I think this is wrong and should not exist.
do you care to elaborate or are we being mysterious today?
Readit Newsbigzyg33k commented on Show HN: NextDNS Adds "Bypass Age Verification" · Posted by u/nextdns
bigzyg33k commented on OpenAI to buy AI startup from Jony Ive bloomberg.com/news/articl... · Posted by u/minimaxir
The vast majority went into software development, software that's mostly useless in spectacles. How's Horizon Worlds gonna work in spectacles?
No it didn’t. You’re literally just making this up, I worked at RL
bigzyg33k commented on OpenAI to buy AI startup from Jony Ive bloomberg.com/news/articl... · Posted by u/minimaxir
Certainly the part of those investements wasted on cramming a whole PC into goggles that smash into your face with straps around your head and pretty much all of the Meta and Meta subsidized content to go along with that can be evaluated now, and not in 5 more years. The fact that Quest stalled out 2 years ago with only about 7M actives after tens of billions spent trying to make it go is pretty much all anyone needs to know about Zuck's metaverse investments. Now they're pivoting to glasses with a heads up display and pretending that was the plan all along because Zuck won't admit the cash bonfire that Quest and Horizon Worlds has been, about $100B sunk for only about $15B return with only a few million users.
Based on your comment it's apparent you neither follow the industry closely nor understand it's dynamics. The vast majority of the billions of dollars are being pumped into R&D, not marketing existing legacy devices.
You also seem to be implying in your comment that the orion glasses displayed at connect last year were a last minute pivot, which is a ludicrous statement
bigzyg33k commented on OpenAI to buy AI startup from Jony Ive bloomberg.com/news/articl... · Posted by u/minimaxir
Let's ignore the 46 billion dollars wasted on the metaverse: https://www.nasdaq.com/articles/meta-platforms-has-spent-$46...
Meta haven't abandoned the metaverse, and made it very clear from the beginning that "the metaverse" was something that does not exist, and will not exist in any form until the end of the decade. They continuously reiterate this during earnings calls, while increasing their capital expenditures on it.
You cannot determine it's a waste if the effort isn't completed, and if you have no insight into their progress.
bigzyg33k commented on OpenAI to buy AI startup from Jony Ive bloomberg.com/news/articl... · Posted by u/minimaxir
This is a sign of OpenAI's weakness.
Altman is desperately trying to use OpenAI's inflated valuation to buy some kind of advantage. Which is why he's buying ads, paying $6.5 billion in stock to Jony Ive, and $3 billion for a VSCode fork created in a few months.
Almost anything makes sense when you see your valuation going to zero unless you can figure something out.
I completely disagree. This is really just more of the great execution that I've come to expect from Sam Altman.
Core to OpenAI's strategy is that they control not just the models, but also the entrypoints to how these models are used. Don't take it from me, this is explicitly their strategy according to internal documents (https://x.com/TechEmails/status/1923799934492606921).
Some important entrypoints are:
- Entrypoints for layman consumers: They already control this entrypoint due to ChatGPT, the app. They have a limited moat here because they are at the whims of the platform owners, primarily Apple and Google. This is why they are purchasing Ive's startup.
- Entrypoints for developers: They acquired Windsurf, and are actively working on cloud development interfaces such as the new codex product.
- Entrypoints for enterprise: They have the codex products as described above, but also Operator, and are actively working on more cloud based agents.
A rebuttal that I anticipate to the above goes something along the lines of this: "If they have so much capital and dev experience, why are they acquiring these businesses instead of building internal competitors? This is a demonstration of their failure to execute"
The current AI boom is one of the most competitive tech races that has ever occurred. It is because of this, and particularly because they are so well capitalised that it makes sense to acquire instead of build. They simply cannot afford to waste time building these products internally if they can purchase products much further along in their development, and then attach them to their capital and R&D engine
bigzyg33k commented on How WhatsApp became an unstoppable global cultural force restofworld.org/2024/how-... · Posted by u/insane_dreamer
Your company has been knowingly in breach of the GDPR since it went into effect and shows no signs of stopping despite multiple adverse rulings and fines. There is no reason to trust a company whose entire business model is based on breaching privacy regulations and lying about it.
What you're saying is either an outright lie you are telling us, or a lie you have been told and are yourself choosing to believe to feel better about working for them, or to not put yourself at risk by digging deeper and finding adverse information (which once you know it you may be required to blow the whistle or find yourself legally complicit in the matter).
Basic economics suggests there is no reason Meta (then-Facebook) would pay what it had paid for WhatsApp for "just" a messaging app, especially before it was as entrenched as it is now (and so could trivially be dethroned by Facebook's own offering). They did so because unlike Facebook, people trusted WhatsApp with access to their contacts and that information is extremely important for Meta.
Whatsapp has been audited several times, and to say that an engineer at meta “has been lied to” is laughable given he/she has access to the entire codebase
Source: also worked at meta and had full access to WhatsApps codebase, like most engineers at meta
Pardon my ignorance as I have not worked on Vector DBs yet, could you come up with an example how it'd be different than a full text search?
Here's a (kinda) ELI5: you would use a language model to create "embeddings" of the text, which you can think of as a set of numbers representing the "meaning" of a set of characters.
These numbers can be plotted as points in a space, and embeddings of things with similar meanings are plotted close to each other. So things like "exam preparation" would have embeddings close to things like "top study tips".
Say you have created embeddings for a large corpus of text (in this case all youtube captions) once. If you create embeddings for a user query, you can search for embeddings close to it, and these will be "semantically" similar to the query.
The advantage is that unlike traditional full-text search, the user doesn't need a query that includes words present in the text.