Most of those folks (judging by my own friends) had very low expectations which ChatGPT blew out of the water. When they read "Microsoft search with ChatGPT" they are looking for integration of at least somewhat known quantity into a not so great (perception-wise) search. Win-win. If that bot stumbles in demo, no big deal. They already saw 100 examples, 95 good and 5 goofy; adding one to either bucket is not critical.
Google AI bot is an unknown quantity. Google search is (again, just perception wise) the leader in the search. When the bot stumbles it is a big red flag.
I really do not know why Google rushed it out instead of coming up with a friendly "hey, play with our toy first" approach. With this approach the bot can be iterated and made cool (hey, we can pair it with a stable diffusion-like painter for kids; or a lullaby composer; whaterver). Once cool, then it is "hey, you know, you can start leveraging it from the google search tomorrow". Screwups like this really make me think Google's rot is very broad. My 2c.
They have this. But it's internal. But with 200,000 employees, that's a plenty big enough pool of testers.
I'm not saying I'm ready to replace Google by ChatGPT or Bing AI. I'm saying this is a huge step in the right direction overall for human-computer interaction, and Google has been sleeping at the wheel for this one.
Google has a legacy moat but they aren’t the best by a noticeable amount anymore.
I have since moved to Ecosia a year or two ago as I found the results were very similar and have no issue with it.
Does make me sad the traffic page is gone: https://instruments.digital/duckduckgo-traffic-archive/
Currently they have a "caretaker CEO".
Google was sitting on a massive cash cow, so they appointed someone who would just keep it ticking over.
In the face of an existential threat, like ChatGPT, they need someone who can actually drive innovation. Not innovate themselves, nobody expects a CEO to do that, just create a culture which has a hope in hell of rising to fend off challenges to the empire.
They don't have this.
That have a CEO who is only capable in "good times" ... along with most of the company.
Faced with sufficient adversity, they will need a CEO who can succeed in the face of adversity.
This quote is 18 years old, and already by then it was established understanding that Google had extreme technical magic the rest of the world lacked. A rushed, bumbled tech demo in an area a company who for decades has invested billions in and widely enjoyed a perception of AI supremacy is a wildly different thing to a polished demo from a company nobody expects anything good to come from.
They have constantly encouraged the belief in their technical dominance in their marketing and hiring for as long as I can remember. If that's the perception externally, imagine how much more scathing a defeat it must feel to current employees.
We're still in that phase phase of both Tesla and Bing AI.
The goal posts also aren't "search" they're "AI enhanced search", let's not muddy the waters by moving them. Google may certainly be dominating in search, but they are clearly trying to sprint from miles behind in the latter.
I'll be their paying customer soon. It would be great if that meant I had privacy as well, but I kinda bleakly realize that that might be a bit of a pipe dream.
Remember how much trouble Microsoft got into for having a basic monopoly on desktops with Windows, and trying to bundle Internet Explorer? Replace Windows with Standard Google, and Internet Explorer with AI-based Google Search. You'll cut Google off at the knees with that move. And even if they survive the ~4-5 years litigation, they'll be severely hampered, kind of like how Microsoft was with the mobile phone market.
Another case of the browser doing what the OS and Desktop environment should be doing. I like to point at tabs - DEs and GUI toolkits never really came up with a good way to handle multiple documents well.
Widgets would be a potential solution but they keep being tried and abandoned soon after in desktop OSes.
In Mac Os one can use spotlight with cmd + space with similar results.
Or sometimes I check a calculator I implemented myself (shameless plug: https://getcalculator.app/)
Once again, compared to it just being there in front of you and ready to go that's still work to do to get it there.
You can do it all as one big expression with parentheses and such but if you're doing a bunch of calculations on the go that could get repetitive, and one wrong Esc and your calculation goes away.
There's still a calculator widget for the MacOS notification center. It's accessed in any app through a trackpad gesture or by clicking on the date/time in the menu bar.
The fact that it seems to be similar enough to the iOS implementation of them gives me hope, but only barely.
You also need to know the feature exists (they had notifications before widgets, people might not know it was updated to support them), that there exists a calculator widget, and to add it before you need to use it. That's the same discoverabiloty problem, with the added wrinkle that functionality changed in Monterey.
For most of the past decade. I believe widgets were added to Notification center in 2014.
