vineyardmike

That's the thing though. There are very few "actual workflows" in many people's lives (especially if you exclude their job), and many many "one off (few off) workflow". That's the magic.

So many tasks I need to do once, or just a few times ever, but they build up. While I'm not sure I'd use it for immigration forms specifically, that's the kind of task that's tedious and done rarely, so a dedicated tool doesn't help because who would be familiar with that tool and have it handy?

I’ve been super pro-Luna lately. I really hope that Gemini-Flash-Lite is positioned to compete with it. We all know that Anthropic has abandoned Haiku and it would never be that cheap.

Probably shouldn’t say this here but I’ve been planning to up my $20/mo exploratory ChatGPT subscription to the $100/mo tier as soon as I hit my cap. Between the progress and quality of Luna and their continuous resets, it’s been a few months now that I’ve lived off the $20 tier, frankly waiting for the need to upgrade, credit card in hand.

I’m always trying new models, like many of us here, but the price is just so good for a well balanced, American, hosted model.

It won’t work. I have nothing against taxation and funding education but the issue isn’t that type of education.

If you work in the industry in a well funded company (the ones who’d be paying these taxes), then you probably have more college-grad applicants than can hire. Probably more than you can hire from “good” schools, some with masters degrees, etc. Maybe education should be subsidized, but theres no lack of volume of people with the formal education today. Top schools (Berkeley, MIT, etc) today are reporting growing unemployment rates among their CS grads. We have more than enough students.

But that formal education isn’t the necessary skill missing. It’s understanding how to structure your work. Learning how to understand the complexity of a problem and estimate how long it’ll take. Learning how to spot future issues during code review (not just bugs and not just optimizations, but “one way doors”, future migration headaches etc). Learning architectural patterns and common prior-art. Even learning to show up on time, be polite in meetings, and navigate office politics.

There are just skills you need to see and practice to understand - you can’t teach them in a classroom. That’s why electricians have apprenticeship and doctors have residency, lawyers clerk and programmers had internships. The difference is that before AI, a young grad with an internship learned enough to answer basic bugs and learn on the job. But now that AI can fix bugs and small tasks faster than a person, the minimum skill threshold has exceeded the on-job training standards.

How much of that 16mo is design versus just production? If there was a “plug and play” chip where you just BYO weights, how long would it take?

The bigger issue seems to be that these chips can’t hold that many weights at the moment.

(I’m curious if chips with large weights in them would be more tolerant or less to yield issues. If you flip a few bits in the weights, does it really matter at scale?)

Those jobs aren’t coming back as-is, because AI isn’t going anywhere. Job markets change over time.

I’ve just started transitioning my career closer to management, so I develop/manage roughly 50/50. At this point, if I had to manage a tight budget, I’d rather have an entry level salary as tokens for a senior engineer.

We’ll need a way, as a society, to help new adults transitions from education to productive employee. But individual companies don’t have aligned incentives.

> Or even outside of software!

As a software engineer, I selfishly hope that they spend more effort on non software tasks since I’ve feel like we hit a sweet spot where engineers still have some value and autonomy, but a super charged tool.

Pragmatically, I suspect that “non software” tasks will be a tarpit because most tasks can’t be automated and verified as easily in an RL loop compared to software projects. Especially since most skilled labor is either not nearly as expensive as software engineers (eg biologists), or regulated (eg doctors, lawyers).

> or maybe this functionality is available already

Basically already exists depending on specific trade offs and risk profile.

You already can encrypt your data and store the encryption key offsite. But then you couldn’t use your phone during travel, if you toss the key locally.

You can encrypt the data at rest and leave the decryption key in RAM and just turn off your phone. But they can still take the phone and copy the encrypted data, if they think they’ll get the key later.

My understanding is that this individual would t want the government to access the encrypted data either.

The same way that smart phones aren’t easier nor cheaper to produce than feature phones. Once the technology and features get good, people’s default expectations shift.

I’ve not been sold on flip phones so far, but the latest “passport” style has made me curious.

