The fact that billions were spent on research to distill the internet should not preclude others from spending 10s of thousands to do the same to these frontier labs.
Time to create a bigger moat than "but we spent so much money doing this ...".
124 karma · joined March 11, 2014
The fact that billions were spent on research to distill the internet should not preclude others from spending 10s of thousands to do the same to these frontier labs.
Time to create a bigger moat than "but we spent so much money doing this ...".
Never imagined politics so obviously manipulating the talking heads with nary a care about perception.
What was supposed to be a model, training, and data moat - is now reduced to operational cost, which they are not terribly efficient for.
OpenAI has been on a journey to burn as much $ as possible to get as far ahead on those three moats, to the point where decreasing TCO for them on inference was not even relevant - "who cares if you save me 20% of costs when I can raise on a 150b pre money value?".
Well, with their moats disappearing, they will have no choice but to compete on inference cost like everyone else.
This part is easy and anyone can implement hardware to do this. The tricky bit is always the staying in log space while doing accumulations, especially ones across a large range.
We design an inference accelerator which more or less accomplishes this by quantizing input tensors into logarithmic space. This allows the multiplication (in convolution especially), to be optimized into very simple adders. This (and a few other tricks) has a very dramatic impact on how much compute density we achieve while keeping power very low. We keep the tensors in our quantized space throughout the layers of the network and convert the outputs as required on the way out of the ASIC.
We achieve impressive task level performance, but this requires some specialized training and model optimizations.
Very cool to see ideas like this propagate more into the mainstream.
Depending on the application, you could literally build software in the open and still maintain if not expand exposure.
But, I should also mention, we only use the RISC-V cores as a pre/post-processor, scheduling engine, service processor. We have custom hardware that does the bulk of the inference math (we are a convolutional accelerator with a number of constraints traded off for speed and power). The fabric itself is driven by engines that are programmed by the scheduling engine (RISC-V).
Happy to answer more specific DMs.
10/10 would do it again, except this time we may pay SiFive or someone like that for something requiring less "customization".
It is not about everyone getting equal pay. It is about everyone having equal visibility. The former creates unmotivated employees, the latter creates one of two outcomes: 1. Satisfaction of relative comp for the amount of work done -or- 2. Understanding of what is valuable in this venture; how to spend your time
Often times in larger establishments (after playing enough politics to gain visibility), I found myself in camp (2). What you think is important is seldom actually important to the powers that be. If you find yourself disagreeing with the last statement, go hug your management team / coworkers!
Regardless of how much this made, the OP sold a business and crossed a chasm many find very uncomfortable to cross. Congrats on breaking past the inertia to ship, and then sell; it is truly commendable regardless of the naysayers.
Now I want to build a shed.
We live in a world where even if the outcome is measurable, often times, it is not in our control. A shed, the gym, other such "hobbies" are tangible goals with indicators along the way where our influence of control intersects the measurable progress we see. These are essential to sanity, methinks.
In reality, it never quite works out that way - but I still maintain it is a good way to start. Like many have said, it is essential to identify the path by which you multiply engineering as demanded by the needs of the thing you are building.
Many projects can keep that factor to 1, but it has to be about the love of doing it, not the outcome. The minute the outcome is more important, hire, scale and delegate!
Happy new year to all the awesome moms out there, especially my own :)
Kidding aside, he would likely make a much better leader than the current self indulgent noise.