digdugdirk

Oooo, that's fun! Excellent write up, thank you for that.

Obligatory "Don't forget the doohickey!"

But in all seriousness, the KLR is such a great example of this mindset. Find the tool that suits your needs, learn how it works and how to maintain it, and you're set for life.

Not really - fine tuning can be done on much lower tier hardware, with much smaller datasets. With a model like Qwen 3.8 27B as the core, a small fleet of LoRA adapters for whatever specific use cases you need would be incredibly competitive with the current frontier. Sure, future frontier models will likely continue to improve, but will people need them for everyday usage? I'd wager not. Unfortunately, my wager is dwarfed by OpenAI's and Anthropic's.

Do you have a link to that statically typed Fennel compiler? That sounds fascinating.

I know this sounds ridiculous, but try fine tuning a small local shell -> plain language model, then using the output of that for whatever you need on your end. You'll get the gist of what the frontier model is trying to accomplish, and can handle it with whatever harness workflow you want.

Pinned at the front and back on a rotating axis down the centreline of the car, with the "car" itself being mostly lightweight composite with zero internal components other than the necessary air tanks and a large RC car motor to get it to roll up to the jump point? For the support structure, just put some dark matte scaffolding in the background so it stays out of shot and hidden by the light show. It wouldn't be too far off from standard wirework for movie stunts, and the compressed air could still do enough work to fool the eye. It's not like people have an innate sense for what a gas thruster powered flying car should look like anyway.

But you know, that's just off the top of my head.

They were aiming for better concurrency, I believe. If you're rewriting something regardless, might as well use a more modern language that's easier to reason about during development.

Did you read the article? Meta themselves aren't confident that what they're doing is legal, and they're very clear about the fact that it might be clawed back by the IRS because they're abusing a tax credit intended to be used for experimental research by putting their massive data centre build out into that "experimental research" bucket.

If a company's accountants and lawyers are concerned enough to bury disclosures in their securities filings to cover themselves, but the company leadership is brazen enough to proceed anyway, I'd say that's plenty of justification for people to be mad at the executive leadership.

The US Petroleum Reserve is governmental, not done by the oil industry. The US government buys and stores oil when prices are low to provide a buffer for volatility in the markets or for things like natural disasters. The reserve being low means that the oil companies are very close to having a market that has no alternative but to pay whatever price is asked for oil.

To your point about oil and LNG being expensive to transport - that just means oil corps can turn down production at the locations impacted, and jack up the prices for whatever is produced in the locations that aren't. Lower operating costs + higher revenues = profits.

It really is a perfect storm for massive returns for the major players. As a bonus, it's impacting the Saudi and Russian national players, which are their toughest competition since they don't need to file any quarterly reports. I agree that it can't go on forever, but the oil industry is rolling around in money like Scrooge McDuck in the meantime.

Right, that's exactly my point though. Those are absolutely valuable use cases. But are they useful enough to justify a trillion dollar valuation? Or is most of the economic value in the stuff that already exists, and can be performed nearly as well by qwen/deepseek/kimi/GLM/etc?

And beyond that - how long until those individual Astra capabilities are distilled into separate Qwen-27b size models, with harnesses and scaffolds specifically designed to support that functionality?

The difference now is that they've hit the "good enough" point. LLMs are a tool, and that tool is useful but not incredibly valuable unto itself.

To make a manufacturing analogy - ChatGPT was a manual machining mill, and in the years after we've gone from that to a 3-axis CNC mill. Now we've added a 4th and 5th axis, which is great for the 2% of parts that need that functionality. But the big win was that initial jump from manual control to CNC. Why would I pay an extra $2 million for my CNC machine when I could just design my parts to be simpler to produce instead? The AI labs are trying to make these incredibly complex tools, but the market doesn't want/need them so they're competing on price for the tools that people do use. By selling their metaphorical CNC machines for half of what they cost to produce.

Oh, and we've bet the entire economy on the hope that fancier CNC machines will magically solve all our problems in all industries, from healthcare to the legal system.

So - will AI progress continue to improve? Sure. Will we continue lighting money on fire in order to make it happen? That remains to be seen.

Thanks for posting this! Love your team's work.

Ha. Amazon's in-app AI agent is called Rufus. It's incredibly annoying, and they love directing you to an 'Ask Rufus' page where you watch an AI agent not-quite-finish repeating your search terms back at you before you realize you're not actually on your search results page, and then spend some additional time trying to find the link to take you to said search results page.

I assume somewhere there's a team hitting their AI query KPI's due to this, but I really wish they'd shut off a few server racks and save everyone the annoyance instead.

I've seen previous needle releases running on esp32s - any idea how well this new one would run on something like the newer esp32-p4?

Of course it was. They clearly decided that the benefit to the company valuation was higher than the potential downsides when announcing to the world that they committed a criminal act via negligence.

If it wasn't a marketing stunt, they would have at most quietly settled any legal matters with huggingface behind the scenes, fixed their evaluation harness so it wouldn't happen again, and avoided the potential future liability.

It sounds like your issue is with capitalism, not with renewable energy. Luckily, we have plenty of examples of aspects of society that have been deemed too important to leave purely to market forces. In fact, electricity generation is already (mostly) one of them.

As solar and batteries become even cheaper (we're already at the point where they're cheaper than anything else) we can just choose to overbuild capacity and turn down/off whatever other generation isn't necessary at any given time. Utilities already have to predict grid usage based on weather and all sorts of other factors, so it's not like this isn't something that isn't already happening.

Not quite. Looped models do the extra "thinking" inside the model's layers. So the token gets twice the number crunching performed on it before it gets spit out. I think of it as the first loop "kickstarts" the process, and the second loop refines it.

