discmonkey

I got about two sentences further, it turns out another smoking gun is Mr. Back using c++ in his graduate studies, just like the original bitcoin implementation.

You may not be able to think of a worse experience, but a lot of "newer" programmers may not even know what an LSP is. While it's true that I no longer need to rely on some of the benefits of Jetbrains, when I was getting started jetbrains paving over toolchain difficulties was invaluable.

Assuming that the plugin is enabled for the free version, CLion is also amazing for Rust. Thanks Jetbrains!

Here's hoping this won't be abused by smaller companies that will no longer want to pay for the actual subscription. I also wonder if they are moving towards a different funding model, since the IDE space is pretty competitive with a free alternative (VSCode) out there.

I love the look and the idea, but I wonder if it will go the way of the small/budget phone?

Will folks revealed preference continue to be big and expensive?

Good article. Funnily enough the throw away line "I don't see parentheses anymore". Is my greatest deterrent with lisp. It's not the parens persay, it's the fact that I'm used to reading up to down and left to right. Lisp without something like the clojure macro ->, means that I am reading from right to left, bottom to top - from inside out.

If i programmed enough in lisp I think my brain would adjust to this, but it's almost like I can't full appreciate the language because it reads in the "wrong order".

By definition if I knew how AI would change the world, I would invest/build things to that end. The fact that we still don't have a great AI product outside of chatgpt, shows that no one knows what will happen.

My great-grandmother and grandfather were in Leningrad during the siege. My great-grandmother continued to teach throughout. At some point she was given the option to evacuate with my (very) young grandfather over the "road of life".

As my mother tells the story, my great grandmother had the choice of either taking a bus, or hanging on to the back of some delivery truck. She chose the truck. The bus broke through the ice and disappeared under the water.

It's strange to realize how close one can be to not being "here" and how history weaves its way through your blood and ends up on the front page of hackernews.

Required reading for this theme, and one of my personal favorite short stories:

https://qntm.org/lena

Humans tend to like to stay at there they are, in the tech context especially. It takes a long time relative to the length of a career to learn new systems, make new connections, and achieve some level of independence at a new job. There's also relatively few jobs that at least pretend to be somewhat beneficial to the world while paying somewhat competitive salaries (I can't think of any that I've worked at). Then there's relationships you may have developed with your colleagues.

Finally, if everyone just leaves their jobs without trying to improve them, won't everyone run out of places to jump to eventually?

I did a research project on this a while back - and when it comes to understanding deep network learning rate, regularization, hidden layer effects, and activations, I don't think anything is better than [this little web app](https://playground.tensorflow.org/#activation=tanh&batchSize...)

Article seems to make the argument that is should happen (poorly), but doesn't provide any evidence that it will happen.

Essentially automating project boilerplate that is custom enough to need attention, but not quite custom enough where it's interesting. Some examples include creating dockerfiles, various database models and data parsers, openapi specs, etc.

Classic misunderstanding of programming languages. The only thing stopping cobol from being "known" is these companies paying for it.

yeah - as seen from a few comments on my post, everyone has different opinions on non-objective stuff related to keyboard/trackpad. I feel like the keyboard is pretty responsive while the trackpad isn't, but the only way for you to know is to have tried it I guess.

Glad you are! I don't want to be overly negative. I am comparing my M2 work macbook trackpad with my 2 year old lemur pro trackpad - it's not really a fair comparison. The problem is that the pricing is similar enough where it's hard to justify the hardware downgrade.

I should also mention that my free time to work on projects has dramatically decreased in the past few years, so I am valuing the ability to seamlessly switch between my desktop and laptop on personal projects less than I used to.

Figure I might as well drop a quick review after 2 years with the lemur pro 11

Pros:

* Most things "just work", which you only appreciate after working with other linux laptops. For example, I can seamlessly plug this laptop in place of my work macbook with just one usb-c cable. That being said I think things have generally gotten better in the space so this may not be as much of a selling point anymore. Additionally this laptop doesn't have an nvidia gpu, which means its job is easier.

* Great compatibility for building software between my desktop and this laptop, makes my personal dev work a lot more portable.

* It's quite small and very portable.

* Nice keyboard

* Moral points for supporting a small company that focuses on security (whether this is actually significant is up to the reader)

Cons:

* Battery life is a lie, especially since it drains almost as much battery closed as it does open.

