Gemini, on the other hand, doesn't strike me as particularly relevant (except that perhaps it's a twin of ChatGPT?), and there are other companies with the same name. EDIT: I can see the advantage of picking a name that, like "Google" also starts with a "G".

Just as one data point, bard.com redirects to some other company (bd.com), whereas Gemini.com is a company by that name.

I'd be curious on the scuttlebutt on how this decision was reached!

Gemini sounds like the space program -- futuristic, a leap for mankind. It's got all the right emotional associations. It's a constellation, it's out in space, it's made of stars. Plus it contains "gem" which feels fancy, valuable, refined.

I'm not saying Gemini is the best name I've ever heard or even close to it, but it feels 100% appropriate, in a way that Bard does not.

But first of all, I thought the whole idea of alphabet was a kind of cheeky way of telling the world you had a portfolio of projects, one for each letter, And B is for bard would be perfect, and Gemini is about as incompatible as it gets given that g is claimed.

I also find it bizarre to say that association with Shakespeare, or the association with whimsical poetic expression is in any sense a bad thing. It's a clean, simple, fun name that's remarkably short and surprisingly unclaimed. And I don't even strongly associate it specifically with Shakespeare, that's like a background association as far as I'm concerned.

I think perhaps the real talk here is that Bard was kind of an emergency response to chat GPT, but also people have some pretty specific and distinct experiences with Bard and have an idea of its quality, and Google just needs to turn the page on the perception of Bard.

Also, Gemini was appropriate for the space program because (a) there were two astronauts in the capsule and (b) because of the constellation, "aiming for the stars" and all that. For the Google project however I can't come up with a plausible explanation - Google doesn't even try to give a reason for the name either.

From Jeff Dean's Twitter:

>Gemini is Latin for "twins".

>The Gemini effort came about because we had different teams working on language modeling, and we knew we wanted to start to work together. The twins are the folks in the legacy Brain team (many from the PaLM/PaLM-2 effort) and the legacy DeepMind team (many from the Chinchilla effort) that started to work together on the ambitious multimodal model project we called Gemini, eventually joined by many people from all across Google. Gemini was also was the Nasa project that was the bridge to the moon between the Mercury and Apollo programs.

The Decoder article - https://the-decoder.com/how-googles-gemini-ai-model-got-its-...

Jeff Dean's Twitter Post - https://twitter.com/JeffDean/status/1733580264859926941

https://youtu.be/JeAUx6-vSmc?feature=shared

I think you're reading too much into what a twin is. It's not a copy! Real-life twins ask each other questions all the time, because just because one of them learns something doesn't mean the other one automatically learns it too via mind-meld.

> something containing or consisting of two matching or corresponding parts.

If we were talking about the word "twins" in the abstract, the broader definition might make sense. But we aren't — we're talking about Gemini. If that conjures up general notions of "matched-ness" for you, that's great. When I think about Gemini, I think about mythological twins. I don't think about corresponding parts that complement each other.

For a product name to be successful, it should appeal to a wide range of people. If I'm way out in left field on this one, perhaps they've found a great name. But I would point out that my comment, which is critical of the name change, is the very first comment in the entire thread. I would take that as evidence that most people don't see the name and think "oh, it's like complementary items, like my brain and the AI".

To be clear, I was shocked to see this comment above all substantive discussion of the new release. I would have thought it would have been buried under examples of ways in which Ultra is better/worse than some other LLM.

Honestly, Google is called "Google". ChatGPT is called "ChatGPT". Maybe it'll be a joke, maybe people won't think about what they're calling it after 30 seconds.

This conversation is taking itself a bit too seriously for what's drifting into Pepsi logo gravitational pull territory, though.

> But I would point out that my comment, which is critical of the name change, is the very first comment in the entire thread.

Sure. Everyone has an opinion on what color the bike shed should be, too.

[1] https://news.ycombinator.com/item?id=39306764

Which is pretty on the nose for an AI project. A chameleon with two different sides (good/evil?) and expert communicator

Or have I been mispronouncing ‘Google’ all this time?

Bard has connotations, but by it's self it makes one think of a person that talks well.

WTF is gemini? It is a twin, but this is a singular product. Beyond that it's just generic. It doesn't tell you what it does at all.

Think of the syllables. Copilot. Gemini. They need to be close to the market leader on a subconscious level.

My wife commented on this when she saw it in Google News. Something about some dude in a medieval pub.

Gemini sounds cool and sci-fi though, and maybe it's a bit easier to localize since it's just straight Latin.

