I have no skin in the game, but I will do that for you, if you bring back the children from the death. Can you do that? Let's start from the Nakba. Maybe even from last year.
No one is asking people to go back to Europe. All you have to do is Stop the Genocide, Repair. Reconcile. And stop the apartheid. But you know what, you have decided that Israel is untenable without war. Israel is of no use to the neo Imperialists, unless it keeps the region unstable.
hey just got back on and the papers you shared are the main works that I was about to link. There's also a new VLA paper fro waymo https://arxiv.org/abs/2410.23262v2
In addition to the papers on end-to-end learning for robotics, it might also be worth reading about the state-of-the art in classical robotics. There's a lot of debate in the field about whether end-to-end learning and scaling will solve robotics[1]. On the E2E side, there's the bitter lesson, scaling for LLMs and other AI success cases. On the skeptical side, there's the reliability limit (has anyone seen any ML cross the 1 failure out 100,000 barrier on real data?), and the bitter-er lesson (scaling on search can be better than scaling on data and classical robotics is scaling search instead of data). Data availability is a blocker for research, but in production many use-cases are profitable with teleop so data can be collected profitably, especially with UX design to make teleop more efficient.
Navigating in stair-free commercial environments was solved in mid-2009 by classical planning + SLAM with LIDAR, and open-sourced in the ROS navstack. A LIDAR-free version using stereo cameras was also open-sourced shortly thereafter. The navstack is still maintained and integrated by Open Robotics[2] and Opennav[3]. These techniques (and in many cases forks of the OSS code) power e.g. 10,000 bear.ai robots in restaurants today, as well as some of the newer Roombas. All of this is CPU-only, and can run on a NUC.
Classical planning has also solved arm navigation quite well. The modern technology here is MoveIt! 2[4]. MoveIt! uses essentially the CAD model of the arm (which most robot manufacturers provide in the correct format) plus data about objects in the environment from sensors to plan motions. There are modules to create smoother, human-like motions as well. All of this works efficiently on CPU-only.
Lastly, LIDAR-less SLAM and mapping is also starting: https://docs.luxonis.com/software/ros/vio-slam. LIDAR costs have also fallen to the point where robot vacuums are sold with integrated LIDARs.
The main area where classical has not made as much progress is on soft objects (e.g folding towels) and on object detection. Classical point-cloud based object detection for example is based on correspondence grouping[5], but overall everyone is using at least partially neural nets for these problems.
As for end-to-end in prod without human-in-the-loop, covariant and ambi are the only cases I've seen so far. They benefit from having the ability to have a classical safety layer and a classical success detector via e.g. object weights (I'm not sure what approach they are using, I've just seen object weight elsewhere). With that they can get the much-desired data flywheel effect of self-improving systems.
It does not generate power to provide thrust; it generates power - using the airstream as the aircraft moves through the air - for the avionics and/or hydraulics.
Magenta MAX is T-Mobile's unlimited data plan; $170/mo for 2 lines.
2 lines with unlimited data with Mint is ~$60/mo. You are paying $35/mo because you're only getting 5GB data. Check how much similar plans cost in India, Europe, Israel, UK (spoiler: they are drastically cheaper).
You are delusional if you think T-Mobile and the other big network providers offer good value for money.
Having recently switched to Mint after years of being swindled by T-Mobile, I'm really sad to see this news.
T-Mobile Connect is their existing $15/month prepaid plan comparable to Mint's. It doesn't require a bulk purchase, just keeping enough prepaid balance so that the monthly $15 fee can be deducted.
Last I checked, it had half the monthly data (2GB vs 4GB) and the same unlimited voice and texts policy. I don't follow along closely, so the limits may have changed again.
I wonder if they will reorganize any of that after acquiring Mint.
> You are delusional if you think T-Mobile and the other big network providers offer good value for money.
What part of
> I'm sure some MVNOs are a lot cheaper, and I'm all for it.
did you not understand?
BTW, T-Mobile's cheapest plan now has 10GB - which is more than probably 95% of users need? Paying $60/mo for that via Mint is just money thrown away for most people. To give you an example, I never exceeded 5 GB/mo, let alone 10GB, in over 10 years of using smartphones.
