B.Eng (Mechatronics)
Slower is better obviously but as to the inevitability of ASI, I think reaching top 99% human capabilities in a handful of domains is enough to stop the current race. Getting there is probably not too dangerous.
Current ATGMs poke a hole in armor with a very fast jet of metal (1-10km/s). Kinetic penetrators do something similar using a tank gun rather than specially shaped explosives.
"Poke hole through armor" is the approach used by almost every weapon. A small hole is the most efficient way to get to the squishy insides. Cutting a slot would take more energy. Blunt impact only works on flimsy squishy things. A solid shell of armor easily stopped thrown rocks in antiquity. Explosive over-pressure is similarly obsolete against armored targets.
TLDR:"poke hole then destroy squishy insides" is the only efficient strategy against armor.
Modern vehicles/military stuff are armored shells protecting air+critical_bits+people
Eliminate the people and the critical bits can be compacted. The same sized vehicle can afford to split critical systems into smaller distributed modules.
Now the enemy has make a lot more holes and doesn't know where to put them to hit anything important.
This massively changes offense/defence balance. I'd guess by a factor of >10. Batteries have absurd power densities so taking out 75% of a vehicle's batteries just reduces endurance. Only way to get a mobility kill is to take out wheels.
There are still design challenges:
Quantity has a quality of its own. Military vehicles are created by the thousands, cars by the millions. Probably something similarly sized or a bit smaller, powered by an ICE engine and mass produced would be the best next gen option.
EMP mostly affects power grid because power lines act like big antennas. Small digital devices are built to avoid internal RF like signals leaking out (thanks again FCC) so EMP doesn't leak in very well. DIY crud can be done badly enough to be vulnerable but basically run wires together in bundles out from the middle with no loops and there's no problems.
Only semi-vulnerable point is communications because radios are connected to antennas.
Best option for frying radios isn't EMP, but rather sending high power radio signal at whatever frequency antenna best receives.
RF receiver can be damaged by high power input but circuitry can be added to block/shunt high power signals. Antennas that do both receive and transmit (especially high power transmit) may already be protected by the "switch" that connects rx and tx paths for free. Parts cost would be pretty minimal to retrofit though. Very high frequency or tight integration makes retrofitting impractical. Can't add extra protection to a phased array antenna like starlink dish but it can definitely be built in.
Also front-line units whose radios facing the enemy are being fried are likely soon to be scrap (hopefully along with the thing doing the frying).
TLDR: Jamming is hard when comms system is designed to resist it. Civilian stuff isn't but military is and can be quite resistant. Frequency hopping makes jamming ineffective if you don't care about stealth. Phased array antennas are getting cheaper and make things stealthier by increasing directivity.(starlink terminal costs $1300 and has 40dbi gain). Very expensive comms systems on fighter jets using mm-wave comms and phased array antennas can do gigabit+ links in presence of jamming undetected.
Self driving cars have to be (almost)perfectly reliable and never have an at fault accident.
Meanwhile cluster munitions are being banned because submunitions can have 2-30% failure rates leaving unexploded ordinance everywhere.
In some cases avoiding civvy casualties may be a similar barrier since distinguishing civvy from enemy reliably is hard but militaries are pretty tolerant to collateral damage. Significant failure rates are tolerable as long as there's no exploitable weaknesses.
Time of flight distance determination is in some newer Wifi chips/standards for indoor positioning.
Time of flight across a swarm of drones gives drone-drone distances which is enough to build a very robust distributed positioning system. Absolute positioning can depend on other sensors like cameras or phased array GPS receivers, ground drones or whatever else is convenient.
Overhead is negligible because military would use symmetric cryptography. Message authentication code can be N bits for 2^-n chance of forgery. 48-96 bits is likely sweet spot and barely doubles size for even tiny messages.
Elliptic curve crypto is there if for some reason key distribution is a terrible burden. typical ECC signatures are 64 bytes (512 bits) but 48 bytes is easy and 32 bytes possible with pairing based ECC. If signature size is an issue, use asymmetric crypto to negotiate a symmetric key then use symmetric crypto for further messages with tight timing limits.