Dashboard was first, and then they were reimagined as iOS-style in Monterey.
Read the comment thread you just replied to and tell me how any of what you just said is relevant to me correcting the sentence "Bing isn't dominating anything haha."
- Google's entire search engine has had many layers of "AI" powering it for years.
- Bing hasn't even released this supposed AI search engine to the public.
Your other example was Tesla and the two examples couldn't be more different. Your statement would be like someone saying Tesla was "dominating" electric cars before they ever even sold a single Roadster and had just posted a demo video. It's just wrong. I can be first to market with a banana that glows in the dark, am I in the club now too?
They may dominate if this exact form of conversational answers proves popular and if launched more than a hacked together demo and only then is some strong claim they are doing anything interesting could be worthwhile.
Until then they are kind-of first-but-actually-not-really in a kind-of-theoretical-market, and not dominating it all or reaping any first-mover advantage given their opponents are ready to follow on immediately.
The market exists. Products have been announced. Some are clearly more popular than others. I don't know why you care so much that Google beats Bing, but it's plainly obvious both from people's and Google's own reactions that Bing is currently considered the winner in the space.
Will it last? Maybe. Maybe not. The very thread you are replying to is that first movers ultimately fail. But it's plainly clear Bing has captured the first mover advantage in the space, whether you like it or not.
It could very well be that even a small chance of this happening can cause Microsoft to go all in on making Bing more AI. Being very expensive is the point.
See also: Star Wars, Itanium.
I think they'll ultimately have to open up the charging to get federal funding, but it'll be interesting to see what happens when they do. It's definitely a massive advantage right now.
The Model Y was the top selling model in Europe in December 2022. EV or ICE. https://www.forbes.com/sites/neilwinton/2022/12/07/model-y--...
It will probably make a bigger impact in the US. And the switch to a standard interface is holding up billions in federal funding so Tesla will probably eventually take the hit.
For example Amazon Kindle was not the first eReader. But its platform-ecosystem was years sooner than Barnes & Nobles Nook and Kindle won out.
Amazon itself is technically a "second mover" because there was an obscure online book shop before, but no one else from the established sales companies or Walmart could compete with them.
Tesla was not the first electric car. But it is arguably the first reaching a production of a million, so it is the first e-car from a "main" manufacturer?
In my life I've seen that happen a handful of times. When it does, it's usually due to (1) tragic management ineptitude over an extended period of time, or (2) fear of cannibalizing an existing profitable business (e.g.,: Kodak refusing to move from film to digital cameras, or the car industry being slow to re-invest away from ICE production.) I see no evidence (yet) that AI-enhanced search is going to threaten Google's core business of "displaying ads on relevant search results", so the main risk here is long-term management failure. Right now Google's management is doing everything it can to signal (to shareholders and partners) that they're going to throw every resource they have at the problem.
> better design, cheaper price, better range, better reliability
That doesn't mean the first mover advantage doesn't exist.
They are trapped by the decisions they made as first movers, while later incumbents have freedom to create improvements without worry about the installed base.
Apple is one company that never seemed to fall into that trap. They just tell the installed base “fuck you, buy the new thing” and somehow get away with it.
Apple comes in and innovates against something that existed but was user hostile.
It actually did happen to Apple over a long enough horizon, they cornered the paid digital music market by perfecting it, and upended it, and didn't innovate/upend again, and along came Spotify to upend it for them.
Microsoft Word came after WordPerfect. Chrome came after Netscape Communicator. Python came after Perl. Nintendo came after Atari.
I feel like first movers advantage is a myth.
Maybe. No company lives forever, at some point all of these things will be unseated. But those first movers had pretty good runs, as far as technology companies go. Maybe they aren't still #1 but if you're #1 for a decade or more, that might be as much as any one company can "win" here.
So their point stands. They have to be much better. And all of these were.
All of those products that came after are better than the first movers. If Apple was worse than BB, do you think it would have won?
Apple and specifically Jony Ive started the development of a handheld computer in the early 90s. Apple was definitely not a second comer to that market.
https://www.businessinsider.com/jony-ives-first-apple-design...
That's an odd way to define "not a second comer". The Apple Newton was a PDA, but it wasn't the first to hit the market.