* Not great screen, terrible trackpad, and silly webcam considering the price of the laptop.

* As mentioned no gpu, while costing about the same as razor laptop.

Overall, I think I am probably going to switch back to a macbook after this, not being able to go a day without charging and your laptop always being on low battery is a bit anxiety inducing. Also (and this doesn't matter to a lot of people) I really value a laptop trackpad and this one is just plain bad.

Idk inventing convolutions and a bunch of other stuff we use everyday is somewhat significant. Machine learning, if we call it a field, is a whole lot newer than physics, and so a few people have contributed quite a bit in recent memory.

I have to agree. Especially given the very real possibility that your ML project won't be cutting edge research grade. At that point someone who doesn't have bias and is willing to search for a reasonable looking approximation to the problem and try a canned solution may actually be an optimal candidate.

They do have this, you can choose to bid for a target conversion cost (I want to pay at most $x per conversion). In general I find all of this pretty silly as a Google employee.. I don't think you can distill the complexity of any change down to one article. Say for example that Google did just raise how much advertisers paid per click across the board, why would that lead to billions of dollars in profit? I would bet that the majority of advertisers on Google already spend their whole budget, so that would mean that now they would just be getting less clicks and conversions per dollar of budget spend. Logically they would then move some of this budget to other advertising channels such as Facebook. Charging more per impression always has second order effects, but who cares about that on hackernews

I agree in general, but most people that run 50 miles a weeks also eat healthy. So there's a lot of correlation there. IE show me a person that runs 50 miles a week but also eats mostly process foods and drinks lotsa soda.

Meta is a company that makes money off of users endlessly browsing content. It would follow that making it easier/faster to generate content would benefit Meta.

I was pretty impressed with my interaction.

When I asked it to help me practice French, Claud let me ask clarifying questions about specific phrases it used, with background on specific conjugations/language constructs.

I do wish that it's responses were more "chat like" though. I feel that its default response to even a simple phrase... "Merci!" - is something like paragraph -> 5-6 bullets -> paragraph.

While this makes sense for technical questions, it quickly makes the experience of "chatting" with Claud pretty tedious.

Oh yeah I agree that it _could_ do all those things, but it would be a bit of overkill to always send every observation an agent encounters into the API/chatbox, and ask it to spit out an evaluation or action.

This paper does a nice job of separating the "agency" from the next word with context type predictor. I think that's why I like the paper, it is just chatgpt, in the same way that pizza is just dough, sauce, and cheese.

This paper feels significant. If chatgpt was an evolutionary step on gpt3.5/gpt4, then this is bit like taking chatgpt and using it as the backbone of something that can accumulate memories, reflect on them, and make plans accordingly.

Time for my yearly tradition of making it to day 4 in Haskell and feeling very smart before completely giving up on the first hard problem that needs regular arrays :)

For people complaining that they can't play with the model... I work at Google and I also can't play with the model :'(

I once saw a Trader Joe's employee cut melon for the free food sample station (pre pandemic)...

She was cutting each melon in the same exact fashion, using the same set of minimal knife strokes. I walked up and asked her about it, and she explained the technique. I still think about that.

It would be great to implement some of the windowing improvements as an addition to a current linux windowing system.

Pinning different applications together or being able to merge applications with tabs both sound useful... These sorts of ideas are why it's great to have another open source OS.

I mean you can pay for billboards with positive and encouraging messages... The question is, why don't you?

Agreed that the hour invested may not be worth it for a large percentage of people (again I got lucky, I would feel so differently if I was rejected after 7 interviews).

Google's point is just that they prefer to avoid false positives at the cost of (potentially) a lot of false negatives. The current interview process is probably some local optimum;

I haven't worked at a company yet that is actually good at interviewing. Where good is optimized over high recall and accuracy and a small time investment.

I know that Google does have one big advantage, in that a good percentage of people that get the offer end up accepting. That (unfortunately) gives Google a lot more leeway and possibly less incentive to further optimize the interview process. Software engineers are in high demand, but also Google is in high demand among software engineers.

At my previous job, trying to find a candidate for a role essentially involved lowering the bar until somebody was no longer in demand, since we weren't "in demand".