News

Anthropic Economic Index Report

Anthropic has released their 4th economic index report, which analyzes how Claude is being used and how it is impacting different industries. The full report covers a lot of topics, but I will highlight a few that I found interesting here.

The first takeaway is that the harder the task, the higher the speedup that Claude provides.

12 years of schooling means a high school education, and 16 years is a Bachelor’s degree.

They measure difficulty in terms of the amount of human education expected to be needed to do the task alone. This comes with a lower success rate (above, right graph), but even when controlling for success rate they still find Claude provides more value for tasks requiring more human capital.

This follows nicely into another observation, which is that Claude currently covers most of the high skill, white collar jobs.

Education level of all tasks vs. Claude-covered tasks. All task distributions gotten from O*NET

Because of this, they warn that we may see deskilling in the workforce; as AI does the harder parts of the jobs, humans are left with more routine work. It assumes that AI will be replacing those high skill jobs, instead of augmenting and transforming them to be even more than what they currently are. Either way, its something to keep an eye on if you are a professional.

The final takeaway is that they expect AI to increase US labor productivity growth by over 1%, which would double the current trend rate.

I would highly recommend reading the blog post or full report, since they have a bunch of other details, information, and takeaways that I did not discuss here.

Releases

Claude Cowork

Continuing with Anthropic news, this week they released Cowork, which is meant to be Claude Code for non technical tasks.

It uses the same (or at least similar) set of tools as Claude Code to go and complete taska, and also uses Claude’s Chrome plugin to use the browser to complete tasks as well. It is available in the Claude Desktop app on Mac for Pro and Max subscribers.

Interestingly, it was made in just 10 days using Claude Code according to the Anthropic team.

Despite having one of the most viral product launch tweets in the AI space, accruing almost 50 million views in five days, I don’t think this is actually going to be a very revolutionary product.

The implication of Cowork is that the terminal was too intimidating for the average user to go and use. While that might be a part of the problem, I think the larger issue is actually knowing what these agents can do and how to steer them to be able to complete the task successfully.

There is also the issue of the actual UX. I think the majority of people, because of their inability to steer and properly utilize these models, need to have it more tightly integrated with the existing tools that they use. Having to go to another site and input information about another site or something else that they are using is an extra step that most users will be unwilling to take. I think the ideal agents for the average person are ones that they don’t actually interact with and instead are just doing things behind the scenes for them and surfacing them with questions and different human-in-the-loop prompts to go and get feedback from the user to make sure that everything is going as they expect.

Because of this I expect it to be used by a few people and they will have great success with it, but this will not be a ChatGPT moment where the general populace will be using agents to get work done all of a sudden. We will see if this is true or not in a few months time.

Flux.2 Klein

Black Forest Labs has released the small versions of their Flux2 series of models called Flux Klein. These models are meant to do fast local inference and have been distilled to generate images in only four steps. They come in two different sizes, 4 billion and 9 billion parameters, with both the base model and also fine-tuned version. The fine-tuned versions are able to do both image generation and image editing.

The models are in direct competition with Alibaba’s Z image model. They are roughly the same size and use half the number of steps, making them about two times faster to use.

Z-Image is made specifically for very realistic images, as well as text rendering, and Flux is able to somewhat keep up with it, but does often fall short for those tasks when compared to Z-image. For every other art style, Flux.2 Klein is much stronger than Z-Image, making it a good all around model for day to day use.

Left: Z-Image. Right (Flux Klein 9B) — From r/StableDiffusion

For image editing, it seems to be as good as Qwen-Image-Edit, while being a much smaller and faster model. Z-Image does not support image editing right now, but it has been teased that an image editing version will be released in the near future.

Overall, I would recommend Flux.2 Klein if you’re looking for fast, cheap image generation or you’re looking to run an all in one image generation model at home.

Quick Hits

GLM Image

Black Forest Labs was not the only company to release an image generation model as Z.ai entered the space with their GLM image model. Even though I am a fan of Z.ai’s LLMs, I must say that their image generation model is a flop and is not worth using or checking out right now. It benchmarks very well, but in real-world comparisons, it does not have the same level of quality of other open source models that are smaller and faster.

Finish

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Bathroom cleaning robots by Loki Robotics — From Twitter