I wrote an article about this exact topic: https://jonpauluritis.com/articles/10-technologies-you-need-...

Enjoyed reading your article. It's honest and your rationale is well laid out.

thank you!

My particular prediction for Machine Learning and Data Science is its going to become less and less Python vs R vs Julia. and more like the situation we have for for web-servers. Where basically every language has a solid quality webserver. And like how now if your focus as a company (etc) is on webstuff you'll use Node or something with a excellent webserver and will hire accordingly, but if you've got a big team that already uses java to make the desktop application, then you are not going to switch to Node (etc) for your new web offering: you will use the also very good TomCat or Jetty. Similar if you focus on complex modelling you'll use Julia/Python for that and you will just use their webserver libraries to expose it.

The other way round will also occur (and definately already has started but i expect it to be more and more the case.) You are a web-company wanting to do some ML on some data you won't even think of having a seperate Python/R/Julia program, you will just use the Node equivs (which I am sure today are good, but I don't know them). Similar for the desktop applications in Java or C# they will just use their own ML / Data Science libraries.

And just like there is indeed a role for specialized web servers like Node, there will still be case where you do want to pull out the big guns and move over to Python/R/Julia. but those will become rarer and rarer.

I guess you could say it is commoditization of ML/Data Science libraries.

Does anyone else feel like their brain is broken when thinking about questions like this one? I lean way too much on the pessimistic side about any tool or technology, present or future, to the point that I don't trust my own judgement to predict these things at all.

I think it means you hang around too many old people. Younger people have a good feel for what's changing and the optimism.

Younger people can't predict the future either and optimism doesn't predict the future either.

The future might be terrible.

Young people are frequently wrong too. Reddit communities are a good sample. They don't understand paradigms from 1998 or so.

You need a counter balanced perspective, young with experienced, optimistic with pessimistic.

But one advantage they have is that many are fresh from university and have more exposure to latest research. A new grad might have a better feel for the tech level of, say, optical routers or quantum computing.

Have you ever worked with a grad before though? Most of them are pretty useless - there will be exceptions though.

They've done better than seniors (including me) in some situations, but I wouldn't expect them to carry a project. The variance is huge - you'll have really dumb ones who shouldn't have a job, and geniuses who will probably run their own company later.

You don't have to work with them though. Most of my interactions are tech memes and hanging around with the people who make game-related bots on Discord.

Virtual reality, at long last, driven by furries.

https://www.youtube.com/watch?v=sXr5O4PW3Dw

I for one am amazed that "video game characters" are stuck in video games and don't come out in forms like:

   * an assistant at the drug store that lives on the screen has the image of a body and can make eye contact with you
   * a 3-d graphic performer that does a sketch comedy act with a human performer that is reflected into a mirror like "pepper's ghost"

Technologies that are ready to "break through" (like the internet in 1994) often exist at a mature level somewhere but haven't spread for some reason. For instance, this 1971 book

https://www.amazon.com/Information-Machines-Their-Impact-Med...

anticipated that cnn.com would exist around 1981; actually you could read news headlines on Compuserve. France had minitel, other countries had videotext, but there wasn't enough centralization in most places for large-scale online services to hit big until the technology had passed the threshold at which it could have worked by an order of magnitude.

Then it went off like a bomb.

I think it's because many engineers underestimate how much the force of habit shape people behavior.

habits that shape the consumer, employers, companies making decisions for automation.

maybe drug store managers would feel like they have no one to manage? it would be too disruptive for labor.

From a consumer perspective even available tech like voice recognition doesn't seem to add or change much for me personally like I know Siri is on my iphone right now, but how often do I feel comfortable speaking to her? almost never.Why would I speak if I could type?

Virtual game characters like assistants would look too odd and uncomfortable, except maybe in japan, it's uncomfortable to make eye contact with human strangers, let alone 'robot eyes stranger'!.

maybe if younger kids were exposed to virtual assistants they would be comfortable in adapting to them, just like gen z adapted to preferring typing over answering the phone.

maybe that could be the future of post-gen z generation.

If anyone is reading this and can answer a little further: What are some emerging technologies that can be broken into without a university degree? I've been very successful in my 7 year career as a field service engineer on chip equipment, and while it is a great job, I am actively looking to branch out into coding, or another field in tech. The enormity of different fields contained therein is overwhelming. Any guidance is greatly appreciated.

Capability Based Security - Our operating systems are based on a security model that is great for the academic and research organizations of the 1970s. It trusts everything except the users.

Capability Based Security inverts this, the user is trusted, and given powerful tools to allow running code without trusting it. Usability and performance aren't sacrificed.

Aneutronic Helium 3/Boron fusion looks set to actually happen. The ability to generate large amounts of electricity directly, instead of having to boil water to make steam to turn turbines, removes a huge cross section of limitations from the otherwise mundane area of power generation.

Off-grid living will follow solar's trajectory. The planet is a massive place, the mass majority of it uninhabited. Not for long.

> The planet is a massive place, the mass majority of it uninhabited. Not for long.

The water, food, and logistics concerns that have driven human habitation patterns forever haven't gone away, and show bo signs of going away for a long time. Is it possible to support habitation in places that aren't currently well-settled? Sure, but it's expensive, and that's not going to change relative to the places that are well-settled.

It's expensive now, but those costs are rapidly decreasing. Drone transportation into and out of once-remotely habitated places will be commonplace by 2050. Those “settlements” will have renewable power, desalination, agriculture, industry even. Conjecture, but when you look at the technology curves, telling.

Quantum computing APIs will become much more accessible and start to fill real needs.

Decentralized finance, ETH, binance smart chain, DAO.

Any suggested readings on decentralized finance? I've circled the topic a bit but didn't find an introduction to fire my imagination.

Check out How to DeFi and Part time Larry on YouTube.

Thanks for the tip.

ethereum.org

Liquid biopsy for early cancer detection.

- Satellites

- Anything that merges finance and information

- Zero-carbon tech

Smart glasses

Biotech powered by AI

Privacy & moderation tools

Cuelang :fingers_crossed:

I would agree with smart glasses. So many people wear glasses, lenses or contact lenses which means adoption can happen pretty easily once a good product comes out. Maybe peaked caps (to hold the camera) and glasses combined or something.

Secure voting.