what if you move the microphones and speakers at varying but precise speeds so that doppler shift can be used to shift frequencies? you could play a tone on the speaker, shift the relative velocity (spin the microphone really fast?) and calibrate a frequency range of the microphone. with a calibrated mic frequency range, you can now calibrate that range of the speaker. repeat. each calibration step is going to accumulate error. to be clear, not a practical solution, but fun to theorize.
In some situations the US has gone to war with countries who not long after are close allies. Germany comes to mind, but there are others. In other cases the situation you describe is more accurate. What are the primary factors that influence one outcome or another?
As someone who has been following deep learning for quite some time as well, Bengio and Hinton would be some of the first people I think of in this field. Just search Google for "godfathers of ai" if you don't believe me.
Not only this but my Chromebook wasn't upgradable even though the parts weren't soldered in. I tried upgrading the Wi-Fi/Bluetooth module but it wouldn't grab the latest drivers so I had to stick to the old Bluetooth that barely reaches across the room.
Its obvious why it is set up this way. That said, it can be hard to see other people who make the same wage, spend it all on fancy cars and a bigger house get more aid when you've been living modestly and saving resulting in less aid.
Or you know, talk to your spouse about it first. I dropped down to $0 income for 2 years with two kids and a wife. My family is as strong as ever.
Obviously just one data point and divorce rates are high. Do you have any data on this specific case: depressed about job, quits job to be happier, results in divorce. It seems quiet possible that given the circumstances, quitting the job might decrease the chance of divorce by helping remove so much stress from work.
Yeah right, in my experience I haven't needed as many networks in the ensemble as I first assumed. This paper [1] suggests 5-10, but in practice I've found only 3 has often been sufficient.
Right, the claim was that "Neural networks give probability estimates. Bayesian methods give us probability estimates AND uncertainty" which presents a false dichotomy. I think we agree.
It is common for a network to output the distribution, so the output is both the mean and variance instead of just the mean like you pointed out. For example check out variational autoencoders.
1) make the sortition group big enough, say 1000 or 10000 people, so the required number of people bribed goes up, which increases bribery cost as well as chances of getting caught
2) make a bounty program to help put a lower bound on the cost to bribe
Terran Robotics | Bloomington, IN | Full-time, Onsite\Hybrid
Hiring for two roles: AI/Robotics/Software Engineer and Structural/Materials Engineer
At Terran Robotics, we're building construction robots that turn dirt into extraordinary homes. We've got $6m+ in LOIs, we're building our first production unit right now and completing 2 paid projects in the spring of '23 to de-risk the tech. We aren't inventing a new material. Our walls are similar to adobe which means they are already accepted in building code and already loved by home buyers. The only reason adobe is expensive is because it's built by hand. Our robots change that.
We are looking for people who want to join our small team and get this product off the ground. Specifically, we are looking for someone who has experience with one or more of the following: computer vision/SLAM, AI, robot control, reinforcement learning. We've got our current material and structural system permitted, but are looking for someone with a structural engineering and/or material science background interested in taking it to the next level.
You can actually push a bit if current backwards through the cell to heat it up. Some people have tried this but not sure about what prevents this from being more wide spread
I actually find the "build something that is probably wrong faster" really helpful. I frequently write a function and a quick bit of documentation about what it should do, let copilot finish it, realize my intent was wrong, rethink the intent, etc. If I didn't have copilot I would follow the same process, but it would take a lot longer to realize my intent was wrong.
It takes some time to learn what copilot is capable of and how best to prompt it, but I'm my experience it very quickly pays off.
I use filters all of the time, but they frequently don't work (as mentioned but a sibling comment) sometimes the filter value don't allow a range so if you want anything between 10 and 100 you have to select all of the values between 10 and 100. Other times, the options aren't sorted so you have to select 10,000 uf and 10 mf and 0.01 F. Still other times numeric values are sorted alphabetically so you get 1 ohm, 1.1 kohm, 1.2 megaohm, 2 ohm, etc. So to select a range you need to clock through around the entire range of values looking for the order of magnitude you want.
I wish digikey was as good as McMaster. With digikey I often have to parse through a huge table with many pages to figure out what the difference is between a bunch of search results. On McMaster you can clearly see search results categorized in sub tables and densely arranged to make clear what the options are.
Are there any electronics websites that actually organized like McMaster?
And what about the highly skilled lower paid workforce also using automation in China? And with fewer safety requirements the machines are cheaper too.
It is possible you could get away with that in some places, but everywhere I've lived in the US, it is illegal to sell electricity to your neighbors. The only way around it I've seen is to give it away for free, but it is hard to build a scalable business around that.
I've received money from the NSF SBIR grant program and know another half a dozen others who have as well, and while there is certainly a process, it isn't too bad. All the people I know who have received them are at startups and small companies. That said, the NSF does more than just SBIR and I can't speak to any of that.