Is Software Improving Exponentially?

In a discussion on the AGI email discussion list recently, some folks were arguing that Moore's Law and associated exponential accelerations may be of limited value in pushing the world toward Singularity, because software is not advancing exponentially.

For instance Matt Mahoney pointed out "the roughly linear rate of progress in data compression as measured over the last 14 years on the Calgary corpus, http://www.mailcom.com/challenge/ "

Ray Kurzweil's qualitative argument in favor of the dramatic acceleration of software progress in recent decades is given in slides 104-111 of his presentation here.

I think software progress is harder to quantify than hardware progress, thus less often pointed to in arguments regarding technology acceleration.

However, qualitatively, there seems little doubt that the software tools available to the programmer have been improving damn dramatically....

Sheesh, compare game programming as I did it on the Atari 400 or Commodore 64 back in the 80s ... versus how it's done now, with so many amazing rendering libraries, 3D modeling engines, etc. etc. With the same amount of effort, today one can make incredibly more complex and advanced games.

Back then we had to code our own algorithms and data structures, now we have libraries like STL, so novice programmers can use advanced structures and algorithms without understanding them.

In general, the capability of programmers without deep technical knowledge or ability to create useful working code has increased *incredibly* in the last couple decades…. Programming used to be only for really hard-core math and science geeks, now it's a practical career possibility for a fairly large percentage of the population.

When I started using Haskell in the mid-90s it was a fun, wonderfully elegant toy language but not practical for real projects. Now its clever handling of concurrency makes it viable for large-scale projects... and I'm hoping in the next couple years it will become possible to use Haskell within OpenCog (Joel Pitt just made the modifications needed to enable OpenCog AI processes to be coded in Python as well as the usual C++).

I could go on a long time with similar examples, but the point should be clear. Software tools have improved dramatically in functionality and usability. The difficulty of quantifying this progress in a clean way doesn't mean it isn't there...

Another relevant point is that, due to the particular nature of software development, software productivity generally decreases for large teams. (This is why I wouldn't want an AGI team with more than, say, 20 people on it. 10-15 may be the optimal size for the core team of an AGI software project, with additional people for things like robotics hardware, simulation world engineering, software testing, etc.) However, the size of projects achievable by small teams has dramatically increased over time, due to the availability of powerful software libraries.

Thus, in the case of software (as in so many other cases), the gradual improvement of technology has led to qualitative increases in what is pragmatically possible (i.e. what is achievable via small teams), not just quantitative betterment of software that previously existed.

It's true that word processors and spreadsheets have not advanced exponentially (at least not with any dramatically interesting exponent), just as forks and chairs and automobiles have not. However, other varieties of software clearly have done so, for instance video gaming and scientific computation.

Regarding the latter two domains, just look at what one can do with Nvidia GPU hardware on a laptop now, compared to what was possible for similar cost just a decade ago! Right now, my colleague Michel Drenthe in Xiamen is doing CUDA-based vision processing on the Nvidia GPU in his laptop, using Itamar Arel's DeSTIN algorithm, with a goal toward providing OpenCog with intelligent visual perception -- this is directly relevant to AGI, and it's leveraging recent hardware advances coupled with recent software advances (CUDA and its nice libraries, which make SIMD parallel scientific computing reasonably tractable, within the grasp of a smart undergrad like Michel doing a 6 month internship). Coupled acceleration in hardware and software for parallel scientific computing is moving along, and this is quite relevant to AGI, whereas the relative stagnation in word processors and forks really doesn't matter.

Let us not forget that the exponential acceleration of various quantitative metrics (like Moore's Law) is not really the key point regarding Singularity, it's just an indicator of the underlying progress that is the key point.... While it's nice that progress in some areas is cleanly quantifiable, that doesn't necessarily mean these are the most important areas....

To really understand progress toward Singularity, one has to look at the specific technologies that most likely need to improve a lot to enable the Singularity. Word processing, not. Text compression, not really. Video games, no. Scientific computing, yes. Efficient, easily usable libraries containing complex algorithms and data structures, yes. Scalable functional programming, maybe. It seems to me that by and large the aspects of software whose accelerating progress would be really, really helpful to achieving AGI, are in fact accelerating dramatically.

In fact, I believe we could have a Singularity with no further hardware improvements, just via software improvements. This might dramatically increase the financial cost of the first AGIs, due to making them necessitate huge server farms ... which would impact the route to and the nature of the Singularity, but not prevent it.