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’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
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.
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.
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 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.
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.
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.
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