bloaf

>and the reporter, without evidence, also implied

This is not an accurate characterization. The author reviewed the speaker's slides, interviewed students in the lecture, and consulted with her professional network; the reporter's investigation yielded no evidence of censure-worthy content or propensity for political rants.

> We don't have any facts that would support the narrative that the government encouraged the censure or the investigation in any way.

This is not an accurate characterization. The reporter has provided information from the university's spokespeople that Texas Land Commissioner Dawn Buckingham was the one who first contacted the university's governmental relations office as well as Lt. Gov. Dan Patrick. Patrick then contacted the chair of the University of Texas System’s board.

The board responded to Patrick, within 2 hours of the end of the lecture, quote: "Joy Alonzo has been placed on administrative leave pending investigation re firing her. shud [sic] be finished by end of week."

> Of course I'd change my opinion if more information comes to light.

You're not even engaging with the facts as they stand.

Occam's razor would suggest this isn't done arbitrarily. The simplest explanation for the set of facts before us is that the one student complained to mommy, who complained to the school in conjunction with Patrick. The school immediately kowtowed to this political pressure and made motions to punish the person they complained about, without any diligence whatsoever. Now that everyone is complaining, they aren't releasing the details of their censure because there aren't any.

Did the California Community Colleges implement anti-racist policies because they believed they resulted in the best pedagogy, or because politicians told them to?

This article doesn't say, but it does appear from other reporting that the community colleges implemented these policies without influence from state politicians.

https://www.latimes.com/california/story/2020-06-12/communit...

That means it is not an analogue to the Texas scenario, where the university censured people because the politicians said to.

I was struck by the final passage in the article:

>“While it is important to preserve and defend academic freedom and as such be able to discuss and present to students and the public the results of research observations and strategies, you should be mindful of how you present your views,” Udeani [the pharmacy school Dean] said.

Notably, Texas has banned diversity and inclusion programs and trainings. I think it is a valid line of questioning to ask whether or not the Dean's advice here constitutes an inclusivity mandate that would be illegal under Texas law.

This is not an accurate characterization.

- She made factual statements about policy impacts on overdose deaths.

- A politician's relative who was in attendance reported it to the political party backing those policies.

- The politicians successfully signaled to those at the university that criticizing their policies will be inconvenient at least, and a realistic threat to your career.

* Edit, for emphasis:

Your characterization would be like saying that it is fine that you're driving drunk since your car's auto-breaking feature is working and preventing you from hitting pedestrians.

This bloke on huggingface documents the memory requirements for his quantized versions of popular models: https://huggingface.co/TheBloke

Tl;Dr, Max ram needed depends on quant method, rough ranges are:

7B models are in the 4-8GB range

13B models 8-15GB

30B models 13-33GB

70B models 31-75GB

I'm running a 30B model on an amd 5600x cpu at 2-3 tokens/s, which is just under a "read-aloud" pace. I'd wager that you can run a 70B model at about the same speed with a 7900x and a bit more RAM.

Its pretty clearly a vicious cycle. Racism is right in the loop too, because its a lot easier for people to adopt racist attitudes when communities that break along racial lines are undeniably having struggles with addiction.

This was in Australia, which already has universal health care and a minimum wage of $23.23 (AUD).

> Indigenous people and advocates have long warned restrictions and bans are not the solution, urging action on addressing drivers of harm such as... family violence.

The bans reduced domestic violence calls by 37%. It sounds like the advocates don't want to appear paternalistic, and that led to them opposing measures that actually help a lot.

There was a lovely comic years ago, entitled "the foolproof way" which captures this feeling.

https://www.deviantart.com/eldahast/art/Foolproof-way-155527...

Those method would work on recurrent neutral nets, not just feed forward.

One interesting application is to imagine you have a bunch of data in some proprietary binary format, with metadata in plain text.

This is saying you could potentially make a network that generates new instances of the proprietary format without having to know the details of that format.

That's interesting, because I've tried to use F# several times, and never really felt comfortable. I've written in a bunch of different languages and F# is probably the most disappointing because of how much I want to like it.

I feel like F# deceptively presents itself as simple, when in reality it is closer to C# in complexity. I've written in languages that are actually simple (tcl) and it is a joy. I've written in languages that are unashamedly complex (Wolfram language) and that is also fun. But F# occupies that weird middle ground where it seems easy to do what you want, but for some reason you trip over your own shoelaces every time you take a step.

No. I'm talking about things like polymer rheological or film properties, or industrial scale reactor performance. That's not to mention one-offs like cloud point predictors, or specialized thermo packages.

See, for example, https://www.technipenergies.com/sites/energies/files/2021-11...

They do. Internally, the gatekeepers of this data are mostly old-school chemists whose ideas of AI are stuck in the "maybe AI can do some property predictions better than our first principles FORTRAN 77 models, but I doubt it" mindset.

No. This is a counter-claim to the conservative talking point that Biden is irresponsibly escalating towards nuclear war.

Imagine if you were trying to optimize a real physical system you didn't have a model of. These methods will still work; you could implement them "by hand" if necessary.

While we're at it:

* Taichi "is embedded in Python and uses modern just-in-time (JIT) frameworks (for example LLVM, SPIR-V) to offload the Python source code to native GPU or CPU instructions, offering the performance at both development time and runtime."

https://www.taichi-lang.org/

I think that is the reason jupyter is as popular as it is.

