[cerol]

This is how I think about it.

It's insurance money. If you're a manager of a big company like IBM, Microsoft or Google, you have to align your current product portfolio and future portfolio in such a way that shows your investor that your company will keep growing, even if your current products are stagnant.

You can surely say Quantum computing won't do much in next 5 years. But what about 10 years? 20 years? 30 years? The farther you look into the future, the bigger the probability of having a huge tech breakthrough that could give the company who has it a massive edge on the market.

Even if you have a chance of 1% of having a sort of transistor revolution from QC, it becomes a race to the bottom. If Google starts researching it, IBM will follow suit, and so will Microsoft. If in 30 years this turns out to be a big deal, no one will be 30 years behind.

[bottled_poe]

Ah, the quantum ROI, where we affect the return by attempting to measure it.

[viraj_shah]

This made me laugh, thank you!

[sicp-enjoyer]

I think you are describing the company dynamics accurately, but I can't help think this is just a terrible way to invest. No party has a concrete plan or vision for how to use it, they just throw money because there is a consensus of good feeling around it. Those good feelings were probably created through academic or corporate marketing efforts in the first place.

[cerol]

> but I can't help think this is just a terrible way to invest

Picking a company to invest in only half the job, choosing how much to invest is the other half.

It's a terrible way to invest if you put all your money into it. QC "changing the world" is a tail-end event. You allocate according to the risk.

[sicp-enjoyer]

I am not talking about investing in companies. I am talking about how these companies invest their R&D capital in projects.

> QC "changing the world" is a tail-end event. You allocate according to the risk

But, nobody has a clear idea how it's a risk. They just invest because others invest. You might as well allocate some capital to protect against giant aggressive pigs ruining the southern US.

To put it another way. What value is being provided by the managers of this capital? If they just put money in everything that seems popular in tech media (because it's a tail risk), then couldn't anyone do their job?

[forrest2]

> I am not talking about investing in companies. I am talking about how these companies invest their R&D capital in projects.

Some food for thought:

These companies do have economies of scale on their side for internal tech investments. Things like this are a cheaper bet for them than for anyone else. Investments that seem irrational in a vacuum (aka for anybody else) can be rational for these specialized parties.

They already have hardware specialists, contacts / relationships, software expertise, idle bodies, etc.

[hericium]

> a terrible way to invest. No party has a concrete plan or vision for how to use it, they just throw money because there is a consensus of good feeling around it.

Almost if I were reading about cryptocoins.

[pyinstallwoes]

The economics change when you control the money (military aperatus funds most of the research, does it not?).

[acomjean]

I mean these companies have Research and Development divisions. I was at IBM at the turn of the century when they spent 6 billion dollars on research. One of the pushes was to get research to focus on things they could market and make money with.

But the big research plays (bell labs, xerox parc) seem to get less and less funding if they exist at all. A lot of the inventions of those places were monitized outside those companies. IBM had a chip fab in the research building… long spun of was that business.

At the turn of the century IBM was researching quantum computing, but as I was leaving selling services was IBMs big push.

[ptero]

It is not the amount of funding, it is the allocation that doomed R&D at big companies.

Forty years ago they were the best game in town for applied research (defining applied as, on success, having a fast track to commercialization). Later it became similar to the university research: on success, you write some articles, get company wows, but business people have no idea where to stick it and half heartedly throw a few applications at it to see if any stick. Most don't (e.g., deep blue, watson).

At this point large company R&D centers got passed over (by a lot) by VC- funded applied research and saw a (IMO well deserved) drop of funding.

[chrisweekly]

+1 Insightful.

Also, in the spirit of helpfulness, "passed over" is the wrong turn of phrase as used here; it implies "declined or rejected" (as in, being passed over for a promotion at work). I think "surpassed" or "leap-frogged" are closer to your intended meaning. HTH! :)

[ptero]

Agreed, thank you! I appreciate corrections for my non-native english speakerness :)

[graycat]

Supposedly one of the really big, important things could do with a quantum computer (QC) is quickly solve to optimality instances of NP-complete optimization problems, e.g., problems in scheduling, resource allocation, logistics, etc. which can be formulated as linear programming problems (that need just knowledge of linear equations) where want all the variables to have whole number values, that is integer linear programming (ILP).