Sure, it was in development before that, but that's true of every device that was released in that generation. And besides, "first mover advantage" doesn't refer to the first to begin research on a product; it refers to the first to release a product into the market.
It took more than a decade. They basically built out the features and waited until their competitors made some strategic mistake, of which they made several in that decade.
It was pretty much the same with Netscape and MSIE. That monopoly misuse probably helped, but Netscape also seemed bent on killing itself. Despite the mismanagement, it still took almost five years.
Perl was more popular than Python for more than a decade. Having much of the early web developed on it didn't help in the long run. First mover advantage might be a thing, but it never wins in the long run. And in the long run, ten years is nothing.
Microsoft Word was a loser, but then they changed out the operating system under the winners.
Word Perfect had the OS changed from under them but also had every warning that the change was coming and refused to move to sturdier ground.
It was pretty easy to write off Windows 3.1, and continue to be a solid solution on MS-DOS and with Netware, etc.
But Windows 95 had a lot of fanfare in advance that suggested it would have much better uptake. And Windows NT in parallel was developing a credible foundation, and it got the "new shell" as an option around the time of Win95. My recollection at the time was that the writing should've been on the wall, that Windows was going to be the Microsoft platform.
If WordPerfect was slow to move, that's a bad combination with, er, not as direct of access to the platform teams.
20 years later I'm still programming in Python.
I don't think there's any question that there is an advantage to being a first mover. What I think is a mistake is thinking that it's an absolute advantage, and/or not recognizing that it's also true that there are advantages to to not being the first mover. I mean, there's a reason why the "fast follower strategy"[1] exists as well.
I think in reality though, all of this is over-simplifying things. There are a LOT of variables in the equation for "does this product succeed or not" where "being first to market" is just one of those variables.
Similarly with Tesla
And pretty much all of them have better QC and a vaster maintenance network than Tesla (and in the E.U the charging network all use the same type of connector, so you are not tied to the manufacturer of your car).
But still, whenever you talk electric car, people often talk first about Tesla and they have no problem selling them. This might mostly be true in the E.U though. Also the model 3 is still priced fairly well being in-between the higher-end of the market and the intermediate.
Also, you don't really need to beat Tesla if you just want to make (and sell) electric cars. Tesla doesn't fill every niche and is nowhere near enough in terms of volume to satisfy the EV demand.
(If you want to be a bigger electric car company than Tesla then you have to beat Tesla, yeah -- that's a tautology, not an interesting observation tho).
*written by chatgpt
Google however came in with a different expectation. I remember something about one of their execs disparaging OpenAI over inaccuracies before. If you are going to sling mud, you had better make sure you don't have the same problem. Or it makes you look like a fool.
Then traditional search is going to become "raw index search" that you can query writing something like "intitle:"carbonara" source:"google_index"" or "give me all webpages containing carbonara in its title"
Really, you can believe me, outside Silicon Valley, nobody cares or cared about Juicero.
This is very different for ChatGPT, and I'm sure that if you get interested to it you'll find interesting usages with it that can fit your daily workflow (or just fun! like with image generation models).
One useful thing I learned from this, though, is that ChatGPT can handle Polish just fine. It never even occurred to me to try it - I incorrectly assumed the model was trained on English text only. I suspect that being multilingual from day 1 was a huge factor in ChatGPT's sudden and extreme user growth.
It just needs to be useful enough to dislodge the google monopoly.
People are lazy and are creatures of habit. Give them a single place to talk to ChatGPT and to search, they'll take it.
To put it another way: the main value proposition of using something like ChatGPT to navigate the internet is that you're putting your trust in it to filter out the noise on your behalf. If you can't trust it to actually do that (there's still ad noise in what you get back), then what's the point?
Either people will pay a subscription fee to unlock the utility of an information-distilling agent, or they won't. Trying to sidechain ad revenue into that equation is self-defeating.
Adding a chat front end is just going to lower the SNR, because ChatGPT has no idea what facts are or how to check them.
Unfortunately it's also the main attraction for corporate revenue generation. You can sell stuff conversationally. Woo hoo. These systems are going to turn into automated used car sales bots which use persuasion techniques to steer users towards a sale.
From the user POV the main attraction is the prospect of a kind of universal summarising WikiBot and bureaucratic paperwork automator.
Those are fundamentally different domains.