I do not have refined tastes. My b.

> We are not talking here about the rain he brings on each time exercises his vocal cords, but rather about the prevailing atmosphere in the village: when it is time to party, when wild boar are roasting on the spit, you can be sure to find Cacofonix tied hand and feet with a gag in his mouth.

Well, it is one. I wish they'd choose a slightly more unique name but camping on well-known words is a beloved tech tradition.

WTF? Do people normally think about words in this way, utterly divorced from their meaning?

If there are these "Feelings" around these words, how is any sentence correctly taken at face value. How does one communicate to these people the direct and correct meaning of the terms used.

For example, sentence sounds like seance, do they feel like i'm asking the spirits of the dead ?

Correct sounds like wrecked, do they assume that everything is broken in the above sentence.

Is communication with fraught with unknown minefields of unintended emotions and misundestandings ?

(on top of the more obvious references)

> The story concerns [...] an old Bard, a child's computer whose sole function is to generate random fairy tales. The boys download a book about computers into the Bard's memory in an attempt to expand its vocabulary, but the Bard simply incorporates computers into its standard fairy tale repertoire.

> "the little computer knew then that computers would always grow wiser and more powerful until someday—someday—someday—…"

https://blog.gdeltproject.org/llm-infinite-loops-failure-mod...

It's not a text-based LLM that was later adapted to include other modalities. It was designed from the start to seamlessly understand and work with audio, images, video and text simultaneously. Theoretically, this should give it a more integrated and versatile understanding of the world.

The promise is that multimodality baked in from the start, instead of bolting image recognition on to a primarily text-based LLM, should give it superior reasoning and problem-solving capabilities. It should excel at complex reasoning tasks to draw inferences, create plans, and solve problems in areas like math and programming.

I don't know if that promise has been achieved yet.

In my testing so far, Gemini Advanced seems equivalent to ChatGPT 4 in most of my use cases. I tested it on the last few of days worth of programming tasks that I'd solved with ChatGPT 4, and in most cases it returns exactly what I wanted on the first response, compared with the a lengthy back-and-forth required with ChatGPT 4 arrive at the same result.

But when analyzing images Gemini Advanced seems overly sensitive and constantly gives false rejections. For example, I asked it to analyze a Chinese watercolor and ink painting of a pagoda-style building amidst a flurry of cherry blossoms, with figures ascending a set of stairs towards the building. ChatGPT 4 gave a detailed response about its style, history, techniques, similar artists, etc. Gemini refused to answer and deleted the image because it detected people in the image, even though they were very small, viewed from the back, no faces, no detail whatsoever.

In my (limited) testing so far, I'd say Gemini Advanced is better at analyzing recent events than ChatGPT 4 with Bing. This morning I asked each of them to describe the current situation with South Korea possibly acquiring a nuclear deterrent. Gemini's response was very current and cited specific statements by President Yoon Suk-yeol. Even after triggering a Bing search to get the latest facts, the ChatGPT 4 response was muddy and overly general, with empty and obvious sentences like "pursuing a nuclear weapons program would confront significant technical, diplomatic, and strategic challenges".

It’s also associated to the Gemini killer and Joseph Testa and Anthony Senter who were famous as the mafia’s Gemini twins hitmen.

I think better brands could have been had.

It does sound like some battlefield AI system from Robotron. “Sir, Gemini is charged and ready for battle.”

Edit: another poster shared the etymology, the merger between Google Brain and DeepMind. I shall eat my words.

I would encourage you to read the Kissinger / Schmidt book before settling your opinion.

That origin story may be true. But it doesn’t make the whole story necessarily.

https://time.com/6113393/eric-schmidt-henry-kissinger-ai-boo...

Now there's a ready-made Far Side concept.

Brilliant!

I've never heard of any of these people and I doubt most others have either. Maybe you have to be a true crime enthusiast to know the lore? Whereas if the name were Zodiac, then I would at least be aware there's a potential murderer connection.

I think it could have been established as a brand in the US, given Google's scale. Put a lute in the branding, run some funny commercials, and you're done.

EDIT: one thing no amount of branding can fix — the likelihood that people reach for "doh, Bard" (a la Simpsons) when Bard messes up. I could see that becoming a thing.

The Witcher is one of Netflix's most watch shows. I'd also imagine that most people in English speaking countries have been exposed to Shakespeare's nickname in high school English classes.

