I’m two months late to sharing on here, but life update: I’ve begun working as a research staffer in the Oceanography Department at Columbia University’s Lamont-Doherty Earth Observatory.
My mission to build bridges between climate science & policymakers in government continues.
Warren's repeating the blatant lie that people's electricity bills near data centers have gone up by as much as 267%. Completely fake. This is a misreading of a Bloomberg article that found that wholesale nodal power prices very close to data centers rose as much as 267%. This is NOT a rate that residents pay, and her team is surely smart enough to know that. It has some effect on residential bills, but the effects haven't been large enough to be noticeable as a general pattern.
If the key to becoming a billionaire is to exploit people, as some politicians claim, we at YC are idiots. We've spent the last 20 years choosing the wrong founders and teaching them the wrong things. Or maybe we do actually understand startups, and the politicians are wrong.
In many center- to far-left policy and political circles in New York, there is a considerable amount of handwringing, Luddism, and an intellectual incuriosity about the merits of AI and the radical transformations of production (physical and knowledge) it can confer to all of society.
But then there's another circle that chooses optimism: an acknowledgement of risks, yes, but a courageous recognition that 1) we should not axiomatically treat these risks as intractable, and 2) human ingenuity can and must prevail over pessimism.
Any time I am tempted to submit to discouragement and disillusioned by the former, I'm invigorated by the forward-moving energy by the latter. 💪
Banning data centers in NY will accomplish the same thing as banning fracking in NY a decade ago: pushing lucrative industry to other states (& other countries).
And New Yorkers will continue to use AI (with data centers in other places powered mostly by fossil fuels).
Second for second, @tylercowen packs more substance into a talk than anyone I'm aware of. This is a clear, non-hysterical, and somewhat soothing discussion of our AI future.
Probably the best thing I did to accelerate my rate of learning after my mid-30s was to drop hierarchical thinking when choosing who to learn from. Easily 10x’ed my rate of learning.
I have since realized that, for talented high achievers, hierarchical thinking is the biggest barrier to mastery of their craft.
Most people don’t consciously think about it, but it’s always there.
They decide who is worthy to learn from and who isn’t.
They only learn from people they “look up to”.
And your look-up-to group shrinks in size as you achieve more success yourself, so you deprive yourself of the great opportunity available to you: you can learn from everyone, literally everyone.
Contrary to some beliefs and some (flawed) intuitions, learning like this
- does not take huge effort
- cultivates greater critical thinking
- feels better than hierarchical learning
- can take you to mastery much faster
It does require though that you confront your ego and quiet it a little, not for spiritual or moral reasons, but solely for the purely practical, capitalistic pursuit of your greater goals.
This sounds simple, but few can do it.
The ability to do this cannot be given to you.
Only thing that can be given to you is the pointer to what is truly going on. The rest is up to you.
Josh doesn't even mention the worst part of Fetterman's irresponsibility. Because he won't wear a suit, he's *literally not allowed on the Senate floor*. That's where negotiations happen. He just doesn't go. He sits in the hall and signals thumbs up/down through the doorway.
The Senate is very much built on bargains and personal back-and-forth. Fetterman just sits all of it out. He plops himself on a chair in the hallway, alone, scrolling his phone, until an aide taps his shoulder to tell him it's time to peek his head in and vote.
"A field guide to...making yourself legible to the right people" -- great advice in this post by @majamediaco.
I recently made the same general pitch to a hall full of undergrads: as the job market gets tighter and resumes all start to have the same air-brushed look thanks to AI, shipping public artifacts is the way to stand out. When everybody has a degree and everybody "improved X by Y%" at every job they've ever had, get better mileage by giving yourself something to point to that exactly one person has done.
As a human who's looked a lot of resumes and filled a lot of positions, I can attest that I'm always way more interested in that uniquely shaped project with a landing page, demo video, download instructions, and active chatter than the vast majority of things that show up on a traditional resume.
Here’s a fun data challenge to pose to New Yorkers: can anyone build a forecasting model that outclasses NYCEMOD, or the New York City Economic Model, in predicting city tax revenues as reported in the Comptroller’s Annual Comprehensive Financial Report (ACFR)?
The Office of Management and Budget (NYCOMB) employs tax revenue forecasting models, such as OMB’s internal New York City Economic Model (NYCEMOD).
This model consists of exogenous inputs such as OMB’s forecast of US indicators provided by the S&P Global macromodel and others, and over one hundred equations that integrate dynamics relating to Wall Street, labor markets, wages, personal income, commercial and residential real estate markets, tourism, and Gross City Product.
Given the importance of forecasting future tax revenues in planning ahead for future fiscal policy constraints, transparency and understanding how City government comes to its forecasting conclusion is of great public benefit.
There’s several ways to do this: academic economists build dynamic stochastic general equilibrium, or DSGE models to predict outcomes with actors facing uncertainty in their decision-making. There is also a purely statistical approach where one builds an ML architecture, throws heaps of macroeconomic and market data at it, and gets an R-squared for fit with actual revenues.
But I am sure there are plenty of people with better ideas than me in this massively talented city of ours. Who has the ideal solution?
https://t.co/dR6FqLlGfw
I urge my former colleagues in the New York State Legislature, elected officials and staffers alike, to please read Andy Masley's factual and scientifically-informed writing on many of the canards that proliferate about data centers.
Facts, not moral panic, are needed.
https://t.co/bWhnETWbgj
An awful piece of legislation ignorant of the engineering mechanics of how data centers work, cc: @AndyMasley.
If energy demand and grid reliability was truly the concern, then why did New York pols shut down Indian Point, drag their feet on CHPE, and not mobilizing support for new nuclear energy generation?
Speaker Carl Heastie says lawmakers intend to pass a data center moratorium bill introduced overnight.
Would place a 1-year pause on permits for data centers, outlines other guardrails like energy efficiency goals
https://t.co/RTSTO7F9R4
👀 As fallout continues over Graham Platner's sexually explicit texts, Janet Mills is reminding folks she's still on the ballot:
“People have the impression that I ‘withdrew’ or ‘dropped out,'” Mills (D) told @PressHerald, “but I simply suspended active campaigning. I am still on the ballot.”
https://t.co/Uhku7SkKs1
Many commit a grave category error when they conflate “messaging discipline” with “sacrifice every semblance of moral upstandingness on the altar of The Cause”
NEW: Sen. Bernie Sanders told me he’s “certainly not” rethinking his endorsement of Graham Platner following news that he sent sexually explicit text messages to women.
“My understanding is that his wife, Amy, who I've met, indicated they love each other, but maybe we focus on the issues facing the American people, the people of Maine, and not the marriage issues facing Graham Platner.”