Current landmines are very effective because targets are squishy/fragile:
Clearing an area for people is hard
drones can be much less squishy
Eliminating mine threat requires
This is enough to deal with immobile off route mines. If the minefield has active sensors, those can be spoofed and/or destroyed or blocked at slightly higher expense. Past this, the mines have to start moving to be a threat and then you're dealing with drones vs. drones, not mines.
Ideal mine clearing robots and drones in general should be very resilient:
I think GPT-4 and friends are missing the cognitive machinery and grid representations to make this work. You're also making the task harder by giving them a less accessible interface.
My guess is they have pretty well developed what/where feature detectors for smaller numbers of objects but grids and visuospatial problems are not well handled.
The problem interface is also not accessible:
A more accessible interface would have a pixel grid with three colors for empty/filled/falling
Rather than jump directly to Tetris with extraneous details, you might want to check for relevant skills first.
Rotation works fine for small grids.
Predicting drop results:
I'm using a text interface where the grid is represented as 1 token/square. Here's an example:
0 x _ _ _ _ _
1 x x _ _ _ _
2 x x _ _ _ _
3 x x _ _ _ _
4 _ x _ _ o o
5 _ _ _ o o _
6 _ _ _ _ _ _
7 _ _ _ _ _ _
8 x x _ _ _ _
9 x _ _ _ _ _
GPT4 can successfully predict the end state after the S piece falls. Though it works better if it isolates the relevant rows, works with those and then puts everything back together.
Row 4: _ x o o _ _
Row 5: _ o o _ _ _
Row based representations with rows output from top to bottom suffer from prediction errors for piece dropping. Common error is predicting dropped piece square in higher row and duplicating such squares. Output that flips state upside down with lower rows first might help in much the same way as it helps to do addition starting with least significant digit.
This conflicts with model's innate tendency to make gravity direction downwards on page.
Possibly adding coordinates to each cell could help.
The easiest route to mediocre performance is likely a 1.5d approach:
This breaks the task down into subtasks the model can do (string manipulation, string matching, single digit addition/subtraction). Though this isn't very satisfying from a model competence perspective.
Interestingly the web interface version really wants to use python instead of solving the problem directly.
Not so worried about country vs. country conflicts. Terrorism/asymmetric is bigger problem since cheap slaughterbots will proliferate. Hopefully intelligence agencies can deal with that more cheaply than putting in physical defenses and hard kill systems everywhere.
Still don't expect much impact before we get STEM AI and everything goes off the rails.
Also without actual fights how would one side know the relative strength of their drone system
Relative strength is hard to gauge but getting reasonable perf/$ is likely easy. Then just compare budgets adjusted for corruption/Purchasing power parity/R&D amortisation.
Building an effective drone army is about tactical rock paper scissors and performance / $. Perf / $ emphasis makes live fire tests cheap. Live fire test data as baseline makes simulations accurate. RF/comms performance will be straightforward to model and military is actually putting work into cybersecurity because they're not complete morons.
Add to that the usual espionage stuff and I expect govts to know what will work and what their enemies are doing.
Ukraine war was allegedly failure to predict the human element (will to fight) with big intelligence agencies having bad models. Drone armies don't suffer from morale problems and match theoretical models better.
Vulnerable world hypothesis (but takeover risk rather than destruction risk). That + first mover advantage could stop things pretty decisively without requiring ASI alignment
As an example, taking over most networked computing devices seems feasible in principle with thousands of +2SD AI programmers/security-researchers. That requires an Alpha-go level breakthrough for RL as applied to LLM programmer-agents.
One especially low risk/complexity option is a stealthy takeover of other AI lab's compute then faking another AI winter. This might get you most of the compute and impact you care about without actively pissing off everyone.
If more confident in jailbreak prevention and software hardening, secrecy is less important.
First mover advantage depends on ability to fix vulnerabilities and harden infrastructure to prevent a second group from taking over. To the extent AI is required for management, jailbreak prevention/mitigation will also be needed.