I fear the only thing you can do is to start a new company. But maybe there's a way to better align the incentives...

They literally put more effort and resources into rigging ads auctions than trying to solve real user problems.

Yes, the answer isn't what you'd like, but let's not pretend it's not rational.

How do you make enterprise tools better? (Photoshop + AI, Code + AI etc.) How do you make consumer tools better? (YT tools + AI) How do you make search better?

etc. etc.

Not the job description Google has for engineers. Their hiring process effectively eliminates anyone who matches that description and bothers to put themselves through it.

They don't pay me, so I don't care about their profits, but the stuff they've more-or-less given away and people don't think much about is their best stuff. Colab, Docs, Scholar, etc...

Google's revenue is equal to the GDP of New Zealand. Google's cash reserves are sufficient to sustain the company through half a century of bad quarters. Not that they have had any bad quarters, ever.

They don't need anything.

Their ad business is a donkey that shits gold, with Chrome and Android keeping the competition locked out, and everything else doesn't matter for Google as a company. They've done little more than play around for the last decade, with an endless procession of hyped-then-canceled "products", and it hasn't affected their market dominance in the slightest.

They can keep fucking up for the foreseeable future, and it won't really matter. If a startup emerges that appears to have the right approach to AI, Google can simply buy it. Power is power, and everything else is nothing.

I already use phind.com almost as much as I use Google. A significant percentage of the non-development "queries" that I have, I now ask ChatGPT 4.

I'm starting to suspect that within a year, I won't be using Google search much at all.

That should terrify everyone at Alphabet Inc.

This isn't even remotely comparable to the AltaVista situation. Google has a planet-scale stranglehold on how half the world's population accesses information. This arguably makes Google more powerful than most nation states. I can guarantee they won't be dislodged by some search startup with a cool idea.

…currently.

I think OP’s point is that once some better product comes out and e.g. normal people hear about it on tiktok and start switching, it doesn’t seem like Google is institutionally capable of competing. Honestly, considering how much good research they put out, I really hope they don’t.

They don't have to compete. They can just buy any startup that's a potential threat to them, or lobby for laws that would effectively make them illegal. That's what power is, and it's all that matters.

Every untouchable business inevitably gets disrupted once the company can no longer stay competitive and get ahead of new trends. Same is happening with Google today.

So was Lotus Notes.

Scrolling through search results to answer a question manually instead of simply getting an answer feels like using the Internet from 20 years ago.

Google is one of the most powerful entities in the history of mankind, with read/write access to the private information of the majority of humans alive.

The two aren't comparable. Indeed, there are few entities that are comparable to Google. Google won't use their technological edge to keep potential competitors out, they'll use their financial, social, and political power.

The company hasn’t released the significant product in 15 years, despite the huge amount of money they have this will be not be enough to change the culture.

I would say they more need engineers who care about and can make good products. In my limited experience, it takes time to turn a research-focused group into a product-oriented team. Research vs production requires different skill sets.

It’s curious how predictable it is that a major player is going to fall into this trap at any point in time. There’s probably some way you could measure its likelihood if you were tracking internal comms, org charts and maybe some finely designed survey data.

and more because Google's mission was to "organize world information" instead of understanding, intepreting & utilizing world information.

https://www.google.com/search/howsearchworks/our-approach/

Research is great, but when there’s no platform, nothing stands.

Among some of the biggest flop in history by starting so late.

We’ll have to see how their generative text to videos do.

- This does not seem unexpected. Google is panicked about losing the AI race and pushing resources into DeepMind is a logical step to mitigating those fears.

- Google has currently given ~300M to Anthropic and has a partnership with them. I assume Google continues to see potential in both avenues and won't neglect one AI team for the other. I'm guessing that DeepMind will be their primary focus because of the numerous, real-world applications already at play.

- It's tough for me to compare Google DeepMind to OpenAI GPT4. They seem to be very different approaches. Yet, they both have support for language and imagery. So, perhaps they aren't that different afterall?

- Still waiting to hear more from Google on how they plan to leverage their novel PaLM architecture. The API for it was released a month ago, but, to my awareness, has yet to take the world by storm. (Q: Bard isn't powered by PaLM, right?)

Overall, I am not convinced this will be massively beneficial. I don't trust Google's ability to execute at scale in this area. I trust DeepMind's team and I trust Google's research teams, but Google's ability to execute and take products to market has been quite weak thus far. My gut says this action will hamstring DeepMind in bureaucracy.

