Potential legislative solutions to this challenge include the Retirement Savings for Americans Act of 2023 and the Portable Benefits for Independent Workers Pilot Program Act.
@digitalarun.bsky.social describes these and others in more detail in the article.
www.brookings.edu/articles/wor...
a long article about whether the “power of the purse” that Congress wields is a floor or a ceiling on Presidential spending.
a fun (long) read from @caity.bsky.social. As Kramer once said, it’s “a story about love, deception, greed, lust and unbridled enthusiasm. yes, that’s what led to Billy Mumphrey’s downfall…”
Our first Tech Leadership Lab of 2025 is on Wednesday 02/05 at 4:45PM: former Etsy CEO Chad Dickerson chats with @digitalarun.bsky.social about guiding Etsy from startup to IPO and beyond, growing revenue 14x 2011-2017, and lessons since imparted to dozens of startups. Sign up: bit.ly/dickersonTLL
I wonder what the intersection between people downloading VPNs for the first time specifically to get on TikTok and people vulnerable to a VPN scam is 😊
How? By shifting youth thinking from “Capitalism is good and an enabler of the good society” to “Capitalism is evil and should be torn down.” You might disagree with him and see this as a narrative fitted retrospectively to justify today’s position — but its a fascinating perspective nevertheless.
Before we compete with AI for our jobs, we’ll be competing with it for our electricity. This issue will be central to the AI policy debate.
Infrastructure power needs are also going to be a critical constraint for many countries seeking AI sovereignty.
Our next Fireside Chat features Markus Herrmann Chen of the China Macro Group. Join us Monday, January 27th at 12:30PM to discuss the #TikTokBan and what the incoming Trump administration could mean for China's tech sector and US-China tech competition.
Register now: bit.ly/mhchen
Absolutely — any legislation that requires “taking the training data out” seems pointless. The transaction costs of opt-out should also be considered. Personal data might be a better candidate than copyrighted data for opt-out — we don’t let copyright holders opt out of other forms of fair use.
The week’s more visible changes in Meta content filtering obscured these revelations about their training data governance choices. Here’s hoping 2025 brings greater clarity about how broadly the #fairuse doctrine covers copyrighted works being used to train #AI systems like ChatGPT, Claude and Llama
if they do acquiesce to an acquisition, wouldn’t Google/Waymo be another possible suitor? Apart from their user base, Uber and Lyft have deep operational expertise and IP, something that Waymo or Google can’t rapidly replicate, and which seems very synergistic with their existing tech.
Related: an excellent 1/1 NYT oped by Jessica Grose about the virtues of modest levels of solitude, and of “embracing loneliness as a normal feeling that we all experience from time to time, rather than necessarily being pathological.”
“Idleness as such is by no means a root of evil; quite the contrary, it is a truly divine way of life, so long as one is not bored,” Kierkegaard wrote.
the #OpenAI plan to become a for-profit company reminds me of this old cartoon.
3/ Is it sufficient to accept superficial fixes that balance out generated content for a vast majority of prompts (like the LLMs and image generators have done) or do we need to delve deeper into understanding the machine equivalent of the gender beliefs of their underlying models?
2/ What’s the right metric to measure bias in generative AI models? Do we want them to reflect “base rate” reality, or do we want them to be aspirational? Two colleagues and I looked into this a little a year or so ago in the context of LLM recall of Nobel Prize winners.
1/ in an interesting experiment, #sora created a white male-presenting character when prompted to generate an “academic giving a lecture.” what’s surprising is that it consistently did so on 16 consecutive trials. This will likely be “rectified” rapidly, but raises familiar (and hard) questions:
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(NYU's term for "post doc" is "research scientist")
AEA JOE link:
www.aeaweb.org/joe/listing....
Triggered by @annagoeddeke.bsky.social's post: "The Deadweight Loss of Christmas" (a very cool paper) makes me wonder if government economic policy bodies should include experts from the other social sciences with an established track record of interdisciplinary thinking. Longer version below.
18 months later, my June 2023 TEDx talk about the challenges that generative AI might pose to human intellectual autonomy is finally online. Would be delighted to hear what you think.
(And yes, I know, Google’s LLM is not called Bard any more:)
What’s something you didn’t do in your 20s that you wish you had done? (Granted, this works better for groups in which there’s a critical mass of people willing to admit not currently being in their 20s, but it engages the younger folks in a mixed-age group a lot more than one might expect.)
I’m enjoying Wolfgang Streeck’s “Taking Back Control.” I don’t agree with a lot of it, but it’s an interesting read.
I wrote something about the migration from X to Bluesky. (I did not choose the title, and do not like it, but there you go.)
www.nytimes.com/2024/12/07/o...
holding a shiny round silicon wafer
me holding a silicon wafer at ASML’s headquarters last week. i’d argue that their machines represent humanity’s most incredible engineering accomplishment to date.
2/ True, some are vertically integrated (Google, maybe Meta), but OpenAI and Anthropic aren’t, and all depend on Nvidia (and thus indirectly on TSMC and ASML). The hardware-software value capture dynamic could also invert. Many economic forces counter data-driven winner-take-all dynamics from LLMs.
1/ Looking at the premise of the original article linked to — I’m not sure that the “LLM builders” today are going to be the eventual value capture layer. They are sandwiched between the user layer (copilot, retail, advertising) and the infrastructure layer, both of which seem to have more power.
this is very compelling. i don’t think we really have a good understanding of what has led to the sudden dramatic recent success of fantasists. Part of this might be understanding what has made humans susceptible to them in the past, and perhaps also how fragmented the “chorus” was pre-broadcast TV.
so here’s an essay i wrote for the @aspeninstitute.bsky.social recently. our focus on copyright and training data is making us miss the more important IP challenge raised by #AI: making sure people have sufficient ownership over their human capital. www.aspeninstitute.org/blog-posts/a...
