orasis

Since Apple controls the App Store they would likely be sued into oblivion.

You don’t learn how to parent, you learn how to live, in a wholehearted way, and you model that for your children.

Good parenting is foremost about growing up before your kids do.

There is nothing simple or minimalist about C style separate header files with hacked on property synthesizers. The language is an aggregation of hacks.

C, C++, Java, Kotlin, JavaScript, Python, Ruby, Objective C, Swift

I’ve written a lot of Objective C.

It is by far the worst language I’ve used professionally.

While I don’t love Swift it is still a breath of fresh air compared to ObjC.

The best source of truth is found in the here and now, grounded in the body and one’s immediate environment.

We socialize with each other to regulate each other - ideally taking that grounded truth and intermingling it with the grounded truth of others.

This has always been the healthy way.

This is for GPT 3.5 as well.

Nice! Do you generate N questions so N embeddings per document or just one?

Why regurgitate an obviously failed philosophy?

One caveat about about embedding based retrieval is that there is no guarantee that the embedded documents will look like the query.

One trick is to have a LLM hallucinate a document based on the query, and then embed that hallucinated document. Unfortunately this increases the latency since it incurs another round trip to the LLM.

It’s a prank.

Interesting. What systems or algorithms are you referring to by “clustering”?

Can these databases do fast averaging of nearest neighbors for regression or do you have to retrieve the neighbors and manually compute a mean across them?

Best to read the book before watching the film.

Why is there so much aviation disaster porn on here recently?

This is turning into the same sort of high drama news site that most of us are trying to get away from.

I live near Yellowstone. This is a sad joke.

No one wants the pristine nature of our first National Park soiled and the logistics of building infrastructure in such intensely mountainous terrain would be wildly impractical.

The billionaires already have a hard enough time getting their “cabins” built at the Yellowstone Club.

yawn For those of us that actually use ChatGPT on a daily basis it’s an incredible productivity booster.

We know that it’s a language model and you can get it to say naughty things. So what?

It becomes a regression problem. You use ML to estimate the conversion rate for each item. You still have to do feature engineering, but fast regressors like XGBoost make this much easier. https://improve.ai is one such scorer/ranker built on XGBoost.

If you’re worried about having too little data then A/B tests are the wrong tool for the job.

It’s better to just use ML scorers and rankers.

Another reason to not base64 encode is that many URLs with base64 strings will break in iMessage do to strings randomly matching various keywords that iMessage looks for. I think ‘usd’ is one such substring to look out for.

How many bits is this?

Two winters ago I tried to drive my model 3 across North Dakota - never will I do that again. Range was cut in half and I had to stop at every single supercharger.

For a bit of history, this type of thing has been around a very long time:

https://lists.w3.org/Archives/Public/www-talk/2001NovDec/009...

As a 20 year combat athlete I can assure you that a physical fight and video games feel totally different. In a real fight every muscle fiber struggles at it’s limit for survival - the intensity is all consuming both mentally and physically.

Entrepreneurship is an extremely challenging practice. My biggest wins have come from seeing things in ways that don't occur to ordinary people and some of those insights I've discovered through books.

I haven't worked for someone else in over 20 years, live in my favorite place in the world, and work when I want to. That book and the concept of "lifestyle design" are big contributors to my extraordinary happiness.

A little known feature of Swift/iOS is NLEmbedding (https://developer.apple.com/documentation/naturallanguage/nl...). As the name implies, it is a built-in natural language embedding model that will produce the same embeddings across all iOS devices. I can't tell for sure but I would guess it is some sort of BERT model and probably weighs in at hundreds of megabytes.

The author argues that AI algorithms don’t have desires, yet this is precisely what reinforcement learning simulates.

With reinforcement learning positive rewards are assigned for positive outcomes (a “carrot”) and negative rewards are assigned for negative outcomes (a “stick”).

The model is trained to maximize the expected rewards per decision. I’d say this is fairly analogous to desire.

I’ve written an introduction to reinforcement learning here: https://improve.ai/reinforcement-learning/

“The Century of the Self” by Adam Curtis.

https://youtu.be/eJ3RzGoQC4s

It goes through each decade of the 1900s and explains how Freud’s psychology and the new field of marketing completely reshaped society. For the first time in my life I feel like I understood the “why” of how things work in American society. This film is probably best if you’re age 40+ and actually remember some of the events.

That is an extremely difficult film. For me it was on par with watching Schindler’s List.