Users have been pretty relaxed about being manipulated and distracted by social media and covert PR/sales/influencer operations, so there's going to be a huge market for the bad stuff.
But it's just corporate noise, as it always is. The real value will come from processed search in the sense of automated teaching and intelligence augmentation.
Unfortunately there's not where most of the research will go. It's not going to become common until LLMs are taught to fact check with high reliability, and the cost of entry is low enough for that to be offered as a service.
Meanwhile - yes, exactly: ads disguised as search results.
This feels a bit like projection though. People in general are trained to tolerate ads for most freemium services, such as social media, search, etc., and chat is no different.
For any market involving human attention, there's a portion willing to pay money for the service, but a significant larger portion willing to trade attention time (e.g. ad impressions) for a free service instead.
Right. That's a transient state, unfortunately - we can trust ChatGPT now because we know OpenAI had neither the time nor resources nor a reason to make their tool biased for commercial purposes (they're busy biasing and constraining it so it doesn't generate too much bad press, but this doesn't affect the trustworthiness of responses to typical queries). A model like this obviously won't be allowed to gain widespread adoption as a search proxy - it's destructive to commercial interests.
> If you can't trust it to actually do that (there's still ad noise in what you get back), then what's the point?
Exactly. The problem is, as users, we have no say in it. If Microsoft and Google decide that conversational interfaces are the future, then we'll be doing searches via ChatGPT-derived sales bots. End of story. Google and Microsoft each have enough clout to unilaterally change how computing works for everyone. And if they both decide to compete on quality of their ML search chatbots, there's no force on Earth that could stop it. Short to mid term, if they want it, we have no choice but to use it (long-term this might create an opening for a competitor to claw back some of the search market with a chatbot-free experience).
> Either people will pay a subscription fee to unlock the utility of an information-distilling agent, or they won't. Trying to sidechain ad revenue into that equation is self-defeating.
This, unfortunately, has been proven false again and again. Newspapers. Radio. Broadcast TV. Cable TV. Music streaming. Video streaming. On-line news and article publishing. And so on.
Advertising is a disease, a cancer that infects and slowly consumes every medium and form of communication we create. Often enough, creation of a new medium is driven by the desire for an alternative, after the old medium became thoroughly consumed by advertising and seems to be reaching terminal stage.
Side-chaining ads into a chatbot interface is going to be even more powerful than ads in normal search results - not only you can tweak the order of recommendations like search engines do today, you can also tweak the tone and language used in the conversational aspects, effectively turning the bot into a sneaky salesman.
aka "bullshit"
…and replaced by b.s. chatbot wranglers, who will be paid much more, and who will produce more total output, and who will be selected preferentially from among the people that best understand the work the chatbots are doing…so, yeah, in lots of cases, the people that were writing bullshit will end up wrangling chatbots, in jobs that bring in more money for their employer, and probably at higher pay (though, by historical trends of automation, a lower share of the generated value) who write bullshit.
This is even more clearly the case for people who have writing bullshit as an incidental part of their job rather than a core part, since the incidental part will consume less time, increasing productivity, without eliminating need for the core job. So its not even a “lose one job but move to the replacement job” situation, its just a “be more valuable in existing job”.
This is also a pattern. Their voices are not better than some paid services (NaturalReader for example). Their OCR and document understanding is inferior to Amazon Textract. Even in speech recognition there is the excellent Whisper from OpenAI doing just as good or better. Google's generative image models are not the best, and locked away for good measure. I think SD and MJ rule.
Google's AI was cool in 2000 for search and in 2016 for games. But now the best people are leaving them - almost the whole team who invented transformers has their own startups.
I also think maybe, just maybe, their TPUs are bad and they can't scale high quality models to the public. Maybe they lost the race because GPUs were better in the end. Maybe it's stupid, but how can we explain the lack of advanced AI? The other explanation is they won't mess with something that makes them so much money (current search/ad model).
In your example, if I told that at random about 30% of the results were made up, you would not consider that a time saver. In fact it would be total time waster since you would have to vet every single entry. People think since 70% is accurate, only 30% work is needed but not if you don't know which 30% is bogus. You would need to check the entire work using conventional means including perhaps a 'regular' search engine.
Almost 100% next iteration will sport a fact checker, powerful style and format controls, and a much larger context. The development of advanced fact checkers will have a big impact on anything propagated online.
