davidhs

It is not as you feel any different when you are being recorded. Once recorded, you don't know what they will do with the video.

I recommend trying Codex too. In fact, I recommend running them side-by-side if you have the budget, e.g. have both independently plan the same feature or implement in a different worktree, or have them critique each other's work.

I personally find GPT-5.5 to be a better programmer than Opus 4.8, it is extremely thorough, but I don't like the code it generates ("austere"), and find Opus 4.8 to write more "human friendly" code. The programming comments GPT-5.5 makes is pretty awful where-as Opus 4.8 is good. I feel like Opus 4.8 is better at grasping my intention than GPT-5.5, and honestly find GPT-5.5 to be kind of "autistic". I do prefer the language (not the writing) of GPT-5.5, as I find the philosophical flowery language of Opus 4.8 kind of annoying.

I have only managed to try Fable 5 a little bit, which feels like a much more generally smarter version of Opus 4.8, that is much better a programming and grasping your intention, and I think even the intention of your code, and is _really_ good at spotting bugs or problems with logic in your code. It feels wicked smart but is extemely expensive. It feels smart in the sense like it has a "bigger brain" and is much more sensitive to subtleties/details.

These are different "brains", have different "personalities", etc. I think the best thing is to develop a feeling for it yourself.

> Looks like it's going to be a thoroughly frustrating experience, even worse than initial rollout.

Honestly, why bother with it? They are effectively just releasing the model in-name, but we just get Opus 4.8.

Mice have the best drugs.

There are people interested in overcoming aphantasia (or hypophantasia, an extremely weak form of imagination).

Today I have medium-ish hypophantasia, but I remember when I was doing phantasia exercises, in particular "snapshotting" and "memory streaming", at least two times, there was a subtle shift in my perception and all of a sudden I could remember a ton of things, as if I opened a door. It would only last maybe 10-20 minutes (I would practice 30 - 60 minutes per day).

It wouldn't surprise me a bunch of those memories are in the brain but you just don't have access to them in everyday waking consciousness.

So, for me, it feels like a lot of my memories are visually indexed, and if I can't visualize then I can't remember, but once I configure my mind through meditation and these exercises, it is like I can "tune my mind" to mind's eye access (radio/TV analogy here) and with it the memories.

Then once I stopped the exercise (for the day) it would go away in around 10-20 minutes (kind of like how a muscle pump goes away rather quickly after exercising).

Maybe if Terence Tao had memorized the entire Internet (and pretty much all media), then maybe he would find bits and pieces of the problem remind him of certain known solutions and be able to connect the dots himself.

But, I don't know. I tend to view these (reasoning) LLMs as alien minds and my intuition of what is perhaps happening under the hood is not good.

I just know that people have been using these LLMs as search engines (including Stephen Wolfram), browsing through what these LLMs perhaps know and have connected together.

It looks like these models work pretty well as natural language search engines and at connecting together dots of disparate things humans haven't done.

> It’s almost certainly not

AIs are RLHF'd to have a corporate-pleasing interface w.r.t. metrics.

The strength of the glasses alters the size of the image that lands on your retinas. More (-) means a smaller image thus you stop seeing movement much closer to the focal point.

Do you? Don't you just halt and say this is too complex?

If the internal representation of Tesla Autopilot is similar to what the UI displays, i.e. the location of the w.r.t. to everything else, and we had a human whose internal representation is similar, everything jumping around in consciousness, we’d be insane to allow him to drive.

Self-driving is probably “AI-hard” as you’d need extensive “world knowledge” and be able to reason about your environment and tolerate faulty sensors (the human eyes are super crappy with all kinds of things that obscure it, such as veins and floaters).

Also, if the Waymo UI accurately represents what it thinks is going on “out there” it is surprisingly crappy. If your conscious experience was like that when you were driving you’d think you had been drugged.

> Yes machine learning vision systems hallucinate, but so do humans.

When was the last time you had full attention on the road and a reflection of light made you super confused and suddenly drive crazy? When was the last time you experienced objects behaving erratically around you, jumping in and out of place, and perhaps morphing?

