Humm no. OVH is French, OVH US is not, both are two different subsidiaries. In fact, you cannot order OVH US infrastructures with a European OVH account, you need to create a US account.
Hi, im a presales engineer for OVHcloud, a cloud provider. OVH is a "pinacle" VMware partner, we are a huge reseller of VMware licenses, and were able to secure a 3-5 years contract with broadcom with only 5 to 15% of price increase.
Of course, the clients I talk with are mostly interested in moving to the cloud or are already in the cloud, so it won't be applicable to you if you'd stay on-prem. I wanted to share my experience.
For some clients, change of technology would be more expensive than paying a bit more to VMware. You'd have to re-train half your IT department, and the migration could be long, risky and complexe. So in this case, a lift and shift move-to-cloud can be competitive, and frankly a serious option.
I see a lot of projects with Nutanix, but you'd be surprise of the price, which is almost the same as VMware. Nutanix comes with way more features than vanilla vsphere which explains the cost increase. You'd have NSX and vSAN packaged, plus replication features. Nutanix offers a great alternative. Actually, OVH proposes Nutanix too, so we can be agnostic and have a sort of leverage over Broadcom.
Some clients are ok to move to public cloud (equivalent AWS/Azure..). The smaller the infra the easier it is. It can be very cheap at OVH. Also it's great if you do containers because of the universal nature of them, they are easy to migrate.
However, If the client has a lot of Windows Server, the cost is actually higher (at OVH the price of the Windows Server Licence is higher than at Azure..) because we cannot leverage the Windows Datacenter licenses
The cheapest viable option is to go to Proxmox on Baremetal servers. The features are close to a standard vSphere environnement. The lack of enterprise support is the thing that stops most clients to do this move.
All good points, except perhaps the cost of the move. With VMWare licences anecdotallty increasing ~8x, the cost of moving could well be recovered quite quickly. Organisations tend to think and react strategically, and this will mean 3-5 year (or more) financial projections for major projects. If a $1m VMWare annual bill is now $8m, over 5 years thats $5m vs $40m. A change to a $1m annually cluster isn't going to cost you $35m, so you should definitely look at changing to minimise your expenses, assuming you get the support etc that you need elsewhere.
The article emphasizes the wrong thing, in my view. The interesting part is that compression -- without learning a model -- can be used for classification. This raises the question of what other information-theoretic measures can be used; cheaper, lossy ones.
I remember seeing an example of using zip to classify languages. You take a set of documents of equal size where you know the languages, then individually concatenate and zip them with the unknown text. The smallest compressed output is likely to be the target language.
Ideally, you'd take all the documents in each language, and compress them in turn with the unclassified text, to see which compresses it better. But this won't work very well with gzip, since it compresses based on a 32KB sliding window. You might as well truncate the training data for each class to the last 32KB (more or less). So to get any performance at all out of a gzip-based classifier, you need to combine a ton of individually quite bad predictors with some sort of ensemble method. (The linked code demonstrates a way of aggregating them which does not work at all).
How much better would that get if you append all but one of the equal size documents? (or other combinations like 2 of the top results after using a single one)
Better, if the compressor can use all that extra context. Gzip, and most traditional general purpose compressors, can't.
It's hard to use distant context effectively. Even general purpose compression methods which theoretically can, often deliberately reset part of their context, since assuming a big file follows the same distribution throughout as in its beginning often hurts compression more than just starting over periodically.
An increasingly common refrain in machine learning is “intelligence is compression.” Folks who believe that might bristle at the distinction between learning and compression.
I doubt it because learned features already constitute lossy compression. The question is what kind of compression; lossy vs. lossless, learned vs. unlearned.
The point is not to have "elegant and compact" code, this is meant to be a fun curiosity, and doing it in 10 lines is just an additional layer of challenge for the heck of it.
The interesting thing is not in whether GZip can achieve SOTA, it's that it can do a decent job at all. (The interesting thing is not in whether the bear can recreate Mozart exactly, it's that it can play the piano at all.)
Yeah, it does demonstrate that you can use compression to measure similarity of two images.
But it also demonstrates that it's a pretty poor similarity measure. Something as simple as counting % of matches between the black and white pixels performs much better.
It's not trying to break records, it just shows a neat aspect of compression. It's still 8 times better than baseline, which showcases that compression can learn representation.
I personnally see a lot of people abusing it and not willing to find themselves a situation, when I pay their salary with huge taxes. It's not so fair for active people who have the ambition to reach a greater comfort than the bear minimum. But, it really makes you feel safe to know that your country will never let someone in need down.
As long as you're an employee, your job is to produce monetizable value for you employer. You can be asked to do whatever your manager decides you to do, even if it's boring work. As long as you don't share a common vision with your company, you'll always find something to say about the decisions it made. This can be called frustration..
What to do is up to you. Bear with it, or work on other projects that you believe will make more sense to you.
Not to mention that this is not the whole system, but just the fusion reaction makes me laugh.
It takes a tremendous amount of energy to reach such condition and temperature to provoke this reaction.
That amount should be taken into consideration too..
