3,684 karma · joined February 26, 2013
The buy-once, upgrade-years model puts too much risk on the developer. Which in turn results in lousy experiences for customers (dropped support for software, loss in value of hardware on the second hand market). I actually bought an iOS app twice because I found it crazy to be able to use the same €5-app as a baby monitor for over a decade. That is probably a single developer churning out features at a low pace, but continuously for a big part of a career.
In my country a family perhaps pays about €5k total a year for two cars, health, house and the assortment of legal and liability insurance. That is quite modest (not for all income classes though), since there are catastrophes possible in nearly any avenue of life. A minimalist insurance scheme would save one about €2k/yr. That just isn’t that worthwhile utility wise.
Surrounding collusion. I can’t tell you what to believe, but keep in mind that there are a lot of reasons why correlated moves in prices can occur without communication. Lots literature in industrial organization (the field of why markets have particular ordening and how actors behave on markets) on signaling. A though experiment might be the games of poker versus bridge on explicit vs implicit signaling / coordination.
2. Collusion is a strong word. It hints at breaking the law, willfull action, etc. Looking at the price of a competitor and acting upon that, and internal information, is not collusion. It is completely legal and economically rational behaviour. There are hints and information everywhere on which to act. Groceries are an oligopoly, and they are ogipolistic buyers as well. Lots of information for grocers in the price bids of their suppliers, that all groceries get in tandem.
3. I've worked as an economist at one of those government agencies. They are filled with keen PhD / MSc economists looking to bust kartels and find collusion. Geographical price dispersion models are so '00s. There is a lot of positive energy and interaction between academia and government. Actually _proving_ collusion is terribly hard. Prices that move in parallel is not collusion. Proving collusion is finding documents, emails, phone calls, tracking cars with staff members of various firms to motels , paper trails of inside information in another firm. That's collusion. And I fear that's not what happens in the grocery sector.
The motel one comes to mind as real life example of how DoJ in the US prosecuted a proper cartel. The talk was by more a broad-shouldered officer type, than an economist. Certain set of transport firms always had a interesting way of responding to auctions. Always the second best offer was quite far behind and there was a pattern to which firms did or did not reply to a bid request. End of the investigation, they could trace employees of the firms to meeting in a motel before bidding. And somebody left a paper trail.
But still, the one building the LLM-integration is 4x as expensive as the one manually entering the data. It's all about TOC, scale and risk perception. I also love that "risk people" (in the banking context, I'd say: model people) think their data quality should be exceptional and then use end user computing MacGyver style models. Spit and popsicle sticks.
I agree with your assessment that the IT risk barrier is very high in big corp so that entry might be hard for Trellis. Plus a continuous push afterwards to go back to traditional cloud once their offerings catch up.
Our customers are asking for integration with a lot of their systems (say HR / patrolling), but never ever offer to hook up their accounting system. If we want financial data, we either get a PDF with their audited financial statement or in exceptional cases a custom audited statement (you know, the one where a print of a part of the ledger gets a signature from the CPA for a not insignificant bill).
So I am enthusiastic from a data science point of view. Financial data processing of customer data is / was scarce since limited to what was feasible to manually process. That is nearly in the past.
Most entertaining would be the discussion where CrowdStrike would argue that based on common IT-risk criteria, you should never hand over the keys to an unaudited party not practicing common IT-risk best practices and (thus) the liability is on the organization. Talk about CrowdStrike managing risks worldwide. They are doing it right now!
I'm not gloating though. I think what's happening to Florida right now (sea level changes, hurricanes, uninsurability) is what will happen to for example Amsterdam in a few decades. Flood risks are mostly uninsured in the Netherlands, while hurricane risks seem insured in Florida. I don't see house prices correcting for flood risks in Amsterdam, even though the risk of going under seems well inside the time boundary of current sales / mortgages. People are myopic and seem to expect states to handle all adverse effects of risk, both in the Florida case ("Florida residents already pay too much for insurance"), and in the Dutch case (no insurance, but we'll get bailed-out, right?).