Honestly, on an iPhone, I wish I could completely mute/disable the Phone app, so when it calls it doesn't overtake whatever you are doing, or just delete it.

> I know they seemed to be trying to temper our expectations leading up to this

Before the release of the model Sam Altman tweeted a picture of the Death Star appearing over the horizon of a planet.

LLMs can be useful when you have access to a verifier or verification process.

I recently took a picture of the ingredients list on my multivitamin and fed it into ChatGPT o1-pro (at least that was the config.) and it made up ingredients and messed up the quantities.

What a mess this language is becoming.

Also, everything you publicly write today is just used as AI fodder. :/

Since when did information travel quickly in the brain (compared to the speed of light)?

Sounds like you have hypophantasia.

Mind's eye/visualisation/phantasia is not seen through one's physical eyes. From how I've heard people explain it, it's:

* (1) Seeing inside your head. * (2) Feels like seeing behind you or/and somewhere else. * (3) Seeing through another set of eyes (mind's eyes) * (4) As if I just saw something, but not with my own eyes.

People can have no mental imagery or visual perception in one's thoughts, aphantasia, to very low/unclear/fuzzy/uncertain mental imagery (hypophantasia), to regular phantasia, which is not as real as looking through one's eyes, and hyperphantasia, where it's almost as good or as good as seeing through one's eyes (the fidelity, resolution, etc.)

Then there's also "prophantasia", or the ability to project visuals in one's visual physical scene, or what one might describe as being able to visually hallucinate. These are the visuals one can see through one's eyes. Prophantasia also is on this low (being able to voluntarily project unclear shapes in the visual noise in one's eye lids in the dark), to high (being able to project "holograms" in one's visual scene).

When people talk about it online they seem to not disambiguate between these visualization modes.

There are potentially other modes of visualization out there that I don't know of.

EDIT: your imagination can also happen in other sense modalities, including sound, olfaction, taste, bodily sensation, etc.

I tried GPT-4o earlier where I was iteratively asking it to write and in improve a simple JavaScript web app that renders graphs of equations and it had a lot of trouble with substituting slow and ineffecient code with faster code, and at some later point where I asked it to implement a new feature how the graph coloring is rendered it started derailing, introducing bugs and very convoluted code.

Very impressive. Its programming skills are still kind of crappy and I seriously doubt its reasoning capacity. It feels like it can deep fake text prediction really well, but in essence there's still something wrong it it.

This article feels overblown. Is async Rust perfect? No, far from it. It feels like a MVP that Rust's developers have neglected for a while. Hopefully picking up some steam these days with partial implementation of async functions in traits. But there still problems with it.

Async Rust is rather nice to use when you're writing a web server. Structuring your code in an async manner is honestly very useful. Writing a composite Future or a Future state machine by hand is super tedious. Async makes most of that pain go away.

We're becoming (cognitively) obsolete.

The problem I find parenthesized languages is the amount of visual noise coming from the parentheses. If you're learning how to write your first interpreter or compiler I kind of assume you already know how to program and understanding S-expressions is not too difficult. Personally, I would have liked to learn and implement closures, continuations, macros, garbage collection, type systems, etc. earlier, and then going deeper into syntax.

My suggestion was more for people who are starting out developing a programming language. It's the over-emphasis on the syntax so early on I find to be suboptimal. I also find that slapping on a more human readable or aesthetically pleasing syntax afterwards to be relatively easy.

After taking a compiler course in uni I found the emphasis on dealing with syntax mostly a waste of time. To begin with, do yourself a favor and use S-expression syntax (like Lisp) for your language. They're dead simple to parse. With the syntax out of the way, you can get to meat and potatoes of implementing a language. Later on you can always define a "look" for your language, and you can spend an inordinate amount of time on that.

It's kind of like English. English is in some sense a simple language (grammar), a poor mixture of other languages and its orthography is not good (not an elegant language), but everyone speaks it.

The Brits love it.

We all know that natural language communication between people never leads to misunderstanding.