razodactyl

I appreciate you.

I'm sure there's a name for the type of conversation killing argument you make here: I get your point though, I think it would be a better opportunity to shed wisdom instead of voting down your comment for its negativity.

First and foremost: HN thrives on intellectual curiosity and discussion so keep that in mind; it's actually a good skill to be critical else we end up going down the road of "who cares about privacy and physical ownership".

I enjoy cool workspace inspiration so I'm leaning closer to your side but the critical discussion has merit in the fact that we end up with "slop" if nobody is bringing anything new to the table (yay I made a pun).

"Cancer killing /b/" and all that. If we spend too much time with kin we become closed off to cool ideas or better ways of advancing us all.

Not sure I know where I fall regarding your point: Yes to trade secrets, but also science and AI should be for the good of all.

OpenAI seems to be trading roles back with Anthropic becoming misanthropic. I hope they both start heading in the direction of how the AI field was prior to LLMs.

Collaboration and benefit for all should always be the primary motivator.

Concise responses come from people with writing skills who can get to the point without adding more words to sound smart.

"Elegant prose instantiated through remarkably tailored execution of written word may allow an author's desired intention to flow in a certain way to achieve a precise effect whilst simultaneously allowing said author to sound of much higher mind and thought to the reader." - I probably butchered it but my point is that AI slop seems to be the average of the outputs.

Images that look similar to others because they're average of all the current outputs. Same with music and video. We're noticing when something is AI because it has this signature that's average to other outputs.

Original content is crafted even though inspired by other works.

We're at a weird point where AI is capable but constrained.

As compute increases and AI becomes more personalised I feel the current implosion will explode again into variety.

So essentially PlayStation is over everyone go home... because we don't buy content anymore, we license it and denial of physical media is final nail in the coffin.

Yeah. It keeps catching me off guard that it answered me already.

Heh. Summarising allows the benefit of full intelligence whilst preventing "misuse". Where "misuse" is likely competitors stealing thinking traces. Even though this is clearly work inspired from the OpenAI Strawberry era.

Oh! Big deal. Exciting.

Me too! Writing Winsock and learning WinAPI on XP then Vista. It took me a while to realise Linux was better / OSX was my gateway drug haha

Hmmm.

I think it's good practice to get on top of the cautious thinking of "LLMs aren't that smart for now".

Eg. Fable isn't as good as the hype: it has cool tricks like scratch-padding to check expectations in advance, but we're not there just yet...

Specifically I mean: thinking in terms of it changing abruptly ensures we're ready for if the LLMs do get smart enough to do multi-level strategy and cause a lot of annoyances....

People are still hiring, it's just very competitive - reframe rejection as learning opportunities returning wisdom.

In retrospect, many companies you get turned down from are likely companies you don't want to work for anyway hence the incompatibility.

It may be hard, but positive mindset will go very far towards enhancing your outcomes - you need to bring others up around you as well. Pause on this and think about the first thing that comes to mind when you respond to these words.

The problem is that there are people willing to accept these conditions. Think higher of your self worth in future please.

Was browsing through docs and some examples break and crash the browser. Even when linking out to codesandbox itself.

CR4-DL

Yep. Anyone can call themselves a CEO. You want proper managers. Check General Hammond from Stargate for a shining example haha

Yep. I'm with you here. If it's a 4% loss now for training data to catch up and improve later, we're better off in the long run. I'd like to believe that generally people are nice to AI for the sheer sake of enforcing good communication practices.

Aw. The listen to article widget doesn't work properly on mobile Safari and when using the options button, the popup appears below the "In this article" dropdown occluding it.

At least it read the authors of the article to me.

I wish we would push more towards testing code. Agentic AI excel when it's engaged.

I appreciate a critical eye so I upvoted but consider how your message is received / worded for more impact in future.

Seeing this too. Machines are great at pumping out content.

Tl;dr's, quick references / QuickStarts / cheat sheets and FAQs are also some things they're great at generating.

Especially when it waits a month and all the effort is either irrelevant or incompatible with latest changes that finally got through. So much token wastage to top off the recent chaos. Hopefully it improves just as fast as it materialised.

It's called: the CEO isn't staying in their lane and is injecting incompetence into the company - look for a new job.

So.. their billing system is using '$>claude | jq' somewhere?

See image attached: Tried Windsurf today - approaching daily usage on a Pro Trial - the daily usage isn't spread out over the total weekly usage?

Token prices for AI are getting a bit ridiculous. I'm thinking pi.dev is starting to make more sense.

And now we finally have CSS grid. Remember centering a div? Haha

I think a lot of us are blinded by our own propaganda. I would expect many Chinese geeks to have the same values as us for the greater good of humanity.

These pelicans are clearly indicative of good RL training algorithms.

If anyone's had 4.7 update any documents so far - notice how concise it is at getting straight to the point. It rewrote some of my existing documentation (using Windsurf as the harness), not sure I liked the decrease in verbosity (removed columns and combined / compressed concepts) but it makes sense in respect to the model outputting less to save cost.

To me this seems more that it's trained to be concise by default which I guess can be countered with preference instructions if required.

What's interesting to me is that they're using a new tokeniser. Does it mean they trained a new model from scratch? Used an existing model and further trained it with a swapped out tokeniser?

The looped model research / speculation is also quite interesting - if done right there's significant speed up / resource savings.

Bad feedback loops. It's hard to tell with such a massive report if the numbers are real or bad data.

The worst part is how big AI generated reports are - so much time spent in total having to read fluff.

Generalisations and angry language but I almost agree with the underlying message.

New tools, turbulent methods of execution. There's definitely something here in the way of how coding will be done in future but this is still bleeding edge and many people will get nicked.

LLM feedback loops are scary because they self-reinforce by training over their own data drift and vulnerable people interface with the noise and follow the downward spiral.