Detecting the AI answers is an arms-race.
MangoCats
joined 5 months ago
$100K for a safer driver might be well worth it to a lot of people, particularly if it's a one-time charge. If that $100K autopilot can serve for seven years, that's way cheaper than paying a chauffeur.
Not self driving but "driver assist" on a rental we had recently would see skid marks on the road and swerve to follow them - every single time. That's going to be a difference between the automated systems and human drivers - humans do some horrifically negligent and terrible things, but... most humans tend not to repeat the same mistake too many times.
With "the algorithm" controlling thousands or millions of vehicles, when somebody finds a hack that causes one to crash, they've got a hack that will cause all similar ones to crash. I doubt we're anywhere near "safe" learn from their mistakes self-recoding on these systems yet, that has the potential for even worse and less predictable outcomes.
They're also selling self-driving cars... the question is: when will the self driving cars kill fewer people per passenger-mile than average human drivers?
It's mostly a joke about Alien's fictional face hugger and how people carrying one inside look normal, until...
Also, anything that's too free for too long is likely to either disappear, or turn to profit seeking at some point.
It's a bit of "emergent properties" - so many things are happening under the hood they don't understand exactly how it's doing what it's doing, why one type of mesh performs better on a particular class of problems than another.
The equations of the Lorenz attractor are simple, well studied, but it's output is less than predictable and even those who study it are at a loss to explain "where it's going to go next" with any precision.
Steam locomotive operators would notice some behaviors of their machines that they couldn't entirely explain. They were out there, shoveling the coal, filling the boilers, and turning the valves but some aspects of how the engines performed - why they would run stronger in some circumstances than others - were a mystery to the men on the front lines. Decades later, intense theoretical study could explain most of the observed phenomena by things like local boiling inside the boiler insulating the surface against heat transfer from the firebox, etc. but at the time when the tech was new: it was just a mystery.
Most of the "mysteries" of AI are similarly due to the fact that the operators are "vibe coding" - they go through the motions and they see what comes out. They're focused on their objectives, the input-output transform, and most of them aren't too caught up in the how and why of what it is doing.
People will study the how and why, but like any new tech, their understanding is going to lag behind the actions of the doers who are out there breaking new ground.
in the 60s. Heck, they were even working on neural nets back then
I remember playing with neural nets in the late 1980s. They had optical character recognition going even back then. The thing was, their idea of "big networks" was nowhere near big enough scale to do anything as impressive as categorize images: cats vs birds.
We've hit the point where supercomputers in your pocket are....
The Cray-1, a pioneering supercomputer from the 1970s, achieved a peak performance of around 160 MFLOPS, it cost $8 million - or $48 million in today's dollars, it weighed 5 tons
Modern smartphones, even mid-range models, can perform significantly faster than the Cray-1. For example, a 2019 Google Pixel 3 achieved 19 GFLOPS
19000/160 = over 100x as powerful as a Cray from the 1970s.
I just started using a $110 HAILO-8 for image classification, it can perform 26TOPS, that's over 160,000x a 1970s Cray (granted, the image processor is working with 8 bit ints, the Cray worked with 64 bit floats... but still... 20,000x the operational power for 1/436,000th the cost and 1/100,000th the weight.)
There were around 60 Crays delivered by 1983, HAILO alone is selling on the order of a million chips a year...
Things have sped up significantly in the last 50 years.
Distill intelligence - what is it, really? Predicting what comes next based on... patterns. Patterns you learn in life, from experience, from books, from genetic memories, but that's all your intelligence is too: pattern recognition / prediction.
As massive as current AI systems are, consider that you have ~86 Billion neurons in your head, devices that evolved over the span of billions of years ultimately enabling you to survive in a competitive world with trillions of other living creatures, eating without being eaten at least long enough to reproduce, back and back and back for millions of generations.
Current AI is a bunch of highly simplified computers with up to hundreds of thousands of cores. Like planes fly faster than birds, AI can do some tricks better than human brains, but mostly: not.
AI has been advancing exponentially, it's just a very small exponent.
In the 1980s, it was "five years out" - and it more or less has been that until the past 5-10 years. It's moving much faster now, but still much slower than people expect.
They think because they saw HAL in the 2001 movie back in 1968, that should have been reality by the 1970s, or certainly by 2010.
Some things move faster than people expect, like the death of newspapers and the first class letter, but most move slower.
I have seen this happen before, for a while, then somehow M$ convinced them to switch back.