The comparison to the poorest 3.5b is also not as useful as comparing the top 0.1% to the top 10%, which I would imagine pollute orders of magnitude more than the top 0.1%. I'm sure they're both shocking numbers compared to humans living sedentary agrarian lifestyles.
It's more a self reinforcing side-effect of a withering democracy than the cause. The rhetoric from the far right keeps implying that we're much closer to a single party state than the current election cycle suggests and they have proven themselves to be weak predictors of outcomes they don't directly control so I'm sure more shenanigans will be revealed shortly.
Three prosecutors and MIT leadership were responsible for the charges. Most US Attorney's are scummy attack dogs because their work requires it, so I would blame MIT for wanting to make an example of him instead of handling it like a disciplinary matter and a teachable moment.
AI has always seemed like a convenient panacea for the excesses of accelerationism. An overloaded term in the equation that should balance everything, but only if the right conditions are met. That framing discrepancy alone should indicate that AI is being marketed as something that it will clearly never be.
I doubt someone like Thiel would be deluded enough to think of AI as anything other than an economic accelerator and wealth amplifier.
There was plenty of network hacking going on pre-internet and people still figure out ways to hack air gaped computers. Security is always going to be a problem.
It's not minimalistic in the way you're suggesting. Their are tons of extensions listed on pi.dev that give you all the extra features you could want. You just don't need them. The harness is very capable with just the 4 primary tools. The minimalism is a claim on the harness architecture, not the number of lines of code or the capabilities of the harness.
What really doesn't make sense to me is setting uniform token targets for all engineers. I'd be more interested in setting token ranges with hard limits for certain roles that see diminishing returns from the overuse of coding agents and where maintaining institutional knowledge, architectural awareness... is more valuable than moving as fast as possible. Like everything else, these limits should be adjusted over time as tooling for those roles improves but it really feels like there are human limits that organizations should avoid exceeding.
Politics is frequently a game of semantic drift. The application of labels with unclear meaning to further dilute meaning or extend it for the purpose of engagement, legal reclassification... it's not engineering and you can't expect well defined terms from people who want power without accountability.
Why should open weights correlate with cost? Cost correlates with the expense of running the model more than it does to the expense of developing the model.
It would be so simple if businesses could choose their competition or simplify disallow modes of competition they found inconvenient. I can't imagine any amount of regulation would make that possible in today's competitive landscape with the existing laws and the enormous volume of prior art.
You should really look into who Jack Conte is and why he created Patreon. He's a smart guy who relies heavily on maintaining a positive social image and is more emotionally aware and stable than most tech founders. I imagine from his perspective the decision, severance and post were all just the smart thing to do.
Even founders that don't naturally empathize with employees they need to cut encounter a process that is emotionally taxing. It's just not an easy thing to do. If you handle layoffs badly it can impact your earnings potential, your social image and your psychological health.
The first time I saw a giant floating tv billboard at the beach was the first time I felt the urge to sink a vessel. I found it offensive but everyone else seemed to just accept it as normal.
That sounds dangerously like your organization has overcommitted to AI, is hemorrhaging money and is squeezing their human engineers to make up the difference.
AI was always going to be geo-politically fragmentary. As soon as we started talking about it like a utility it was clear that every country was going to be strongly limited to the resources it could develop and the infrastructure it could build out. The US and China will still be selling hardware, managing infrastructure and licensing models and yes the domestic market is massive.
The developers of Prince of Persia still talking about the game more than 30 years later seems very bizarre to me. I remember a game called Flashback having very a similar graphical sprite animation innovation around the time PoP was released and I remember it being very fun to play, but nobody talks about it the same way. What's the deal with Price of Persia?
Reading the first few paragraphs of what he calls "the most sophisticated academic social science paper I have yet seen from an AI" does not impress as much as I hoped.
"Posterior beliefs about market demand are purely referencedependent: holding dollars raised constant, they track only performance relative to the founder’s
self-chosen goal—jumping half a standard deviation at the threshold, responding steeply for the first ten points past it, and flattening thereafter"
Humans generally don't verbalize data this way. The summary document is also very fluffy.
Now you're arguing against your own analogy? Hunter was ubiquitous position in human society prior to the domestication of animals. 50% of the workforce in hunter-gather societies. Today, 12 millennia after the domestication of wildlife, that number is down to 9-14% of the global workforce dedicated to the production, distribution, processing, sales of meat (not including cooked food) according to opus.
Considering that only 1% of the US workforce was a software engineer I expect similar workforce optimization to occur in software engineering specializations over the next 12,000 years. /s But seriously, it's never going to zero.
We don't need as many hunters because we've domesticated sources of meat. We still need ranchers, butchers... an entire supply chain to get meat to consumers. We didn't remove humans from the loop, we just created specializations.
Software specialization might look very different in 10 years but I doubt that technically specialized humans will be completely removed from their professions. We might not be carrying bows and arrows anymore but we will be carrying the equivalent of a rope and a Stetson.
Languages have been reporting compile and runtime errors for decades. Additionally very few senior developers don't already have their minds wired to spot typos the way copy editors spot bad punctuation. Typos were only really a problem for students.
The capacity of the person prompting it to understand is the threshold they won't cross. They can squeeze the gap as much as possible by dumbing down answers or slowly ramping up information complexity but there is a limit to comprehension.