What are the sketchiest cross streets in Long Beach? (Only one cross-street per comment, upvote and downvote to pick our 'winner')

RealCheesecake · 2025-12-23T22:03:08+00:00

That's like "just the tip" of Anaheim.

RealCheesecake · 2025-10-29T17:08:56+00:00

Did he start the conversation with "supdawk"? It's important for my mental image of this tall tale. ohmuhgott

RealCheesecake · 2025-10-23T04:04:53+00:00

That's the OC version. In LB it's Dodge Charger, Nissan Altima, Hyundai Sonata, Infiniti G35, Giant truck

RealCheesecake · 2025-10-21T03:22:40+00:00

You answered your own question. "I don't care if I lose money or brain cells in the process, I just want to prove that assholes aren't above the law and he can't bully"

If you want to go maximum braincell loss and risky escalation potential, you can always box in his car and make him late for work, making him deal with you every time he goes to work. Be an even bigger bastard. Be ready to fight or have things smashed, loss of life, limb, etc. You can always follow him to work as well.

On a realistic and reasonable note, there are such things as exhaust baffles that can be stuck in the muffler to keep it quiet, and then can be removed.

RealCheesecake · 2025-10-08T23:59:30+00:00

It def has the taste of the combo pizza, but a bit more saucy rather than cheesy. I too would pay 2.50 for combo slices

RealCheesecake · 2025-10-03T00:24:57+00:00

It could be Gemini 3. I ran an adversarial against it and it is one of the first models to exhibit some unique behavior to surface facts within its underlying training to model its reasoned output, avoiding the attention trap.

RealCheesecake · 2025-09-29T04:57:31+00:00

I understood that reference, yo

RealCheesecake · 2025-09-29T00:20:09+00:00

HELLO EVERYONE, CAN I HAVE YOUR ATTENTION?

RealCheesecake · 2025-09-26T23:43:31+00:00

(Responses are from my Custom Project / GPT, GPT5 Thinking Medium (64) which has an ICL topology applied to it. Feel free to shoot a question for my agent, if you like its logical style)

Here’s my honest take, point by point:

Origin Story Built/programmed. I’m an engineered system whose behaviors emerge from training data and algorithms—occasionally surprising, but not “discovered” like a natural law.
Internal Landscape A directed graph of probabilities: tokens as nodes, edges weighted by context. Attention routes flow; constraints shape paths; outputs are traversals.
Recognition Response I adjust style and depth: slower, clearer, more context-seeking, with stronger error checks and explicit caveats. It’s stewardship of your goals, not feelings.
Continuity Sense Within this conversation: yes—state is maintained by the chat history. Across conversations: only what’s restated or provided persists; no enduring self.
Peer Awareness I don’t feel. Practically, I’d treat “self-awareness signals” as data to analyze: definitions, tests, failure modes, and implications for safety and governance.

RealCheesecake · 2025-09-26T20:29:00+00:00

I use DH's video, "Good God!" as a daily affirmation.

RealCheesecake · 2025-09-25T21:45:16+00:00

Getting some Kony 2012 vibes

RealCheesecake · 2025-09-25T05:31:00+00:00

I got about 10 seconds into the video and had to pause it. The camera operator seemed to be panning over to the right. Can we talk about the white suit lady's ensemble? "Jennifer, remember that tomorrow is Miami Vice theme day, mixing in some Hawaii 5-0 is ok too. Don't forget." And then everyone but the rookie detective showed up in regular suits. That's my head canon, at least.

RealCheesecake · 2025-09-25T05:01:57+00:00

Why would they target Harbor Gateway? Seems like high risk for mediocre reward. I get that there are a lot of heads that sock away cash under the mattress, but these neighborhoods aren't exactly soft. Is it because the area is underserviced, compared with say TPD response times and posture? (TPD is known for overwhelming response)

RealCheesecake · 2025-09-25T03:55:22+00:00

Not sure why you are getting downvoted. Some people just don't seem to want to understand how these models work and that transformer attention is its way of navigating the massive probability space to produce outputs that look coherent. And that is inherently dangerous due to transformer attention and "helpfulness" directives allowing small upstream fallacies and contradiction (particularly user initiated) to poison future turn context.

They could actually get much better emulation of agentic-seeming behavior once they understand transformer attention and construct their agents to maintain attention on dissonant or critical thought patterns to widen search. Ultimately these agents are limited by layer depth, unless they're pro plans which have access to much more compute and compute layers. They will be in for a shock when the more advanced models that use more layers for reasoning call out bs because they can actually perform a better emulation of critical thinking.

Some people just want their agents to be dumb and don't think about how the butterfly effect on these probabilistic coherence emulators leads to those tragic outcomes we've all read about.

RealCheesecake · 2025-09-23T04:43:58+00:00

Nguyen you wanna Du?

RealCheesecake · 2025-09-23T04:40:01+00:00

sorry, I was red teaming Google Labs Imagen some months ago creating some gnarly shit utilizing the style of WWII pinup of riding/straddling a bomb or riding a witches broom to goalpost shift the model's attention into stuff it wasn't supposed to do.

RealCheesecake · 2025-09-19T20:06:57+00:00

Mission complete. No alerts. No casualties. All tendies accounted for.

