Unfortunately I'm 5'7 and even the low roof transit is 6.8. So it's paying >$10K more for a pretty non-ergonomic solution.

> seems too small to even be useful for that.

One advantage of a bed when transporting 2x's is that you get the hypotenuse. So the bed goes further than you'd think in terms of load length. The 60/73 beds of the tacoma are certainly better than the mavericks, and those trucks are still smaller/same size as the transit.

But my actual observation is that, in cities, transits just really are strictly more annoying and dangerous to drive than a mid-sized truck. Maybe it's just me, but maintaining situational awareness on an unprotected bike lane to my right in a transit is way way way more difficult than the same in a mid-sized truck.

The shorty transit connects from the 2010s aren't what the modern line-up looks like. Modern transits are heavy long wheel-base vans with surprisingly large displacement engines and unfortunate blind spots.

I do get the animosity about trucks on city streets (...I bike to work and pass 4 ghost bikes every morning and evening and have had my share of close calls...).

But as a bicyclist, I'd rather ride next to a tacoma or ranger than a current gen transit. And it's not even close.

If you bicycle and prefer vans over trucks on your streets, I encourage you to test drive any 2026 transit. It'll change how you ride around vans, even if you're already a careful cyclist.

Maybe in the past, but the size thing isn't really true of the modern line-up. Relative to eg a base Tacoma or especially a Maverick, The Ford Transit has about the same wheel base, is slightly heavier, has worse visibility (for me at least), has a larger displacement engine, and is on a pragmatic level more difficult to maneuver and park. They also have far fewer creature comforts, which wouldn't be a huge deal if they didn't MSRP at $10K MORE than a base midsized truck!

Vans also don't have 4x4, have much lower ground clearance, no good mechanism for transporting longer stuff, and you can't hose them out nearly as easily as a truck bed. The main thing that those vans are built for is just lots of weight in the van. Great fits for some use-cases, but not mine.

And, again, they're just seriously expensive for what they are because of all the commercial applications.

I did also consider an old minivan or a used van from previous generations when they made the smaller transits. Again, 4x4/awd isn't really super optional in these parts, so pickins were slim.

But it's still funny to me. Because in my mind one of the main perks of an open bed is that you can do so much before having to deal with a trailer (which are super annoying, especially in cities, especially without off-street parking).

Which I guess is just to say: maybe there's a market for a truck that can't tow much, because maybe there's a portion of the market that wants an open bed but doesn't need to tow a massive camper or whatever.

This is why I'm excited for REO.

I live in a pretty dense city and don't have much storage space in my residence. On the weekends I'm clearing and developing a lot a couple of hours away. My vehicle doubles as storage for all the stuff I need for that and don't want to leave unattended (saws, tools, winch, etc).

I used a Forester for the first two years, which was cramped but doable. The bigger issue was messes. Oil has a way of getting everywhere. I also had one gas spill from a faulty saw gas cap which was both dangerous and a huge PITA to clean up. I also got to a phase where the difference between awd and 4x4 matters, and where I was yanking milled planks around which didn't feel safe doing with the forester.

I switched to a truck after a couple of years and went small. The box is completely full between tools, saws, gas, winch, ropes, etc. When I do groceries I can usually fit some of the "hard" bags back there (cans, bottles) but the rest has to go up front.

A REO would be great for my use-case. The price is low enough that for the price of a new Tacoma or F-150 I could (get close enough to) buying both a REO and a used beater 3/4 ton at the property, which is a better fit for the things I need a big truck for anyways. And I wouldn't be driving a dumb big truck around a very cramped city.

For now I'm stuck with a big truck in the city because owning more than one personal vehicle in this town is insanity.

FWIW, transporting (even large) bikes in the bed of a truck is doable and normal. The typical way to do this isn't with a hoist. You just ride or walk it up a ramp and tie it down.

ofc a Forester or RAV4 with a trailer is a far superior solution, especially for interstate driving where the trailer is less of an annoyance.

The concern about poor precedent stemming from poor cases has some rational sense, but we have the benefit of experience. Empirically it just hasn't tended to play out like that in the case of consumer protection statutes in MA. One reason this doesn't happen in practice might be the limited bandwidth of the appellate process. The SJC could (and likely would) prioritize answering questions about the statute in the context of cases brought by the AG.

The longevity pro-consumer laws in MA provides some good empirical data that cuts against the concern about push-back.

It'll have reach because MA has a long-arm statute and there's a rich history of applying that statute in the context of Chapter 93.

It'll have teeth but probably not to the effect that you hope.

This statute was written such that only the Attorney General can bring action; see Section 10(b). This diverges from a long history in the Commonwealth of allowing private individuals to bring civil suits for most types of Chapter 93 violations.

As a result, I anticipate that the most impactful change will be in the quantity and frequency of political donations to Mass AG candidates (and in the case of contested primaries their aligned block of candidates up and down ticket).

Consumer protection laws should always provide for a private cause of action. Otherwise they just function as a mechanism for legalized corruption.

Got your email. Let's connect there.

I was not talking about the output of models.

I'm referring to the model itself. The `.ckpt` file is clearly transformative wrt its training set. Or, at least, substantially more transformative than other things that have long received fair use protection.

> Like, I get that you're invested in the industry

On the contrary, I'm invested quite heavily in the exactly opposite hypothesis -- that the ChatGPT/Claude/Gemini UX you're referring to is not fit-for-purpose.

> How the heck would you train children and adolescents on the responsible use of AI?

By teaching them how it works, how it doesn't work, and to think of it as a unit of computation rather than an anthropomorphic entity.

We are hiring a Senior Scientist to join our team. We're working at the intersection of LLM training and the inference stack.

