Hacker News Reader

Comment by ethbro | Hacker News Reader

> The market allows for this silicon giant because of the current Deep Learning and VR hype.

One of three things is true:

1) Nvidia has misstepped and no one will buy large, expensive chips

2) Companies are buying large, expensive chips because they're purchasing based on hype rather than use

3) Companies are buying large, expensive chips because even at their prices, their performance delivers greater business value

I'd argue that improvements in ML techniques have tipped us into (3). Intel and Microsoft's fortunes weren't built on being faster: they were built on allowing businesses to do new categories of work on computers.

Amdahl is the new Moore

View on HN

Don't forget 4) Companies are buying large, expensive chips because they are being used and delivering value, but hype has occluded other more cost effective solutions. See the articles about, 'you don't need deep learning' (or was that big data?)

You gotta trace the money, though. I don't think ML is all hype, but if you only look one level deep you can get some silly conclusions. For example, just because Nvidia can sell these things does not mean the purchaser will ultimately recoup their value, but even if they do the clients of that business might not recoup their costs. At the end of the day, a lot of people are investing huge amounts of money into ML, but it is hugely possible that this is in part due to expectations that won't actually be met in the end.

Or... What if we do not care if the first, second or third order of customers recoup anything.

What if only what is important is that by these being available, and the first several adoption catagories identify new categories/opportunities of work that will allow for the next leap in whichever direction can only manifest on the carcasses of these early adoptions...

I expect there's certainly a lot of that.

But entry data analysts are ~USD$60k / yr?

At that price, substituting hardware for even low-hanging, first-order prediction models starts to look attractive.

What they were emphasising today was replacing a $2 million CPU based render farm used for offline rendering with their new hardware at 25% the cost and 10% the power usage for the same or better results. To the extent those numbers are realistic (and it seems like they are) it's going to be a pretty straightforward value proposition for companies that have render farms. This was SIGGRAPH so ML wasn't the main emphasis.

Yep, fair points. I was mostly replying regarding ML hype. Clearly, the value for renderfarms is proven at this point.

There is still the implementation, debugging and testing/validation cost.

Reply on news.ycombinator.com