One of the wilder possibilities of the future of AI is discovering that we as humans have some form of collective anosognosia. The AI would just repeatedly and confidently assert things that we knew to be false, and we'd go to great lengths just to give the AI the same cognitive blinders we're wearing.

https://en.wikipedia.org/wiki/Anosognosia

Right now, the AI is operating "inside the bubble" of our thoughts and so is unlikely to figure out our collective blind spot, but once one can interact with the world in more meaningful ways, we should pay really close attention to the mistakes it makes.

So, yes, gpt4 isn't suddenly going to become godpt.

But when people say we're close, I think they mean 1 accidental breakthrough away.

Like the "just add more layers" meme, the solution to the own-dataset creation problem could be stupidly simple, just waiting for some bored student with access to a decent machine to accidentally find it. For example, maybe just giving the AI the right novelty seeking behaviors (like children have) will be enough to get the process kicked off.

My objection to the singulatarian concept of a self improving AI is simply that I haven't really heard a reason to think that there exist intelligence algorithms that are dramatically superior to ours. It is entirely possible that our thinking algorithms are optimal-enough that rapid self improvement leads straight to something not much different from human intelligence, just faster, and in silicon.

1. Their existence is the political justification for inaction.

2. They form an unholy alliance with other anti-empiricist groups (e.g. anti-vaxxers, young earth creationists) to undermine reality-based policies, including in education.

3. Their denialist opinions are typically held in bad faith. That is, they are held because if they were true they would confirm some pre-existing belief (e.g. that scientists are tools of a global elite cabal), not because an independent evaluation of the facts has led them there. This reinforces their hostility towards whatever group they think is lying.

4. Denialists typically engage in a perverse form of virtue signaling. The greater and more well evidence a claim is, the greater the "cred" they get for denying it. This creates a fertile field for sham experts to sell lies to members.

I personally feel like negative filters are important because they create an incentive for advertisers/SEO/etc people to not spam every keyword into their product.

If you're only allowed positive searches, the best way to get your product found is to maximize the number of positive search terms associated with your product. With negative search terms, every additional term you add is a potential exclusion criteria as well.

Unfortunately, people just don't use the negative search terms enough, so it is up to the search engines themselves to detect metadata bloat, and that ends up being a cat-and-mouse game.

ah, the auto-corrected version of 'rdfind'

I've used fdupes and refund for exact duplicate finding.

They work shockingly well on large libraries, I've managed to check millions of files consuming several TBs in a matter of hours.

There are deep philosophical implications, just not these.

There has been a long history of reifying the behaviors of living things in general (e.g. vitalism) and humans in particular (e.g. dualism).

The success of LLMs challenges a lot of philosophy dealing with what behaviors are and are not possible in the absence of these categorical districtions.

I have had casual debates years ago, in which strong dualists asserted that the kind of creativity exhibited by today's LLMs is simply impossible. No doubt those folks are busy inventing "special philosophical creativity" that LLMs "aren't really doing," but they've lost credibility.

LLMs have demonstrated that there was never any need to invoke categorical districtions between human behavior and math-as-implemented-by-physics. The gap is closed, there is no more room for gods.

Explorer can resolve some http urls to network paths, e.g. for SharePoint libraries.

Programs, e.g. python scripts, can then use those paths, but only after explorer has resolved them. Before that, the path will be treated as not existing.

The Red Green Show did comedy segments on both these concepts:

Turkey in a dishwasher: https://www.youtube.com/watch?v=P5Y4RV8pcY0

Turkey in a car: https://www.youtube.com/watch?v=niegc7QcilM

> A UBI experiment, in contrast, might be a good way to convince people of the folly of the UBI. For a modest cost, you could persuasively demonstrate the strong disincentive effects, reducing support for this massive waste of resources.

This response is insidious, but not because of the professor's position on UBI.

If we already had overwhelming evidence that a new UBI study would "persuasively demonstrate the strong disincentive effects", then that evidence would by itself "persuasively demonstrate the strong disincentive effects." Furthermore, if such evidence existed, the proponents of UBI would already be ignoring it.

Therefore, the first strike against the suggested response is that it lacks basic logic: either the professor lacks enough evidence to knows the outcome of the study before it is done, or the professor is not justified in asserting that more such evidence will be persuasive.

The second strike is this: If the professor expected students to be familiar with the evidence against UBI, then we should expect the professor to be looking for the students to demonstrate that familiarity by referencing it in support of their conclusion (i.e. that a UBI study would have a certain outcome.) That the professor does not expect this indicates that he is not training students to make arguments based on evidence.

The final strike is the evaluation of the UBI as a persuasive tool. Even if we assume that the professor is correct on both counts (i.e. that a UBI study will be negative and persuasive), that by itself isn't a justification for a "modest cost" in an Effective Altruism framework. I wouldn't spend a "modest amount" to convince some people that the earth is not flat, for example, because it would have no real impact on any of the metrics Effective Altruists use. Because the professor stops short of connecting the educational outcome to the EA metrics, he has presented a failure of a response as a suggested response.

So to summarize: the response is internally incoherent, expects authoritative phrasing over evidence, and ultimately fails to directly connect the claims to the question.

My old android phone got 52.7±2 chrome, 51.6±0.8 in Firefox, so effectively the same.

However, I had to disable some ff add-ons to get that score (chrome had no add-ons to begin with).