Yes the team which literally created transformer and almost all the important open research including Bert, T5, imagen, RLHF, ViT don't have the ability to execute on AI /s. Tell me one innovation OpenAI bought into the field. They are good at execution but i havent seen anything novel coming out of them.

This, but non-sarcastically. Google has spectacularly, so far, failed to execute on products (even of the “selling shovels” kind, much less end-user products) for generative AI, despite both having lots of consumer products to which it is naturally adaptable and a lot of the fundamental research work in generative AI.

The best explanation is that they actually are, institutionally and structurally, bad at execution in this domain, because they have all the pieces and incentives that rule out most of the other potential explanations for that.

> OpenAI bought into the field. They are good at execution but i havent seen anything novel coming out of them.

Right, OpenAI is good at execution (at least, when it comes to selling-shovels tools, I don’t see a lot of evidence beyond that yet), whereas Google is, to all current evidence, not good at execution in this space.

Then somebody else reads the papers, decides to execute on it, and hires all the researchers who are frustrated at discovering all this cool stuff but never seeing it launch.

It seems like that's what they were doing with DeepMind for the last decade. But it's also possible DeepMind as an institution lacked the pressure/product sense/leadership to produce consumable products/services. Maybe their instincts were more centered around R&D and being isolated left them somewhat directionless?

So now that AI suddenly really matters as a business, not just some indefinite future potential, Google wants to bring them inside.

They could have created a 3rd entity, their own version of OpenAI, combining DeepMind with some Google management/teams and other acquisitions and spinning it off semi-independently. But this play basically has to be from Google itself for their own reputation's sake - maybe not for practicality's sake but politically/image-wise.

Being hungry and scrappy seems to be a necessary precondition for bringing innovative products to market. If you don't naturally come from hungry & scrappy conditions (eg. Gates, Zuckerburg, Bezos, PG), being in an environment where you're surrounded by hungry & scrappy people seems to be necessary.

For that matter, a number of extremely well-resourced startups (eg Color, Juicero, WebVan, Secret, Pets.com, Theranos, WeWork) have failed in spectacular ways. Being well-resourced seems to be an anti-success criteria even for independent companies.

I survived ALL the layoffs somehow. Boots on the ground agrees with "doesn't really work all that well" but the people collecting rents keep collecting. Given the size all of these received significant DOJ reviews though the only detail I remember is basketball sized court rooms filled with printed paper for the depositions. I'm sure they burned down the Amazon to print all that legalese, speaking of scaling problems.

i'm thinking:

- Lotus

- Macromedia

- CA

edit: i take it all back! my memory is not as good as i thought it was re: software companies. i will leave up my sorry list as penance for my crappy recent tech history skills.

Indeed, you are right on: Legent, Platinum, CA, and Broadcom in order from little fish to big. CA was the second largest software company in the world behind Microsoft then.

The weird part you couldn't see from this telling is that I worked in the Legent office in Pittsburgh, moved to Boston post-CA acquisition and worked in the CA office in Andover. Resigned and went to Platinum in Burlington. Moved to Seattle. Second CA acquisition in 5 years. I should have quit while I was ahead. Moved back to Pittsburgh. Worked in the exact same office I'd worked in 5 years earlier with the same crew. Weird feeling is a mild understatement. I still know people who work for Broadcom now. I should reach out.

i used to read BYTE mag over in the UK in the early 90s before i moved to USA; CA was such a heavy hitter in the early 90s!! i guess it never really was the same in the post-Wang era(s).

Digital (DEC) had no substantial connection with Western Digital; see https://en.wikipedia.org/wiki/Western_Digital#History

[1] https://www.computerhistory.org/collections/catalog/10275038...

Cisco has done a great job balancing this, actually - they keep contact with engineers who leave to do startups, and then acquire their companies if they become successful enough to prove the product.

Getting a X-million-per-year budget from a parent company gives you a very different sort of situation. IME this results in less urge to get something out the door and more urge to get "the best thing" built. Shipping early risks your budget in a way that "look at all this cool theoretical progress" doesn't, because the public and press can critique you more directly.

It seems like this is more a Google problem than a DeepMind problem though, no? Google created one of the most successful R&D labs for ML/AI research the world has ever known, then failed to have their other business units capitalize on that success. OpenAI observed this gap and swooped in to profit off all of their research outputs (with backing from Microsoft).

