I was sceptical because 'AI' and 'quantum' seems to be used interchangeably and fits your regular snakeoil salestalk but google has done enormous amounts of research into non-classical computing. They've also done their AI projects to solve protein folding faster and more accurate than any contemporary solving models[1]. which is why the name sort of makes sense even though many on HN would appreciate nuance.<p>"Nature is quantum mechanical: The bonds and interactions among atoms behave probabilistically, with richer dynamics that exhaust the simple classical computing logic."<p>"Already we run quantum computers that can perform calculations beyond the reach of classical computers."[citation needed]<p>[1] <a href="https://www.deepmind.com/blog/article/AlphaFold-Using-AI-for-scientific-discovery" rel="nofollow">https://www.deepmind.com/blog/article/AlphaFold-Using-AI-for...</a>
For those who are unaware, there's a good reason to put this in Santa Barbara: it's already the home of Microsoft Station Q, a quantum computing research facility on the campus of UCSB. When I left the math department there in 2014, there were more and more graduate students attaching themselves to it. Not to mention the growing tech industry in Goleta (the city UCSB is actually located in). So it's a perfectly sensible place to put a quantum AI lab. Even if you don't know what that means, yet!
I think QNN are very interesting from a compsci perspective, and interesting from a quantum tech perspective, but not so much from a real world perspective.<p>As I understand it loading classical data into a quantum computer - into quantum ram - is a big bottleneck. So running a QNN over a picture of a cat can't give a speedup vs. running it on a classical machine. Is this wrong HN?<p>I haven't found a result showing QNN's do offer strong speedups for training or testing - I have found papers saying it looks good - but I haven't found the result. I think this may be a literature search fail by me though.<p>For generalisation I <i>have</i> seen
papers claiming that there will be better generalisation with QNN but I <i>have</i> failed to understand this result and <i>do</i> need to work harder!<p>I also believe that the most promising algorithm for quantum ML (HHL) has been "dequantized" I think that Grover's and QMC are pretty secure but also only quadratic in speed up (I say only - this is because that means there is a window of quantum advantage that may or may not be useful before the quantum algorithms fall off a cliff as well.<p>Ok - I need to understand this stuff for real, so please shoot me to bits !
>> Within the decade, Google aims to build a useful, error-corrected quantum computer. This will accelerate solutions for some of the world’s most pressing problems, like sustainable energy and reduced emissions to feed the world’s growing population, and unlocking new scientific discoveries, like more helpful AI.<p>Are "sustainable energy", "reduced emissions to feed the world's growing population" and "unlocking new scientific discoveries like more helpful AI" goals that Google is currently working towards?<p>Regarding the need to feed "the world's growing population", note that absolute increase in global population per year has levelled off for several decades and may even be decreasing:<p><a href="https://en.wikipedia.org/wiki/Population_growth" rel="nofollow">https://en.wikipedia.org/wiki/Population_growth</a>
In Santa Barbara?<p>That should be interesting. There's been some good physics from there. Flash LIDAR came from Advanced Scientific Concepts there.<p>UC Santa Barbara is Hollywood's vision of a college. Everyone is good-looking and the college is right on the beach.
The hardware side has been up there for a long time, and the theoretical side of the team has been in the Venice office. I guess they got a new building in Santa Barbara and wanted an announcement. I wonder if they are forcing the theorists to move up north?
Tiny feedback for anyone reading who worked on this page:
<a href="https://quantumai.google/learn/lab" rel="nofollow">https://quantumai.google/learn/lab</a><p>It would be great if the audio clips had the standard seek bar with the ability to pause/play. Perhaps when I scroll up or down to a section, pause the current audio clip. Then resume playing it when I come back. But also allow me to seek around. Rather than just restarting from the beginning. Because these clips are several minutes long and I am given no indication of their length.<p>Currently all I can do is either continue listening for an unknown amount of time, or go to the next/previous section and completely lose my progress.
Personally I think we’ll soon discover that what we’re doing in ‘quantum’ is indistinguishable from classical analog at that frequency and noise temperature, and that will also be the point where it becomes broadly useful and scalable.