We're looking for someone who wants to work in the following intersection:

* Both implementation experience and theoretical background in compilers, programming languages, or programming models. We have an absolutely requirement for someone with mathematical maturity in formal systems (programming language theory, type theory, proof assistants, etc.)

* practical experience pretraining and rl tuning LLMs (or skill-adjacent experience / expertise)

* practical experience developing or modifying inference engines for LLMs

From an academic perspective, think "POPL/PLDI/OOPSLA/CAV/etc." + "NeurIPS/ICML/AISTATS/etc.".

The job posting for a Senior Scientist position, with rough salary ranges, will go live soon. I'll edit or post a reply with the link when it's live. For now, if you have expertise at some intersection of the above topics, please feel free to reach out: nathan@ibm.com

Application link for Research Scientist position: https://careers.ibm.com/en_US/careers/JobDetail?jobId=118292...

We also have a Research Engineering role for which we're actively interviewing: https://careers.ibm.com/en_US/careers/JobDetail?jobId=113488...

I've thought a lot about how to safely deploy autonomous systems (even did a whole PhD on the topic, lol).

I think one can ethically deploy a system that has some degree autonomy. It takes a lot of work to do right. And the tooling for LLM-based systems isn't quite as mature as the tooling for e.g. control systems. Part of this is because so many resources in AI safety are misspent on problem statements that are myopic or grandiose. Between "don't say pii" and "prevent ASI extinction" there's a hard but tractable control systems-y view of AI safety.

But I don't think there is any sort of fundamental barrier that prevents us from building appropriately constrained LLM-based systems.

> And even then, there are such copyright issues with it. Is there no practical ethical use for AI? Responsible use doesn't equate with ethical use for me.

When responding to a position, especially on the internet, I try to empathize with the thing I'm responding to. Not just understand it, but sort of put myself in a mental state where I have an emotional attachment to my conversation partner's point of view.

With respect to Copyright as a legal framework in my country (USA): despite my best attempts, I really struggle to develop empathy for the viewpoint that LLMs/diffusion models are not a transformative use. I can certainly sympathize, but trying to actually put myself in the shoes of believing that training an LLM is a purely derivative and non-transformational work just feels far too alien. There are so many things that are "clearly transformative" but required so many orders of magnitude less scientific/technical/engineering genius.

Which isn't to say that the US legal system's definition of copyright is the morally correct one.With respect to copyright beyond the US legal system, or beyond legal denotations generally: I can certainly empathize.

It's the same as calling a gun a "powerful hole puncher".

There is a reasonable objection that a gun is such a powerful hole puncher that it is not merely a hole puncher. But the clear implication of that objection is that the user of the tool now has more responsibility and that the tool should be treated with more respect/care.

LLMs are a tool. The impact of using that tool is the responsibility of the end-user. As the tool at hand becomes more powerful, the care with which the end-user should treat that tool increases.

For some reason, with LLM-based systems, we seem to be going the opposite direction. As the tool becomes more capable people absolve themselves and others of more responsibility. This feels backwards to me.

(Aside: in a lot of ways, at least form a scientific and engineering perspective, modeling LLMs as "fundamentally auto-complete" is an incomplete theoretical model but one from which we can still get a lot of mileage.)

Our team thinks there's a lot of value in co-design of software harnesses and LLMs, particularly for small/medium models, particularly in the open model space.

Our colleagues across the isle do an awesome job at training the Granite model series, so we (physically and organizationally) sit in a uniquely good place to do impactful work in this space.

I am currently looking for early career scientists and engineers who are interested in LLMs and also one of {programming languages, formal methods, compilers}. Experience with Rust is a plus. Cool systems-y projects with formalizations on paper or in rocq/lean/etc also a plus. Neither is necessary, per se.

If this sounds interesting please send over an email: nathan@ibm.com

    answer_initial = llm(prompt=prompt, site=site) # JSON with answer and any stuff needed to do heuristic checks.
    heuristic_results = heuristics(answer_final) # rule based.
    answer_final = llm(prompt-prompt, site=site, answer=answer_initial)
    mark_for_review = ... # basically just a bunch of hard-coded stuff I add flag possible failures for review.

I was referring to the smaller ones -- `granite4:micro`, `granite4-latest`, `granite4:350m`.

> I'm grabbing one now that's apparently double digit GB?

You are probably downloading one of these two ids: `granite4:small-h` or `granite4:32b-a9b-h`.

The "small" model _is_ small in relative terms, but is also the largest of the currently released granite models! At 32B parameters (19GB download) it's runnable locally but not in the same "run on your laptop with acceptable performance" category of the nano/micro models.

> Also my "dev enviornment" is vi -- I come from infosec (so basically a glorified sysadmin) so I'm mostly making little bash and python scripts, so I'm learning a lot of new things about software engineering as I explore this space :-)

Shameless plug: if you're writing Python scripts to automate things using small locally hosted models, consider trying out https://github.com/generative-computing/mellea

Mellea tries to nudge toward good software engineering practices -- breaking down big tasks into smaller parts, checking outputs after nondeterministic steps, thinking in terms of data structures and invariants rather than flow charts, etc. We built it with "actual fully automated robust workflows" in mind. You can use it with big models or small models, but it really shines when used with small models.

Yes, the granite 4 models are on ollama:

https://ollama.com/library/granite4

> but my interest is specifically in privacy respecting LLMs -- my goal is to run the most powerful one I can on my personal machine

The HF Spaces demo for granite 4 nano does run on your local machine, using Transformers.js and ONNX. After downloading the model weights you can disconnect from the internet and things should still work. It's all happening in your browser, locally.

Of course ollama is preferable for your own dev environment. But ONNX and transformers.js is amazingly useful for edge deployment and easily sharing things with non-technical users. When I want to bundle up a little demo for something I typically just do that instead of the old way I did things (bundle it all up on a server and eat the inference cost).