IMO, at the time, it was to buy ABK and make CoD an Xbox exclusive. That clearly didn't play out when everyone screamed about it being (rightly!) anticompetitive, and so they had to resign themselves to accepting that day 1 gamepass exclusive was going to be their way to get people to switch over from PS. That also didn't work.
The 'K' part of ABK was also probably going to be their way to drive mobile into Xbox as well with their 'everything is an Xbox' push at the time.
I'm actually doing something similar, myself, and doing a MSc in CS right now. I'm somewhat jealous of how little group work you had to do! Almost every course I'm going through now has 1-3 group work assignments each.
Often the reason is something like _"that's how it is in the workplace"_ which is a blatant cop out, imo. It's clear the reason that Universities force group work is because it's a cost cutting exercise.
They need to pay the hours for people to mark assignments. Make groups of 2, and you've cut the number of hours that need to be paid by 50%. Make groups of 5, and you've cut the cost by 80%. Of course, this comes at the cost of some students unfairly carrying others.
Once they take in your job application, they're processing your data. You've then got a right, wherever you're from, to see what information they hold on you. That includes interview feedback, test scores and so on.
Or just allow what happens in the EU. Every time I've applied for a job and been rejected, I put through a GDPR request and find out the reasons I was rejected.
> I would eat my hat if Mistral doesn’t go out of business in next 5 years
Hope you're hungry. The Mistral are going to what most great European companies are good at - regulatory arbitrage. They're going to insert themselves everywhere within EU (French govt, etc) and extract value that way whilst delivering subpar services to what open weight Chinese models can deliver. Honestly they'll probably be profitable before most other AI providers are simply because there's very little pressure to improve models.
It's a business that seems to have high operational leverage. Effectively, similar to airlines. Enormous capital outlays with low marginal costs, so once the current infra has been built at cost x, the additional data centre at cost 5x (or whatever multiple) might mean that it's not profitable to keep serving at the current prices.
This is why I think in the long run, the Chinese models will probably end up winning where it matters. You can get a cluster of relatively affordable 30 or 4090s, load up DeepSeek v4 and let it rip. Your only ongoing cost is power. We're already seeing companies recoil at the sight of their API bills from the frontier labs, for the price of 1 years worth of tokens you can host your own decent model that's 75% of the way there.
The "guardrails" are just Anthropic's attempt at building a moat. Guarantee they'll be seeking regulation around AI as well to ensure a form of regulatory capture. Guardrails, in this context, are useless. Anyone who's sufficiently motivated will either get around them, or will just run their own model on their home hardware. There's already tools that one can use to remove the guardrails present in open weight models.
Look, I'm not from the US, I'm guessing maybe the pay for tradesmen isn't as high as in Australia. But what you're suggesting as a comparison involves a pretty high degree of variance and odds are stacked against you. You need to get into a good PhD program, get funding, compete against everyone else doing those things and so on.
The path I outlined in my OP is a _very_ common path that people take in Australia and not at all unrealistic. The barrier to entry is drastically lower, and the access to funding/capital is far easier.
Unironically the most simple (note; not easy) way to become a multi-millionaire. Do a trade in your 20s, leverage that into running your own trades business in your 30s, and have a >10m valuation business by your 40s.
I think they're more referring to the scalable service economy. Haircuts, which are a service, don't scale (unless we're talking about robotics or something).