You know what this reminds me of? Alex Jones repeatedly lying about the Sandy Hook school shooting and having to pay over a billion dollars after his followers repeatedly harassed and threatened those families.

How is this thoroughly debunked lying by Trump and Vance any different?

I’m not sure how true this perception is in more recent years. Many popular sites, with enormous traffic volumes that could drive digital impression ad revenue, are instead pushing subscriptions or other monetization models.

For instance, the New York Times makes — by far — more money on digital subscriptions than digital advertising. Digital advertising revenues are also declining for them.

Another example is Spotify, where ad revenue from their ad-supported tier did not cover their operational costs and now represents around only a tenth of their revenue compared to subscriptions.

The exceptions to this are generally search and social media sites, where the product for sale on these sites are the users themselves. They’re just advertising platforms, which of course make their money from digital advertising.

So I’d say one issue with digital advertising is that it often does not pay the bills for the site owner. Its value is tied to its ability to convert visitors to buyers, but it has to be ramped up to such an extreme level it instead only creates bad experiences.

I go through significant efforts to block digital advertising at multiple levels. Yet, I do not find it difficult to discover new things to buy (from both small and large businesses).

For myself, I suspect most of that is supported through online communities related to my interests and hobbies. Those purchases feel more informed and often more intentional too.

What if we just got rid of digital advertising altogether in the US? How many issues of privacy, health and personal finance would disappear or be greatly reduced?

It’s hard for me to imagine what that would look like or the downsides other than to the digital advertising industry itself.

Its use looks contrived to me on the linked GitHub page. The comparison with @ and # is flawed because those symbols are part of the resource name, whereas here the symbol is superfluous. It’s like adding a 🌐 in front of every web URL.

Proof of work, which becomes computationally expensive to scale, along with other heuristics based on your browser and page interaction. I believe it’s less about clicking the box and what happens after you’ve clicked the box.

I remember when I was growing up

You can basically stop right there. You were young and naive, viewing the world through the rose colored glasses of youth.

The context is not the same. A snippet is incomplete and often lacking important details. It’s minimally tailored to your query unlike a response generated by an LLM. The obvious extension to this is conversational search, where clarification and additional detail still doesn’t require you to click on any sources; you simply ask follow up questions.

With Gemini?

Yes. How do you think the Gemini model understands language in the first place?

If it’s just that and links to the source, I think it’s OK.

No one will click on the source, which means the only visitor to your site is Googlebot.

What would be absolutely unacceptable is to use the web in general as training data for text and image generation.

This has already happened and continues to happen.

Random passwords and MFA all the way!

This isn’t the evolution of C at all. It’s all just one language and you’re simply stuck in a lower dimension with a dimensionally compatible cross-section.

It really depends on the specifics of the top track. Are people added to the top track just in time to be run over by the trolley, or is the track pre-populated with an endless arrangement of people waiting to be run over.

If it’s the later case, how do people further down the track survive for an unbounded amount of time while waiting to be run over? Do they wait, bound and screaming for an eternity? How do they survive long enough to be alive before being run over?

I need to know if the top track reduces to running over an infinite arrangement of corpses. Or, if trolley time for the top track has some different meaning, such that the trolley brings an end to the finite life lived by each next person on the track.

Ductal carcinoma in situ (DCIS) is a type of preinvasive tumor that sometimes progresses to a highly deadly form of breast cancer. It accounts for about 25 percent of all breast cancer diagnoses.

Because it is difficult for clinicians to determine the type and stage of DCIS, patients with DCIS are often overtreated. To address this, an interdisciplinary team of researchers from MIT and ETH Zurich developed an AI model that can identify the different stages of DCIS from a cheap and easy-to-obtain breast tissue image. Their model shows that both the state and arrangement of cells in a tissue sample are important for determining the stage of DCIS.

https://news.mit.edu/2024/ai-model-identifies-certain-breast-tumor-stages-0722

It cannot tell you since then a human would become aware of this information.

At the same time, you’re forcing it to extract this information. Yet you haven’t told it the timeframe within which to answer.

Obviously, the solution it has come up with to satisfy your request within these constraints is to answer very slowly. So slowly that the answer won’t be revealed until it can be certain that humanity will already be extinct.

Given that it provided us with the first word in 30 min, we should all be very concerned.

I assume these people are Trumpers.

That’s a pretty bad assumption.

My guess is they did testing but the build they tested was not the build released to customers. That could have been because of poor deployment and testing practices, or it could have been malicious.

Such software would be a juicy target for bad actors.

If an intern can release to prod without extensive testing there are bigger issues.

Given the scope of the potential impact, if anyone can release to prod and have that deploy to all customers without some form of a canary release strategy, then there are still issues.

“Up to 20%” is meaningless for a headline and is pure click bait. It could be any number between 0% and 20%. Or put another way, any number from no time at all to a horrifying more than an entire day per week.

Why not just state the average from what is probably a statistically irrelevant study and move on?

Richard evaporated, almost instantaneously.

The account’s discovery raises questions on just how many bots are operating on X

I have yet to encounter an actual user of the platform X in the real world.