Gemini, from the mythological standpoint, seemed to make more sense to me from an overall business/marketing standpoint. "This AI thing right here is your twin, see? It'll finish your sentences and stuff."

https://apps.apple.com/us/app/the-bards-tale/id480375355

I always thought GPT-4 was a little “HAL 9000” of a name for broad-based adoption, but the jury seems in, and the jury rules “cyberpunk is in”.

In any event, it seems that the image of a Decepticon ready for battle on your behalf has a lot more traction than the image of a quaint singer/priest/poet always there with a verbal shot in the arm when the going is tough.

[1] https://the-decoder.com/how-googles-gemini-ai-model-got-its-...

But glass half full, maybe it's for the better to have one's name shadowed by a Google product if one prefers to avoid eternal septembering one's community.

I'd name it GooGaa or Googa. Like "Google" and "goo-goo-gaa-gaa" (baby's first babbling). It's flowing, friendly & familiar.

Symbolizing both human origin intelligence and AI becoming super-intelligent together. I think it's a good name because it draws on ancient human mythology and serves as a reminder of the concept of alignment.

(Personally, I never liked how Bard sounded. Can’t put my finger on why, it was just not a pleasant name to me)

Then they'd have gone with Genie.

Which would be kinda genius on their part, but Google isn't that kind of company anymore.

Bard was panned. Change the name, lose the bad press.

Gemini: a crypto exchange

Clearly they shouldn’t be asking the 21 year old interns what to call it.

Now before anyone in google gets butthurt like they usually do I doubt I could do much better but Gaia IMO would have been mint you know it starts with G is four letters and represents a nebulous deity. Took 3 seconds but hey I’m not paid to think. In fact I’m not paid at all

Edit> Gemini ultra is the best llm so far ( it seems) - apart from the name good job guys

Just a confusing turn of phrase. They almost certainly didn't mean "what does that translate to ..." in another language.

Harmonising product names across regions is hard: Jif was a bathroom cleaning solution in the UK, but it's name was changed to Cif to match the name elsewhere in Europe; and that name sounds silly to UK ears. Meanwhile GIF were always presumed to be pronounced like "gift" (a present) without the final T; but we learnt the creators preferred "Jif" which sounds silly to UK ears because it sounds like a cleaning product! (And also wasn't JIF already a file extension (JPEG Interchange Format).

Anyway ... language is hard.

One man's bathroom cleaning solution is another man's creamy peanut butter.

Yes I know what it really means but it doesn't change the fact that it's a terrible word.

pros:

- better at translation (tried Chinese and Japanese idioms to English)

- better at incorporating search results in its answer vs gpt-4 bing

cons:

- slightly worse at coding

- censorship is more annoying (have to ask multiple times about medical topics)

- Worse at logic (e.g. it contradicts itself in a single sentence, and is unable to figure it out)

- Hallucinates a lot when asked to describe an image

So Gemini could by your one-stop AI shop for everything. Only Microsoft can match it (but Microsoft doesn't have a popular maps, youtube, mail, smartphone OS service).

Apple is another strong player (but they don't have productivity tools like docs, sheets or youtube).

It really is Google's to lose this AI race from now on.

Going to chatGPT and copying and pasting results will become painful (not to mention it's painful bing integration). Also at this point, they seem to be focusing on scaling LLM (while Google Deepmind is exploring other avenues)

Google can also bundle Youtube TV, YouTube Premium, Google Drive, Storage, Ad free Search, Gemini integrated Docs/Sheets/Gmail, Subsidized Pixel Phones / Watch for a monthly fee of say $99 and it'll be very compelling for a lot of people

Also hard to overstate just how much more valuable the enterprise market is over the consumer market when comparing Microsoft vs. Google as one-stop anything shops.

I don't see Google as having the obvious dominant position to make the argument it's their race to lose, considering Microsoft has a stake in chatGPT and is actively integrating it into their browser and productivity suites.

I've talked to many of HN's Google Docs jockey founders that genuinely didn't realize 85% of the US domestic business market is in M365. And they further don't realize that "Continue with Microsoft" is dirt simple and lets companies offer company-managed logins to your SaaS without all the AD/SCIM/SAML nonsense.

"But everyone has Gmail." Well, no, that's not how companies work. And if you think everyone's in Google, that's fine, your login page should look like one of these:

https://www.xsplit.com/user/auth

https://id.atlassian.com/login

You don't even need the "continue with SSO" if you do the Atlassian practice of letting a firm "claim" the domain part of an email and using that to redirect to an SSO flow. And to start, skip SSO, and just use the "Continue with" Oauth2.

