hodder

Forgive me because I do not understand the supply chain for memory. With Micron et al effectively scalping their customers with an oligopoly on probably the lowest intellectual IP in the chain, does this not guarantee 10 years from now a) We are either overbuilt as hyperscalers cut capex, or b) hyperscalers vertically integrate. Or is it truly that hard to make memory?

And if that is not true, perhaps it isn't really a commodity at all.

The claim that Alberta is actively trying to get rid of all wind and solar development is internet hyperbole that ignores real capacity data. Alberta actually ranks second in Canada for clean energy growth, and its renewable output surged by over 25% year-over-year into 2026.

The high-profile project cancellations people point to weren't a government ban. They happened because the province changed its transmission rules. Previously, ratepayers subsidized the massive utility costs required to connect remote wind and solar farms to the central grid. The province ended this, forcing private developers to internalize their own grid connection costs. Once forced to pay for their own infrastructure, highly speculative, unfinanced projects simply became economically unviable and dropped out of the queue.

If a private wind or solar developer wanted to build a massive farm in a remote, rural area (like Southern Alberta) where land is cheap but high-voltage power lines do not exist, they only had to pay for the immediate wire connecting their project to the nearest local substation. Taxpayers were subsidizing those players, because it was a "load pays" system.

Please do not fall pray to the general trope that Alberta is a backwards hillbilly province. Subsidizing private developments with public money is not something that should be encouraged.

On Canada broadly, you are correct in your baseload numbers and I agree with you.

(Energy trader here)

Your arguments are much lower quality than an LLM will generate. You are so transparently biased against them it is shocking. I’d certainly rather learn from an LLM than someone like you who is both grossly misinformed and a dick about it.

They absolutely are good at checking work. It really depends on the level and you are grossly underestimating their ability and over generalizing their limitations. To say an LLM can’t grade pretty much any undergraduate level or under subject well is to not understand how far they’ve come.

On average yes this is almost certainly true. As I said above technology is a lever and most people are incredibly lazy. However if one has drive and determination they are also incredibly powerful tools

Spot on analogy.

See my response above on this.

recently vibe-coded a personalized skateboarding block-training app. The platform maps curated YouTube tutorials to specific tricks I want to learn, logs my daily progress, and tracks failure rates alongside the specific reasons for missed attempts.It also functions as a structured video journal that integrates seamlessly into my coaching routine. For instance, during a session of 10 daily kickflip attempts, the app logs my success metrics and video capture so my coach can review my exact mechanics. Over time, this data-driven feedback loop visualizes my progression curve and systematically improves my landing consistency.

In another case I follow a bodybuilding cutting regimen and it helps me create and track recipes consistent with my diet plan and macro guidelines. It helps me also create tasty recipes that fit my criteria based on the ingredients I have on hand.

Those are just 2 examples.

I also recently built a backyard jib setup with a platform, ramp, PVC jib rail for snowboarding, and it helped me architect the design for it.

Once more, you are making massively blanketed biased assumptions about me.

You seem to believe LLMs cannot even produce simple exams and rubrics is that right?

When did I say I wasn't doing and just reading. That is your own heavy bias creeping in.

Your initial response post was to me, and you absolutely injected the heavily biased assumption that I was doing no active learning.

Sifting through information to separate truth from fiction is a modern, experience-based skill that I’ve developed YES.

However, your perspective on how LLMs are used might be too narrow. While no one is suggesting using an AI to find a one-shot cure for Alzheimer's, LLMs are incredibly effective tools when paired with textbooks to master subjects like undergraduate physics.

You are very closed minded. LLMs can absolutely give pragmatic and fast information in a useful (non-sycophantic form). You need to examine your extreme biases here.

Just because you can't use a tool doesn't mean the tool isnt useful.

Your bias on display here is frankly silly. Im not saying LLMs are ALWAYS the best way of learning something just like they aren't always the best at anything. They are a valuable tool though. Yes so is youtube and textbooks, and professsors, and peer review literature, and pen and paper, and block training etc.

