Art9681

...uses gpt-image-2 for his blog image.

We ship features faster and workers are more independent. They can get the answers they need faster than ever. And i'm talking about the business itself if the business has enabled that. There are a ton of productivity gains.

But make no mistake. Being more productive does not equal higher profits because your customers think you've added value. Both value and productivity are highly subjective terms which is why it is measured differently depending on where you work.

Most businesses adapted to AI by shipping a lot more features in smaller increments of time. What they should have done is become much more ambitious and build moon shots in two quarters instead. You need to go big or go home if you're going all in on AI.

They are selling inference at severely gimped capability. Even in openrouter the quality and speed of the model being served varies by provider. When you dig into the details (which most people don't do), not all providers are equal.

DeepSeek hasn't proven anything except what they say. You're inherently trusting a company's statements over others. When an independent third party corroborates the numbers then we know for sure. Until then, every company is just selling a story for investors and users.

OpenAI and Anthropic have more compute and the best frontier models to throw at the optimization problems. They have published articles on these efforts. For example, Dots, and Anthropic's upcoming "persistent agent" is because of these optimizations. Both companies often publish articles detailing a lot of their technical efforts. They just get buried among the flood of other news.

I get these surveys in the mail and promptly toss them in the garbage. The people willing to spend their precious time on them are probably the ones whose opinions matter the least.

I encourage you to read "About the Study".

"Ipsos conducted sampling, interviewing and tabulation for the survey using the KnowledgePanel, a nationwide survey panel designed to be representative of the U.S. adult population. KnowledgePanel members are recruited through probability sampling methods using address-based sampling. Panel members who do not have internet access are provided with a tablet and internet service. KnowledgePanel members receive a per survey incentive, usually the equivalent of $1 (though for some it is $2) in points that can be redeemed for cash or prizes."

LLMs will absolutely take over game development. That does not mean the result will be a fun game that has value. Just like a group of expert humans can put together a technically and artistically impressive game but it has little appeal.

Taste remains king. Despite that. LLMs will absolutely be able to create elaborate games by this time next year.

You have to actually spend some effort reading the article they published to answer your own question.

The usage numbers tell a different story. Not only is the great majority of AI users on American frontier providers, they are also willing to pay the premium price for the premium product. It's not like tech is oblivious to the Chinese models. It's that the industry is aware they are always 6 months to a year behind.

You didn't discover some new trick for cost performance. And the rest of the world isn't dumb.

You're just too broke to afford the supercar and justifying the hooptie. It gets you to the kindergarten class after all. And that's all you need.

I'm a Principal with 26YOE. It's solved today. Not tomorrow. The industry isn't changing. It already happened. It happened so fast a lot of people not paying attention blinked and missed it. The sudden realization gave way to fear. And many a blog was written lamenting the loss of a bygone era.

It's highly entertaining I think.

Can we get some examples of what a good UI looks like then? I would like to see a UI design expert take a couple of these slop designs and show what each should look like according to their taste.

There is always a limit unless you start scaling horizontally in the sense that you have multiple accounts via subscription or API. There is always some limit to any single account, even via API.

I'm thinking the persistent agent is something that can't scale to multiple agents. Imagine only one agent you can invoke as many times as you want on a single account, but it cannot invoke subagents or scale itself. It's just always there ready to do work when you need it. But it behaves as "one".

This would be trivial to implement. Of course, if you have the money, you can have multiple $500 subscriptions and have multiple persistent agents.

Anomaly detection is getting better. A small delta can still trigger it. Wether a human reviewed it is another story. But the post mortem will reveal all the signs in hindsight.

Yea every PR submitted before LLMs was top tier work. Humans are born with an innate instinct to code and build complex software. It's the great equalizer. There are not outliers in coding. It is with great pleasure we "LGTM" and rubber stamp contributions. Nothing ever went wrong until LLMs ruined it for everyone.

/s