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Maybe I’m a wierdo but I actually like the Brave version of their Search + AI solution: https://search.brave.com/ask

After switching between Perplexity, Phind, and a couple others, it seems like the best balance for my use.

You can always just use the regular Brave search. It does seem to include an AI summary by default, but you can turn that off: https://search.brave.com/settings#:~:text=Make%20AI%2Dpowere...

I find it is grounded in facts (based on the results) more and doesn’t typically make stuff up. I am usually using it for things I am more well versed in (web dev) so I have a baseline knowledge to draw from.


I’ve used djlint on a liquid project and it worked well. It supports twig too: https://djlint.com/docs/languages/twig/

They also have an online demo/playground so you can at least give it a shot to see if it works.

I’ve used the twiggy LSP before and there seems to be a few VS code extensions for it: https://marketplace.visualstudio.com/items?itemName=moetelo.... and https://marketplace.visualstudio.com/items?itemName=Stanisla...


I’m always surprised by how performant the Cohere models are. They output quick. I tested out the BF16 and it seems pretty good. I tried out the FP8 one and it did seem a bit dumber. Curious to see how this ranks in benchmarks


Maybe look at https://void.cloud/ (Edit: sorry, meant https://viteplus.dev/, not Void cloud)

They are not a runtime, but they do seem to be interested in wrapping a lot of tools with simple top-level commands


There seems to be a "neuter" fork out there that disables a bunch of stuff: https://github.com/GarethCott/warp#whats-different-from-upst...


Looks like there is a "neuter" fork out there: https://github.com/GarethCott/warp#whats-different-from-upst...


There have been a number of people leaving them because of that bait and switch it seems. That 20% turned out to be something closer to 2% or even 1%


I noticed that too. I’ve been using cmux (based on ghostty, has a more basic UI) and have been happy with it: https://cmux.com/


I feel similar. I have been using cmux over the last few weeks: https://cmux.com/

Seems to fit a good balance for the way I want to use my terminal


Love cmux but lately it's having performance issues. It is not responding for a few seconds when I switch between terminals in the same workspace. I'm tired of it and just use ghostty. I miss the notification from cmux though :(.


You’re paying the subsidized cost. Those margins will shrink once the real bill comes due. I really think everyone will look back at this time as the golden area of cheap AI. We are already seeing the costs (and restrictions/limits) creep up with the Western models.


I think the opposite. AI will get cheaper as models become more efficient and we solve the datacenter/energy problem. I bet 10 years from now AI, that is way better than what we have today, will be close to free.


Just like how cloud costs got cheaper and we solved the datacenter/energy problem over the past 10 years.


For the most part, we did, actually. We had plenty of energy and computer until AI came along.

Energy will get fully solved eventually. To think otherwise is to bet against humanities ability to innovate, which I don't think is ever a wise bet.


ZIRP and Moore have helped the cloud build up with a promise of profits and ever increasing performance. The future is likely different.

"Power will be cheap" is hope you can hang any hat on. We've been increasing compute per watt but again that's on Moore. I don't think it makes sense to bank on a new energy surplus.


Cloud did get cheaper. What are you saying?

I just ran a quick gpt check - EC2 Prices have gone down by more than 80% after accounting for performance and inflation over last 20 years.


You can practically host a website that serves millions of users a day for nearly free using Cloudflare. Imagine doing that in the year 2000.


It amazes me how productive it's possible to be using AI, but I also has this nagging feeling that we are being reeled into being so reliant on this that when the price starts going up, we will simply eat the cost.

The math is pretty simple, and it's easy to justify still paying the price even if it goes up 10 fold, when compared to hirering more resources its still cheap.

So I guess having multiple players and competition in the market is the key?


Going forward, models will start specializing. Anthropic will build a BioMed model for large drug companies. A math/compsci model for frontier theoretical research. A physics modelf or nuclear research. They can communicate each other for synergy effects e.g. for areas where math meets biomed etc. This will be cost reducing as well. We plebs don't need advanced models for our plumbing software work. Following example applied to AI capabilies will make it clear.

Does everyone need a graphing calculator? Does everyone need a scientific calculator? Does everyone need a normal calculator? Does everyone need GeoGebra or Desmos ?


I don’t see why this would happen when the modern models already use MoE, which gives them most of the benefits of having specialized models.


as long as the chinese exist and offer alternatives I think were going to be okay in terms of price, as long as you dont lock in in any american model


Compute has been getting exponentially cheaper nonstop for decades. Much more likely that current capabilities are effectively free within 5-10 years


> I really think everyone will look back at this time as the golden area of cheap AI.

Chinese models like Deepseek v4 are as good and 10 times cheaper. You can even run Deepseek locally. So no, cheap AI wont be over. Just the US investors won't be able to profit off of the artificial bubble that is there now but wont be in the future.


> You’re paying the subsidized cost.

100% agree. I have been trying to tell everyone to build their ideas, and exploit this environment where 100B of VC money into OpenAI/Anthropic = some percentage of money invested into your idea. This is the golden era of building! The music is gonna stop soon. Build now ffs!


The open models of similar scales (ex. the new 1T deepseek model) are a fraction of the cost per token, so I don’t see how that can be the case. Inference is profitable, it’s the training that makes it unprofitable.


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