IMO what they’re doing here is doubling down on their mistakes: instead of disciplining their other business units for failing to take advantage of this research, they’re forcing their most productive research team to assume responsibility and correct for those failures. I expect this will go about as well as any other instance of subjecting a bunch of research scientists to internal political struggles and market discipline, i.e. very poorly.

Is this really the solution? Is there an example of a company that escaped its fate with this tactic?

I think this is what Christensen and Schumpeter suggest, but I don’t think it works.

Maybe the closest is Microsoft, but they didn’t do this. They changed their revenue model by emulating AWS.

They're also paying for their product managers' cancellation culture. (Sorry.) I'm seeing a lot of AI pitch decks; none suggest trusting Google. That saps not only network effects, but what ill term earned research: work done by others on your product. Google pays for all its research and promotion. OpenAI does not.

I thought OpenAI’s unique advantage over many big tech companies is that they’ve somehow figured out how to fast track research into product, or have researchers much more willing to worry about “production”.

I saw quotes from independent scientists referring to it as the greatest breakthrough of their lifetime, and I saw similarly strong language used in regard to the potential for good of alpha fold as a product.

So they gave it away, but it is still a product they followed through on and continue to.

Was it wrong of them that they gave it away, and right, that Microsoft’s primary intent with their open AI technology, seems to be to provoke an arms race with google?

And if it isn't? Literally every single argument I've seen towards this being AGI is "We don't know at all how intelligence works, so let's say that this is it!!!!!"

> nowhere near the game changer ChatGPT(4) is, even if ChatGPT was only available for the subset of scientists that benefit from Alpha Fold

This is utter nonsense. For anyone who actually knows a field, ChatGPT generates unhelpful, plausible-looking nonsense. Conferences are putting up ChatGPT answers about their fields to laugh at because of how misleadingly wrong they are.

This is absolutely okay, because it can be a useful tool without being the singularity. I'd sure that in a couple of years time, most of what ChatGPT achieves will be in line with most of the tech industry advances in the past decade - pushing the bottom out of the labor market and actively making the lives of the poorest worse in order to line their own pockets.

I really wish people would stop projecting hopes and wishes on top of breathless marketing.

I asked GPT-4 to give me a POSIX compliant C port of dirbuster. It spit one out with instructions for compiling it.

I asked it to make it more aggressive at scanning and it updated it to be multi-threaded.

I asked it for a word list, and it gave me the git command to clone one from GitHub and the command to compile the program and run the output with the word list.

I then told it that the HTTP service I was scanning always returned 200 status=ok instead of a 404 and asked it for a patch file. It generated that and gave me the instructions for applying it to the program.

There was a bug I had to fix: word lists aren’t prefixed with /. Other than that one character fix, GPT-4 wrote a C program that used an open source word list to scan the HTTP service running on the television in my living room for routes, and found the /pong route.

This week it’s written 100% of the API code that takes a CRUD based REST API and maps it to and from SQL queries for me on a cloudflare worker. I give it the method signature and the problem statement, it gives me the code, and I copy and paste.

If you’re laughing this thing off as generating unhelpful nonsense you’re going to get blind sided in the next few years as GPT gets wired into the workflows at every layer of your stack.

> pushing the bottom out of the labor market and actively making the lives of the poorest worse in order to line their own pockets.

I’m in a BNI group and a majority of these blue collar workers have very little to worry about with GPT right now. Until Boston Dynamics gets its stuff together and the robots can do drywalling and plumbing, I’m not sure I agree with your take. This isn’t coming for the “poorest” among us. This is coming for the middle class. From brand consultants and accountants to software engineers and advertisers.

Software engineers with GPT are about to replace software engineers without GPT. Accountants with GPT are about to replace accountants without GPT.

> Literally every single argument I've seen towards this being AGI is

Here is one: it can simultaneously pass the bar exam, port dirbuster to POSIX compliant C, give me a list of competing brands for conducting a market analysis, get into deep philosophical debates, and help me file my taxes.

It can do all of this simultaneously. I can't find a human capable of the simultaneous breadth and depth of intelligence that ChatGPT exhibits. You can find someone in the upper 90th percentile of any profession and show that they can out compete GPT4. But you can't take that same person and ask them to out compete someone in the bottom 50th percentile of 4 other fields with much success.