My differentiation for this comment, was “preventing someone from using your product to build a competitor” vs “letting a competitor see your strengths/weakness to benchmark against you”.

Competition is competition and it’s two sides of the same coin.

They said they also block usage of Claude models to build ML models.

Which is definitely protecting their turf, but also probably a little bit hiding their “RSI” abilities for competitive reasons. My theory is that a lot of “safety blocking” is actually WIP training of new business directions. Anthropic has started hiring biologists and has opened a preview of a “Claude code for bioinformatics”. I’m guessing they’re tweaking their bioinformatics market play, and block “bio safety” requests so competitors can’t learn about their training.

For the 1.2B passengers: the transfer doesn’t contain passenger data, just internal operations data

Eg. Airline code, marketing materials, pricing histories, etc

Also, to answer the question:

> Affiliates and Acquisitions. We may share information with any corporate affiliates (e.g., parent company, sister companies, subsidiaries, joint ventures, or other companies under common control). If another company acquires, or plans to acquire, our company, business, or our assets, we will also share information with that company, including at the negotiation stage.

I can probably live most of my life without the transistor being invented, but it’s certainly better with new technology.

“Needs help” is an unnecessary and negative framing, don’t be a hater. We can basically always do what AI does (if not computers at large!), but either it’ll take longer or be boring.

With AI you can automate checking way more price comparisons than manually, with way less effort. With AI you can automate routine shopping tasks like converting a shopping list into an online shopping cart. I can search for specific products across dozens of sites manually, or I can ask AI to find it for me.

Literally everything from generic coding agent to shopping.

I run it in a MacOS vm, fwiw, for certain tasks. I usually hand it a repo and say “install all build dependencies” and it’ll click through installation GUIs where necessary. I wonder if the TOS of an application is enforceable if a bot agreed and a human never saw it.

It can UI test web apps if that’s part of your job, but it can also just use the browser for tasks. I’ve had it research flights by checking different dates automatically and compiling the results for me. I’ve heard others use it to handle building a shopping cart for instacart/grocery delivery.

Probably the hero usecase for most people would be app/web development. It can control either a browser or a device simulator and can iteratively build and test the application, by clicking real buttons.

It doesn’t matter what the actual reality is. People think that data centers waste water, and they don’t like that.

The beef from a single hamburger uses far more water than a year of ChatGPT usage. Few try to reduce consumption in favor of more efficient foods by comparison. It’s about perception.

Those in power seem to think that a compute advantage is necessary to maintain economic advantage. Despite this, the voters universally hate data centers, so much so that both NY and TX have data center construction moratoriums.

Despite this, those in power refuse any environmentally aware energy policy nor water policy. Despite this, companies have been trying to be environmentally aware for either moral or marketing purposes to get social permission to build DCs. Despite this, companies are “forced” to build their own “dirty” power sources since political power is disrupting green energy build out. Despite this, demand is still high so that compute costs are continuing to rise. Despite this, our economy is increasingly predicated on a few companies using more compute than geopolitical rivals with cheaper electricity. Despite this, those in power are, again, unwilling to create a compromising policy (aka clean energy) that voters actually would demand before tolerating more DCs.

What’s going to lose first? Voters/environment, politicians/the oil lobby, big tech, or the overall american economy?

> I don’t think there’s some practical way to force existing corporations to include something in their charter

Laws are but a pen stroke away.

<legalese intro>

No existing nor new C corp and their executives shall be be considered in breach of their fiduciary duties or obligations if they take an action they deem to be in the best interests of society at large, as long as it’s not fraudulent or otherwise illegal behavior.

<legalese outro>

> a serious problem with standard corporations... immoral activities for profit

A politician could trivially write a law to end this "problem", at any point. Or courts could start rejecting suits where investors sue. There is nothing inherent in nature that requires this outcome to exist.

This is an entirely self-made problem that society tolerates when it doesn't have to. Corporations used to need a blessing from the government to be formed, explicitly to avoid the risk of a massive corporation who can compete with the government and have investors that push anti-social goals.

> Perhaps Gemini itself was resource-starved because Google liked to rent out TPUs to Anthropic instead.

