bradfa

How well do modern projectors which cost comparable to consumer TVs do when the room may get indirect sun through windows? This is my one fear that would hold me back from serious projector consideration.

I'm glad they're reporting it as the energy storage capacity and not the power output capacity. Too many news sites like to report the power output capacity in stories like these, which is horribly misleading, and then often they also frame it as though this is equivalent to adding actual power generation to the grid, which is even more misleading.

SELV usually is defined to have both a voltage limit and a volt-amp (ie: power) limit. Generally defined somewhere around 60V peak to peak and 250V*A.

48V is under the SELV voltage limit, even with some margins.

But historically, some countries have had lower limits. I recall Japan being one of them for a while. I'm not confident that SELV is a harmonized standard worldwide, or at least it wasn't until recently, if it is now.

The browsers could kick ALL their keys out and break all of eMudhra's customers websites. Those customers could sue.

Many HSMs do not force you to use unique labels for keys. So it's somewhat understandable if a human mixed up some keys during a non-standard or deviated process. This doesn't explain how so many different keys were "generated" so poorly or why no one cared about mismatched signatures.

And the discussion mentioning wrap/unwrap testing kind of feeds directly into the fear that either:

1. These weak keys were created outside the HSM and then imported.

2. These weak keys were meant to be the wrap keys somehow. Like, if they hadn't paid for some of the wrap/unwrap features on one of their HSMs and so were using easy-for-humans keys to handle the wrap/unwrap operations so they could more easily move keys between HSMs.

Good leadership requires brains. Average leadership is attainable without brains.

Curious how realistic the skills learned in such a program are still applicable in 1-2 years. This industry is moving very fast, it feels like the self motivated, self starter, self learner has been thriving. Probably a good thing to have such a program, but I have doubts.

Before we had LLMs, we had product managers, project managers, scrum leaders, etc as roles on software engineering teams. I think as LLM-enabled development progresses we'll start to see these roles and the crossover to engineering continue to meld.

It's not like engineers didn't know that project management, voice of the customer, and organizing tasks as an intermediary between engineering and management was a thing that could/should/needed to be done. It was just a delegation of tasks before because there was more work than one person could do. Now, all of these roles can be partly offloaded to LLMs, but still having a human in the loop to guide engineering and interface to the business/customer will still be valuable.

Knowing what to build overall, what to build next, what's coming later, and how the product relates to the business goals is still very much a human endeavor.

Feels more like perforce, but effectively, yes.

A few ideas on why reducing profit by investing into the company might not be their best choice without the new investment round:

Hiring people is hard, takes time, and timing of big sales closing causing income may not line up well enough with the hiring process to offset that income fully.

Their machines are sold for high prices. It’s not small and not cheap. If a buyer pays in a lump sum that can be a big income and Oxide may not be able to time that ideally for tax purposes.

Buying electronics components is funny. Want to buy 1000 units? Price X. Want to buy 100,000 units, price is X/25. But till you can place an order for every component at the 100,000 quantity, you can’t get those price breaks so your cost to manufacture machines is much higher. $400M may let them buy at those bigger quantities and get those price breaks and it may not have been worthwhile to buy inventory at the lower quantity pricing if the investment round was looking to close real soon now. Cash flow is king, and hard, for hardware companies.

Unless you plan to physically assault it with weapons, it’s extremely unlikely to catch fire.

Literally the point of the linked GitHub repo.

Berget's "Cached input tokens are billed at the same rate as regular input tokens" pricing model is kind of painful for lots of coding use-cases, especially when competitors are offering significant discounts for cached input tokens.

There has been massive innovation and development in apples in the past 20 years. Every apple farm with a clue is growing trees for the past decade that look nothing like the trees of old. They’re growing varieties that didn’t exist 20 years ago. If you’re still seeing Red Delicious anywhere, it’s on the buyers at your local markets that missed the boat.

Just read the terms of service and read this blog post and I think your concern will be addressed.

Arduino have muddied this water now, too, as some newer ones come with a full fledged Qualcomm SOC, multiple GB of RAM, and power consumption which requires quite a beefy heatsink.

These attacks are a very effective sales pitch to everyone who runs an internet facing service to utilize AI tools to secure it sooner rather than later. The cynic in me wonders if the marketing team had any influence over the poorly constructed sandboxes or tasks given to the agent swarms when all this went down…

Yes. The vast majority of a solar panel is glass and metals. Both are easily recyclable.

Distance from the equator helps. As does if it snows where the panels are, then vertical simply not having snow on them plus the reflection of the snow helps quite a bit in winter.

If so, then the class of GPU used here may be significantly higher than mere mortals generally have access to simply due to cost.

Obviously nation states will likely have significantly more resources than this, but this is not script kiddie levels of GPUs.

These seem pretty minor compared to hacking HuggingFace.

This writing style, which reads like an LLM wrote it, is draining to read.

I put up with it when I'm actively using an LLM tool, because I just accept that this is how these tools write, but when reading a blog I expect to read words written in one of the vast varieties of normal human-written blog formats.

As long as you are constantly diligent in staying on top of what each provider is doing that may impact you.

It reads to me an argument for self hosting, maybe a less capable model to deal with smaller compute resources, but when starting to use that model and inference software to build a benchmark you can easily rerun when you change things to observe the impact of the change.

Maybe that’s a similar level of diligence but they feel different to me.

Hand written exams are coming back into fashion. You get a pencil and the exam book. Nothing else. Show your work.

Catching cheaters is still hard but it will keep honest people more honest.

Which NEC commercial display do you have? How do you like it for normal TV duties? What tradeoffs were you willing to make when you bought it compared to the features which were available in consumer-focused "smart" TVs?

Or it’s so they can continue to operate in the EU where this is required.

I don't know, but unless that contract is public, not many people know. I get the impression Oracle got a little bit of market pushback on the risk, as theirs seems to be one of the largest.

It would be nice if the article cited the actual contracts the labs have signed so that others could also read them and draw their own conclusions (maybe it does and I got tired of the slop-like writing style too early?).

Are the contracts actually take-or-pay-style? What are the terms? What are the amounts of compute and money involved for each future time period? What happens if the datacenter costs spiral upwards? What happens to the datacenter investment if the buyer goes bankrupt, goes public, or gets acquired (potentially by the datacenter owner)?

I personally think the datacenter build-outs are going to generally be a big swing and a miss. The problem 1-2 years ago was making models good enough to be useful for a variety of tasks. Now we have that. The next problem is making the models efficient enough to run a profitable business. Recent Chinese lab model releases (because they're already constrained on compute resources) and OpenAI price cuts on Luna seem to indicate that this transition to chasing efficiency has already started.

Contrast with Claude Government with all green 100% uptime. So either no one is using it or the people within Anthropic running that one have different priorities.