Sure, the eventual societal equilibrium of a world with instant AI-generated nude photography is that value of shame over nude photography inflates away to zero.
But that’s cold comfort to a teenage girl being mocked from the next lunch table today.
I opened the lesswrong homepage through archive.org on an arbitrary date in 2010, where I found a post about raising $100000 for a grant program. Most of that went towards papers and fellowships at the singularity institute AFAICT.
Start small and be consistent. A few years ago at over 300lbs I started by walking around the park across the street. About .5 miles. Every day I tried to add 1%.
After six months I added a light jog for a mile.
Six months after that I was well enough to start HIIT classes. Six months after that I was strong enough to start real weight training and distance running.
Three years later I am down ~80lbs, able to run 10 miles at an 8:00 pace, and bench 205.
These aren’t extreme numbers for someone who started off reasonably healthy. But if you’ve been sedentary a long time, the difference in how you move and feel will be shocking.
Starting off can pose real challenges to your sense of self-worth, because you feel pathetic when you see how small your initial efforts are compared to what you see online and in media. It’s important to shift your mindset toward self-comparison, being slightly better than yourself yesterday.
If you’re struggling because you have chosen other priorities over your body (e.g. coding, family) in your 20s, I promise you, you will get there with consistent effort and compounded effort over time.
>What’s the clinical definition of “tight shoulders”?
Chronic contraction of the upper trapezius.
>[I]s it shown to correlate significantly with inhalation problems?
There’s not much in the medical literature beyond noting that that upper trapezius is an accessory muscle in expanding the lungs. (MDs correct me if this is wrong.)
Physiotherapy research is less rigorous but more expansive on the point. See e.g. Kim et al.
>BACKGROUND:
Forward head posture (FHP) causes changes in the strengths and rigidities of cervical muscles.
OBJECTIVE:
The aim of this study was to investigate correlations between FHP and respiratory functions and the muscle activities of respiratory accessory muscles in young adults in their 20s.
METHODS:
A volunteer sample of 33 healthy young adults participated in this study. Craniovertebral angle (CVA), cranial rotational angle (CRA), vital capacity (VC), forced vital capacity (FVC), forced expiratory volume at 1 second (FEV1), peak expiratory flow (PEF), maximal voluntary ventilation (MVV), and sternocleidomastoid (SCM) and upper trapezius activity ratios were measured.
RESULTS:
Significant positive correlations were found between CVA and VC, FVC, FEV1, PEF, and MVV, and a significant negative correlation was found between CVA and SCM activity ratio. Significant negative correlations existed between CRA and VC and FVC, and significant positive correlations between CRA and SCM and upper trapezius activity ratios.
100% of people know the most common 1000 words. The remainder of those who know more words fall into a consistent curve across languages that follows Zipf’s law. This is different than “most people know 1000 words on average.”
After the CPUC voted to approve the self-driving expansion, the same people that tried to block self-driving cars there pulled two regulatory levers.
First, the California DMV, with result seen here.
The incident that triggered this event happened when a human driver, who is still at large, hit a pedestrian who flew into the path of the Cruise vehicle.
The car executed a maneuver to pull over for a safety stop, but failed to recognize the woman who was dragged some distance.
Second, they reached to the Federal agencies via Nancy Pelosi’s office, with primary focus being the NHTSA, the National Highway Traffic Safety Administration.
The request was to gather data, which given the friendly posture of the NHTSA at this time will likely result in the opening of an investigation.
Both of these moves have some bite. The California DMV can suspend licensure as happened here.
But they’re fairly straight-shooter civil service types in the end, and they’ll eventually clear the vehicles for use. You can see this in part because of the action against Cruise only, rather than Waymo.
Some may attribute this to Waymo’s greater political sway in California. But my experience of the products themselves is that Waymo has a higher quality self-driving system.
The NHTSA is a bit trickier to predict.
The NHTSA’s powers are broad in theory and as granted by statute. They could theoretically issue an order to remove a type of vehicle from the road for imminent threat to public safety.
However, their typical modus operandi is to issue recalls and work with the auto companies. They won’t want to test these powers under the current court, so my opinion is that they won’t take much action.
Generally I appreciate Elon Musk’s work a lot. He created two world-changing companies in SpaceX and Tesla. I wanted him to be good at running Twitter/X.
It seemed like a good match. Staid company meets indefatigable executive.
