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From a consumer standpoint are two arm robots ready to do anything useful yet for us? From your experience.

Folding laundry seems like one but then quickly falls apart the more I think about it. Not sure what else.

It’s great hearing Artosis’ voice again. He also commentated one of the DeepMind AlphaStar show matches.

Claude is the most expensive route for enterprise. With copilot at least you can choose cheaper models if things get too expensive and restrict them in the worst case. None are cheap though you’re talking hundreds of thousands to millions of dollars a year if you have over a thousand people using it.

Thank you for writing this.

Tons of value left, especially for open source models. I would say the benchmark is yet to be truly saturated (just look at the legs and seat to see what I am talking about) and I always look forward to seeing them. Thank you!

Anyone else make the switch to projectors from TVs as a primary way of watching media?

I encourage those who want to read more to start a book club with their friends. My club has read 6 books now and it gets at two things the article mentions, isolation and illiteracy.

I’ve recently also subscribed to a few in print magazines to address the desire for up to date recent information we get from social media.

HN is still hard to quit, the amount of useful information here is still high. digg.com summarizes X which I’ve found to be useful for not feeling like I am missing out on discussions there.

If you’re a copilot cli user (we exist) you know that the auto mode leaves something to be desired. It only changes models at the start of a session or after compaction. Most dev tasks are now sub agent heavy and there is no model routing on the sub agents.

I do notice that there is no mention of effort levels in the comparisons. 5.6 Luna Max is really good and really cheap. A 5.6 Sol high orchestrator with 5.6 Luna max is cheap, has frontier level performance, and is faster than Sol alone. This can be accomplished with simple agent instructions. Looking forward to running my own benchmarks on HydraFusion to see how it fares. Gone are the days of a single model doing all of the work it seems, unless the work requires no tool calls.

What’s fun at the staff level is anticipating issues with the foresight that comes with experience. Going deep on a new tech so that when a situation arises, you are ready with the right tool and the depth to back it up. This is another way to deliver value the staff level.

Having this work on Apple metal is huge for the accessibility around training splats. I remember two years ago I needed an RTX Nvidia GPU to run things like splatfacto on nerfstudio. Very neat optimizations as well like the depth map and sky dome, 3dgs has come a long way. Awesome!