It's not going to write me something I'll hand to an editor. But for certain things, it could definitely give me a head start relative to a blank sheet of paper.
imagine where we'll be just two papers down the line!
There are largely three groups of people
1) ChatWhat?
2) It only makes bullshit!
3) OMG, this amazing, and scary and amazing, and useful. Oh wow...
The LLM won’t revolutionize search as it is today for factual queries. They’re Clippy 2.0. It’s great people are finding use for the models, but I wish this search story would be balanced out a bit.
I was laid off recently, and I’m using the LLM to write a bunch of cover letters. I give it my resume, a blurb about the company and job and a bit about what I like about work, and it outputs a cover letter. I don’t like writing BS cover letters where I pretend I majored in the company mission and my whole life has been teaching me their values. GPT can do that for me though- and yes I fact check but I’m fact checking against my resume and personal opinions which I obviously know quite well.
The ability of an LLM to generate decent content (provided you're an attentive editor or the users of the content aren't too discerning) could be huge for Office365, but that's irrelevant to any potential threat to Google, since Docs is of very little importance to Google's revenues and strategy in a market where Office is completely dominant and has always had a more full-featured product.
True. And also, keep in mind ... it doesn't truly have to be _better_ than Google search. You just need to start and maintain a _social trend_ so that the mainstream public _chooses_ it over Google. People use Google because it's the first and only option that comes to mind -- they haven't actually compared its accuracy to anything else in a long time (the audience of Hacker News is of course an exception).
There are a few types of search queries that people seem to do, factual lookups ("who is the exec of abc?"), but also generally treat the search engine as the entryway to the internet ("I need a teaching plan about Ukraine"). We'll see that LLM fall flat for facts (assuming people care), but they can supplant some of the general traffic. Realistically, its a bad fact search replacement, but it could be a great tool to put next to a search bar, making a better "starting place for accessing the internet".
With the teaching plan example, the original user was probably going to make a query for a template (or 5), then copy+paste, then do 10-100 queries learning all about Ukraine history and culture, then rewrite that into the template, editing down to manageable size, then send to peers to edit and review, then format for distribution. That could be dozens of Google searches. Now, one or two AI queries, and they have a template, basic written text, and can focus on a couple queries for fact checking. Oh, and since they used bing to do the AI part, they may just stick with bing for the fact check part. Google was irrelevant in that whole flow instead of getting dozens of queries over a day before, but if that feature was moved to Office365, then they may never have used bing for search while still killing a chunk of google's traffic.
The danger to google is not equal to the opportunity to bing. If 5-10% of traffic never reaches a google search, that's a huge chunk of google's revenue, even if it doesn't translate to searches on a different engine. Think of the potential impact an AI code generator could have on StackOverflow. When I need to pick up a new language, I often query "how to append to an array in python" in a search engine, but a LLM (or large-code-model) built into my IDE could supplant that query entirely. I
I doubt you hand wrote cover letters by making dozens of search queries (similarly, I doubt people devise teaching curricula by learning the history of Ukraine through a series of Google queries). But when you weren't taking the time to write them yourself, I bet you had more time free to search for jobs, or do general internet browsing using Google as your gateway to the internet...
People having more time free to browse the internet is unlikely to be a threat to Google's business, even in the highly unlikely scenario Google is incapable of advancing its existing AI products beyond their current state
But is this related to search? I'm a "pro ChatGPT" user (ie, I pay) and I don't use it for anything search related. It's entirely unrelated.
* How does getting recommendations from a chatbot (what TV to buy) play with websites that produce such content (TV reviews) * How does it play with websites that rely on ad impression * How can you monetize a chatbot? (there's an easy way: free tier + monthly subscription) * How to reduce the massive compute cost of a good chatbot without making it bad (this also seems more straightforward)
Maybe Google simply can't squeeze these customers any further than they already are, but at the same time can't turn back the clock to a time when SEO optimization didn't really exist.
Google was worried Facebook would disrupt their Adwords dominance by having social ads.
ChatGPT, if successful (a large IF), will disrupt search and probably a dozen other business models.
I'm awaiting the true counterstrike from Google, not this initial flub.
What if this was the best shot?