Okay, integer linear programming problems .... To get all excited about quantum computing (QC), need to get excited by the big money to be saved by solving all those important, practical ILP problems.

Okay, I had a good background in pure/applied math and in computing and got into ILP for scheduling the fleet at FedEx. Since the promised stock was 1+ years late, I ran off and got a Ph.D., in one of the best programs, in more in hopefully useful pure/applied math, and much of that work was in ILP.

Here is some blunt truth about the NP-complete problems and the cartoon at the beginning of the famous book by Garey and Johnson: The math guys were talking to their manager explaining that they couldn't solve the manager's problem but neither could some long line of other math guys.

Here the blunt part is the meaning of "solve" -- with a computer program running in time only a polynomial in the size of the problem get an optimal solution to any instance of the problem including the worst cases. And here optimal means down to the last penny to be saved. So, for some network deployment by AT&T that was to cost $1 billion, save down to the last penny, in polynomial time, including for the worst case instance of the problem.

Yup, maybe the savings would be $51,937,228.21. And do want to save that last penny. But if the manager would settle for saving just the first $51,900,000.00 in reasonable computer time for all or nearly all the actual instances of the manager's real problem, then there would be little or no difficulty. And should be able to tell the manager that savings of more than $55 million, or some such, were impossible -- that is, have an upper bound.

So, much of the difficulty was saving the last $37,228.21, guaranteeing to do so, for all instances of the problem, including the worst cases.

Well, I can assure readers that should I have insisted on a career saving, e.g., $51,900,000.00 where savings of $55 million were impossible, then I would have spent the last several decades homeless on the streets or dead from homeless on the streets -- no joke.

Bluntly, there just is no significant demand for solving ILP problems in practice. The "managers" don't want to get involved.

Selling pizzas from the back of a truck? Sure -- might sell 100 pizzas a day. Selling solutions to ILP and other NP-complete problems -- f'get about it.

Uh, since there is no significant demand for saving $51,900,000.00 with a bound of $55 million, there stands to be not significantly more demand for saving $51,937,228.21.

Thus, there stands to be no significant value for QC for solving NP-complete ILP problems. Sorry 'bout that. If some people want to get the $51,900,000.00 savings, they've been able to do that for decades and have voted loud and clear "We don't care.".

E.g., in one of my attempts, a guy sent me an ILP problem, we talked, and two weeks later I had running code that in 900 seconds on a slow computer got a feasible solution guaranteed to be within 0.025% of optimality. The problem had 600,000 variables and 40,000 constraints. I had done the work for free. Still, then, suddenly he was not interested.

So be it.

There was another one: I was writing the code using the idea of a strongly feasible basis, and suddenly the customer was not interested and returned to some not very good heuristic code he had.

Better, a lot better, to sell something a lot of people actually want, e.g., a lot better to sell pizza.

And I am doing a startup that to me continues to look good, software running, but it has nothing to do with NP-complete or ILP and wouldn't be helped by QC.

So, to me, e.g., even if Google gets a good QC that can solve ILP problems, then I don't believe that they will have many customers or much of a business and there will be no big reason for IBM or Microsoft to worry.

Since there is no significant demand for using ILP to save money now, I don't see a significant demand for using QC on ILP to save money in the future.

Their employees might be better off selling pizzas. Let's see: From some of my arithmetic about costs of pizza, can do well for $2-3 a pizza. From a pizza truck in a good location might be able to sell the pizzas for an average of $10 each, e.g., an extra $1 for anchovies! Might sell 100 pizzas a day for $1000 a day, maybe 20 days a month. Looks like a better career than QC research!

If there is no demand for pizzas, then there won't be much demand for pizzas with anchovies.

Uh, the Google QC researchers are well paid? Terrific -- park the pizza truck near the Google QC research building!!!!

For some parts of US national security, the situation for a good QC might be significantly different -- I doubt it, but maybe.

[pyinstallwoes]

That's the positive, positive outlook, yeah.

Negative, positive outlook is that it is a disinformation campaign so one may maintain the lead in a particular trajectory of technical dominance. Whilst doing so, as an extra game theoretic safety precaution which also amplifies the disinformation campaign is to fund any research in the direction of the disinformation campaign as both a distraction and 'impossibility canary.'

Quite... deliciously deceptive.