agnosticmantis

"Most single mothers start from behind; they're less likely to have a college education or a high income. Single motherhood is a lot less prevalent in higher-educated women. This college gap exists for white, Black and Latino families."

These seem to be things to control for before making a causal claim. I haven't read the original study, but wouldn't be surprised if they didn't control for these (and other) important factor because then they'd likely not reach their desired result.

I meant to say layoffs are not (necessarily) due to ChatGPT disruption, even though the title may suggest that. All sorts of companies are doing layoffs, SO happens to be one of them.

PSA: "after" does not mean "due to".

It's a shame that companies that are actually creating great tech and solving difficult problems are shrinking while some vaporware nonsense raises a billion:

https://www.theverge.com/2023/9/28/23893939/jony-ive-openai-...

Really? And they could do LSTMs?

Even if true, they could take a random subset of size 100 out of the 300k and compare on those.

Is this the standard we apply to other cyber-criminals? Or any crime for that matter? Do we ask how vulnerable the victims were? And how we should make them less vulnerable and give a free pass to the aggressors?

This is a false comparison. Being hacked by NSO isn’t an accident. There’s an agent involved here with clear intent to harm and significant monetary motives.

If in a car accident we knew one party intentionally caused the crash (and were paid for it handsomely), we’d hold them responsible, regardless what claims car companies make regarding safety.

I find it interesting that most comments here are blaming the victim (Apple’s iMessage and by transitivity its users) rather than the aggressor (NSO and its users).

How come NSO isn’t yet designated as a (cyber-)terrorist group worth hunting down and extinguishing?

I was a kid back then, so not really aware of the cutting edge research happening in those days, but here’s for example the description of Russel & Norvig’s “Artificial Intelligence: A Modern Approach (2nd edition, published 2003)”:

“The long-anticipated revision of this best-selling book offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For those interested in artificial intelligence.”

Some may find it interesting that John McCarthy coined the term Artificial Intelligence and was called a/the father of AI before the deep learning folks took over. This AI referred to the symbolic flavor not the connectionist one.

Nowadays (god-)fathers of AI are Geoff Hinton and Yann LeCun and others, but 20 years ago things were very different…

Out of curiosity, are there any spies that read hacker news?

> They then sell this data on dozens or hundreds of data broker platforms.

I wasn’t aware of this part specifically, so I’d like to learn more. Has this been covered in the news or something? This seems like a big deal.

> … The Information reported, citing an internal source.

Luckily the projection is from an unbiased and reputable source that can be held responsible later.

Out of curiosity, what are some examples of Google packaging and reselling data?

How about when a competitor uses VC money to gain market share by “selling” dollars for 90 cents to customers? It’s hard to become profitable in such a market when the competitors are burning cash to gain market share. Isn’t that how Amazon, PayPal, Uber, etc. grew to their current scale and killed the competition?

How does this play with wildfires?

Thinking of the recent article [0] on the “miracle house” in Hawaii that survived the fires even though entire blocks around it burned to ashes. The key was to not have combustible stuff on or close to the walls:

“But Michael Wara, the director of the Climate and Energy Policy Program at the Stanford Wood Institute for the Environment, said it was likely the Millikins’ decision to dig out the existing landscaping directly surrounding the house and replace it with river stones that made the biggest difference.

“What folks in the wildfire business call the zone zero or the ember ignition zone, is kind of a key factor in whether homes do or do not burn down,” Wara said.

Having nothing combustible in the 5 feet directly around a house is enormously important.”

[0: https://www.civilbeat.org/2023/08/what-saved-the-miracle-hou... ]

There are some inequalities too, so we need some slack variables. /s

Because nowadays cars are computers on wheels with lots of sensors, so we don’t need to only rely on human ears and brains like we had to in 1950s.

I think modernizing traffic signals will end up making transportation more efficient and safer. (Just imagine knowing the timing of the next 5 traffic lights on your path.)

Maybe we should try other signaling methods (radio?) for emergency vehicles that’s easier to process for computers. That may be end up being useful for human drivers too ultimately.

Yes please.

I’d say it depends on what “writ large” here refers to. Is it “the larger population of Tech startups” or “tech companies in general”?

If former then maybe the thesis holds true, but data scientist in more established companies do vastly different things than in startups.

It’d be good to extend the analysis by accounting for company size.

Now we have a word for green too? /s

Looking it up, it seems like there are only five words for colors:

pimeja (black), walo (white), loje (red), jelo (yellow), and laso (blue and green)

I’d call it Hacker Onion.

Have we finally found the killer app for blockchain?

Until we learn that this monitoring app has itself been acquired. /s

I meant the LLM weights are not publicly available in the case of ØpenAI, so whatever you contribute to it will be locked up, just like SO locked up their user-generated data.

By the same token (no pun intended), locking up such data in a closed (in many senses) LLM wouldn’t be a desirable outcome?

Neat idea!

The PR industrial complex has been trying so hard to convince us that the all-knowing all-seeing almighty AI is going to take our jobs and turn us into Soylent or whatever. Now let’s feed it some garbage and see if in all its glory it can tell sense from nonsense.

That’s a good point, I hadn’t thought of these cases.

On a second thought, I guess a lot of marketing content would also love to be crawled by anything that crawls…

What’s the incentive for people to allow the crawler at all?

Unlike search engines, chatgpt doesn’t cite references at all (last I tried) or even if it does it often makes up nonexistent references. And because it rephrases the content, there’s often no way to prove they got the material from a particular source, so harder to litigate plagiarism too.

How would contributing to the weights of this LLM help content creators?