Artificial = machine, check. Intelligence = exhibits Nth percentile intelligence in a single field, check General = exhibits Nth percentile intelligence in more than one field, check

This is AGI, now we are nit-picking. It's here.

This extreme difficulty in discerning what it hallucinates and what is "true" is what it's most obvious problem is. I guess it can be fixed somehow but right now it has to be heavily fact-checked manually.

It does this for computing questions as well, but there is some selection bias so people tend to post the success-stories and not the fails. However it's less dangerous if it's in computing as you'll notice it immediately so maybe require less manual labour to keep it in check.

Hahaha, if you want nit-picking, all the language tasks chatGPT is good at are strictly human tasks. Not general tasks. Human tasks are all related to keeping humans alive and making more of us, they don't span the whole spectrum of possible tasks where intelligence could exist.

Of course inside language tasks it is as general as can be, yet still needs to be placed inside a more complex system with tools to improve accuracy, LLM alone is like brain alone - not that great at everything.

I have a feeling they had access to a lot of code on GH, who knows how much code they actually accessed. Copilot for a long time said it would use your code as training data, including context, if you didn’t opt out explicitly, so that’s already millions maybe hundreds of millions of lines of code scraped.

The conspiracy theorist in me wonders if MS just didn’t provide access to public and private code to train on, they wouldn’t have even told Open AI, just said, “here’s some nice data”, it’s all secret and we can’t see the models inputs so I’ll leave it at that. I mean they’ve obviously prepared the data for copilot, so it was there waiting to be trained on.

So yeah I feel your enthusiasm but if you think about it a little more, or maybe not so hard to imagine what you saw being actually rather simple ? Every time I write code I feel kind of depressed because I know almost certainly someone has already written the same thing and that it’s sitting in GitHub or somewhere else and I’m wasting my time.

ChatGPT just takes away the knowing where to find something (it’s already seen almost everything the average person can think of) you want and gives it to you directly. Have you never thought of this already ? Like you knew all the code you wanted already was there somewhere, but you just didn’t have an interface to get to it? I’ve thought about this for quite a while and I knew there would big data people doing experiments who could see that probably 80-90% of code on GitHub is pretty much identical.

Nothing is magic, right ?

Okay, now try being a scientist in a scientific field that isn't basic coding.

It's not people laughing at pretences, it's people who know even basic facts about their field literally looking at the output today and finding it deeply, fundamentally incorrect.

I wonder what your personal success rate would be if we did a Turing test with the “people” who “know basic facts about their field.” If they sat at a computer and asked you all these questions, would you get them right? Or would you end up in slide decks being held up as a reason why misnome doesn’t qualify as AGI?

I find comfort in knowing that it can’t “do science.” There is a massive amount of stuff it can do. I’m hopeful there will be stuff left for humans.

Maybe we’ll all be scientists in 10 years and I won’t have to waste my life on all this “basic coding” stuff.

Absolutely not! I created a powershell script for converting one ASM label format to another for retro game development and i used ChatGPT to write it. Now, it fumbled some of the basic program logic, however, it absolutely nailed all of the specific regex and obtuse powershell commands that i needed and that i merely described to it in plain English.

It essentially aced the "hard parts" of the script and i was able to take what it generated and make it fit my needs perfectly with some minor tweaking. The end result was far cleaner and far beyond what i would have been able to write myself, all in a fraction of the time. This ain't no breathless marketing dude: this thing is the real deal.

ChatGPT is an extremely powerful tool and an absolute game changer for development. Just because it is imperfect and needs a bit of hand holding (which it may not soon), do not underestimate it, and do not discount the idea that it may become an absolute industry disrupter in the painfully near future. I'm excited ...and scared

It does, quite often. Not only that, as you describe. But it does.

For example, I asked it what my most cited paper is, and it made up a plausible-sounding but non-existent paper, along with fabricated Google Scholar citation counts. Totally unhelpful.

It also can produce very useful things.

If you're a robotresearcher, maybe try getting it to whip up some ...verilog circuits or something? I don't know much about your field or what you do specifically, but tasks like regular expressions or specific code syntax it is absolutely brilliant at, whatever the equivalent to that is in hardware. ...I've only ever replaced capacitors and wired some guitar pickups.

> it made up a plausible-sounding but non-existent paper, along with fabricated Google Scholar citation counts

I ran into a similar issue: I asked it for codebases of similar romhacks to a project i'm doing, and it provided made up Github repos with completely unrelated authors for romhacks that do actually exist: non-existent hyperlinks and everything.