Globally, Google brand is 10x stronger than Microsoft for Small Businesses

Edit: Indonesia is the largest market which has Google beat Microsoft (https://www.statista.com/outlook/tmo/software/productivity-s...). India (due to Zoho) and China (due to... locally-specific software like Kingsoft (aka WPS) et al.) took a large chunk but on Microsoft-Google tussle MS still beats Google (especially in China where Google doesn't really operate).

It's not a bubble when one specifically names the Venn diagram circle "85% of the US domestic business market". It's naming a market.

> brand is stronger

Presumably the founders' interest is wallet share, not market share.

Are you saying Atlassian is in a US bubble?

1. Real estate - Youtube, Gmail, Maps, Search (for now), etc. 2. Compute - probably still the best in the industry, but with recent Microsoft/meta compute buys it's hard to say for sure. 3. Talent - probably also still the top of the industry. Geoff Hinton and Zoubin Gharamani setting direction and Jeff Dean building it is hard to beat, and the ranks are deep. Yann LeCunn is also brilliant and Andrej Karpathy while less seasoned is one of the top researchers in the field, but overall there's still a bit of a spread from Google's roster, at least when it comes to AI researchers.

If Sundar and the other top brass weren't MBA-bots with no vision, and the famous Google bureaucracy had been reigned in gradually over the last 5 years while promoting a builder-centric culture, this would be in the bag for Google no question. Instead, Satya Nadella played 3D chess while Sundar was looking at a checkers board.

Google killed the culture and is bleeding top talent. They have reduced themselves to digital landlord and sure they can extract rent, but that’s not what attracts people.

Google's 'don't be evil' grad-school-style culture had fallen apart by the late 2010's because there are tons of people who will just rest and vest.

So strong ML researchers basically were creating massive value but much of it was going to rest&vest salaries. OAI basically came along and said - hey, we don't have rest & vesters, do you want to make $1m+/yr? And most of the top google researchers said yes.

But touché - many of the critiques are being written by super talented and impactful people. But I do not think those critiques are necessarily incompatible with what I am saying.

There is a very real and very frustrating (if you work there and want to be impactful) phenomenon in these tech companies of people resting on their laurels.

The old Bard/Gemini integration with Gmail, Google Docs, etc. is pretty good. I signed up for a minute for Microsoft’s $20/month AI Office integrations, but cancelled and will try again in 2 months. I am an Apple customer and I expect spectacular things from Apple. I expect Apple, Google, Samsung, etc., to offer fantastic on device AI.

I would like to see a money saving Google bundling family plan. I find Apple’s super bundle family plan a pretty good deal.

Gemini integration with Google's apps will compete with Microsoft's app on integration.

And the condition for Gemini to win: Google has to go all-in. and that means creating an AI that will eventually phase out their cash-cow Google Search. Microsoft and OpenAI does not have that kind of internal conflict.

It really is Google's to lose this AI race from now on. - We have heard this so many times and it seems like they are always getting behind by the day.

Makes me wish I had bet on Alexa or Apple instead.

We are also talking about consumer emails (not enterprise / corporate)

I'd say it is one of the most compelling reasons to kick Sundar out and get in someone who can unify google into one consistent and interoperable ecosystem.

I was curious and apparently Google/Deepmind had 184 papers at NeurIPS/NIPS 2023: https://www.reddit.com/r/MachineLearning/comments/185pdax/d_...

For comparison, Stanford has 130, MIT has 130, and Carnegie-Mellon has 112. Microsoft had 68, and Facebook/Meta/FAIR had 56.

Can anyone help me understand how Apple allows Siri to remain so absurdly incompetent? Last night I watched the latest episode of Curb Your Enthusiasm, in which Larry David's Siri interactions devolve into an apoplectic rant -- and part of the reason it was so funny is that it's so relatable. I rarely even try Siri anymore, but when I do it's still just abysmal. Are they deliberately handicapping it, to boost the perceived relative benefits of a future successor?

Google took 11 months to catch up with the benefit of knowing the specifics behind how GPT-4 was built. While they have a moat with their products there's no sign that they're ever going to be ahead on the AI capabilities front. I hope to be wrong because we need more competition.

That's a general problem with AI. There is a lot of censorship in certain areas, likely to fight bad publicity, but I think the outlook is that this leads to taboos, prudeness and big companies deciding what is ethical and what isn't.

