rufasterisco

Build/vibe-code your own benchmark and find out, the work pays off and lets you try many models.

Also try fine-tuning small models and see how they perform.

I don’t understand. The model is open, you can host it and use it without giving Meta anything.

I’m not saying Meta is not eager to syphon data from users, but I don’t see how this happens via this specific product.

The article clearly states he was not on board.

There are many reasons for critizing him over things he is responsible for.

Never been a fan of mob lynching.

> The Greenland government’s statement said it “would not be proportionate” to demand the equipment be removed. An application for permission remained under processing, it added.

They could have written “ Island’s government says no denial given…” and it would have been equally true.

some small models are fast, and fine tuning can be done locally

for example in gaming context, if you need an answer below 5 seconds, they are the sweet spot

Following the same reasoning, smartwatches would have been a failure. They might be niche, but sales prove there is a market to explore/deepen.

Overall, openAI can sit on a mountain of money and bet mobile phones are the final form factor for human/AI interaction, as they have been for human/internet.

Or deploy some of that money and figure out whether that is true.

It’s also about creating an environment for those features to emerge, without being constrained by someone else platform, that could natively embed it at any time, and (probably more important) app marketplaces.

A signal for opportunity is also given by Apple’s inability to give their users Siri and Google sitting on transformers while OpenAI grabs the chatbot marketplace.

Also, anything they build does not cannibalize their other product lines.

There are lots of incentives for them to try out and figure out features on the fly, which arguably also happened with the IPhone (app store).

Some people like it better when they direct the solution because they walk away with a better understanding of it.

This has emotional/psychological aspects (it feels less like LLMs are replacing you), as well as practical ones (overall complexity is bounded by what the dev brain can understand/grasp).

A dev work becomes more and more about reliability, signing off safe software with a litmus test: “I will be on to handle this code failure as if I had written it”.

All the above points towards keeping tight control over some level of abstractions and delegating others.

Isn’t that counterbalanced by the fact that the reason they exist in the first place is to be a sovereign platform?

I am assuming the reason companies switch to them is not price or tech. US cloud providers have the advantage on both.

Selling EU companies data would mean destroying trust over their main selling point, not to mention incur on EU wrath.

Feels like living one whistleblower away from doom.

I refer to fully EU clouds, parent list includes US clouds that do not need bags of money, Clouds Act in enough.

> The obvious conservative response to a technology whose downsides are unfathomable is suppression, not encouragement. “Move fast and break things” might be an ethos conservatism can accept when the object being broken is the B2B SaaS status quo. But it cannot do so when the objects in question are human intelligence, sociability, agency, and existence.

Hold on.

I accept all the rethorical apocalyptic stuff, it comes with the title and each of us can have an opinion.

But “move fast and break things” is Facebook motto, and when it come to sociability, society at large, and politics, I you cannot say that.

Facebook/Meta merely breaking B2B SaaS?

It’s not really about “Meta is bad”. It’s recognising the fact that social media, spearheaded by Facebook has changed society and politics.

Some like it some don’t. I don’t want to enter a culture war, but can we agree that with Meta the “object in question” is not just a SaaS? It is sociability, it is society, it is politics?

This guy is an associate professor of politics at Princeton University.

How can you advocate for future policies over AI while at the same time misleading on the tech revolution that has shaped the past, what, 20 years?

What is being taught in those classrooms?