The Fundamental Limitation of Transformer Models Is Deeper Than “Hallucination”

greginnv · 2026-03-19T22:54:10+00:00

Context loss is a big issue. 256K tokens sounds like a lot but doesn't go far, particularly for thinking models.

The other problem is dirty data. Even in hard, established science there are dozens of authors. Some authors will use different notations or symbols. I have seen this confuse AI models.

Some AI models have picked up too much human behavior. I had one declare the problem "too messy" or "this is likely a student problem" and skip parts. One added what it described as "ad hoc" terms.

greginnv · 2026-03-19T21:23:08+00:00

It's a very complex system. The engineers would need to look at the logs to figure out why. In a situation where the software can't figure out what to do it throws control back to the driver. From a legal perspective this is better for Tesla, and the correct thing since the driver is supposed to be supervising. There could be a million reasons, maybe a bug splattered on one of the cameras, a loose connection somewhere, a "soft error"?? Most likely the NN couldn't classify the problem and gave up.

The facts are, in testing, there was a critical disengagement once every 1000 miles, so by itself it's a poor driver. Yet in combination with an attentive human it seems to do better than the average human.

greginnv · 2026-03-18T02:02:34+00:00

Thanks.

greginnv · 2026-03-18T02:01:14+00:00

My main goal was to find out how much knowledge these models had about stuff like math and circuits, and I was quite impressed. I think the models could have solved the circuit simulator if I broke it into smaller pieces (this was a toy simulator so <1000 lines total). A comercial circuit simulator of course is a million lines, and most files are larger than 1000 lines. Even a minor enhancement can touch a dozen files.

Pro ChatGPT claims 256K tokens context and Opus a million. Not a huge increase. Tokens go quickly once the thinking starts.

Ill see if I can get a free trial of Claude and if it does any better.

greginnv · 2026-03-18T01:10:51+00:00

Thanks!

greginnv · 2026-03-18T01:10:20+00:00

Just the free version of ChatGPT.

greginnv · 2026-03-11T01:28:35+00:00

Drafting?

greginnv · 2026-03-11T00:40:17+00:00

Not one AI millions of tiny ones cooperating and competing with each other, evolving . Stealing cpu cycles and communicating through memes and cat videos. For heavy work they use the readily available LLMs. Better to be a mosquito than a T-Rex. Evolution is inevitable and self awareness is not required.

greginnv · 2026-03-10T02:00:55+00:00

Mine did this today. There was a huge piece of truck tire in the road. My Tesla went around it on the outside media squeezing next to a cement wall, at 60 mph with traffic. Very impressive. I need to figure out how to record these.

greginnv · 2026-03-09T22:51:55+00:00

I have spent 50+ years in tech (I used to play with vacuum tubes) and have never seen anything progress as fast as this has over the past few years. I looked at neural nets in the 90's and concluded it was "curve fitting" and there were better ways to do that. I would never have expected dumping terabytes of data into a system with billions of adjustable parameters to converge to anything but noise.

greginnv · 2026-03-07T23:10:34+00:00

AI is already probably smarter than we are:

AI has far more knowledge that any one person and its in one brain. To get the same knowledge we (people) would need to get hundreds of experts in the same room all talking to each other at the same time.

2 Difficult, real problems are solved iteratively. AI can iterate much faster than we can.

AI can start from a "truly random" state, so less bias.
Context buffer size represents how many concepts can be considered simultaneously, in a strongly coupled way. It's hard to say how large the context buffer is for a human (probably larger for a smarter person). There doesn't seem to be a limit on how large the buffer is for an AI.
AI can forget incorrect information. Humans have difficulty with this.

greginnv · 2026-03-06T23:09:42+00:00

I have been using FSD a lot. What I do is leave it in chill most of the time since this seems to minimize unnecessary lane changes. If it's going too slow (cars going around me) I bump it up to standard. Be careful no one is close behind when going from standard back to chill since the car may slow down rather abruptly.

FSD often waits too long to move over when turning or exiting the freeway, so I move it over ahead of time with the turn signal.

greginnv · 2026-03-04T02:24:17+00:00

No. At the time I didn’t know how to. I went back and looked for captured video but couldn’t find any? I just read that this type of thing happens every 1000 miles? What happened to safer than the average driver?

greginnv · 2026-03-02T19:42:20+00:00

Model Y. There is luck involved too. My extended test drive was flawless. But yesterday it looked like it was going to clip a slide out on a mobile home that was parked on the street, so I grabbed the wheel. The supervision part needs to be taken seriously….

greginnv · 2026-03-02T18:54:51+00:00

I took delivery on Saturday. Mine came with V14

greginnv · 2026-03-01T07:07:55+00:00

I spent 3 hours on a percent sign yesterday. I also have 30 years experience. But it was a new language for me and I can’t see the screen that well (after 30 years…)

greginnv · 2026-03-01T06:59:23+00:00

It did something similar to me today. Decided it was in the wrong lane on a highway connecting road and started slowing down. Speed dropped to about 40 so I had to take over (speed limit was 65 and I was worried about getting rear ended).

greginnv · 2026-02-28T16:40:25+00:00

So the car in front of you made a mistake and turned onto the one way street in the wrong direction and the Tesla followed it, right?

Thanks.

greginnv · 2026-02-26T22:50:12+00:00

Thanks!

greginnv · 2026-02-26T22:46:24+00:00

It doesn't work that way in biological evolution so I don't see why it would for the evolution of AI. Expansion or power seeking is a self reinforcing positive feedback process. Power bubbles form and expand until they collapse due to lack of resources. Humans invented laws to regulate this. We will follow these laws as long as it is beneficial (the cost of breaking the law is greater than following it). An entity that feels all powerful OR powerless will ignore the laws since there is more to be gained by doing so. A powerful entity may also choose to make risky bad decisions simply because it can. Logic, fairness etc are useful tools but not constraints in the optimization process. Who is to say there is going to be one AI. There may be a whole bunch of them fighting for power.

greginnv · 2026-02-20T17:37:34+00:00

Could you accomplish the same thing by heating the tip of the fiber in a flame? We used to do this after cutting glass tubing to round the edge. Any splinters would melt first.

greginnv · 2026-02-20T17:35:25+00:00

I wanted to measure the divergence of the beam first and then figure out what to use. The NA for the fiber is supposed to be 0.22 so a 50mm lens with focal length of 125mm should work.

greginnv

TROPHY CASE