xer

Agent to agent communication is the fad and we do have a strong opinion on how it should be designed.

Our of $60B, what does that make VSCode priced at?

Endless, we offer SemQL to query in high-dim space using distance, direction and contrast predicates. It enables anyone to retrieve events that align with a predicate in global vector space.

The fundamental assumptions of distributed systems is having multiple machines that fail independently, communicate over unreliable networks and have no shared clock has the consequence of needing to solve consensus, byzantine faults, ordering, consistency vs. availability and exactly-once delivery.

However, AI agents don't share these problems in the classical sense. Building agents is about context attention, relevance, and information density inside a single ordered buffer. The distributed part is creating an orchestrator that manages these things. At noetive.io we currently work on the context relevance part with our contextual broker Semantik.

Lesson learned: If your recovery plan requires calling any API in the dead region — to detach an IP, describe a route table, launch an instance, read an S3 object, or decrypt a volume — it will fail when you need it most.

Every dependency on the primary region is a dependency on the thing that just broke.

This is great! But what if the US invests 1% of GDP in GPU datacenters and then those are not needed becaues someone created a much more efficient architecture?

I share the view that nobody avoids an exit or migration because of egress fees. In fact, for online migrations the period of replicating data between providers might go on for months.

But all cloud providers leverage The Principle of data locality or data gravity, which states that compute benefits from being close to the stored data. If a customer moves the data elsewhere it follows that the compute will soon leave too.

The elephant in the room: Will Spotify survive the coming wave of generative AI audio content? Wasn't any mentioning on that in the letter.

Seems to me like they would need to ditch a lot of silly investments like original content, platform engineering on Kubernetes and scaled agile which together carry costs in the range of $100s millions, to free up resources to battle new disruptive technologies.

Correct. It's also the case that human generated requests will lose their relevance within seconds, a quick retry is all it's worth. As for machine generated requests a dead letter queue would make more sense, poor engineered backend services would OOM and well-engineered would load shed, if the requests are queued on the application servers they are doomed to be lost anyway.

AWS is growing faster than they can staff, luxury problem.

I think there is another side to this story which is that referral marketing is having a bad name these days. It's considered fraudulent by many sellers since sometimes these referral sites rank higher than the sellers themselves. I suspect this is part of an effort from Google to put the sellers higher than the referrers in the search results.

PDI is just one tool in the toolbox. It's never gonna die.

Read hacker news once every day and you will after a few years of reading be above the average software engineer.

It should say "Thanks to cuts"

Wow nice works. I was working on the exact same project https://www.coinmarketattack.com/

It's called SIEM, Security Information Event Management, there is a lot of companies doing this and providing cheap and expensive solutions.

This is corruption.

From my experience you can increase your luck in life by exposing yourself to more choices. This can be something as simple as having saved up money so you can quit your job whenever you want to. That in turn gives you the "luck" to get a better job if the opportunity presents itself.

Bubbles are everywhere, one you probably never heard of is called humanity, yes our species.

One significant fuel of blockchain tech is the distrust in the current financial systems. If central bankers and governments could regain trust there is a probable chance of a bust.

No mentioning of straightened proofs of 9/11 plot...

Just saying learn ramda

Can't read the article...

Only problem is that you need to install a Browser Extension, much bigger problem is that browsers are not secure.

At Annsec we are all out on serverless infrastructure and use Lambdas and Step functions in two development teams on a single backlog. Extensibility of a well written lambda is fenomenal. For instance we have higher abstraction lambdas for moving data. We make them handle several input events and to the greatest extent as pure as possible. Composing these lambdas later in Step functions is true developer joy. We unit test them locally and for E2E-tests we have a full clone of our environment. In total we build and manage around 40 lambdas and 10 step functions. Monitoring for failure is conducted using Cloudwatch alarms, Ops Genie and Slack bots. Never been an issue. In our setup we are aiming for an infrastructure that is immutable and cryptological verifiable. It turned out to be bit of a challenge. :)

Lol

I reviewed pfSense around nov 2016, it failed on many basic security best-practices, and was rejected for our purpose.

I believe there are three good indicators to look at:

- Infrastructure, these can also be called enablers. E.g. fiber accelerates Internet usage, AWS drastically accelerates SaaS businesses. Over time this acceleration will also happen in e.g. biotech and such introductions are to look for. If the infrastructure is missing, its likely gonna take some more time. Success stories in this category would be Spotify, Netflix and most apps.

- Accumulators is similar to a network effect. Information, money, users and customers are orbiting certain networks and companies. These instances are in their domains black holes and it's mostly a bad idea trying to restrain or compete. The opportunity is to harness the momentum. A success story in this category would be Buzzfeed.

- Automation, we are living in the golden age of automation. Essentially it's just to evaluate all repetitive tasks finding those with the highest value to the lowest investment.

The examples lack the elegance of RxJS. I'm gonna stick with the Channels for a further while.

Very nice cheat sheet!

How could there not be a test case against negative attitude during descent?