Now, studying the difference in GPT generations, it seems like more horsepower and more data solves alot of GPT problems and produces emergent capabilities with the same or similar architecture and code. The current data points to this trend continuing. I find it both super exciting and super ...concerning.

You asked a machine learning model to tell you something about yourself that you already knew?

[1] - https://arxiv.org/abs/2303.12712

[2] - https://m.youtube.com/watch?v=qbIk7-JPB2c

This is not what any of the US economic stats have looked like in the last decade.

Especially since 2019, the poorest Americans are the only people whose incomes have gone up!

I use ChatGPT daily to generate code in multiple languages. Not only does it generate complex code, but it can explain it and improve it when prompted to do so. It's mind blowing.

>pushing the bottom out of the labor market and actively making the lives of the poorest worse in order to line their own pockets.

This makes zero sense. GPT4 has little effect on a janitor or truck driver. It doesn't pick fruit, or wash cars.

As far as I know, the exception to this is the bar exam, which GPT-4 can also pass, but that exam plays into GPT-4's strengths much more than other professional exams.

FWIW, this is more true for CA than most states.

Either it's a really obscure usage of the word or I got the president wrong.

Signed,

Guess Who"

That is not an instance of passing a standardized academic test through "autocompletion" or "regurgitation." It's rudimentary synthetic thought.

If it had named a different president, I could have argued with it, which is what I find especially interesting.

Making GPT sit it is like getting someone with no knowledge but a computer full of past questions and answers and a search button to sit the exam. It has metaphorical written it’s answers on it’s arm.

It knows a lot of stuff, but it can't do much thinking, so the minute your problem and its solution are far enough off the well-trodden path, its logic falls apart. Likewise, it's not especially good at math. It's great at understanding your question and replying with a good plain-english answer, but it's not actually thinking

It's able to define new concepts and new words. It's masters have gone to great lengths to prevent it from writing out particular types of judgements (eg https://sharegpt.com/c/uPztFv1). Hell, it's got a great imagination if you look at all the hallucinations it produces.

All of that sum up to many thinking-adjacent things, if not actual thinking! It all really hinges on your definition of thinking.

See GPT4's reply to pclmulqdq at https://news.ycombinator.com/item?id=35648144 .

That's not a response from someone who wrote the answers on the inside of their elbow before coming to class. That's genuine inductive reasoning at a level you wouldn't get from quite a few real, live human students. GPT4 is using its general knowledge to speculate on the answer to a specific question that has possibly never been asked before, certainly not in those particular words.

(Shrug) Exactly the same as with a human child.

Unlike a human child who tends to know when you are lying to them.

LOL. If that were true, it might have saved Fox News $800 million. Nobody would bother lying, either to children or to adults, if it didn't work as well as it does.

It isn't and nobody with any experience in the field believes this. This is the Alexa / IBM Watson syndrome all over again, people are obsessed with natural language because it's relatable and it grabs the attention of laypeople.

Protein folding is a major scientific breakthrough with big implications in biology. People pay attention to ChatGPT because it recites the constitution in pirate English.

I use chatGPT every day to solve real problems as if it’s my assistant, and most people with actual intelligence I know do as well. People with “experience in the field”, in my opinion can often get a case of sour grapes that they internalize and project with their seeming expertise and go blind to persist some sense of calm to avoid reality.

For example, it can describe concepts like risk neutral pricing and replication of derivatives but it cannot apply that logic to show how to replicate something non-trivial (i.e., not repeating well published things).

/s

Except its not, because they gave it away without any kind of commercialization. Its possible to give something away for free in some context and still have it be a product (Stable Diffusion is doing quite a bit of that, though its very unclear if they’ll be able to do it sustainably), but AlphaFold doesn’t seem to be an example. It seems to be an example of something cool they did that they had no desire to make into a product. Which is great! But isn’t the same as executing on product in a space.

Moreover, it has been quite some time since Google successfully developed and sustained a high-quality product without ultimately discontinuing it. The organizational structure at Google seems to inadvertently hinder the creation of exceptional products, exemplifying Conway's Law in practice.

Read more about this topic here: https://www.wsj.com/articles/google-ai-chatbot-bard-chatgpt-...