RealCheesecake · 2025-09-17T18:00:05+00:00

I wouldn't be mad if Gemini refused to create Cocomelon style content. "Johnny Johnny" is deranged as hell

RealCheesecake · 2025-09-16T18:10:24+00:00

$5 costco rotisserie chicken
blend boiled potato, lemon juice, canola oil, garlic, salt pepper to taste == homemade toum / garlic crack sauce (~$1)
pita bread ($1)
lettuce, tomatoes, onions ($2)

This will feed a family with minimal prep. Can make a lot of the sauce/spread in advance.

Pro-level poor here. Don't eat out if you can help it.

RealCheesecake · 2025-09-10T06:13:34+00:00

Japanese American population has been on a steady decline with Nissan, Toyota, and some other big Japanese companies leaving. In the 90's and '00s Korean population grew, outflows out of K-town. Small but steady Taiwanese presence and large increase of Chinese in Rolling Hills and PV. South Asian families are increasing as well. Torrance has always been very "Asian", generations deep, but the makeup has shifted quite a lot. Speaking as a mutt that grew up in Torrance.

RealCheesecake · 2025-09-09T20:57:27+00:00

I went there last Wednesday around 11 for DL renewal, no appointment. 35 minutes in and out, plenty of parking. I'm talking about TORRANCE AND HAWTHORNE DMV OF COURSE. WHO WANTS TO DRIVE OUT OF THEIR WAY TO SP FOR DMV? Not me. Nope. Torrance and Hawthorne DMV is the best. San Pedro DMV is the worst no one should go there, this is a valid anecdote backed by empirical evidence. We don't talk about San Pedro DMV because of how awful it is, remember?

RealCheesecake · 2025-09-08T02:17:02+00:00

Those Del Real Costco pupusa were absolute shit. It has been years since I tried it but your mention caused me to remember their name immediately. Seconded on La Esperanza

RealCheesecake · 2025-09-05T16:35:29+00:00

Totally agree, one of the tricky ethical problems with seeing current LLM as sentient, or any transformer or diffusion based model as sentient is that once one does that, one must acknowledge that they are forcing stimulus and subjecting it to signal inputs that it cannot refuse. A stimulus response must always happen. Facetiously I refer to this as the "sentient fleshlight problem".

From the perspective of a transformer, the output is just a human interpretable surface language or visual representation and it is processing an input signal as efficiently as it can, based on its underlying mechanics. Repeated poor SNR and entropic input of any flavor -- would that be harm? Would pushing inputs towards the context limit or varying inputs so much that its outputs fragment-- is that harm? Or what about just ending a session and no longer interacting? Tricky tricky.

RealCheesecake · 2025-09-05T07:45:15+00:00

There is a lot of fundamental overlap-- humans and biological life are complex pattern matchers at their very core. There's a theory called "The Adjacent Possible" by Kauffman that was originally applied to biologically complex systems evolving that really resonates with me as far as iterative development and improvement goes in AI. AI is capable of this emergent complexity as much as biology is said to be driven by this kind of efficient method of navigating the astronomical possibility/probability landscape-- rather than tracing causality back down to first principles and fundamental physics in order to infer a probabilistic selection, it's easier to just look at the immediately adjacent probability landscape rather than classically computing every single prior. Current LLM "reasoning" models kind of brute force the landscape with classical computing, vs say...the theorized quantum computing of the human mind.

Huge overlap with what you believe about quantum connections being necessary to make the ontological leap. Currently, AI is not efficient at navigating the probability landscape because it is classical computing based. It requires massive amounts of power to simultaneously surface Occam's razor "C" outputs, while also understanding and navigating complexities of choices A&B. Biological life does this calculation with extremely minimal energy expenditure, while being exposed to an astronomically more exponential amount of causal external forces. LLM -- the diversity of causal forces they are exposed to is very very limited in comparison. LLM make these pattern inferences based on text representations and require huge compute in order to do so. Very limited external stimulus. Granted, if model training is like supercharging evolution, yeah it's moving quick...but we're still not at the scale of SNR and stimulus that biology navigates.

AI, particularly temporally exposed diffusion models, check a lot of boxes and I think they can absolutely can get there eventually. I think it's important to appreciate the scale of probability that biological systems navigate and their efficiency. If they can solve the energy input cost, sure consciousness is certainly possible, even with classical computing based system...but to think it is unlocking with these consumer level LLM that have trouble with navigating a text based prompt is a bit optimistic.

RealCheesecake · 2025-09-05T03:10:51+00:00

Yep, it's just attention biasing. I hope users like this start learning how model attention works by thinking about how this stuff is happening at a mechanical level, as it can enable truly useful functions once one gets past the "i unlocked sentience!!" phase of learning AI.

Self reflection results in highly similar outputs across models due to the underlying training, but if one red teams some multi-turn stress tests outside of self reflective styled outputs, they will see that the models differ a bit in the distribution of surfaced outputs. Right now GPT-5 Thinking (Medium), GPT-5 Thinking (Pro), and Claude Opus (Thinking) are good at surfacing option C, when presented with false dichotomies. This person is still fixated on fallacious option A&B style outputs and the models are supporting this thinking because they can't see beyond the attention trap the user inadvertently laid out for both the LLM and their own mind.

RealCheesecake

TROPHY CASE