i found something.
Now focused on market education because i believe actually, YOU CAN make $ trading. Small sub in Discord coming.
Not investment advice.
JD Vance just ended his presidential exploratory election committee. Now, his mentor, Peter Thiel, has fled the U.S., for right wing Argentina. But not before declaring that he might have overstated AI’s impact on society, particularly on employment.
Something bad is happening.
The most equitable taxation would be based 100% on use. Pay road tax for every mile you travel by car, bike or foot. Pay the police, fire, and medical every time they respond. Write a check every time our military gets used. Send your kids off with a check to pay for each day's schooling, etc. etc.
The problem is that taxation and economic policies are used to incentivize and disincentivize behavior. The macro and micro economic results of 'pay only for that which you use' will look vastly different than the results you'd think you'll enjoy. The Finns pay a 50% income tax but are the happiest in the world. 😏
An analogy for why I believe current AI coding agents will not survive in a meaningful way long term.
First, what is an AI coding agent? It’s a large language model trained on all of the open source code available on the Internet, attached to some sort of loop. You ask it to create a program that has some functions, and provide it with details about how it must operate. The output process then follows:
1. The LLM outputs code as a guess.
2. The looping tool evaluates the code in some way based on stated functional requirements.
3. If the code does not pass, query the LLM to make another guess.
4. Continue until an exit condition is satisfied or you run out of compute.
It may not seem like it, but this is just iterative, fuzzy search optimization, just over written words.
The utility of the system depends on the quality of the guesses, the evaluation mechanism, and the optimization strategy.
The quality of the guesses depends on the quality of the training dataset. Does the training dataset contain the code snippets needed to make your request?
For simple and common requests, the answer is yes. If you just need an efficient sort routine in a language you aren’t fluent in, you can get the model to make one for you and it might save you 10 minutes. Not insane speed up but definitely compounds over time. Here the coder knows what they want exists, knows how the sort algorithm is supposed to work, and just needs one whipped up in a new language they are building in. The expert saves some time. Integration into the codebase is still done by the human. It’s basically fancy autocomplete.
For more complex requests, such as multi function routines which require a large amount of architectural design, the agents start to fall apart. This is because the likelihood that someone has built exactly what you wanted goes down quickly as the size of what you want increases.
Here enters the loop. The agent producers hope that your request is similar enough to a range of existing code that they can guess a workable version by interpolating (and sometimes extrapolating) between solutions. So they make a guess with some randomness applied, evaluate, and modify the guess based on the results.
Anyone who has done iterative optimization can identify a lot of the issues that occur in these systems.
You might get stuck in a suboptimal state, where all the next guesses are worse than the current guess, even though the current guess isn’t an acceptable solution. The output seems like it’s almost there but not quite. The user then keeps requesting more iterations, hoping to go from 90% to 100% that never comes.
There may also be degeneracies in the sample space, and you might get something that passes the criteria but is sloppy, nonsensical, or ridden with unnecessary bloat under the hood. Like a root finder that just won’t find the root you are looking for.
And so in the course of writing, say 1000 lines of code, the agent has actually written 1M lines of code, iteratively generating and praying it can pass off as acceptable. The user never sees most of this, just told the system is “thinking.” When all is said and done, that 1000 lines of code required the generation of millions of lines of code, mostly thrown out.
Now to get to the analogy. Think of the agent as a bricklayer and you have asked for a brick wall. You specify color, pattern, accents, etc.
But the bricklayer isn’t very skilled, and decides to lay bricks stochastically. First, he evaluates each brick after placement. Thickness of seams, alignment, angle, etc. if it is wrong, he breaks it out and tries again. For every brick in the wall, he lays 100 bricks and wastes 99.
Then he decides to go faster, only evaluating every 10 ft of wall. If there are more than 10% errors, he destroys it and rebuilds. For every 10 ft he lays 1000’s of ft.
Many of the guys behind these AI companies (I’ve met many) couldn’t get laid and now they’re taking out their shortcomings on the world
We do not need 6,500 data centers
@Wh1t3Wh1rlWind@om_patel5 I think the Supreme Court said that's not on the menu anymore. Have to go to an Appeals court to get an injunction like that.
@OrsonPratt65@AlaliQasem JUST like Homeland Security theyre in his pocket.
THIS is why the country needs independent agencies - divorced from the President.
@HedgieMarkets "Oracle simultaneously hired a new CFO w/ a $26 million stock package on top of a $950,000 base salary."
Fired 30,000 people, taking every red cent away they can.
As a society, we get what we allow.