His early moves prompted a lot of pushback but were generally wise: Diversified away from ad revenue. Introduced breaking changes to accustom the user base to faster development. Cut costs they couldn’t afford by shuttering a data center. Shrunk a bloated team to die-hards via whaling-and-culling. Not least, open sourced some recommender system code, and largely solved the content moderation problem via Community Notes.
Individually, all good steps. Sure, there were many misfires along the way: the verification system, launch of Twitter Blue, and erratic public ideation of potential features.
But I am ready to declare the Musk&Twitter/X experiment a failure.
The crux of the matter is this: Twitter exists as part of an ecosystem. Elon has alienated a large part of that ecosystem, both in terms of creators and advertisers.
I don’t know whether the network effect will tip or the business will run out of cash first, but I am confident it will not grow enough to justify the investment.
Maybe I’m wrong. Maybe alternate revenue streams and the value of Twitter’s data for AI training will be enough to keep it viable.
He was forced to due to ad revenue plummeting as a reaction to his own actions and policies.
>Introduced breaking changes to accustom the user base to faster development.
What does faster development have to do with breaking almost a decade's worth of UX and muscular memory? You can ship _bad_ changes quickly. I lost track of the amount of times I tapped Reply instead of Retweet after they shifted all buttons right when they introduced viewcounts.
> Shrunk a bloated team to die-hards via whaling-and-culling.
I'd argue there's a reasonable middle ground between "a bloated team" and "just the die-hards".
> largely solved the content moderation problem via Community Notes.
Community notes existed before Musk, and their role is to dispute a claim or provide context. They don't moderate content in any way.
>He was forced to due to ad revenue plummeting as a reaction to his own actions and policies.
That’s incorrect. The need to diversify away from ad revenue was a topic discussed with Jack prior to the acquisition. The rationale was that advertisers effective control content moderation policies due to the revenue which they provide.
This is true. Whether it’s bad on or not depends on your viewpoint and ideological position. What advertisers want for now, e.g. with regard to social policy, may be aligned with what you or I want now.
But there’s no guarantee that will be true in the future.
>I’d argue there’s a reasonable middle ground between “a bloated team” and “just the die-hards.
Layoffs are painful, and they were handled poorly. But there can be no doubt the prior company was massively overstaffed.
If you’re going to cut, generally you want to cut deep to prevent future rounds. Arguably not increasing the size of the first layoffs led to the second, and more people could have been preserved in total.
There’s very little virtue in “middle ground” in this context.
> Community notes existed before Musk, and their role is to dispute a claim or provide context. They don’t moderate content in any way.
It doesn’t moderate content in any way… except for placing large labels to “dispute a claim or provide context.”
Sure, if you very narrowly constraint content moderation to the Trust and Safety definition of removing content and administering bans it doesn’t.
Birdwatch existed, but the prominence of the feature and improved reliability of the feature weren’t launched until after acquisition.
It solved the main edge cases for content moderation by only displaying labels when moderators who disagreed sufficiently on other issues agreed on that particular label.
It has significantly impacted the disinformation at scale problem for the better.
Ad revenue diversified away from Twitter, and Musk is desperately trying to get any cashflow he can while refusing to pay bills
>Introduced breaking changes to accustom the user base to faster development
Why is this a good thing, on any planet? "We broke shit on purpose so that you would be used to us breaking shit regularly"
>Shrunk a bloated team to die-hards via whaling-and-culling
This is a weird way to say "fired anyone who told him that he was being dumb"
>Not least, open sourced some recommender system code
No he didn't. This one irks me so much. I work with machine learning models every day, and if you were familiar with working with ML, you would easily recognize what was "open sourced" (it's just source available) as just the basic scaffolding code AROUND the model. It would be like if you said you were going to open source your excel spreadsheet of important data, and you just put up the code for OpenOffice on github. You didn't "open source" anything that matters, and certainly not "the algorithm"
This is the kind of highly emotional reaction that’s not helpful.
Yes, I am quite familiar with building ML models, both training and building my own for which I’ve been paid large sums of money, and I’m here to tell you that you don’t know what you’re taking about.
There’s so much more information about an ML system than just the trained model that is important for understanding the effects of the system on a society, and its legal, ethical, and social ramifications.
Just seeing the type of RS being used, the ranking approach, and the information on SimClusters is enough for RAI folks to start to understand the ecosystem effects and how that can show up downstream in social effects.
This strikes me as less a leak and more clever marketing from Mistral.