I mean, that's cool and all, but the numbers are really going to shift when it accidentally goes off and orders that same hardware from every vendor in your local region and the top 5 online results for comparison.

It's the same problem as all other LLM solutions (that I hope OpenAI is working on!) it's non-deterministic, and there's no way for the user (or model provider) to know what the distribution of possible outcomes is. This just gets compounded when multi-call harnesses come onto play.

Is this Python in Rust in WASM in Go?

The Monty name was a perfect choice, Yakety Sax was playing in the distance as I read through the readme.

Jokes aside, I do love seeing WASM as a bridge to enable cool stuff like this.

So much of the current bubble is predicated on the hype train continuing on its current trajectory. If anything lags behind, the bubble deflates.

For one potential path - Less datacenter construction means less GPUs, so less $$$ for Nvidia, which means less for them to spread around to prop up the LLM industrial complex, which means lower valuations, which means OpenAI and Anthropic can't get their trillion dollar valuations, which means VC's race for the exit to cash out, etc, etc.

Same! Still getting used to it, but the benefits of being able to host my notes on my Tailscale network are huge. Having a built-in Lua engine to customize the interface and content is a really interesting concept, though I'll admit I haven't explored it beyond adding an AI assisted voice to text button. Still, it's been fun using it!

Kinda? Originally a Canadian subsidiary of a British company, privatized in the 80's, then sold to Boeing, then bought back by Bombardier with big financial support from the Ontario government, then sold off to a domestic buyer in a corporate restructuring. Their big commercial aviation product is an old Bombardier design.

To your point - Even as domestic "competition", the market is still separated by aircraft type.

And honestly, their history is a good example of why countries act in this way. When they were sold to Boeing, it seemed to be a way for Boeing to "grease the wheels" in order to land a big Air Canada contract. When Airbus got the contract instead, Boeing immediately put De Havilland up for sale and let the company languish until it was purchased by Ontario/Bombardier. Corporate histories can be interesting!

Honestly, most of the incentives aren't aligned with breaking them up or trying to lower prices. If the large corporate entities were broken up, they wouldn't have the scale to compete against their much larger American counterparts. They'd either get pushed out or bought up. And low prices aren't the goal for a company that is protected by government policies - they'll aim to maximize profits within the policy framework instead, and the framework itself does the job of preventing competition from smaller upstart rivals.

Think of the Canadian aircraft manufacturer Bombardier. Canada wants to keep a domestic aircraft manufacturer around so they have a backup in case of US shenanigans (like what just happened with the F-35) so the government ensures there's ongoing contracts for those domestic aircraft as well as subsidies for things like manufacturing plant expansion or modernization. But Canada's population only needs so many aircraft, so why would they waste government resources on a new upstart rival aircraft manufacturer? Bombardier knows this too, so why would they spend their own resources on R&D or modernization when they know they can get the government to pay for it instead? It's a feedback loop, and not necessarily a good one.

Yes, Canadian dairy prices were always higher than US prices, probably by 10-20 percent or so. There's an internal quota system, and a prescribed allowable volume for imports with very high tariffs on imports above that prescribed limit. Canada did this to protect its dairy industry, and to ensure there's a level of self sufficiency to their food production.

Canada has the same issue in many industries, where the need/desire for Canadian firms to compete against US firms - even though Canada has a population roughly a tenth the size of the US - results in a handful of bloated monopolies/monopsonies that the Canadian population has to deal with.

For an alternative perspective you can look at the US healthcare system, where the US has a protectionist system that props up its healthcare industry (insurance, providers, pharma companies, etc) at the expense of its population, to the tune of about 2x what Canada spends per capita.

Canadians who live near the border will commonly hop over for some shopping and fill up their tank with cheap gas, while Americans try to fill their prescriptions from Canadian pharmacies and travel to Mexico for procedures they can't afford to get done in the US. It's all a matter of what the system is set up to do.

If the US military purchased camera guided smart munitions with a miscalibrated camera, such that it ignored adult targets and instead specifically targeted children, would that also be a simple mistake per your argument?

What model? And what hardware do you run it on?

I find these style of models are great, but fail hard, and fail randomly. I'd be hesitant to use it for a daily driver, but I'm using dual 3060s, so it's not like I'm quantizing a frontier model here.

How do you find the overall experience? And do you have any special sauce or recommendations for going this route?

In regards to people with reasons to illuminate several sq km at once - I'd bet that major metro areas would see a massive savings in electricity/maintenance if these were deployed over a metro region. Whether that is more than the cost of a satellite? Who knows, it's still fiction until these people try it out. But it's at least an interesting use case.

Super cool! I noticed you had a blurb about it being used for mesh networks? Could you please go into more details/provide links to resources to learn more about that?

Ooo... Any chance you remember where you read that? I'd love a reference to check it out. Sounds interesting!

Other fields of engineering usually have a regulated licensure, upon which they can call themselves a Professional Engineer. This gives them the ability to make final approval/sign-off on designs and technical reports. It's most common in civil engineering, where a PE license is required for all publicly funded projects (and most privately funded ones as well, due to local/regional/national regulations) to be approved.

This license requires the holder to uphold code of professional ethics, and makes the engineer themselves be personally responsible for the safety and viability of the design itself. Losing a PE license is rare, but it does happen. The industry board (usually a regional board) can also discipline/reprimand engineers who fail to meet the professional standard - rubber stamping projects, personal misconduct, etc. Losing a license is a huge deal, but even reprimands can have a serious negative impact on someone's career.

In the industry the previous commenter works in their hypothetical would absolutely meet the bar for discipline or reprimand.