aparsons

I generally break these queries into

- the low-hanging fruits (where there is a Wikipedia page or similar for X, and both Google and Bing do a good job of mining these)

- the tougher nuts ("who was the UK prime minister when the wright airplane first flew" - Google and regular Bing fail at this, but Bing chat correctly brings up Arthur Balfour). This was just an example I made up to try - but the ability to connect more dots than plain old search, which is hard to explain but you get a sense of the capability as you use ChatGPT/Bingchat - helps a lot.

Oh I agree with that. LLM doesn't give you better search - better search {index, ranking, SEO-tolerance, ...} gives you better search.

To me, Bing chat - although imperfect - augments search positively to fill my specific needs.

0) I don't see half a page of ads before the first real result, disguised to look like real results.

1) The interface is clean and noise-free : it takes away a huge context switching load I incur when going into individual results (which for most searches these days, is the top 3-5). I just want the content summarized, with no ads, in a form my brain is used to.

2) I can ask follow-up questions with context, again without ever leaving the interface. Otherwise, the follow up question's answer is often on another website.

3) I can ask more creative questions, which is not really a 'search' feature. Something like 'write a snippet of code'. You can try "unique_ptr in rust - show examples too" and it gives me a passable and concise answer. It presents two options, but to get what I exactly want, I can ask "how to use Box?" as a follow on.

4) It's vastly better at 'connect the dots' queries - see my other comment please.

One underrated feature is the 'next query' suggestions - I can use a single click instead of typing out 'one more example' or see more subtle examples by clicking 'how can I use Box for recursive types?'.

They don't. They're fairly orthogonal concepts. You can have a concept of lifetimes without memory management (for example, the object changes state while you have a reference to it).

Strong disagree on this.

I don't treat it like a person, but rather as ChatGPT that has access to Bing's search index. For factual queries ("who invented X? at what company?") it's more reliable than ChatGPT and saves me quite a bit of time. Similarly for content aggregation tasks - I'm *scared* to click on a lot of "Top 10 X", "The best Y in Z" type pages because they're SEO and advert mined. Bing does the initial aggregation for me, and if interesting, I ask it to tell me more about that resource or visit the page myself.

There will always be a segment of people who troll on the internet - that doesn't detract from the immense productivity tool it can be when used correctly.

180 million a day sounds about right

How would one go about finding such consulting gigs? I’m semi-retired now, but with nearly 4 decades of experience, I still didn’t feel comfortable becoming a full-time consultant.

Could you share any of these “hosted” services? I’m thoroughly disillusioned after paying for 3 streaming services and still not finding quality content

Thanks for sharing. I love the design and how this app feels. Did you use any existing CSS library/framework or is everything “hand crafted”?

I’ve posited repeatedly that when Reddit IPOs, I’ll be reallocating a significant chunk of my portfolio into their stock.

Their management has historically lacked focus, but if Reddit ever builds a half-competent search index, and positions itself as a search-first, discovery-second destination, they will be in the FANG tier of stocks.

They have the data. They have the dedicated, active user base. They have free moderation. The hard parts are solved. If only they get someone like Satya at the helm. (Also a big reason for me to believe that an acquisition may also be a good play for a AMZN/MSFT)

This has been the case for a long time on mobile. 1.5 vertical screens of ads is not uncommon.

Sequencing in distributed systems is difficult to handle correctly. When faced with such a situation, it’s often a matter of philosophy rather than technical brilliance - are you willing to accept that failure is inevitable even with a neat “waiter” implementation? What happens if the waiter waits forever? Is shaving seconds tangibly benefitting customers (for Sentry it might) and worth the operational overhead?

Framing these problems slightly differently - is 10 second latency close enough to “real time”? - unlocks solutions like an online batch processor that reads out of your DB (if it doesn’t support NOTIFY) on an indexed incremental identifier.

I bit and got the book, hoping for something interesting. It’s more or less the documentation on MDN or a WS library docs rephrased.