It's not just blind optimism for the future of AI. We need search to be better because it's a cesspool of SEO spam/content farms and AI generated garbage. Search engines have declined in effectiveness and utility. We've lost even basic functionality like the consistent ability say "-whatever" to filter out garbage. Google, even DDG, have really dropped the ball here.
We're left looking for a savior and suddenly AI comes in and promises to be able to tell us whatever we need to know, it hints at a near future where AI is trained to see the spam and bring actual content to the top of search results again. We're so over dealing with the mess Google has made of their once awesome search engine that for a brief moment the entire internet was excited about fucking Bing!
I have to admit, I'm disappointed that it doesn't appear that Sydney will be the hero we need, but these are still early days and I hope all the attention leads to advancement in our understanding of AI and that fear of competition gets these companies to put a little more effort into improving the search engines they have now.
But the bigger thing is that Satya Nadella also has the "it" factor - he has a way of communicating effectively. Even when Microsoft is fucking you over for the last few years, they come out smelling like roses. Sundar doesn't have that gravity and gets overshadowed in public by the Google Cloud guy.
The markets hate the perception of weakness and punish it. Microsoft is taking Bing, a joke product, and it's repackaging of Chrome and pushing it from a place of strength. No different than stitching a bunch of random shit together created Teams, which made Slack instantly irrelevant and was the equivalent of flipping the bird at Google. They're dangerous to Google because of that.
Seems like it’ll be more interesting anyway.
I really hope so. LLM for search seems like a big leap right now. It isn't even really search but just a UI change for interacting with the underlying search engine. The caveats being that the people who actually think and create don't gain the clicks that they would get today (with the accompanying ad revenue) and there are no citations.
I really hope more companies realize that LLM for Wikimedia sites would be a vastly superior application of the technology. Could you imagine the impact this application would have given the sheer amount of knowledge and data that is on these sites? Learning and teaching would be changed from virtually the ground up. IMO, this is the killer app and not general search. Given the extreme verbosity and general un-readability of many technical pages on Wikipedia, a LLM that can summarize and answer questions correctly is a huge paradigm shift. Oh,don't know what the Second Law of Thermodynamics is? Here you go. In whatever length of text you want. Want to know how this relates to Information Theory? Okay, here's a primer on that. The internet can once more become a place that people come to for learning rather than being fed total crap by an algorithm.
I do have to commend Satya Nadella though. He and Microsoft know exactly what they are doing. They know Google and Sundar Pichai are on the backfoot and they really are making them "dance". Bing + ChatGPT isn't really scalable right now. Riding the hype wave and putting pressure on Google hoping they make poor decisions based on short-minded thinking is the best thing they can do right now. Looks like it's working out well for them.
To question the underlying premise: what makes you so sure that an improved interface for searching _isn't_ meaningful? From what I can tell, we're a lot closer to optimal collection/categorization of data in search engines than we are to optimal interfaces for searching that data. We've all seen stories like the grandmother typing in questions into google with "please" and "thank you" (https://www.theguardian.com/uk-news/2016/jun/16/grandmother-...), and the concept of having good "google-fu" shows that right now, being able to find the answer to your question is influenced not just by whether the answer exists but whether you're skilled at _asking_ the question.
I don't think this improvement is limited to non-technical folks either. As an example from just the past couple of days for me, I recently have been running into issues with Linux gaming on my laptop due to abysmal power management, and from doing some research, it's somewhat of a known thing with my laptop brand and model. I decided to research what laptops are known for being good for gaming on Linux and also fit my specific preferences (at least 1440p, 16 GB or more RAM, and AMD CPU/GPU for good measure due to my issues being related to Nvidia's weirdness on Linux). I spent a good hour or two finding specific models that seemed promising, searching for mentions of them in places like /r/linux_gaming, looking up availability and prices, and while I found a few potentially decent options, I didn't have much confidence that I was finding all potential options. I found some options for laptop-specific searches that were purportedly able to let me select on whatever criteria I wanted (e.g. noteb.com, notebookcheck.net), but none of them let me pick the _exact_ critieria I wanted; some of them were too granular (e.g. making me search and select exact GPU models to check off instead of letting me just say something like "discrete AMD GPU from 2021 or later", or giving me a list of 30 or so different resolutions and making me manually check off the ones I wanted to include without enabling bulk checking with shift-click) and some of them were not granular enough (e.g. only letting me select a single resolution to search for at a time, or allowing me to require a discrete GPU but not specify the vendor). On a whim, I decided to open up a session with ChatGPT and present it with these criteria to see what it came up with. I needed to nudge it to prune a bit (occasionally it would give me a clearly incorrect option, e.g. one with an Nvidia GPU or only 1080p), but within a few messages, I was able to get it to generate dozens of options. Unfortunately, it only had knowledge up through 2021, and despite trying various roleplaying methods with it to circumvent the "I can't search the internet" policy based on things I saw back when it first became available, I wasn't able to get it to completely finish the job, so I only was able to use those options as a guide for looking up newer models and then finding reviews from people who had used them for Linux gaming. If/when a language model like that that has access to search current data is made generally available, it genuinely seems like that would be a game-changer.
