People may say it increases creativity but I see it more as lowering the bar to produce things. The same could be said for a lot of inventions like photography made producing images easier and I'm sure a lot of portrait painters lost their jobs to photographers. I think the danger is that we may see a very rapid erosion of jobs in the creative space that won't be easy to transition into new fields which I feel will have a detrimental effect on our society.

Half Life Alyx is still considered to be one of the best VR games ever made and one that is still consistently recommended to new users even years after release. IMO people buy hardware because of the exclusive content. If a standard game console came out and it only had one AAA game on it, I probably wouldn't bother buying it. But if there were 3-4 games that looked really interesting it starts to look more worth the investment. Playing VR games takes a lot of committment (time / physical space / $$$) so the payoff has to be worth it or you'll lose people. With the huge amount of money spent on R&D for new hardware I think it's a valid argument to say that maybe funding content would have been a better investment in terms of ensuring platform growth.

Also, side note but not every game requires free motion. Plenty of hits had no movement or teleport etc. A lot of these were completely new (sub-)genres that didn't exist or hit the same as they would in a traditional pancake game. Plus lots of kids seem unaffected by free movement (maybe as high as 50% of users by my rough estimate).

But back to the original post, I think 'having good taste' and knowing when something feels like the right solution is one of those hard to define qualities that can make the difference between average and great products (and has far reaching effects in any business).

Their channel recommendations: "We use external models (not trained on Slack messages) to evaluate topic similarity, outputting numerical scores. Our global model only makes recommendations based on these numerical scores and non-Customer Data"

Meaning they use a non-slack trained model to generate embeddings for search. Then they apply a recommender system (which is mostly ML not an LLM). This sounds like it can be kept private.

Search results: "We do this based on historical search results and previous engagements without learning from the underlying text of the search query, result, or proxy" Again, this is probably a combination of non-slack trained embeddings with machine learning algos based on engagement. This sounds like it can be kept private and team specific.

autocomplete: "These suggestions are local and sourced from common public message phrases in the user’s workspace." I would be concerned about private messages being leaked via autocomplete, but if it's based on public messages specific to your team, that should be ok?

Emoji suggestions: "using the content and sentiment of the message, the historic usage of the emoji [in your team]" Again, it sounds like they are using models for sentiment analysis (which they probably didn't train themselves and even if they did, don't really leak any training data) and some ML or other algos to pick common emojis specific to your team.

To me these are all standard applications of NLP / ML that have been around for a long time.

I am not defending Slack, and I can think of number of cases where training on slack messages could go very badly (ie, exposing private conversations, data leakage between workspaces, etc), but I think it helps to understand the context before reacting. Personally, I do think we need better controls over how our data is used and slack should be able to do better than "Email us to opt out".

I've yet to see any programming jobs replaced due to AI. Writing code is only half the job; understanding a company's existing tech stack, API's, internal struggles, business needs, etc, and figuring out how to implement what the business wants are all important. AI will still have a hard time with these things for a while yet.

Steam users with VR Headsets: 2.24% (vs 2.07% last feb)

See https://store.steampowered.com/hwsurvey (VR section)

Not directly and not in every case, but it IS possible to use embeddings to link to similar material. People are doing it pretty commonly using the RAG approach and Bard is already providing sources, etc. It may not be perfect, but the onus is on the AI companies to figure out how to do it right not just claim helplessness.

> Okay... but then, if I write a book should I be able to opt out of you being allowed to read it? What conditions should I be able to put on who can read my work?

Sites that don't want to appear in search results or have sensitive info they don't want to get into search engines can use the Robots.txt which is as old as the internet. There are many valid reasons to have mechanisms to prevent something from being included in training data, and I would also argue this is a core feature that is necessary to spur adoption by businesses as we've already seen. Otherwise, I am not sure I understand your reasoning.. people can publish websites and opt to have them excluded from search, the same should apply to AI.