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connectors are bad for signal integrity and GDDR is particularly picky about this

We're talking about ordinary RAM to augment, like a cache.

Not as GPU VRAM expansion.


"repeatedly struck down" means somebody keeps bringing it back


They're proposals by a minority. I'd like to see it go to see chat control go to grave permanently, but I'd also rather not that the democratic system allows for the permanent barring an impossible to define class of proposals from even being proposed. Or do you have other solutions?


I'm definitely for creating EU directives that enhances digital privacy rights and sovereignty to block whole classes of privacy-endangering surveillance proposals in the future. That seems like the best solution to me. It's much better than allowing those proposals to be made again and again until they are passed in some shady package deal. Even if such a proposal is struck down by local laws, constitutions, or the ECHR, once they have the foot in the door, they will only be modified minimally to comply with the constitution.


you've posted this multiple times and it's not actually true. go read the ingredients list on a supermarket burger


You're right, it's more salami, hot dogs and other meat products. But you're right on burgers themselves for the most part.


> go read the ingredients list on a supermarket burger

Perhaps a tangent, but they're not required to list "chlorine" as an ingredient if the slaughterhouse washes the beef with bleach to kill bacteria.


they're obviously trying to steer customers to the monthly subscription instead of the pay-per-token API.

now, the consensus of the commentards on this website, who don't have access to any of anthropics financial data, is that the monthly subscriptions are a money loser!

so either the leading AI company's business dev team is wrong or the Jacker News comment section is wrong, it is a mystery


no, the other such labeled companies are foreign owned firms like Huawei that the government never intended to do business with in the first place


Grocery stores track their customers very extensively and cash purchases are fairly rare. I'm very confident that Costco, for example, knows everything that every member has bought from them since the tariffs started.


Hydrogen is so hard to handle that NASA never really figured it out; hydrogen leaks just delayed Artemis 2 last week. There's been about 70 years of trying to solve these issues for space launch and very little progress. It doesn't seem like it'll be easier trying to do this as the scale of every gas station?


The article skips that i think most realistic and plausible option - fuel cell using hydrogen extracted from the standard hydrocarbon fuel right on the truck. Thus hydrogen would be present only in the short path - from fuel splitter to the fuel call. The fuel cell has higher efficiency than ICE and having electrical engine works better for trucks than ICE too. Such setup is overkill, at least for near future, for regular cars, while for trucks it seems worth the investment.


I have done a deep dive here: https://www.mikeayles.com/blog/on-vehicle-hydrogen-generatio...

Short answer, it takes more energy to generate than the energy it produces.

You can do things like only producing electrical power from the alternator when decelerating, ensuring no load comes off the engine, but that would require accumulation as you're not actually burning fuel then either.

But running the numbers on the power requirements, I reviewed one commercially available system (at 12v 14A) and calculated that the HHO they are able to produce is 0.037% by energy going into the engine vs regular fuel.

When presented with 0.037% of the fuel substituted, their 10-15% claim on fuel savings becomes a bit of a red flag.


i meant hydrogen from regular fuel, not from water.


Surely that's a thermodynamic waste? Use the energy in the fuel to extract hydrogen from the fuel to them use the energy in the hydrogen to generate electricity to turn the wheels.

Is there a chemical process that achieves this with a better efficiency than just using the fuel to turn the wheels?


Onboard reforming has been explored and it's not great. The end-to-end efficiency is poor (<50%). It adds a ton of complexity. It requires having a reactor running at over 700°C. It takes time to warm up. It's not cleaner. Impurities like sulfur kill it.

In the end it's only about as efficient as just using a regular diesel engine, much harder to service, more expensive to maintain, and doesn't improve your carbon footprint at all. What's the point?


coding like a hospital patient


Google fucks up 90% of their products, why do you think Gemini is in the 10%?


well, it's basically existential, so the incentive is there to not only get it very right but also to limit the delta with how right anyone else gets it. The same can't really be said of the long tail of products Google have done.

Look to GCP as an example. It had to be done, with similar competitive dynamics, it was done very well.

Look to Android as another.


You must not know the stories of why GCP came to be.