Nonsense. Absolute nonsense. Ive crafted LLMs to create drills and practice exams etc. Im not just reading about new sport activities, or videography/photography or linear algebra or physics. I'm putting it into action. As I said above, technology is a lever. Maybe you are just reading stuff and not drilling problems. That isnt me.

You really just need to augment with tight prompting and know how to extract information and links to peer reviewed literature and well sourced information. Once again, technology here is a lever. Separating wheat from chaff has been key in academic and information pursuits forever and it is becoming ever more important.

Im learning new things at a pace I never imagined at 40 years old. New sports, new businesses, new academic pursuits. Technology is a lever and AI is the biggest lever we've ever had. It enables laziness or incredible productivity. Choose your own path forward.

What is your question here? Has anyone considered monte carlo search for code gen?

Yes. Alphazero etc. Surely the labs extensively research ideas like this. Do you have a specific task you are inquiring about?

I just (vibe) coded up a little block training app for skateboarding. I noticed that the vast majority of skaters don't land anything consistently and just huck their skateboard around. Unlike in other sports where people follow some sort of progression most skaters never learn fundamentals or practice in a logical way. This is my solution to that using modern block training, progression gates, and tracking methods. This is still a tiny MVP:

https://blainehodder.github.io/shredlog/

Most skateboarders don’t land tricks, they just huck boards around haphazardly.

This was an idea to bring an ultra barebones mvp to skateboarding to see if people might like the idea.

Voting for separation (as oppose to actually separating) is absolutely in the best interest of most Albertans.

You cannot be serious. The Freedom convoy may have been misinformed but the government response was an absolute disaster and the courts have agreed.

Entropy balancing cannot fix unobserved confounders.

"Teasing out causation" is exactly why this methodology fails. You are confusing the intended purpose of a statistical tool with its real-world validity. No one is questioning what an Entropy-Balanced Poisson Regression or a Synthetic Difference-in-Differences model is designed to do.

The issue is that the authors have profoundly violated the mathematical assumptions required for these tools to actually function. Throwing high-level econometric terms into an abstract does not make the underlying logic scientific, but rather acts as a linguistic tuxedo on a fundamentally broken causal claim.

If you cannot see through economic (and other) confounders that invalidate their approach and their biased statements, I cannot help you. This isn't science. Getting an LLM to run an SDID model and spit out a result doesn't = science.

I know what a linear regression is and how to examine event studies, lol. What you don't understand is that the author is leaning on linguistics to insinuate strong evidence of causation where it doesn't exist. If this was a quant in finance, they'd be out the door in days.

"The problem isn’t science at all; the problem is people and politics."

Agree completely.

"Entropy-balanced Poisson and synthetic difference-in-differences event studies"

LMAO does the author really take themselves seriously as they type that.

This author has no understanding of statistical methods. This sort of article is the reason why people distrust science. Not because the scientific method is flawed, but rather because nonsense like this get published.

Of course the market can and this is a silly question. These issues are tiny amount of money for the global capital markets to swallow. Masa Son has endangered ostrich eggs for breakfast worth more on the daily. I kid, but seriously this is a very small amount of money to the global markets. It is more of a worry on the psychology than the size.

Remember they arent selling the entire floats of these companies. I cant read the article because Im not willing to pay for the Economist, but 400-500b in equity issuance is not a big deal to the global financial markets even though it sounds big.

Exact same argument for crypto though. It is all just supply demand. BTC has much more demand currently and likely more sustainably. Alt coins are just less popular. It is all just supply vs demand.

We do this now with something even less intrinsically valuable than tulips: BTC.

It all just comes down to supply and demand.

Spot on. That is what I was trying to get at.

It's a specific subtype of Gell-Mann Amnesia effect. They "know" AI cant do their own jobs, but it seems pretty good at summarizing what others do without understanding the nuance. It seems to really apply to the AI Lab CEOs who appear "shocked" everyone isn't simply replaced with LLMs by now so the timelines get kicked.

Gell-Mann Amnesia AI effect. They "know" AI cant do their own jobs, but it seems pretty good at summarizing what others do without understanding the nuance. It seems to really apply to the AI Lab CEOs who appear "shocked" everyone isn't simply replaced with LLMs by now.