This was the core hypothesis.

I agree that other organizations can compete with few resources, but my hypothesis is that Gemini training specifically is being given nearly 0 resources, despite Google obviously having lots of resources. The hypothesis is based on an assumption that Google profits more by selling ALL their compute to others training models instead of using it themselves for training.

They already have good models, so “better” isn’t as profitable.

The answer is far more benign.

They getting a higher ROI renting their TPUs to Anthropic et al instead of performing training and serving their own models. Google cloud has insane backlog, and has rapidly expanded to satisfy it. While those DCs get built, they’re cannibalizing their own products for it.

This makes sense because (1) they are investors in Anthropic, so they still win and (2) they can always catch up on model training later when the profit opportunity shifts, or abandon it if there is no way to recapture that value.

> Injecting more money into the film industry would just lead it to the same people at the top of it where they'll produce the same mediocre output as they have for ages

Not necessarily, if you apply discipline and intentionality.

Canada famously created “CanCon” (Canadian Content) by law. They forced media in the country to be X% local, and that built out the industry by sheer necessity. The reputation was poor in the early years, but now a talent pipeline, local services, and industrial knowledge has built up and they have a thriving entertainment industry.

Germany has the disadvantage against Canada which could benefit from speaking English and cross selling to the US and UK. But it can become a source of local pride and distinction. The French are very proud of their language, even though it’s also not heavily spoken internationally.

The building blocks exist to successfully build cultural capital if it’s a priority.

Goodwill is supposedly €1.504B.

> Are you trying to be sarcastic or funny? I can't tell.

Take a liberal arts class and your reading comprehension may improve.

> knows what a partial differential equation is.

I’ve met a few but tbh that’s a pretty weird way to judge “inherently better”.

> You neither need not count on someone who wrote a thesis on 'feminist perspective of aztek dance'

I like how we just make up fake arguments in incoherent grammar as a reason to criticize the humanities. There'd be irony there if people still were taught what that meant.

> just peddling political nonsense

Is this because the word liberal is in the name? Because that's not what that word means in this context.

Did you read the article? As it highlights elegantly, "liberal arts" is about the educational methodology and structure, not the course material. You can learn STEM subjects in a liberal arts education.

> fairly easily... not so easy.

Yea, totally, STEM majors are inherently special and better at learning ;)

> The education was in learning how to learn, learning how to solve problems, and how to distinguish fact from fiction

Sounds pretty close to a liberal arts education.

That said, not everything is about a job or work. Sometimes (usually) education is itself a goal.

> west points the wastefulness of western labs whether in terms of gpu clusters being ran, cost of inference.

Can’t possibly be intentional media strategy by a geopolitical target, right? If its going to negatively impact valuations and revenue of major rivals, seems like a desirable strategy?

We just saw OpenAI take the steps to significantly lower the cost of one of their models, which confirms that at least one western lab has a large margin on inference, not a large inference cost.

Meanwhile, we don’t know how many experiments these east/west labs are performing relative to each other. We also know that many western labs have a whole portfolio of models too, which is product breadth not necessarily waste.

Great reading list! They’re honestly two stories that I reflect on constantly while thinking about AI lately.

Player Piano, not to spoil anything, is about a world run by engineers and machines. The machines are “optimal” and make every decision. How do people find purpose, and how should the engineers that build the machines view their role in society?

Manna is the story of two societies with competing visions of how AI (which ironically starts out strikingly similar to an LLM) interacts with welfare/universal basic income and post-scarcity society. For good measure, it also hypothesizes the end state of the internet panopticon and personalized “scores” and rates.

Anyone who says that shit publicly says crazier shit privately. Half the quotes floating around came from his resume and courses he was selling. So presumably the more polished material.

(2024) > for example in private i say “fat people” and “retard” and “trannies are disgusting.” the final leap is doing so online. if it costs me, this [new years] resolution was accomplished.

>> quoted from ryanckulp.com

Yea I don’t think an apology is coming. The scrubbing of statements is contextually a funny plot twist though.

Billionaires use Gmail alongside impoverished people across the world.