wppick

Even if it says milk the quality still depends on what they fed the cow that produced the milk. How much Palm oil was in the cows diet and what effect does that have on the milk. Even things like was the milk taken from an infected/inflamed utter?

Go to your grocery store and see if they have half and half or whipping cream with just milk and cream as ingredients. At lot of grocery stores I've been to don't have any cream it's a recipe with cream guar gum and a few other ingredients. They shouldn't be able to call that recipe the same name "cream". My point is even trying to just buy these ingredients is itself complicated

It has come as a shock to some AI researchers that a large neural net that predicts next words seems to produce a system with general intelligence

When I write prompts, I've stopped thinking of LLMs as just predicting a next word, and instead to think that they are a logical model built up by combining the logic of all the text they've seen. I think of the LLM as knowing that cats don't lay eggs, and when I ask it to finish the sentence "cats lay ..." It won't generate the word eggs even though eggs probably comes after lay frequently

It's called "prompt engineering", and there's lots of resources on the web about it if you're looking to go deep on it

All tax. Income tax, payroll tax, consumption tax

Also upwards accumulation of wealth can sometimes mean less tax revenue. Middle class salary workers pay a lot of tax, so with more upwards accumulation of wealth (maybe accelerating due to AI) then what will happen to tax revenue? People getting laid off don't pay tax, and shifting that money to corporate, tax havens, and cap gains types of taxes will probably end up lower overall

Debt is just promises for future currency. One persons debt is another person asset. But what happens is when you "over promise" by accumulating too much debt then all those people with debt as their assets think they have X dollars, but if there's more debt than underlying resources can cover then it might end up all those people only end up getting like 0.65X or possibly even lower. Kind of like a bank run

Some people are gifted in memorization of these things

Those are usually people who aren't changing languages or frameworks. Memory is mostly recency and repetition, so if you want better memory then narrowing scope is a good strategy. I'd rather go broad so that I can better make connections between things but have to always look up the specifics especially now with LLMs right there

One of the reasons I hate interviewing for software jobs is that the logic seems to be the opposite of this, and instead you should have any possible esoteric concept or possible problem ready at the top of your head instantly. And the same idea now with not allowing LLM for technical interviews

An ounce of prevention is worth a pound of cure, after all.

  Don’t do what? Consider the primary cause of conflicts: simultaneous operations occurring on the same data on different nodes. That happens because data may not have distinct structural or regional boundaries, or because a single application instance is interacting with multiple nodes simultaneously without regard for transmission latency.

  Thus the simplest way to avoid conflicts is to control write targets

  Use “sticky” sessions. Applications should only interact with a single write target at a time, and never “roam” within the cluster.

  Assign app servers to specific   (regional) nodes. Nodes in Mumbai shouldn’t write to databases in Chicago, and vice versa. It’s faster to write locally anyway.

  interact with specific (regional) data. Again, an account in Mumbai may physically exist in a globally distributed database, but multiple accessors increase the potential for conflicts.

  Avoid unnecessary cross-node activity. Regional interaction also applies on a more local scale. If applications can silo or prefer certain data segments on specific database nodes, they should.

  To solve the issue of updates on different database nodes modifying the same rows, there’s a solution for that too: use a ledger instead

The formula is usually more money and ability to work special team isolated from the usual toxic orgs. I think A9 was probably somewhat like that, and AWS probably used to be at some point long ago

One of the most interesting things to me when reading this was that it was treated as a bug even though it was that hard to reproduce. Most dev shops would not have the bandwidth and management but in to spend the time to dig into something like that unless it was high severity, and also it sounds like it was also getting caused from a modded version of the software

Kubernetes is way heavier than Erlang’s lightweight processes, so for millions of tasks at scale, a middle-ground solution could blend Erlang’s concurrency efficiency with k8s’ orchestration power, dodging containers’ overhead while keeping flexibility for diverse workloads. That's if you don't actually need the strict isolation of pods/containers and you're just trying to run something at massive scale. I don't get why so many people want to run everything as heavy container processes or pods vs coming up with a better solution. The point is we don't have to fit every problem into the shoe called kubernetes if it doesn't seem to fit, and we should look at other ways to spin up millions of processes

Try experimenting with diet like cutting out/down on sugar or salt and see if it makes any difference. There's no strong evidence that EMF can cause tinnitus but would be interesting to test that out somehow too (camping/cabin trip in a radio free zone?)

https://en.wikipedia.org/wiki/Executive_functions

"Executive functions include basic cognitive processes such as attentional control, cognitive inhibition, inhibitory control, working memory, and cognitive flexibility. Higher-order executive functions require the simultaneous use of multiple basic executive functions and include planning and fluid intelligence (e.g., reasoning and problem-solving)."