Finally, after 60 pages of docs I can Google, there’s a section called “Scaling Websockets”, which is an interesting and challenging topic.

Turns out it’s one paragraph long, saying - “Yeah it’s hard. You should consider using Ably. Next book will cover it.”

Shameful.

Referrals don’t mean much if more than a small fraction of candidates have one

I very much get a cargo-cult vibe from this statement.

In a 30-year career, I’ve pair-programmed under 100 times. Usually to get someone up to speed on a confusing part of the code base.

In fact, I’d go as far as to say that if pair programming is a recurrent need, you need one or more of better engineers, better documentation, or better code reviews.

That’s a sponsored newsletter post AFAICT. There are a handful of those that shill for companies willing to part with their dollar

Yes.. I thought that incident made him look very, uh, disgraceful.

He likes to predend Repl.it is some marvel of technology when it is unironically a weekend project (which the intern he attacked did better). Bruised egos are dangerous.

I’d really like to see the author write an explanation as to why. I completed by PhD in “AI” (as it was then called) in 2001. Very little DNN work then, but I haven’t a clue where the connection lies.

This author doesn’t have a clue about anything. After the first paragraph, this might as well have been written by GPT-3. Sounds like a consultant trying to cash in on the news of the week to me.

I think part of it has to do with black box models being easier to build incrementally. I’ve seen many teams start off with 3-5 features, which gets you to some threshold for launch (say 90% precision and recall) and get badly burnt on the other 10% post-launch

I hate to use this language on HN - but this post is a crock of shit. This is just an opportunistic post by the author that cleverly evades defining anything in solid terms, providing even one concrete example, and is a pot of handwavey BS. It started off encouragingly, and two paragraphs in, the smoke alarms in my head were blaring. The author doesn’t even have a clue (or for some mysterious reason didn’t mention) about what went wrong for Zillow.

Zillow’s massive screw up was that their key business assumption was a self fulfilling prophecy. If a model learns that “price to pay today is price to pay yesterday in this area * 1.05”, and Zillow is buying multiple homes in a neighborhood spread over time, you can see that the price is headed to the moon (and the buyer who puts their faith in the model to the gutter) in no time. In my parents’ town, they offered a neighbor a price, and came back 3 months later with an offer $70k higher. I have a strong suspicion what was supposed to be a price prediction model ended up being a price discovery agent due to the lack of a “visited” set. Oops!

This sounds like an ad :)

Very dishonest indeed. Does YC not do any due diligence anymore? They seem like they’ve become a quantity-over-quality investment firm now, casting the widest net possible based on the strength of their reputation.

The signage on the vehicle indicates this lad is from Kilinochchi [1]. Not surprised in the least- the last time I was in Ceylon, I learnt that the people in the North are expert boat-builders and very resourceful.

[1] https://en.m.wikipedia.org/wiki/Kilinochchi

You’re thinking mid-2000s IE. In the 90s, IE was far ahead of everything else. The gap between 2008 IE and Chrome was FAR smaller than the gap between 1997 IE and Netscape/Mosaic

The IE effort was gargantuan - it was not NT in terms of sheer difficulty, but 1) we had built operating systems before NT, but never a web browser, and 2) Microsoft wanted to keep it under wraps as much as they could.

The IE team had a carte blanche to succeed by any means necessary. If they wanted a system call to work differently, you had to get it done or risk getting a meeting with your boss’ angry boss.

Same for me (chrome on windows)

This is extremely slow and laggy on the Pixel 3

Machine and abstract machine are both overloaded terms. If the set of system calls is considered the “ops” for your OS “machine”, characterizing it as an abstract machine is not incorrect.

Comments like these are generally not constructive to discussions. You are on the internet, on Hacker News, so I assume you’re probably living in a first-world country and completed secondary school or college. Which number do you think is more likely?

Law of conservation of complexity