USD dominance isn't going anywhere despite hurt feelings over Trump or US policies.
Dead Comment
USD dominance isn't going anywhere despite hurt feelings over Trump or US policies.
I have many questions:
- Will Meta fuck this up as they seem (in my opinion) to do with most of the acquisitions? Oculus? Drop.io?
- Did they grossly overpay?
- Will innovation slow to a crawl (eg. Instagram, Whatsapp)?
- Will Manus' top talent bail?
- How is it conceivable Meta couldn't build this themselves. It can't possibly have been Manus' user base they were after, can it?
- How much trouble am I in for telling my wife to sell her Meta stock two weeks ago?
The acquisition is confusing to me.
Dead Comment
I wonder what the next recycling movement will be? Discarded EV batteries? Dead solar panels?
How does this next iteration play out?
I don’t say this as someone who is suggesting we not think about consumption but rather it’s a fake feeling that it’s going somewhere other than the landfill. I would be curious in other countries how economical it really is to recycle.my favorite is Japan where some areas will incinerate certain qualities of plastic for energy. I think that is a useful way to reuse it.
Metals, eWaste, Batteries ... all profitable to recycle.
Paper & cardboard ... depends on market price.
Plastics ... depends on oil prices, market price and type of plastic.
Tires ... usually profitable, usually involves a hauling fee.
AMP's robotic solution is going to face immense competition from general edge models, probably very soon. The mechanical piece is simple engineering. All the magic is (was) recognition.
The revenue from AI is growing at a much slower rate than recurring capex and depreciation is accumulating. This will create distress opportunities that cash-rich companies like APPL may seize. Might be a private equity deal, might be in the public markets as some of the players dip hard after IPO.
As this plays out, APPL's silicon has unified memory, power consumption and native acceleration that gives it an edge running SLMs and possibly LLMs at scale. Wouldn't shock me to see APPL introduce a data-center solution.
The only thing these companies sell are tokens. That's their entire output. OpenAI is trying to build an ad business but it must be quite small still relative to selling tokens because I've not yet seen a single ad on ChatGPT. It's not like these firms have a huge side business selling Claude-themed baseball caps.
That means the cost of "inference" is all their costs combined. You can't just arbitrarily slice out anything inconvenient and say that's not a part of the cost of generating tokens. The research and training needed to create the models, the salaries of the people who do that, the salaries of the people who build all the serving infrastructure, the loss leader hardcore users - all of it is a part of the cost of generating each token served.
Some people look at the very different prices for serving open weights models and say, see, inference in general is cheap. But those costs are distorted by companies trying to buy mindshare by giving models away for free, and of those, both the top labs keep claiming the Chinese are distilling them like crazy including using many tactics to evade blocks! So apparently the cost of a model like DeepSeek is still partly being subsidized by OpenAI and Anthropic against their will. The cost of those tokens is higher than what's being charged, it's just being shifted onto someone else's books. Nice whilst it lasts, but this situation has been seen many times in the past and eventually people get tired of having costs externalized onto them.
For as long as firms are losing money whilst only selling tokens, that means those tokens are selling at a loss. To not sell tokens at a loss the companies would have to be profitable.
- Amortized training costs.
- SG&A.
- Capex depreciation.
All the above impact profitability over various time horizons and have to rolled into present and projected P&L and cash flow analysis.