Using Twitter the way it was intended to be used, like it’s 2010.
Dubai
Joined May 2019
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Deepak Dhingra retweeted
Is it possible to block a gif?
Because this shitass gif is always accompanied by the most braindead, most historically illiterate takes.
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Deepak Dhingra retweeted
Every month a new guy discovers LLMs; discovers a skill the current LLMs require to get good results; and writes about the future jobs that will always be available for smart people like HIM, that are SKILLED in using LLMs.
The next generation of AIs doesn't need his fancy prompt. The image model goes from needing to type in just the right set of weird words and cryptic sorcerous invocations, to most people being able to type in English what they want and get a pretty good result.
There are still tasks that require careful invocation. But they are a much smaller fraction of all the tasks people are trying to do, or you can get a bleh result without the elaborate invocation to get it really good. And to improve on the bleh result you need to be substantially more of an expert than back when the Guy was memorizing a rule about adding "trending on Artstation" to the image prompts, as would always require a human paid to do that.
Another generation of AIs comes out. The next generation of Clever Skills is obsolete. Image models just obey the instructions for compositing panels without mixing them up, and you don't need to be an expert to get them to do it right. Another human value-add is gone. A wider set of tasks require no human expert.
Now a new Guy notices LLMs have become useful in his field for the first time. He discovers they require SKILL to use CORRECTLY. He posts about how there will always be jobs for humans who are SKILLED in using LLMs like HIM.
But it is not an infinite cycle. It is not the same each time it repeats. Now the Guy is a highly paid programmer or a career mathematician in 2026, instead of a graphic artist in 2023.
In six months the models will no longer require his vaunted Skills.
And by then there will be another Guy.
But the process doesn't continue forever. The Guys are coming from fields that were harder and harder for AIs. The brief centaur eras are shorter and shorter.
Today it is writers who are laughing at how bad the LLMs are at their job, and who will perhaps soon be posting about how it takes Skill to get an LLM to do their job Correctly. But the models are coming faster, and the eras of kinds of human value-add in each field are shortening.
There is a point when you run out of Guys, either because the centaur eras are too short for people to develop SKILLs and post to Twitter about them; or because there are not lands left for AIs to conquer; or because ordinary people are not reassured by some Nobel laureate proclaiming there will always be jobs for Nobel laureates with the SKILLS to prompt robotized biology labs Correctly.
But we'll never run out of amateur economists who assert entirely *without* a brief contemporary example that there will always be jobs for humans skilled at operating AIs!
We'll run out of professional economists saying it when nobody is paid for that work anymore.
I guess we'll also run out of amateur economists when they're dead.
Deepak Dhingra retweeted
Every agent will need its own computer. And with new Hosted agents in Foundry, every agent gets its own dedicated enterprise-grade sandbox, with durable state, built-in identity and governance, and support for any harness or framework.
Read more:
devblogs.microsoft.com/found…
Deepak Dhingra retweeted
New essay on the economics of structural change and the post-commodity future of work.
1. Almost any question about the impact of advanced AI on the economy needs to start at the same place: what is still scarce? Answer that, and the analysis becomes pretty straightforward. This essay explores what becomes scarce if AI really can replicate most of what humans do in production, and what this mean for the future of jobs.
2. My conjecture, working through the economics: labor reallocates across sectors, and the sector it reallocates to has properties that keep labor a meaningful share of the economy. Ultimately this is about the structure of demand itself. For this, we have to go back to Girard, Augustine and Rousseau: once people's base needs are met, their preferences shift to comparative motives (e.g., status, exclusivity, social desirability). This motive is inherently non-satiated.
4. The key paper is Comin, Lashkari, and Mestieri (Econometrica 2021). As people get richer, they don't buy proportionally more of everything. They shift spending toward sectors with higher income elasticity. They estimate income effects account for 75%+ of observed structural change.
5. The ironic consequence: the sector that gets automated becomes a smaller share of the economy, not a larger one. Agriculture got massively more productive and its share of employment collapsed. Manufacturing too. The "stagnant" sectors absorb the spending and the jobs.
6. So the question is: which sectors have high income elasticity in a post-AGI world? I argue it's what I call the relational sector. Categories where the human isn't just an input into production, it is part of the value.
7. Why does the relational sector have high income elasticity? Because human desire has a mimetic, relational dimension. We don't just want things for their intrinsic properties. We want what others want, and we want it more when others can't have it. Girard, Rousseau, Augustine, and Hobbes all saw this.
8. In work with Kristóf Madarász, we showed this experimentally: WTP roughly doubles when a random subset of others is excluded from the good. And in new work with Graelin Mandel, AI involvement kills the premium. Human-made art gains 44% from exclusivity; AI-made art only 21%.
9. This all comes together for the core argument. The sector that absorbs spending as AI makes commodity production cheap is one where human provenance is part of the value, and demand for it grows faster than income. Exactly the profile that keeps labor meaningful.
10. To be clear about the claim: I'm NOT saying aggregate labor share must rise. It may fall. The claim is about sectoral composition, i.e., where expenditure and employment go once commodities get cheap, and the fact that the sector that will absorb reallocated labor maps to a substantial component of human preferences and desire.
11. If you're interested in the formal model, a linked companion technical note works out all the economics.
Read the essay here: aleximas.substack.com/p/what…
Deepak Dhingra retweeted
When you check on your Claude Code to see how hard it's cooking and it's just been waiting for you to approve the initial mkdir command.
Deepak Dhingra retweeted
You can’t convince people of new ideas because most of the time you’re not debating logic, you’re holding a blade to the ideological structure that makes them feel safe
Deepak Dhingra retweeted
Designing an inference chip for robots is actually very difficult.
In data centers each chip is bathed in jacuzzi and babysat by nannies. If they died it would be hot swapped by one of their clones.
The fault rate of GPUs in datacenter is actually quite high. Industrial average annual fault rate of H100 is 9%. Ideal conditions could reduce it down to 2% but never below a single digit.
The fault recovery of GPU nodes actually could take a while, from minutes to hours. It is not instantaneous.
In robots, the chips are out in the cold and they need rapid self recovery. The fault tolerance is in a different league. It is not uncommon many robotic companies struggle to get the chip running more than a few hours without rebooting.
For chip companies, this is great since they would tell robotic companies to buy more chips for hot swapping.
For robotic companies, this is bad since it is obviously not a scaleable solution but they are stuck with endless back-and-forth JIRA tickets with vendors.
Deepak Dhingra retweeted
it terrifies me how many talented people are contributing to a future they wouldn't want to live in. building something addictive. exploitative. destructive. something they'll ban their own kids from using. and for what? a paycheck? surely there's a better way to use your gifts?
Deepak Dhingra retweeted
"A man is honorable in proportion to the personal risks he takes for his opinion." - Nassim Nicholas Taleb in Antifragile
Deepak Dhingra retweeted
Anthropomorphization of intermediate tokens as reasoning/thinking traces isn't quite a harmless fad, and may be pushing LRM research into questionable directions.. So we decided to put together a more complete argument.. 👇🧵 1/