In fact, your laptop example is a perfect illustration of my point. Finding a laptop for Linux gaming is extremely complex. Let's not kid ourselves. The number of things that can go wrong (especially with a Nvidia GPU) is bonkers - my machine completely nukes the display manager every time I update Debian forcing me to do a re-install of SDDM. But the problem here isn't fundamentally search. We know what we're looking for and the exact criteria. Like you said, the problem is collection and categorization of data and presenting it to the user in a helpful manner. This is a digital version of a computer salesman who actually knows their job. LLMs are just salesmen who know about a lot. I'm just extending this to teaching and the knowledge industries and saying, "Look, if you can present information about computers so well, you can tell me about heat death a lot better"
Lots of CEOs in the past have conducted layoffs pretty much the same way-- notify everyone at the same time (per local laws) and write an email blaming themselves as the cause.
Yet the media ran article after article for almost 2 weeks with personal stories about how people felt particularly slighted by Google, when they did it pretty much the same way as other companies.
Amongst 12,000 people at any point in time, they will be doing normal life things-- like feeding their baby at 2am-- when they got the email. Yet somehow this became the basis of so many "Google doesn't care about its employees" stories.
Furthermore, Google's ongoing incorporation of ads into Google Maps and declining search quality may be turning search into a wasteland of SEO. This may be the proverbial straw that broke the camel's back, prompting discussion about whether a leadership change is needed.
Google IMHO is still innovating, but still hasn't figured out how to turn that into product/profit. Since their P/E is under 20 they could just issue a dividend of 4 to 5 percent and people would immediately stop expecting growth from them.
Also, they might just be creating a reputation for themselves of killing every new interesting thing that people just aren't as interested in trying their new things. That's a self-own.
Google search is worse than before.
Youtube recommendations feel worse than before.
Gmail lets in spam (maybe I was unlucky few times).
Android market / play market has very bad search...
Rest is stagnating? Maybe even better, at least they dont change it for worse.
They hired thousands of employees yet you cannot contact a person. What do those people even do?
"Everyone" (apart the CEO?) knows that in Google you get promoted for shipping half baked stuff, so for years they ship half baked stuff to kill it few years later.
Yes, and when we look again in 6 months, they will surpass Google already. It happened too many times in the last few years - something thought impossible was actually doable with a clever twist or two[1].
"When an error is made by their AI during a demo, Google's CEO, Sundar Pichai, should take the following steps to address the situation:
Acknowledge the error: The first step is to acknowledge the mistake and apologize for any inconvenience or confusion it may have caused. This helps to build trust with the audience and demonstrates that the company takes responsibility for their technology's shortcomings.
Explain the cause of the error: Pichai should explain the technical details of what went wrong and how the error occurred. This helps to demonstrate transparency and honesty and can help to build credibility with the audience.
Demonstrate the progress made in AI development: Despite the error, Pichai should showcase the progress made in AI development and highlight other successful demonstrations that have taken place. This helps to reassure the audience that the technology is making progress and that the company is committed to innovation and improvement.
Outline the steps being taken to prevent future errors: Pichai should outline the steps that are being taken to prevent similar errors from occurring in the future. This can include a discussion of the company's testing and development processes and any additional measures being put in place to improve the reliability of their AI systems.
By taking these steps, Pichai can demonstrate a commitment to transparency, innovation, and the improvement of their technology while also acknowledging the limitations and challenges of AI."
There you go - problem solved.
but in these cases ego can make us blind. or the belief that just because someone asked a question we have to respond.
Here's one of the many failures Jobs had during demos.