It was an idea from the creators of Kubernetes and the execs at Google fought it the whole way


No, this is bunk. App Engine and GCE, the earliest components of GCP predate Kubernetes.

[I've been there for nearly all the relevant time]


I hadn't heard that, that's interesting. Any sources you'd recommend to hear more about it?

I think it's a slightly different point though. What I'm saying isn't about where the idea came from or whether it was part of some precient top down bet / strategy from the very beginning.

It's more where did the strategy evolve to (and why) and did they mess it up. GCP and Android are good examples of where it at a minimum became obvious over time that these were massively important if not existential projects and Google executed incredibly well.

My point is just that there's therefore good reason to expect the same of LLMs. After all the origin story of the strategy there has a similar twist. Famously Google had been significantly involved in early LLM/transformer research, not done much with the tech, faltered as they started to integrate it, course corrected, and as of now have ended up in a very strong position.


> well, it's basically existential, so the incentive is there to not only get it very right but also to limit the delta with how right anyone else gets it. The same can't really be said of the long tail of products Google have done.

I've yet to see anything that threatens Google's ad monopoly.


The threat to Google is that browsers themselves get displaced.


I mean I guess this is classic disruption theory.

It's not that a dominant position goes away overnight. In fact that would be precisely the impetus to spur the incumbent to pivot immediately and have a much better chance of winning in the new paradigm.

It's that it, with some probability, gets eaten away slowly and the incumbent therefore cannot let go of the old paradigm, eventually losing their dominance over some period of years.

So nobody really knows how LLMs will change the search paradigm and the ads business models downstream of that, we're seeing that worked out in real time right now, but it's definitely high enough probability that Google see it and (crucially) have the shareholder mandate to act on it.

That's the existential threat and they're navigating it pretty well so far. The strategy seems balanced, measured, and correct. As the situation evolves I think they have every chance of actually not being disrupted should it come to that.


Because Google has the money to build 10 different versions/iterations of Gemini and can essentially force one to work. They have most people's data and most people use them for mail/search/browser/maps as well.

In my opinion though this is a race to the bottom rather than a winner takes all situation so I don't think anyone is coming out ahead once the dust settles.


Google built ten different chat products, how did that go?


Does it matter? Microsoft won by default with Teams because it actually turns out no one cares about chat or even has a choice in it: employees use whatever the company picks.


No one uses Teams for personal use. LLMs are used daily for personal use by hundreds of millions of people at this point.


It's bundled with office and no serious business can live without excel.


The world, other than the US, runs on WhatsApp. Business, support and payments are done there. So people do care.


If you're going to say "other than the US" then you've got to say at a minimum "other than the US and China", but really "other than the US and China and Japan and Korea and Taiwan and Thailand and Russia and most of Central Asia".

Only mentioning the US is wildly americentric even by HN standards.


Gosh doesn't that sound familiar.


This was the same argument made for Google Wave and Google+ and both completely tanked


The tech behind wave eventually made its way into Google docs though and pioneered collaborative document editing, so wasn't a complete failure even though the product itself was killed.

No comment on Google+, Google has a storied history of failure on any kind of social media/chat type products.

Where Google wins is just simply having enough money to outlive anyone else. As the saying goes "the market can remain irrational longer than you can remain solvent" In this case, Google is the market and they can just keep throwing money at the wall until OpenAI, Anthropic, etc. go under.


Google Docs has no features remotely like what Google Wave was.

And there was collaborative editing long before Google Wave.


> made its way into Google docs

Google didnt make it though, they bought a startup which did it and integrated their tech.


Social media has strong network effects that keeps competitors at bay. What network effects are OpenAI/Anthropic/etc accumulating?


Yes, but Gemini is actually good and so are their APIs.


Agree. Look at how miserably MSFT has failed at integrating AI tastefully in their business.

Google makes money selling ads. Nothing else matters.


They target those ads by ingesting as many signals as possible from as many input devices & sensors as they can possibly convince people to use. They make a lot of money from advertising b/c they have managed to convince the most number of people to give them as many behavioral signals as possible & they will continue to do so. They kill products only when the signal is not valuable enough to improve their advertising business but that's clearly not the case w/ AI.