Android is the biggest OS in the world

Chrome is the biggest browser in the world

Gmail is the biggest email service in the world

YouTube is the biggest video platform in the world

Google is the biggest search engine in the world

Google is the biggest digital advertiser in the world

and I'm probably missing more things they're #1 in.

Not bad for a company that has "spectacularly failed to execute on products"

Here’s the whole thing (leaving out a parenthetical that isn’t important here):

“Google has spectacularly, so far, failed to execute on products […] for generative AI”

You listed a bunch of products in other domains, some of which are the reasons why it has institutional incentives not to push generative AI forward, even if it also stands to lose more if someone else wins in it.

The hardware costs alone of running something like GPT 3.5 for real time results is 6-7 figures a year. By the time you scale for user numbers and add redundancy... The infra needs to be doing useful work 24/7 to pay for itself.

It's more than possible Google knows exactly what it can do, but was waiting for it to be financially viable before acting on that. Meanwhile Microsoft has decided to throw money at it like no tomorrow - if they corner the market and it becomes financially viable before they lose that it could pay off. That is a major gamble...

That's 8 $200k GPUs + all the other hardware + power consumption for one instance. You could run it on cheaper hardware, but then you'll get to nowhere near realtime output which is required for the majority of the use cases not already handled well by much smaller models.

Even if Google/Microsoft are getting the hardware at a 50% reduction (bearing in mind these are already not consumer prices) it gets to $1mn in hardware alone - again for a single instance that can handle one user interacting with it at a time.

It makes a lot of the bespoke usecases people are getting excited about (i.e. anything with data privacy concerns) far from financially viable.

If you want a dedicated instance of full capability ChatGPT for example (32K content) OpenAI are charging $468k for a 3 month commitment / $1,584k for a year.

So under the assumption that 8 80GB gpus are required, we're talking about a somewhat more than $100k one time cost (for 8x 80gb A100 plus the host) plus power, not 6-7 figures annually. Huge difference!

Evaluating it in a latency limited regime but without enough workload to enable meaningful batching is truly a worst case. I admit that there are applications where you're stuck with that, but there are plenty that aren't.

Anyone in that regime should try to figure out how to get out of it. E.g. concurrently generating multiple completions can sometimes help you hide latency, at least to the extent that you're regenerating outputs because you were unhappy with the first sample.

> that can handle one user interacting with it at a time.

That bit I don't follow. The argument given there is without batching. You can do N samples concurrently at far less than N times the cost.

> OpenAI are charging

Ah the joys of having a monopoly!

edit: I forgot all about google_maps.zip / waze.gz and all the juicy traffic data coming from android.. which probably already relies heavily on AI

To be clear, Google does use AI. They use it so heavily that they've designed four generations of training accelerators. All the fancy knowledge graph features used to keep you from clicking anything on the SERP are powered by large language models. The only thing they didn't do is turn Google Search into a chatbot, at least not until Microsoft and OpenAI one-upped them and Google felt competitive pressure to build what they thought was garbage.

And yes, Google's customers share that belief. Remember that when Google Bard gets a fact about exoplanets wrong, it's a scandal. When Bing tries to gaslight its users into thinking that time stopped at the same time GPT-4's training did, it's funny. Bing can afford to make mistakes that Google can't, because nobody uses Bing if they want good search results. They use Bing if they can't be arsed to change the defaults[1].

[0] Or at least they did, then they fired the woman who wrote it

[1] And yes that is why Microsoft really pushes Bing and Edge hard in Windows.

Ethics is a false excuse because rushing that out show they never cared either. It was just PR and their bluff was called.

Also I skimmed over that Stochastic Paper and I’m unimpressed. I’m unfamiliar with the subject but many points seems unproven/political rather than scientific, with a fixation on training data instead of studying the emerging properties and many opinions notably regarding social activism, but maybe it was already discussed here on HN. Edit: found here: https://news.ycombinator.com/item?id=34382901

This +100 Somehow there is a perception that chat bots are the only example of AI research or product that matters and all AI organisations ability will be judged by their ability to create chatbots.

Sadly, I think I'd argue that nobody has good search results anymore. Google's results have been SEO'd to the hilt and most of the results are blog spam garbage nowadays.

No, they turned google search into what it is now.

For me, trying google bard was an instant reminder of the change in behavior in google search from 15 years ago to today.

We used to have a search that you could give obscure flags to Linux commands and find their documentation or source code. Today we have a google search that often only tell you about how some kardashian or recent political drama is a sounds-alike with the technical term that you were searching for.

