Good article but this misses the obvious - but slightly more distant - eventuality: the no-code vendor goes bankrupt meaning no further support or security fixes, or is bought out by some other firm which means exorbitant future licensing costs and no further features.
Again, some people might not care about that but it seems kind of a biggie to me.
My pet theory is that OpenAI releases are on hiatus pending the US elections. It would be a huge disaster to release SORA in the next few months and have it some way sway voting. What do you think?
I don't know of any official source. But reading between the lines:
Murati also told the Journal that Sora is “much more expensive”.
And just how few sample videos they have output. The point of AI generated content is you _never_ need to reuse it, you can just generate more.
That seemed easy. What was required to make the batteries dispatch power in this way? I have rooftop solar and batteries in the UK and I would definitely engage in a similar scheme like this except I wonder how much work the power companies would have to do to make it work.
Chances are your system is already capable of doing this. If you have a hybrid or grid-tied system that is.
All that's really required is a suitable power meter that links up with a central control authority to orchestrate the whole thing. That's where the complexity lies.
Technically it's easy. The complexity is all with laws and commercial interests.
There are hundreds of thousands of residential batteries in the UK already, and ~0 of them currently can be called on for demand frequency response. That's because 'demand response' is not something you can typically be credited for on your electricity bill. The closest you get is you might have a half-hourly varying pricing scheme encouraging you to discharge your battery when prices are low. The only UK supplier to do that so far (octopus) still uses day-ahead prices though - so you aren't reacting to market conditions, but instead predicted market conditions 24 hours ahead.
I think the fix for the uk is for the regulator to step in and switch half hourly pricing for second by second pricing. Get rid of 'frequency services' (unnecessary with second by second pricing). Then make most/all users of the grid pay those second by second prices (no more 'fixed X per kwh' contracts).
All electricity contracts should be pay-in-advance, and meters should have an option to cap spend per hour/day.
Nobody wants to spend their time micromanaging their electricity usage to such a point. Such a scheme to all users will never pass. Lack of day-ahead means it's impossible to plan anything.
You can still plan based on day-ahead prices. And just take the risk on the difference between day ahead and spot pricing if you like. And if you don't want to take that risk, you can buy contracts for difference between the two from someone else willing to take on the risk. And if you don't want the hassle, you can sign up with an electricity provider willing to do all of the above and not even tell you about the complexity of such stuff.
In theory Byte Pair Encoding is unique, but practice makes it harder. It's also complicated due to regex and utf-8. Most of the time the differences should be too important because the neural network should be able to handle typos.
In BPE you may have plenty of escaping problems, problematic character like ' and \ are nasty to get right : worst case if you don't handle your errors being that if you have trained your byte pair encoding dictionary on escaped sentences, then a single \ should never occur as it is encoded as \\, so if you split the string between the \ then the byte pair encoding might fail to find the key in the dictionary.
Making the thing deterministic and stable when you change your regex version (and when you train one network you'd like to not have to retrain it when there is a bugfix in a regex library). Porting to other platforms also becomes very hard if you want replicable results.
Not in the original scope, but truffle has a way to generate interpreter from a java annotated switch case. And it also generates the bytecode format/length, and if you do changes in the interpreter it can change the bytecode format again.
So I think it is related, if not even the same thing. Plus, GraalVM also does JIT out of box. And it has GC.
That said, it's not all rainbows and unicorns, GraalVM has higher memory usage and is only 10-15% faster in production usage. AFAIK, Twitter is using it in production.
I’m going to have a stab at actually answering the questions, rather than just taking the opposing point of view.
There is another way: organising regular off-sites for the employees to meet up, get to know each other, build relationships, share culture and attend workshops so that they can learn the common tools and techniques that are valid across an org.
I would argue this is a better way to onboard new staff too, if you can hire them to coincide with these off-sites.
Even if the off-site is 2/3 week-long all-expenses-paid trips pa, this will probably work out cheaper than hiring office space for a year