Executive function is not just emotional control. It's higher levels of thinking. It's the E in CEO. AI is really just an amplifier, just like how a calculator in one person's hand could be much powerful than in someone else's

If you don't need the isolation of of k8s then don't forget about erlang, which is another option to scale up to 1 million functions. Obviously k8s containers (which are fundamentally just isolated processes) and erlang processes are not interchangeable things, but when thinking about needing in the order of millions of processes erlang is pretty good prior art

The higher your executive function the more use you will get out of LLMs. This is really the skill you should be testing for in interviews now. Not letting a candidate use AI for their interview is not a useful evaluation anymore. I want to see how you use it. Do you prompt well, how much are you trusting and verifying what it outputs

The one issue is the accuracy of these AI models, which is that you can't -really- trust them to do a task fully, so that makes it hard to fully automate things with them. But the other is cost. Anyone using these models to do something at scale is paying maybe 100X over would it would cost in compute to run deterministic code to do the same thing. So in cases where you can write deterministic code to do something, or build a UI for a user to do it themselves, that still seems to be the best way. Once AI gets to the point where you can fully trust some model, then we've probably already hit AGI and at that point we're probably all in pods with a cable in our brainstems, so who cares...

Processes are great for things like pilot take off procedures, or anything that is repeated and you want to be able to control and optimize including with methodologies like lean, six sigma. If there is too much uncertainty around a process then it's not really a process it's just a problem. I think this post groups those two things together into one

Cool idea, but I wouldn't run this for security reasons unless it was open source and I compiled it myself

Don't forget to break it into microservices

Pretty much every big tech company you could think of uses some type of open source software, including Apple, Google, and Facebook.

These companies contribute massively to open source. The article would have more impact if better examples were chosen.

I think the model of open source works fine as is. Maybe people will write open source out of passion to work on cool project, and maybe to build a name for themselves. Companies will open source to give back, but also to get additional resources to help debug and build out the codebase. This just feels like begging for money. If you want to make money write sass software, don't corrupt open source

Ya the one between your ears. Kidding! Maybe Sourcegraph Cody https://sourcegraph.com/cody, or possibly Github copilot. I think Cody might handle the multiple files better, and allows you to pick from multiple models.

My understanding is that the author is saying you could build google docs to go from one state to another by submitting a form and doing server side rendering returning the entire webpage of the new state. This is obviously much worse user experience and way less efficient, but I guess it technically would work.

Listen here, you can't tell the English what to do. We'll drive on whatever side of the road, use metric or not when we feel like it, and call fruit whatever we want

To add to this... maybe YouTube could build a concept of bring your own algorithm or "curators" where I can follow a curator who either manually, or by using their own algorithm creates their own unique feed that I might enjoy more than YouTubes default. Maybe kind of like a spotify playlist or something. The curators could get a small piece of the ad revenue from videos they recommend as a sort of referral fee. This could also probably be done by an external service like a Piped, but they could instead just show their own ads instead of getting the referral fees.

I find that YouTubes recommendation algorithm is not great. It would be a cool feature to be able to something like assume a persona and have recommended videos that similar like minded people watched. There's effectively infinite videos on YouTube but it's common I can go there looking for a video and find nothing interesting to watch. In some cases it's pushing recommendations for videos all similar to a recent video I had watched, but I'm no longer interested in that topic

Interestingly and semi-related: in Japan, the electrical grid is divided into two frequency standards: 50 Hz in the eastern part of the country (including Tokyo), and 60 Hz in the western part (including Osaka). Which was due to influence by German tech in the east and American tech in the west. Electrical appliances have to be labeled to indicate their compatible frequency to warn customers

Another source of shrinkflation is changing ingredients. Something that used to be 50% water is now 75% water as an example. Another is changing from olive oil to canola or palm or, and things like that.

Isn't this kind of the same thing that crypto miners do?