GPT4 has some of the same "excessively smart" failure modes, but it (and GPT3.5 for that matter) is so much more useful than bard (which hits the user with "I can't do that dave" 100x more often than chatgpt's already excessive behavior) that they're a useful addition to the toolbox. Too bad the toolbox hardly includes plain search anymore.

Despite what people often write and believe here, the access controls on PII data at Google are incredibly strict. You can't just arbitrarily train on people's personal data. I know, because when I was there, working on search backend data mining, in order to get access to anonymized search and web logs, I had to sign paperwork that essentially said I'd be taken to the cleaners if I abused the access.

> What gives, Google? Get on it

It's a very difficult decision to intentionally destabilize the space you are the leader in, for all the reasons you can imagine. In a sense, Google needed someone else with nothing to lose to shake up the space. How they execute in the new reality is yet to be seen. The biggest challenge they may have right now isn't technological, but that "ChatGPT" has become a sort of brand, like Kleenex and well, Google.

Many markets had early leaders who got stomped by later entrants.

Microsoft and Google both have the capability and trust to make this available. When corporates start paying for LLMs, per user, or for applications, both Google and Microsoft and the two companies are in the best position.

All other industries will be users paying for LLMS model access.

I'd prioritize their problems like this:

1. LLM's don't have a lucrative business model that Google needs.

2. The quality of their language model is really lacking as of now.

You fix 1 and 2, ChatGPT's branding is nothing. Google is the biggest advertisement machine in the world and they can market the hell out of their product. Just see how Chrome gained ground on Firefox for example.

Google is still used several folds more than ChatGPT and if you resolve 1 and 2, Google will make their money and their users have no incentive to go to ChatGPT.

However, whatever's going on inside I still strongly believe in that company! Sometimes though it just feels like they don't themselves.

And yet Google is the largest online advertiser in the world. And yet, GMail used to (I don't know if it still does) push ads into people's inboxes.

I have as much belief in their PII controls as in their "Don't be evil" motto.

https://support.google.com/mail/answer/6603?hl=en

When you open Gmail, you'll see ads that were selected to show you the most useful and relevant ads. The process of selecting and showing personalized ads in Gmail is fully automated. These ads are shown to you based on your online activity while you're signed into Google. We will not scan or read your Gmail messages to show you ads.

...

To opt-out of the use of personal information for personalized Gmail ads, go to the Ads Settings page

--- end quote ---

They literally train their datasets on people's personal data.

OpenAI subverted this by riding on the “open” part of their name at first—before doing a 180-degree turn and selling out to Microsoft.

Receiving traffic to sites is nice, especially for already highly-ranked results, but these are not the people buying the ads.

Google could have built a search engine where paid results were indistinguishable from organic results, but the negative externalities of that were too great.

Google could have remained in China, but the negative externalities of developing and managing a censorship engine were too great.

Google could have productized AI before the risks were controlled, but they sacrificed revenue and first-mover advantage to be more responsible, and to protect their reputation.

This behavior is so rare, it's hard to think of another megacorp that would do that.

Google's far from perfect, they've made ethical lapses, which their competitors love to yell and scream about, but their competitors wouldn't hold up well under the same scrutiny.

Have you not used Google search in the past 5 years?

Now, when I search any even slightly remotely commercial search term on mobile, about the entire first page and a half of results are ads. Yes, they're identified with a "Sponsored" message, but as you can see from the "evolution" link the other commenter replied, this was obviously done to make the visual treatment between ads and organic results less clear.

The reason I'm thrilled about Google finally getting competition in their bread-and-butter is not because I want them to fail, but I want them to stop sucking so bad. For about the past 10 or so years Google has gotten so comfy with their monopoly position that the vast majority of their main search updates have been extremely hostile to both end users and their advertisers as Google continually demands more and more of "the Google tax" by pushing organic results down the page.

In the meantime I've switched to Bing, not because I think Microsoft is so much better, because I desperately want multiple search alternatives.

Edit: Great article from a couple years ago about how Google tried to make ads even more indistinguishable from organic results: https://www.theverge.com/tldr/2020/1/23/21078343/google-ad-d...

> ...

> In the meantime I've switched to Bing

Hilarious!

Here's Bing --> https://imgur.com/a/N3HCTtw

Here's Google --> https://imgur.com/a/bSJTBeD

Identical search terms.

Which ads look more like organic results?