Google has barely released a successful product in 20 years.


Depend on the definition of the "product". For example some banal cloud storage in which everyone competes. And it's an "old" product, despite being invisibly improved behind the scenes, just like at any other provider. Google has pretty competitive storage AND they are fully abusing Android integration for AND they have pretty good bundling of that storage with other products, including, you've guessed it - LLM Gemini. So say a person is not a professional user of LLMs like a developer burning tokens in a dozen accounts simultaneously. A person has a phone and eventually memory runs out, so he buys a one click Google storage for 4 bucks. And suddenly he has Gemini Pro included too. So why pay 20 bucks to Anthropic, when Google costs 1/5 of that AND has other stuff bundled too?

So maybe Google is lagging on truly new products (btw, does Gemini itself with its TPUs count as a new product? I'd say yes), but "old" products are entrenched enough to carry them and compete.


Google Drive is easily the worst of the desktop cloud storage options. It’s okay for Google Docs but not other files if that’s what you’re talking about..


I get 2TB (which I use) and AI Studio for $20, that's the best deal out there for me.


In a world where OneDrive exists?


I've used OneDrive across 3 companies with no problems.


Which one would you say is the best?


I'm back to Dropbox.


Google is good at buying existing products and scaling them, which is exactly what they did with DeepMind.


Deepmind was their worst acquisition ever. It is a vanity project that burns cash.


I thought that the likes of Android, Google Docs, Google Translate, etc. were fairly successful. Chrome and ChromeOS also seem fairly popular too.


A lot of those are getting pretty close to 20 years ago.


This year:

chromeos is 17

android is 18

chrome is 18

google docs is 20

google translate is 20


In retrospect, it is wild how good/successful google was 17-20 years ago!


Few years ago, we had Google Bard, the ancestor of Gemini, which was supposed to be an AI LLM, and when you right-clicked the page, it was a fake page with hardcoded sentences in a .js file...


> was supposed to be an AI LLM

Are you claiming Bard wasn't an LLM???


None of them looks like their original form, none would survive without google’s enormous investment.


Google Cloud is good and successful. Except they can't implement billing hard caps, or pretend they can't.


Im not sure what you consider successful. They've been struggling to get market share vs azure, and the product isnt that good. lots of rough edges, and piss poor support


Their API business model seems to be hope enough people accidentally go over free tier: $0 for the first 5000 monthly places lookups, $40 per 1000 after that


Neither does AWS and you can argue they aren't good but they're objectively successful, so it doesn't seem like a good metric.


Because the product quality doesn't matter if the competition isn't making any money.


0% interest to defend Big Don’t Be Evil, but success rates for most businesses, new or existing, are low. Succeeding at 10% of their ventures isn’t that bad, considering they add up to the trillions of dollars of valuation for big G.


Persistence. Google has a lot more endurance then OpenAI does in this game.

The current AI market is going to destroy anyone who's specialized into it compared to having alternative revenue streams to subsidize it.


Does Alphabet/Google have any other significant alternative revenue streams though besides their ad revenue? And won't that decrease significantly the more people use AI tools for research than firing up a google web search? I find myself using Claude more and more doing web research and comparing products/reviews...without getting a single ad served up from Google.


google the only ai which invests mixing llm ai with real ai, and it seems work well.


race to the bottom. google in house cheaper inference hardware. anthropic buys it.


The conclusion Google is engaged in consumer capitalism is wild.

They're engaged in computing research and merely engage in consumer capitalism as a consequence of political and social constraints.

Products are a means to an end not the goal.

OpenAI and Anthropic are product companies and are more likely to fail like most product companies do as they will lack broad and wide depth.

Google has experience in design, implementation, and 24/7 ops with every type of SaaS there is. They can bin LLMs tomorrow and still make bank. Same cannot be said for OAI or Anthropic.


Do they though?

Google does things I hate with their products. But the money printing machine keeps going whrrr faster and faster.


Aluminum is 8% of the earth's crust and silicon is 28%; I think we're good


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