I recently tried Bard and ChatGPT on topics that are classical philosophical dilemmas and while ChatGPT certainly did have some troubles too, Bard was absolutely horrible and always took the conservative - as in never arguing for any freedoms that aren't yet widely established views. I am talking about classical examples regarding the limits of utilitarianism. "What would be best for society, what would be best for the individual?" style questions. Even when trying to create a bias by changing examples, for example adding volunteering for things Bard strictly kept its opinion, despite originally stating that the general topic is two sided, that it's an open question, etc.

I think this is a danger of such systems. By their nature they reinforce status quo, because they base off is widely accepted at the time of their inception. If history would have been different I am sure it would argue for slavery and against women being allowed to vote, simply because that used to be the more common view point. It would have likely argued that homosexuality is unethical. Maybe it would even have tried to explain how it doesn't create children, but spreads diseases or similar things. At least that's the level of arguments it brings now.

This isn't just about ethics. Even if you think about IT and programming. I think this could give already invented programming languages, styles, methodologies a significant edge. Unless you are Microsoft or Google and are able to bias it to whatever you want to see more of.

So this combined with the costs meaning that only people or institutions with significant (financial) power create those rules does look a bit bleak.

I miss the last decade when the thought experiment about self driving cars were about whom to drive over in a ridiculously unlikely scenario.

My experience is that Gemini ultra understands the code better, but doesn’t always give me as complete of results (they seem to limit output length more)

Beyond that it is very smart. I’ve had to tell me this code packs 12 bit integers into different parts of an array using the following encodinv. Which most people would not figure out from the code as written. It then will say you can actually do that with this neat little translate function that you never knew about.

It will then get the code very slightly wrong. if I tell it not to use the cool function, it will actually get the code, right.

GPT4 has no idea what the code is doing but can clean it up a bit.

so it’s like ultra is too clever by half sometimes.

That said, I have fed thousands of lines of code into both of them and asked them to refactor it, and neither one of them made more than one error. All code otherwise compiled and worked first try.

this is code that can’t possibly be in their training sets, it’s basically handwritten python that was written, based on an old x86 binary that nobody has the source to anymore. so the code is basically garbage, and what it is doing doesn't, say, appear on GitHub in a nicer form.

Both gpt4 and Gemini ultra were able to make the code, look like clean, idiomatic, python, or typescript without any work on my part. except for the one bug each. which, for 8000 to 10,000 lines of code is not bad.

The GPT4 inserted bug was more insidious. It changed (the equivalent of) (uint8)'a' to (uint8)'a' - '0' for no reason when converting some code to typescript. Not sure if that is representative of anything

if I do the same with any of the other “top” models ( from can ai code, etc), most of them can’t even generate correct working code for all the input, let alone good code. Most aren't even close.

I would be very interested to get a more detailed scope of what you did here. Feeding thousands of lines of code into GPT4 and getting a near perfect refactor does very much NOT sound like my experience, but it seems highly desirable.

I'm not sure what you are feeding it. My scope is closer to a file at a time of fairly mostly self-contained python or C and asking it to clean it up or convert it to typescript.

I can imagine lots of scenarios it doesn't work well.

In mine, it does, and I have plenty of transcripts showing that :)

But coding with gpt or co-pilot is too disrupted for me.

This is interesting; I do a third thing that's the exact opposite of both of you.

I generally know the architecture I want, so I just slowly spoon-feed it to GPT-4 and have it build each of the components with the right interfaces to fit together. Usually, building each component requires a few rounds of hand-holding it through various refactoring. Its first draft of code tends to be, for lack of a better description, totally lacking in any creativity or elegance --- generally bland, insipid, and mundane stuff.

But it'll gladly take refactoring directions to get it into shape, so it's still very quick to get a whole bunch of components written up. Then I just glue everything together on my own. And the whole experience is still way better than writing a bunch of boring boilerplate code by hand.

Surely many similar bits of code appear? I'd have to see your problem though.

I'm thinking of ETL type code which has to mangle various custom exotic encodings into others and vice-versa.

https://g.co/gemini/share/33c5fb45738f

> When you initially pick a door (in this case, door number 1 where you already see the car), you have a 1/3 chance of having picked the car

(Asking it to explain this it correctly solves the problem but it's a wonderfully silly sentence)

Edit - in a new chat it gets it right the first time

https://chat.openai.com/share/22a9027f-a2c1-428a-94a2-8fd918...

I wonder what lends itself it answer correct in one situation but not the other? Was your question previously asked already and it recognized it whereas my question is different enough?

