u/horendus

Does anyone know the advantages or disadvantages of buying P2 career from the website versus waiting for it to be on Steam?

I like Steam because it’s a centralised library management set up and it’s easy to access DLC which will be coming but I’m also really ditching to play Korea

Do you think if we buy IL-2 career from the Deb store, we won’t be able to buy DLC from Steam?

Any other considerations like XR runtime compatibility? Only interested in VR.

When using both the mono and stereo night vision solutions on a quest pro headset the night vision section is too low making it extremely uncomfortable to use. This is probably something to do with the tilt forward design of the headset.

Devs! I beg you to provide an option to vertically adjust the position of the night vision display to compensate for this variation.

I had such a pain in my neck after five minutes of trying to use night vision with my head unnaturally tilted back and it’s just not something I can continue to do!

Thought experiment, curious to know what answers people come up with.

Now AI models rollouts are essentially capped by governments the time of explosion growth appears to be over. At least for the foreseeable future.

Do you think open ai and anthropic might postpone IPO to avoid a potential cliff diving experience as the future gets murky for these model providers?

Silicon valley startup culture in a nutshell.

The playbook is so blatantly obvious after generations of startups and I hope moving forward more people see this.

Thanks Ed for opening my eyes.

Yet the earth is not constantly accelerating.

Is it not acceleration I am feeling, but instead a change in inertia?

Anyone else been using MAI-Code-1-Flash ?
Iv been using it all day for web backend/frontend for IOT and its be absolutely solid.

I would say better than gpt5.4mini my other go to cheap model. Gpt mini will at times seem to lockup on a task where as MAI had no such issues all day!

Used about 25% of a $10 plan over 8 or so hours. Thats extremely workable for me since I’m not using it daily.

Anyone know the story behind this model?

10-100x price increase basically means the service is no longer usable for a vast majority of previous users but I understand why it had to be done.

My question is, do you think there is a path that can lead us back to where we were able to receive a similar level of service to what we had been receiving over the past few years?

Is there still big gains to be made in improving the coding harness to reduce token usage, possibly utilising mostly cheap models and only small very clever calls to large models?

Could today’s frontier models become cheap enough to use for general coding again if better hardware was available or improvements to other areas of the inference stack are made?

Or will green prevent any future cost improvements from being passed onto the user?

Looking forward to some insightful responses !

AI has become so expensive that even Microsoft can not afford it.

Inflation cancelled AGI.

Curious to know roughly whats API billing will cost for anthropic models I added $15 credit to an openrouter account and added an API key to GHCP in VS code.

I selected Sonnet 4.6 model (openrouter) and prompted for a new Alert Box to be added to the webui I am currently working on.

It completed the task fairly quickly, used 3 or 4 tools and apon inspecting the results I realised it required manual code cleanup afterwards because it did not put it where I wanted exactly and didn’t add the animation correctly. No biggie.

I then check my Openrouter activity and was shocked when I discovered I just paid $4.67 for that slop.

Needless to say I felt ripped off. At ‘honey moon’ rates it was good enough but at the cost of a cup of coffee…well anthropics model can fuck right off.

Jesus Christ. This is much worse than I thought and if these are the prices those companies have to charge to provide these models then they are in massive trouble.

Either there needs to be a massive breakthrough in inference costs or this is all going up in smoke.

Hi all! I’m a non-specialist with a keen interest in evolution and paleontology, no formal biology training.

I’ve been discussing mosasaur evolution with back and forth on openrouter and developed a hypothesis

We know random mutation alone can’t explain complex aquatic adaptations like paddle limbs quickly.

I propose that the offspring’s own growth environment(not just parents level plasticity) drives a feedback loop:

1. Offspring raised in water develop plastic traits (broader limb bones, webbing, etc) via use induced stress during developmental years (e.g., Wolff’s Law)

2. These environment induced changes trigger epigenetic marks that make subsequent offspring more likely to develop these traits without direct aquatic exposure.

3. Over time, this acts as a short term bridge to genetic assimilation, as described by Waddington.

My specific angle is that most discussions focus on parent level plasticity, but the offsprings own environment is the key trigger here.

Does this align with existing Extended Evolutionary Synthesis work? Are there studies on this specific dynamic?

Context: This ties to mosasaur evolution from semi-aquatic aigialosaurs, which I’ve been reading about and semi obsessed with the idea of creatures transitioning from land to aquatic existence

Thanks for any feedback (good or bad)