I have seen that people on forums like this one and stackoverflow are usually able to predict the next big things in tech quite well. Like this thread:
https://news.ycombinator.com/item?id=21324768&p=2
So, what CS areas would be good to invest time in learning for the near future?
Of course construction is not only for buildings but for someone who had no experience in this sector I was caught off guard expecting to see old fashioned blue prints.
Put another way: It doesn’t matter if you have a product which would help people and save them money, if people, for whatever reason, aren’t inclined to buy your product.
The biggest problem isn't making better software, which already exists, but getting DOTs to stop making Bentley's proprietary file type a requirement for deliverables. The second problem is realizing that the CAD approach of imitating a paper process from last century isn't actually necessary.
We're quite close now to delivering the final version of IFC4.3: the open standard for BIM (building information modelling), now including semantic modelling of long linear infra https://ifc43-docs.standards.buildingsmart.org/ Eagerly awaiting to replace your PDF.
I read a proposal a while ago to simplify an open BIM spec down to meshes for solids and a generic dictionary for attaching property data. That struck me as very sane and very easy to implement. You could have a free product like Blender spit out BIM compliant deliverable at minimal cost. Apparently some high ups at Autodesk talked to the author and he came to understand the error of his ways.
I wish I knew how to code, or just had the balls to quit job and make a company. Since I worked for years in various companies I see that no ERP handles the usual problems.
Also, could you mention some of the usual problems ERP cannot handle?
Do you mind if I bend your ear about what your needs are? If so, send me an email. It's in my profile.
But there's also so much risk it all gets captured & eaten by the existing titans, that we don't make any gains begetting a new "silicon foundry" where new folks & new ideas get created. There's so much risk that chupmaming remains as rareifiedly arcane, in which case this money doesn't really help the world much.
2. spatial computing : If Apple’s foray into it has validated anything, it is that it is just getting started and it holds a lot of unrealized potential.
3. Robotics - it has been important for a long while, but its trajectory is still upwards and reach very promising.
This is definitely an emerging field that is trying to develop market share. Unclear if the tech is really there in the long haul for comfortable spacial computing though. What you're seeing now is literally akin to something like the Apple I being released. We have a LONG road to go but there's very little doubt that the end goal is something powerful.
• AI
Duh? It's useful now, and likely will only get better. No question here that sharpening your AI skills is a safe bet.
• Synthetics
Lots of work going on quietly around synthetic engineering, BCIs, etc. If you're interested in the human body interface then this is a field that has some interesting problems but, like spacial computing, probably won't come to fruition for many decades.
• Security
Always useful and always changing. A no brainer if you're looking to skill up in a specific computer science niche.
Http://voxon.co (disclosure: founded the company )
Http://look.glass (disclosure: worked at company)
Http://lightfieldlabs.com
Http://leiainc.com
Has demand for 3D tech like this increased since you started Voxon?
The war in Ukraine has transformed drone tech. Ukraine alone is burning 20k to 30k drones a month. The military applications are leading to huge investments; economies of scale are leading to rapid improvements in tech and reduction in costs.
https://nitter.net/Tatarigami_UA/status/1692962111675138074#...
A drone with a FLIR can do a great job of sweeping for UXO and mines. Which will be big business (it would take every mine clearing team on the planet 750 years to clear Ukraine given current non-drone tech).
AI!
Did I mention ai?
Srsly go into ai.
Start learning what is already here (so much) learn to use it, learn to fine-tune it and if you then still not busy enough: learn to really understand ai architecture.
The industry is adding ai right now left and right.
This takes time and experts.
And all the small companies probably haven't even touched it.
And currently there is no end in sight. The r&d progress is still as high as not higher than yesterday.
A new interface is ripe for development. Once a user is used to such a clear and intuitive UI, they can't go back. And GPT technology is exactly that. ChatGPT is the herald of the new era UI.
The various industries have deeply balkanized the field & expertly extract value with endless apps that primarily capture value for the app maker, while barely creating value for the user. We are in a late-appification stage.
I think the biggest value area of the future are undoing the damage of all this disruption & market capture - of undoing all these apps! - & building strong principled powerful general computing systems.
This is targeted to data scientists far more than general general computing, but I like how broadly this post expands the problem of what data science computing is: The Road to Composable Data Systems: Thoughts on the Last 15 Years and the Future. That unpacking of concerns, understanding & building the general substrate, calls powerfully to me. I think even more general computing forms lie in this direction, that expand how all computing by all users would work, in a way that better augments the user's intellect. https://wesmckinney.com/blog/looking-back-15-years/ https://news.ycombinator.com/item?id=37367236
Figuring out how to make general progress that's even more accessible, less specialists & more "just how this computer works" in a way that everyone can potentially see & touch is the valuable work that is almost entirely ignored & unworked on now. It's a colossal opportunity.
Learn about strength training and cardio. Taking care of your body pays dividends long term.
There is so much unbroken ground in tech, especially point solutions with existing web technologies that haven't been made or just started to grow. LLMs just icing in the grand scheme of things (especially in Business Process Management) along with other ML models.