[1] https://en.wikipedia.org/wiki/Citizens_Property_Insurance_Co...
From OP, in the OVH-case liability seems to override the contract / waivers when OVH was both the storage And backup provider and did not actively underline that this solution is suboptimal, in a situation where multiple data centers are physically very close. That's a chain of evidence.
For CrowdStrike, it is clear that the offering is to more mature counter parties (thus raising the B2B standard of evidence) and that CrowdStrike very essentially did not do / support staging, whatever. This is indeed bad industry practice, but one that can thought to be explicit from the start of the agreement. At least in my locale you either make explicit agreements OR industry standards are leading. We do not do industry standard X is pretty clear. Read the list in OP, replace CrowdStrike with Microsoft and then think of the international liability cases you've heard from where Microsoft was found liable for downtime, hacks and other issues.
Look, liabilities will always arise in such situations. But I expect only minor liabilities will arise. Mostly (AFAIK IANAL) the terms & conditions are applied in B2B-cases. This case is pretty obvious: you got what you signed up for. CrowdStrike with full scale access to your machines and no guarantees. On the other hand, Crowdstrike lost 125 billion in market cap. That's an indication of {liabilities + loss of future profits}. Pretty massive event for not being willing to do staging. But I expect it's mostly that CrowdStrike is tainted from now on. A friend of mine had a very bad stint as an employee of CrowdStrike recently and from what I learned from that case, I'm happy that the nature of the firm is somewhat more in the open now.
I know there is a debate in the group that needs “fast toilets” whether they should be free. Well that debate is moot when there are near zero options. A coffee brings what €1 of margin? A toilet could cost €1, and still help those in need. I hate paying for dirty toilets (German and Belgian gas stops grmbl, learn from France). But a clean toilet can be a lifesaver.
To delve a little deeper. They seem aware (under HOW WE CONDUCTED THIS STUDY [1]): "While the information collected by the OECD reflect the gold standard in international comparisons, it may mask differences in how countries collect their health data. Full details on how indicators were defined, as well as country-level differences in definitions, are available from the OECD."
They do not mention the specific CDC caveat mentioned above regarding the check box on US death certificates.
And then the pincher: The study points to CDC [2] where explicitly this effect is mentioned as a possible issue with the reporting via death certificates ("Efforts to improve data quality are ongoing, and these data will continue to be evaluated for possible errors.").
I'll leave the interpretation to you. They mention there is a gold standard and that some countries might not follow that gold standard. The conclusion is mainly based on US CDC data vs. OECD non-US data. They link to a CDC report mentioning this issue. Should they mention this fact in the study in the main body, or is this transparant enough?
Going back to the Noahpinion link with graph above in this discussion. For me the time series gives quite the hint that ICD-10 is not being followed appropriately and that false conclusions may arise. If this were my report, I'd take one or two paragraphs to explain why this issue doesn't affect my conclusions in the main body of text.
And then even a 'How to solve this (partially)'. As an actuary I know death is very unlikely in the childbearing age. Show a comparison table of deaths per 100k for women in the age of 20-40 between countries, including the 'US-Black' category. If that comparative line is a lot more flat (my expectation), I would really presume there is a data collection issue. The other interpretation would fail Occam's razor (that non-pregnancy death in US / US-Black categories are less likely than in other OECD-countries). First inkling: [OECD - 3], US ASMR in Women up to 20% higher than other countries.
[1] https://www.commonwealthfund.org/publications/issue-briefs/2...
[2] https://www.cdc.gov/nchs/data/hestat/maternal-mortality/2022...
[3] https://stats.oecd.org/Index.aspx?DataSetCode=HEALTH_MORTAN#
Did my homework: “Old English forca, force (denoting a farm implement), based on Latin furca ‘pitchfork, forked stick’; reinforced in Middle English by Anglo-Norman French furke (also from Latin furca ).”
Four in Latin is quattuor. Scared me there.