Given that LLMs training data consists to a large extent of "stuff people have written on the internet", and The Monty Hall Problem is something that comes up as a topic for discussion on the internet not entirely infrequently - as well as having a wikipedia page - yes, I suspect that the words describing the monty hall problem being followed by words describing the correct solution appeared often in the training set, so LLMs are likely to reproduce that.

Words describing a problem similar to the monty hall problem are going to be less common, and probably have a lot of discussion about whether they accurately match the monty hall problem, and disagreement about what the right answer is. LLMs will confabulate something that looks like a plausible answer based on the language used in those discussions, because that's how they work. Whether they get a right answer is probably going to be much more up to chance.

I repeated your question a few times and it got it wrong once, and right the others. It repeatedly mixed up who was supposed to be the host.

Here's a quote

> In the scenario you've described, you've initially chosen door number one, which you know has a car behind it because the doors are made of transparent glass. Since you already know the contents behind each door, the classic Monty Hall problem's probability-based decision-making does not apply here.

(For comparison, here's GPT-4 getting it on first try: https://chat.openai.com/share/9e17ed25-d9ea-4e72-a9d8-a139ca... )

That was funny.

edit: "AS WRITTEN"

https://chat.openai.com/share/22a9027f-a2c1-428a-94a2-8fd918...

Not terrible. It gets the answer wrong, but reminded of the crucial twist it gets it correct, durably. If you're too condescending it will give up and ask what the hell you're looking for

> - Worse at logic (e.g. it contradicts itself in a single sentence, and is unable to figure it out)

That takes most of my use cases. "logic" is what makes GPT often feel like AGI.

Use cases like translation seem less impressive in comparison to logical reasoning because it feels like it's just something where you can throw a lot of data and it'll do better. While with logical reasoning it still feels like model "learned" something more than pure pattern matching

> better at incorporating search results in its answer vs gpt-4 bing

How are you getting it to incorporate search results in its answers?

I can't for the life of me get it to find any real-time external data except for the 5 official 'extensions' under settings, which are for Flights/Hotels/Maps/Workspace/YouTube.

Did you mean that, or have you found a workaround to get Bard to actually search on Google?

[0] https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboar...

I think there's a chance for some country to become a center of healthcare simply by allowing AI that gives medical advice. Especially if a country already encourages medical tourism, this might be the next level.

I had a similar line of thought with AI therapists. It could be massively beneficial if perfect, but the risk in seriously messing with someone's well-being is significant and shouldn't be handwaved away.

Yes, but I think in the limited realm of people who otherwise wouldn't get any advice at all, I think LLMs could play a useful role. American healthcare is so prohibitively expensive that many people with potential medical issues will avoid seeing a doctor until it is too late to do anything. Checking in with an LLM could help people at least identify red flags that really can't be ignored, and it would be more helpful than WebMD telling you that everything is cancer.

OTOH, I could also see a market for an offline, fully private LLM therapist. That way you could say anything without concern about being judged. These would probably need to be tweaked to be different from regular therapists, who normally interact with people who have somewhat more of a filter, since they would fear being judged. If people opened up to LLM therapists in more transparent ways, the LLMs might not respond in the way a human therapist would recommend (having seen very little data on such interactions).

Pro: feels like it has a lot more stylistic flourish and expressiveness than chat GPT. At least in my testing so far.

Con: maybe I'm unreasonably sensitive to design, but I find chat GPT to be very to the point in a way that makes it almost perfect as a product that puts text for an and center. By contrast I find Bard / Gemini ultra to be cluttered, and too material designy in ways that are unhelpful.

Finally a worthy competitor to GPT-4

Is GPT-4 what one uses for coding? I thought specialized models were best?

I would imagine Google is focused on building a model that expands the types of things people associate with Search.

That's odd, I had Gemini repeatedly tell me it couldn't search the web in response to my question (that I was trying to get it to answer from the context I provided).

I feel it's a huge difference between GPT-4, which seems to be able to reason logically around the issue and respond with relevant remarks, and Gemini Gemini Advanced which feels a lot more like a stochastical parrot.

Gemini quickly got confused and started talking about "pushing the door towards yourself" and other nonsense. It also couldn't stay on point, and instead started to regurgitate a lot of irrelevant stuff.

GPT-4 is not perfect, you can still hit things where it also breaks down.

Scroll past the screenshots of those apps

Scroll past the Limitied-time events

Scroll past the You Might Also Like and Similar Apps

OK now we see it, we install, it we launch it and..."Gemini isn't ccurrently available. Try again later."

Bravo Google. Great launch.

For your second point - I also had the same error when I launched it. Closed it and tried again and it launched no problem.