I would say build apps and think about where it's appropriate to make a call to a LLM like GPT-4 or an Tensorflow JS mode, and then decide for yourself
Biotech is heating up. Sure it’s not pure CS, but there’s plenty of crossover. Doing computer vision on the glossy insides of a person is a serious CS challenge for example. Its disruptions are slow but possibly larger than other areas. Intuitive’s surgery robots are everywhere you look now for example.
Augmented reality. Apple’s Vision Pro is a big validation of this direction. We haven’t figured out what the killer apps here are yet and I expect we’ll see a similar gold rush and set of disruptions like smartphones as folks figure it out.
Self driving cars. These were way over promised but we’re getting past the hype. I’d expect to see robust (probably geofenced) Level 4 systems by the end of the decade.
These are just off the top of my head so take it with a grain of salt.
Most western societies have an age curve moving to the right. Lots of opportunities with AI and disrupting the user experience for the elderly. Have relatives who can't use a touch screen because of arthritis, bonus is the have money
I think good synthetic meat etc is still some way in the future, but things like milk, juices, pulps, and animal feed should be easier and make even more sense.
Why grow a whole tree when you just want OJ, a whole cow when you just want it's breast secretions, etc?
* AI
* Cryptocurrency
* Solar
* Biotech/Bioinformatics
Doing some back of the envelope calculations you can get a rough guess that we'll have "human level AI" by 2030 or so. The current trend of AI producing spectacular results will, in my opinion, not cease but continue to pick up pace.
Back of the envelope estimates can show cryptocurrency holding, conservatively, 20% of the worlds wealth by 2030. I suspect the growth of cryptocurrency won't be independent of other technologies. Cryptocurrency gets a lot of flack here and other places but I'll remind people, yet again, that many of the critiques against cryptocurrency are eerily similar to critiques of the internet, email, the world wide web and social networks in the late 1990s and early 2000s.
Back of the envelope estimates can show solar producing over half of the worlds energy needs by 2040. In addition to solar panels, there's battery technology, microgrids, etc. so this is really about what technologies are rolled out to satisfy the 2.5% yearly energy usage growth rate. I don't see any other technology that has "Moore's law"-like behavior in terms of the energy harvested vs. the energy invested than solar and battery technology.
Biotech and bioinformatics will have profound consequences for health, longevity and a host of other issues but I don't have a good sense for what the major innovations are that need to happen before this becomes widely adopted. I suspect AI will help with bio-engineering crops, drugs, food and help with general medicine but I don't quite know what that looks like. We silently hit a roughly $100 whole genome sequencing [0], so it's progressing, I just don't know what rough goals to predict or what to look out for.
All of the above are relying on a sort of "generalized Moore's law" in that the reason the innovation and adoption is so quick is because cost is dropping exponentially.
I created a small post about it with some simple justifications for where the timelines come from [1].
Although i don't know how that matches anyone's agenda - software eating the world is exactly feeding on these "Perpetuum mobile"..
- (enterprisey langages and platforms, identity management) I don't think consumer tech mints any new unicorns or platforms for a while, as a discretionary cost, I think there's a consumer tech winter starting.
- (graphs, GANNs, LLMs, forum tech, api aggregators) When I look anecdotally at where the money is (institutions, endowments, PACs), where it isn't (consumers), and where it is going (favored causes and mechanisms to secure political levers) - the upside goes to an emerging class who works in moderation / trust and safety, campaign management, PR, ad tech/surveiilance, gov tech consulting. Like marketing, but for shifting narrative alignment and "funding," instead of discovering customer desire. "Influence hacking," is a thing.
- (not comp.sci, but likely trend) I joke that the biggest bubble over the next decade will be weekend vacation property and renovations near government towns. All them comrades gonna need dachas.
- (identity management, AI model alignment, software attestation) The mood of money in the econoomy now is being applied to converting frothy QE cash to political influence instead of being invested in innovation. Model alignment, model authenticity, and ability to influence will be valuable.
- (next gen browser tech, virtualization, webasm, react, scripting frameworks) Social platforms are optimizing for hollowing out the value they provided instead of making new products people want, so there are unlimited dollars for anything that sustains their business model a bit longer. Social is the new legacy business model, and they will spend to sustain it the way banks and credit card companies spend to maintain their oligopolies. This means sustaining legacy tech features in browsers that enabled it.
- (PowerBI, python in Excel makes you a wizard) I'd bet on incentives for additional governance roles, where firms will get ESG and tax incentives to hire low tech-skill party affiliates, creating a public sector job consumer bubble. Those jobs are ongoing conversations about higher level metrics that come from these tools.
- (no tech, just a bet) A lot of those jobs will go to childless people without a lot of responsibility, and many will just drink/amuse themselves to death, so get long boxed white wine and short pampers. Luxury goods/bags do well, as they will need new ways to signal status.
- (piecework gig platforms, make google glass shared/augmented reality for toddlers and parents) Reproductive tech and services set for a boom, single parent family management tech could become its own category.
- (LLMs for teaching and testing/exams, higher level abstractions like category theory, graphs, domain specific language design) Premium edu tech to scrape out any tiny advantage in a now-globalized competition between students for university spots. Anything that communicates useful abstractions faster will win.
I'm going to go touch some grass now.
